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/home/bill/web/Cool stuff/Hoyte & Schatten year - solar influence on climate & natural systems, graphs.pdf
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/home/bill/web/Neural nets/callerID-SNNs/
/home/bill/web/Neural nets/callerID-SNNs/callerID-SNNs.html
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/home/bill/web/Neural nets/Computational neuro-genetic modelling.html
/home/bill/web/Neural nets/Conference guides/Conference guides.html
/home/bill/web/Neural nets/Holidays - neural networks and genomics.html
/home/bill/web/Neural nets/Howell 110903 - Confabulation Theory, Plausible next sentence survey.pdf
/home/bill/web/Neural nets/Howell 131011 fMRI - Random, stray thoughts.pdf
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/home/bill/web/Neural nets/Howell 2006 - Genetic specification of neural networks, draft concepts and implications.pdf
/home/bill/web/Neural nets/Howell 2006 - Presentation, Genetic Specification of Recurrent Neural Networks Initial Thoughts.ppt
/home/bill/web/Neural nets/Mind2023/
/home/bill/web/Neural nets/Mind2023/voice musings/
/home/bill/web/Neural nets/Mind2023/voice musings/231106_2212 Glenn Borchardts concept of infinity, avoid myopic thinking.mp3
/home/bill/web/Neural nets/MindCode/
/home/bill/web/Neural nets/MindCode/???
/home/bill/web/Neural nets/MindCode/10 Howell - MindCode Manifesto.odt
/home/bill/web/Neural nets/MindCode/12 MindCode components.odt
/home/bill/web/Neural nets/MindCode/13 Historical [DNA, Protein, Evolutionary Computing, ANN] hybrid basis for epiDNA-NNs.odt
/home/bill/web/Neural nets/MindCode/14 MindCode - arbitrary selections from Multiple Conflicting Hypothesis.odt
/home/bill/web/Neural nets/MindCode/15 Assumed rules of the game.odt
/home/bill/web/Neural nets/MindCode/16 Introduction - Conceptual pseudo-basis for MindCode.odt
/home/bill/web/Neural nets/MindCode/17 Questions, not answers.odt
/home/bill/web/Neural nets/MindCode/20 Static epiDNA-NN.odt
/home/bill/web/Neural nets/MindCode/22 Dynamic epiDNA-NN coding.odt
/home/bill/web/Neural nets/MindCode/50 [Neurological, biological] basis for epiDNA coding.odt
/home/bill/web/Neural nets/MindCode/80 Ontogeny.odt
/home/bill/web/Neural nets/MindCode/80 Specialized epiDNA-NNs for MindCode.odt
/home/bill/web/Neural nets/MindCode/90 Hybrids of [algorithms, conventional computing, ANNs, MindCode].odt
/home/bill/web/Neural nets/MindCode/Howell 050824 Junk DNA & NeuralNetworks, conjecture on directions and implications, IJCNN05 workshop panel presentation.ppt
/home/bill/web/Neural nets/MindCode/Howell 060215 Genetic specification of neural networks, draft concepts and implications.pdf
/home/bill/web/Neural nets/MindCode/Howell 060716 Genetic specification of recurrent neural networks, Initial thoughts, WCCI 2006 paper 1341.pdf
/home/bill/web/Neural nets/MindCode/Howell 060721 Genetic Specification of Recurrent Neural Networks Initial Thoughts, WCCI 2006 presentation.ppt
/home/bill/web/Neural nets/MindCode/Howell 150225 - MindCode Manifesto.odt
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/home/bill/web/Neural nets/MindCode/MindCode webPage.html
/home/bill/web/Neural nets/Neural Networks.html
/home/bill/web/Neural nets/Paper reviews/
/home/bill/web/Neural nets/TrNNs_ART/
/home/bill/web/Neural nets/TrNNs_ART/ART assess theories of consciousness.html
/home/bill/web/Neural nets/TrNNs_ART/ART augmentation of other research.html
/home/bill/web/Neural nets/TrNNs_ART/[definitions, models] of consciousness.html
/home/bill/web/Neural nets/TrNNs_ART/For whom the bell tolls.html
/home/bill/web/Neural nets/TrNNs_ART/Grossbergs [core, fun, strange] concepts.html
/home/bill/web/Neural nets/TrNNs_ART/Grossbergs list of [chapter, section]s.html
/home/bill/web/Neural nets/TrNNs_ART//Grossbergs list of [figure, table]s.html
/home/bill/web/Neural nets/TrNNs_ART/Grossbergs list of [figure, table]s.html
/home/bill/web/Neural nets/TrNNs_ART/Grossbergs list of index.html
/home/bill/web/Neural nets/TrNNs_ART/Grossbergs overview.html
/home/bill/web/Neural nets/TrNNs_ART/Grossbergs quoted text.html
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 1st prize, Matt Pritchard- The Phantom Queen.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 2nd prize, Michael Cohen- The Changing Room Illusion.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 3rd prize, Dawei Bai & Brent Strickland - The Double Ring Illusion.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 Christopher Tyler and David Phillips - Emergent City Flyby with Colossus.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 Kokichi Sugihara - Rising Object Illusion.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 Michael Cheshire - Cubic Confusion.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 Olivier and Chloe Redon - Oh La La Box.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 Pascal Wallisch & Michael Karlovich - Crocs & Socks.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 Peter Veto - The Phantom Wiggle.ogv
/home/bill/web/Neural nets/TrNNs_ART/IllusionOfTheYear/2021 Yutaro Sato, Kento Imai and Kenri Kodaka - Slime Hand.ogv
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/cover image.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p002fig01.01 Seeing an object vs knowing what it is.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p002fig01.02 Dalmation in snow.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p003fig01.03 Amodal completion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p004fig01.04 Kanizsa stratification: transparency images.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p008fig01.05 Noise-saturation dilemma: cell activity; current activity.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p009fig01.06 Primacy gradient of activity in a recurrent shunting OC-OS network.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p011fig01.07 signal function determines how initial activity pattern is transformed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p012fig01.08 Sigmoidal signal: a hybrid of [same, slower, faster]-than-linear.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p013fig01.09 sigmoid signal: quenching threshold; contrast enhancement.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p016fig01.10 Minimal adaptive prediction: blocking and unblocking.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p016fig01.11 BU-TD mismatch -> orienting system -> nonspecific arousal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p018fig01.12 Peak shift and behavioural contrast: prefer new experiences.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p019fig01.13 Affective circuits are organized into opponent channels.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p023fig01.14 gated dipole opponent process: sustained on-response; transient off-response.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p024fig01.15 READ circuit: REcurrent Associative Dipole.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p025fig01.16 Cognitive-Emotional-Motor (CogEM) model: sensory cortex, amygdala, PFC.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p025fig01.17 Sensory-drive heterarchy vs drive hierarchy.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p026fig01.18 Inverted-U behaviour vs arousal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p027fig01.19 ventral What [percept, class], dorsal Where [spatial represent, action].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p029tbl01.01 complementary streams [visual boundary, what-where, perception & recognition, object tracking, motor target].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p030fig01.20 neo-cortex 6 layers: same canonical laminar design cart [vision, speech, cognition].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p030tbl01.02 complementary streams: What- [rapid, stable] learn invariant object categories, Where- [labile spatial, action] actions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p032fig01.21 [Retina, LGNs, V[1,2,3,4], MT] to What & Where areas.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p035fig01.22 Presentation [normal, silence, noise replaced].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p036fig01.23 working memory [longer list, bigger chunk]s.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p037fig01.24 sentence [learn, store, class] via 3 streams.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p038fig01.25 ART Matching Rule stabilizes learning: [real time learn, object attention].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p039tbl01.03 [consciousness, movement] links: visual, auditory, emotional.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p042tbl01.04 six main resonances which support different kinds of conscious awareness.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p051fig02.01 laterial inhibition: darker appears darker; lighter appears lighter.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p052fig02.02 Adaptive Resonance reactivation: features bottom-up; categories top-down.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p057fig02.03 neuron basic [anatomy, physiology].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p058fig02.04 Learning a global arrow in time.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p059fig02.05 Effects of intertrial and intratrial intervals.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p059fig02.06 Bow due to backward effect in time.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p060fig02.07 Error gradients depend on list position.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p061fig02.08 neural networks can learn forward and backward associations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p063fig02.09 Short Term Memory (STM): Additive Model.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p064fig02.10 STM Shunting Model, mass action in membrane equations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p064fig02.11 MTM habituative transmitter gate; LTM gated steepest descent learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p065fig02.12 Three sources of neural network research: [binary, linear, nonlinear].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p068fig02.13 Hartline: lateral inhibition in limulus retina of horseshoe crab.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p068fig02.14 Hodgkin and Huxley: spike potentials in squid giant axon.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p071fig02.15 Noise-Saturation Dilemma: functional unit is a spatial activity pattern.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p071fig02.16 Noise-Saturation Dilemma:sensitivity to ratios of inputs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p072fig02.17 Vision: brightness constancy, contrast normalization.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p072fig02.18 Vision: brightness contrast, conserve a total quantity, total activity normalization.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p073fig02.19 Computing in a bounded activity domain, Gedanken experiment.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p073fig02.20 Shunting saturation occurs when inputs get larger to non-interacting cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p073fig02.21 Shunting saturation: how shunting saturation turns on all of a cells excitable sites as input intensity increases.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p073fig02.22 Computing with patterns: how to compute the pattern-sensitive variable.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p074fig02.23 Shunting on-center off-surround network: no saturation! infinite dynamical range, conserve total activity.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p075fig02.24 Membrane equations of physiology: shunting equation, not additive.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p076fig02.25 Weber law, adaptation, and shift property, convert to logarithmic coordinates.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p076fig02.26 Mudpuppy retina neurophysiology, adaptation- sensitivity shifts for different backgrounds.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p077fig02.27 Mechanism: cooperative-competitive dynamics, subtractive lateral inhibition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p077fig02.28 Weber Law and adaptation level: hyperpolarization vs silent inhibition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p078fig02.29 Weber Law and adaptation level: adaptation level theory.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p078fig02.30 Noise suppression: attenuate zero spatial frequency patterns- no information.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p078fig02.31 Noise suppression -> pattern matching: mismatch (out of phase) suppressed, match (in phase) amplifies pattern.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p079fig02.32 Substrate of resonance: match (in phase) of BU and TD input patterns amplifies matched pattern due to automatic gain control by shunting terms.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p080fig02.33 How do noise suppression signals arise: symmetry-breaking during morphogenesis, opposites attract rule.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p080fig02.34 Symmetry-breaking: dynamics and anatomy.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p081fig02.35 Ratio contrast detector: reflectance processing, contrast normalization, discount illuminant.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p081fig02.36 [Noise suppression, contour detection]: uniform patterns are suppressed, contrasts are selectively enhanced, contours are detected.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p082fig02.37 Modelling method and cycle (brain): proper level of abstraction; cannot derive a brain in one step.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p085fig02.38 Modelling method and cycle, technological applications: at each stage [behavioural data, design principles, neural data, math model and analysis].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p087fig03.01 Emerging unified theory of visual intelligence: BU-TD interactions overcome complementary processing deficiencies.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p089fig03.02 What do you think lies under the two grey disks (on a checkers board).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p090fig03.03 Kanizsa square and reverse-contrast Kanizsa square precepts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p091fig03.04 blind spot and veins can occlude light to the retina.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p092fig03.05 A cross-section of the retinal layers: light stimuli need to go through all retinal layers.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p093fig03.06 Every line is an illusion!: boundary completion, surface filling-in.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p094fig03.07 Complementary properties of boundaries and surfaces.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p095fig03.08 Computer simulation of a Kanizsa square percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p095fig03.09 Simulation of a reverse-contrast Kanizsa square percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p096fig03.10 The visual illusion of eon color spreading.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p096fig03.11 Another example of neon color spreading.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p098fig03.12 Einstein's face: [edges, texture, shading] are overlaid.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p100fig03.13 Ehrenstein percept weakened as lines deviate from perpendicular.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p100fig03.14 Perpendicular induction at line ends: [locally [,un], globally] preferred.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p100fig03.15 orientations: [transient before, equilibrium after] choice.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p102fig03.16 Ts and Ls group together based on shared orientations, not identities.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p102fig03.17 Positions of squares give rise to a percept of three regions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p103fig03.18 different spatial arrangements of inducers: emergent [horizontal, diagonal] groupings, but inducers have vertical orientations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p103fig03.19 [diagonal, perpendicular, parallel]: thats how multiple orientations can induce boundary completion of an object.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p104fig03.20 Sean Williams: how boundaries can form.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p104fig03.21 Four examples of how emergent boundaries can form in response to different kinds of images.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p105fig03.22 3D vision and figure-ground separation: [multiple-scale, depth-selective] boundary webs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p105fig03.23 pointillist painting: Georges Seurat, A Sunday on la Grande Jatte.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p106fig03.24 Do these ideas work on hard problems: Synthetic Aperture Radar [discount illuminant, filling-in, boundaries].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p107fig03.25 Matisse, The Roofs of Collioure.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p107fig03.26 drawing directly in color leads to colored surface representations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p108fig03.27 Matisse: Open Window, Collioure, [continuously, sparsely] indiced surfaces.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p108fig03.28 Baingio Pinna, Watercolor illusion filled-in regions bulge in depth, [multiple-scale, depth-selective] boundary web.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p109fig03.29 Chiaroscuro- Rembrandt self-portrait; Trompe l oeil- Graham Rust.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p109fig03.30 Jo Baer triptych: Primary Light Group [red, green, blue].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p110fig03.31 Henry Hensche painting: The Bather, is suffused with light.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p110fig03.32 Claude Monet painting: Poppies Near Argenteuil.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p112fig03.33 Boundary web gradient can cause self-luminosity, similar to watercolor illusion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p112fig03.34 Examples of Ross Bleckner's self-luminous paintings.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p113fig03.35 Highest Luminance As White (HLAW) rule, Hans Wallach.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p113fig03.36 Blurred Highest Luminance As White (BHLAW) rule.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p114fig03.37 Perceived reflectance vs cross-section of visual field: anchored brightness, self-luminous.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p114fig03.38 Color field painting: Jules Olitski, spray paintings of ambiguous depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p115fig03.39 Gene Davis paintings [full color, monochromatic]: percepts of grouping and relative depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p116fig03.40 Mona Lisa by Leonardo da Vinci: T-junctions and perspective cues give strong percept of depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p117fig03.41 Boundary contours and feature contours- no inhibition, feature signals survive and spread.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p117fig03.42 Two paintings by Frank Stella.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p120fig03.43 Four paintings by Monet of the Rouen cathedral under different lighting conditions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p120fig03.44 Rouen Cathedral at sunset (Monet 1892-1894): equiluminant, obscured and less depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p121fig03.45 Rouen Cathedral full sunlight (Monet 1892-1894): non-uniform lighting, more detail and depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p121fig03.46 Rouen Cathedral full sunlight (Monet 1892-1894): T-junctions greater depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p123fig04.01 Combining stabilized images with filling-in.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p124fig04.02 closed boundaries prevent brightness from flowing.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p126fig04.03 Color constancy: compute ratios, discount the illuminant, compute lightness.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p128fig04.04 reflectance changes at contours: fill-in illuminant-discounted colors.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p129fig04.05 reflectance changes at contours: color contours.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p129fig04.06 reflectance changes at contours: fill-in color; resolve uncertainty.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p130fig04.07 brightness constancy: boundary peaks spatially narrower than feature peaks.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p131fig04.08 brightness constancy: discount illuminant, ratio-sensitive feature contours.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p131fig04.09 Simulation of brightness contrast.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p132fig04.10 Simulation of brightness assimilation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p132fig04.11 Simulation of double step and COCE.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p133fig04.12 Simulation of the 2D COCE.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p133fig04.13 Contrast constancy, relative luminances can be reversed, discounting illuminant.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p134fig04.14 Experiments on filling-in: in-the-act; simulation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p138fig04.15 oriented filtering to grouping and boundary completion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p139fig04.16 Simplest simple cell model: threshold linear, half-wave rectification.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p140fig04.17 Complex cells: pool like-oriented simple cells of opposite polarity.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p141fig04.18 Binocular Disparity to reconstruct depth from 2D retinal inputs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p141fig04.19 Laminar cortical circuit for complex cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p142fig04.20 [, reverse-]Glass patterns give rise to different boundary groupings.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p143fig04.21 Hierarchical resolution of uncertainty for a given field size.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p144fig04.22 End Gap and End Cut simulation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p145fig04.23 A perceptual disaster in the feature contour system.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p145fig04.24 Hierarchical resolution of uncertainty- End Cuts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p146fig04.25 How are end cuts created: two stages of short-range competition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p148fig04.26 End cut during neon color spreading via 2 stages.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p149fig04.27 Bipole cells boundary completion: long cooperation & short inhibition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p150fig04.28 Bipole property: boundary completion via long-range cooperation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p151fig04.29 bipole cells in cortical area V2: first neurophysiological evidence.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p151fig04.30 anatomy: horizontal connections in V1.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p152fig04.31 Bipoles through the ages.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p153fig04.32 Double filter and grouping network.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p156fig04.33 emergent boundary groupings can segregate textured regions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p157fig04.34 texture: Boundary Contour System resolves errors of complex channels model.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p159fig04.35 Spatial impenetrability prevents grouping.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p159fig04.36 Graffiti art by Banksy: amodal boundary completion; spatial impenetrability.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p161fig04.37 Boundary Contour System model: analog-sensitive boundary completion Kanizsas.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p162fig04.38 Cooperation and competition during grouping.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p163fig04.39 LAMINART model explains key aspects of visual cortical anatomy and dynamics.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p164fig04.40 Koffka-Benussi ring.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p165fig04.41 Kanizsa-Minguzzi ring.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p166fig04.42 Computer simulation of Kanizsa-Minguzzi ring percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p167fig04.43 T-junction sensitivity: image, Bipole cells, boundary.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p168fig04.44 main [boundary, surface] formation stages: LGN-> V1-> V2-> V4.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p168fig04.45 ON and OFF feature contours: filled-in regions when adjacent to boundary.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p170fig04.46 regions can fill-in feature contour inputs when [adjacent to, collinear with] boundary contour inputs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p170fig04.47 A double-opponent network processes output signals from FIDOs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p171fig04.48 closed boundaries -> filling-in; open boundaries -> color spread.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p171fig04.49 DaVinci stereopsis and occlusion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p173fig04.50 closed boundary at prescribed depth: addition of [bi, mon]ocular boundaries.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p174fig04.51 figure-ground separation, complementary consistency [boundaries, surfaces].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p174fig04.52 Stereogram surface percepts: surface lightnesses are segregated in depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p176fig04.53 OC-OS [within position, across depth]: brighter Kanizsas look closer.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p178fig04.54 figure-ground separation: bipole cooperation and competition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p178fig04.55 Amodal completion of boundaries and surfaces in V2.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p179fig04.56 Visible surface 3D perception: boundary enrichment, surface filling-in.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p181fig04.57 relative contrasts induce: unimodal and bistable transparency; or flat 2D surface.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p182fig04.58 LAMINART explains many percepts of transparency.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p186fig05.01 Learn many-to-one (compression, naming), one-to-many (expert knowledge) maps.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p186fig05.02 Many-to-one map, two stage compression: [visual, auditory] categories.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p186fig05.03 Many-to-one map: IF-THEN rules: [symptom, test, treatment]s; length of stay.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p189fig05.04 hippocampus & several brain regions [learn, remember] throughout life.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p192fig05.05 LGN [ON, OFF] cells respond differently to [side, end]s of lines.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p192fig05.06 BU-TD circuits between the LGN and cortical area V1, ART Matching Rule.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p193fig05.07 detailed connections between [retinal ganglion cells, LGN, V1].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p193fig05.08 LGN [activation, inhibition], with[, out] top-down feedback.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p194fig05.09 [feature, boundary] contours from Ehrenstein disk stimulus.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p198fig05.10 Competitive learning and Self-Organized Maps (SOMs).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p199fig05.11 Instar learning: bottom-up adaptive filter for feature patterns.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p200fig05.12 Duality of [outstar, instar] networks.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p200fig05.13 Expectations focus attention: instar BU filters, outstar TD expectations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p200fig05.14 Outstar learning, both [in, de]creases for LTM to learn STM pattern.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p201fig05.15 Spatial learning pattern, outstar learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p202fig05.16 Geometry of choice and learning, classifying vector.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p202fig05.17 Geometry of choice and learning, trains the closest LTM vector.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p205fig05.18 catastrophic forgetting due to [competition, associative] learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p207fig05.19 ART: [attentional, orienting] systems learn novel categories, no catastophic forgetting.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p211fig05.20 [PN match, N200 mismatch] computationally complementary potentials.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p211fig05.21 ART predicted correlated P120-N200-P300 ERPs during oddball learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p213fig05.22 If inputs incorrectly activate a category, how to correct the error.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p213fig05.23 A [category, symbol, other] cannot determine whether an error has occurred.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p214fig05.24 Learning top-down expectations occurs during bottom-up learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p214fig05.25 Error correction: [learn, compare] TD-BU inputs, Processing Negativity ERP.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p214fig05.26 Mismatch triggers nonspecific arousal, N200 ERP from orienting system.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p215fig05.27 Every event has [specific attentional cue, nonspecific orienting arousal].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p215fig05.28 BU+TD mismatch arousal and reset if degree of match < ART vigilance.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p220fig05.29 Vigilance [excitation: search better match, inhibition: resonance & learning].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p221fig05.30 predictive error -> vigilance increase just enough -> minimax learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p221fig05.31 Fuzzy ARTMAP can associate categories between ART networks, minimax learn.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p224fig05.32 Learning the alphabet with two different levels of vigilance.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p225fig05.33 Some early ARTMAP benchmark studies (no image - link instead).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p225fig05.34 ARTMAP learned maps of natural terrains better than AI expert systems.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p226fig05.35 Code instability sequences: [competitive learning, self-organizing map].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p226fig05.36 catastrophic forgetting without ART Matching Rule due to superset recoding.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p228fig05.37 neurotrophic Spectrally Timed ART (nSTART) model.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p230fig05.38 Synchronous Matching ART (SMART) spiking neurons in laminar cortical hierarchy.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p231fig05.39 SMART: vigilance increase via nucleus basalis of Meynert acetylcholine.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p232fig05.40 SMART generates γ oscillations for good match; β oscillations for bad match.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p232fig05.41 mismatch reset interlaminar events sequence [data, SMART predictions].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p233fig05.42 Evidence for the [gamma, beta] prediction in 3 parts of the brain.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p236fig05.43 nucleus basalis of Meynert releases ACh, reduces AHP, increases vigilance.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p240fig05.44 models using only local computations look like an ART prototype model.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p240fig05.44 The 5-4 category structure example: ART learns the same kinds of categories as human learners.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p242fig05.46 Distributed ARTMAP variants learn the 5-4 category structure.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p245fig05.47 [long-range excitatory, short-range disynaptic inhibitory] connections realize the bipole grouping law.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p246fig05.48 LAMINART model: BU adaptive filtering, horizontal bipole grouping, TD attentional matching.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p248fig05.49 LAMINART explains Up and Down states during slow wave sleep, ACh dynamics.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p252fig06.01 surface-shroud resonance forms as objects bid for spatial attention.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p253fig06.02 Surface-shroud resonance BU-TD OC-OS: perceptual surfaces -> competition -> spatial attention.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p254fig06.03 ARTSCAN Search model learns to recognize and name invariant object categories.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p255fig06.04 The ARTSCAN Search for a desired target object in a scene: Wheres Waldo.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p257fig06.05 Spatial attention flows along object boundaries: Macaque V1.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p258fig06.06 Neurophysiological data & simulation: attention can flow along a curve.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p258fig06.07 Top-down attentional spotlight becomes a shroud.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p259fig06.08 dARTSCN spatial attention hierarchy [Fast Where, Slow What] stream.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p260fig06.09 Crowding: visible objects & confused recognition, increased flanker spacing at higher eccentricity.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p260fig06.10 cortical magnification transforms coordinates: artesian (retina) to log polar (V1).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p261fig06.11 Crowding: visible objects and confused recognition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p261fig06.12 A more serial search is needed due to overlapping conjunctions of features.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p265fig06.13 basal ganglia gate perceptual, cognitive, emotional, etc through parallel loops.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p267fig06.14 Perceptual consistency and figure-ground separation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p268fig06.15 saccades within an object: figure-ground outputs control eye movements via V3AA.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p270fig06.16 Predictive remapping of eye movements, from V3A to LIP.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p271fig06.17 Persistent activity in IT to [view, position, size]-invariant category learning by positional ARTSCAN.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p272fig06.18 pARTSCAN: positionally-invariant object learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p272fig06.19 persistent activity needed to learn positionally-invariant object categories.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p273fig06.20 pARTSCAN simulation of Li & DiCarlo IT cell swapping data.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p274fig06.21 pARTSCAN [position invariance, selectivity] trade-off of Zoccolan etal 2007.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p274fig06.22 pARTSCAN: IT cortex processes image morphs with high vigilance.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p275fig06.23 IT responses to image morphs, data vs model.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p275fig06.24 Sterogram surface percepts: surface lightnesses are segregated in depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p276fig06.25 saccades: predictive gain fields [binocular fusion, filling-in of surfaces].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p277fig06.26 Predictive remapping maintains binocular boundary fusion as eyes move.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p278fig06.27 knowing vs seeing resonances: What [knowing, feature-prototype], Where [seeing, surface-shroud].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p278fig06.28 knowing vs seeing resonances: visual agnosia- reaching without knowing.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p283fig07.01 Boundary competition: spatial habituative gates, orientation gated dipole, bipole grouping.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p284fig07.02 Persistence decreases with flash illuminance & duration [data, simulations].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p285fig07.03 Persistence decrease: rebound to input offset inhibits bipole cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p286fig07.04 Illusory contours persist longer than real contours.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p286fig07.05 Illusory contours inhibited by OFF cell rebounds, propagate to center.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p287fig07.06 Persistence: [less, more] as adaptation orientation [same, orthogonal].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p287fig07.07 Persistence increases with distance, due to weaker spatial competition in hypercomplex cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p290fig08.01 Motion pools contrast-sensitive information moving in the same direction.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p291fig08.02 Complex cells respond to motion: opposite [direction, contrast polarities].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p292fig08.03 Visual aftereffects: [form- MacKay 90 degree, motion- waterfall  180].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p293fig08.04 Local vs overall motion: aperture problem of EVERY neurons receptive field.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p295fig08.05 sparse feature tracking signals [capture ambiguous, determine perceived] motion direction.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p296fig08.06 Simplest example of apparent motion: two dots turning on and off.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p296fig08.07 continuous motion illusions: [Beta with, Phi without] percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p297fig08.08 Delta motion when [luminance, contrast] of flash 2 is larger than flash 1.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p297fig08.09 motion in opposite directions perceived when 2 later flashes on either side of 1st flash.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p298fig08.10 motion speed-up perceived when flash duration decreases.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p298fig08.11 illusory contours: double illusion in V1-V2, motion V2-MT interaction.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p300fig08.12 Single flash: Gaussian receptive fields, recurrent OC-OS winner-take-all.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p300fig08.13 Nothing moves: [single flash, exponential decay], Gaussian peak fixed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p300fig08.14 Visual inertia: flash decay after the flash shuts off.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p301fig08.15 two flashes: cell activation by first waning while second one is waxing.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p301fig08.16 sum Gaussian flash activity profiles: [waning 1st, waxing 2nd] -> travelling wave.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p302fig08.17 maximum long-rang apparent motion: Gaussian kernel spans successive flashes.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p302fig08.18 G-wave theorem 1: wave moves continuously IFF L <= 2*K.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p303fig08.19 No motion vs motion at multiple scales: flash distance L, Gaussian width K.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p303fig08.20 G-wave theorem 2: [speed-up, scale] independent of [distance, scale size].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p304fig08.21 Equal half-time property: multiple scales generate motion percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p304fig08.22 Korte Laws: ISIs in the hundreds of milliseconds can cause apparent motion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p305fig08.23 Ternus motion: ISI [small- stationary, intermediate- element, larger- group].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p305fig08.24 Reverse-contrast Ternus motion: ISI [small- stationarity, intermediate- group (not element!), larger- group] motion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p306fig08.25 Motion BCS model [explain, simulate]s long-range motion percepts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p306fig08.26 3D FORMOTION model: track objects moving in depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p307fig08.27 Ternus motion: [element- weak, group- strong] transients, element [visual persistence, perceived stationarity].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p308fig08.28 Ternus group motion: Gaussian filter of 3 flashes forms one global maximum.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p310fig08.29 when individual component motions combine, their perceived direction & speed changes.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p311fig08.30 3D FORMOTION model: feature tracking [get directional, inhibit inconsistent] signals.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p311fig08.31 Motion BCS stages: locally ambiguous motion signals -> globally coherent percept, solving the aperture problem.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p312fig08.32 Schematic of motion filtering circuits.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p312fig08.33 Processing motion signals by a population of speed-tuned neurons.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p314fig08.34 VISTARS navigation model: FORMOTION front end for navigational circuits.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p315fig08.35 How to select correct direction and preserve speed estimates.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p316fig08.36 Motion capture by directional grouping feedback.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p317fig08.37 Motion capture by directional grouping feedback: [short, long]-range filters, transient cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p319fig08.38 Solving the aperture problem takes time.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p320fig08.39 Simulation of the barberpole illusion direction field at two times.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p321fig08.40 [, in]visible occluders [do, not] capture boundaries they share with moving edges.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p322fig08.41 motion transparency: asymmetry [near, far], competing opposite directions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p323fig08.42 Chopsticks: motion separation in depth via [, in]visible occluders [display, percept].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p324fig08.43 ambiguous X-junction motion: MT-MST directional grouping bridges the ambiguous position.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p325fig08.44 The role of MT-V1 feedback:  [motion-form feedback, bipole boundary completion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p325fig08.45 Closing formotion feedback loop [MT, MST]-to-V1-to-V2-to-[MT, MST].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p326fig08.46 How do we perceive relative motion of object parts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p327fig08.47 Two classical examples of part motion: Symmetrically moving inducers; Duncker wheel.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p328fig08.48 vector decomposition: (retinal - common = part) motion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p328fig08.49 What is the mechanism of vector decomposition, prediction: directional peak shift.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p329fig08.50 How is common motion direction computed?  retinal motion->  bipole grouping (form stream)->  V2-MT formotion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p329fig08.51 Large and small scale boundaries differentially form illusory contours.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p330fig08.52 Correct motion directions after the peak shift top-down expectation acts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p330fig08.53 Simulation of the various directional signals of the left dot through time.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p331fig08.54 Motion directions of a single dot moving slowly along a cycloid curve through time.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p331fig08.55 Duncker Wheel, large: stable rightward motion at the center captures motion at the rim.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p332fig08.56 Duncker Wheel, small: wheel motion as seen when directions are collapsed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p332fig08.57 MODE (MOtion DEcision) model: Motion BCS -> saccadic target selection -> basal ganglia.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p333fig08.58 LIP responses during RT task correct trials: coherence and [activation, inhibition].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p334fig08.59 LIP responses for FD task: predictiveness decreases with increasing coherence.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p334fig08.60 [RT, FD] task behavioral data: more coherence in the motion causes more accurate decisions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p335fig08.61 RT task behavioural data: reach time (ms) vs % coherence.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p335fig08.62 LIP encodes not only where, but also when, to move the eyes - No Bayes.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p338fig09.01 optic flow through brain regions: moving observer [navigate, track] moving object.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p338fig09.02 Heading (focus of velocity field) from optic flow: humans accurate +- 1 to 2 degrees.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p339fig09.03 Heading with [body move, eye rotate, combined] -> optic flow [expand, translate, rotate].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p339fig09.04 How can translation flow (eye rotation) be subtracted from spiral flow to recover the expansion flow.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p340fig09.05 efference copy command: may use outflow movement commands to eye muscles.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p340fig09.06 Corollary discharges from outflow movement commands that move muscles.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p340fig09.07 Log polar remapping of optic flow:  [expansion, circular] motion maps to single direction.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p341fig09.08 optic flows [retina, V1, MT, MSTd, parietal cortex], V1 log polar mapping.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p341fig09.09 MSTd cells are sensitive to [spiral, rotation, expansion] motion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p342fig09.10 Retina -> log polar -> MSTd cell, heading eccentricity.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p342fig09.11 importance of efference copy in real movements.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p343fig09.12 two retinal views of the Simpsons: [separate, recognize] overlapping figures.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p343fig09.13 How do our brains figure out which views belong to which pear.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p344fig09.14 Heading sensitivity unimpaired: MT tuning width 38°, MSTd spiral tuning 61°.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p345fig09.15 MT double opponent directional fields: relative motions [objects, backgrounds].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p346fig09.16 macrocircuit of 13 brain regions used to move the eyes.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p347fig09.17 leftward eye movement model: retina-> MT-> MST[v,d]-> pursuit.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p347fig09.18 MST[v,d] circuits enable predictive target tracking by the pursuit system.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p348fig09.19 MSTv cells: target speed on retina, background speed on retina, pursuit speed command.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p349fig09.20 Steering from optic flow: goals are attractors, obstacles are repellers.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p349fig09.21 Steering dynamics goal approach: [obstacle, goal, heading] -> steering.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p350fig09.22 negative Gaussian of an obstacle: avoid obstacle without losing sight of goal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p350fig09.23 Unidirectional transient cells: [lead, trail]ing boundaries, driving video.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p351fig09.24 Directional transient cells respond most to motion in their preferred directions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p351fig09.25 M+ computes global motion estimate from noisy local motion estimates.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p352fig09.26 heading direction final stage: beautiful optic flow, accuracy matches humans.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p354fig10.01 [Top-down attention, folded feedback] supports predicted ART Matching Rule.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p355fig10.02 seeing vs knowing distinction is difficult because they interact so strongly.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p356fig10.03 Laminar computing: [self-stabilize learning, fuse [BU pre-,TD]attentive processing, perceptual grouping no analog sensitivity].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p357fig10.04 Laminar Computing: combines feed[forward, back], [analog, digital], [pre,]attentive learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p359fig10.05 Activation of V1 by direct excitatory signals from LGN to layer 4 of V1.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p359fig10.06 Why another layer 6-to-4 signal: on-center off-surround.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p359fig10.07 Together [LGN-to-4 path, 6-to-4 OC-OS] do contrast normalization if cells obey shunting or membrane equation dynamics.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p360fig10.08 [IC 6-to-4, BU-OS LGN-to-6-to-4] excitations BOTH needed to activate layer 4, ART Matching Rule.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p360fig10.09 Grouping starts in layer 2-3: long-range horizontal excitation, short-range inhibition of target pyramidal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p361fig10.10 Bipole property controls perceptual grouping: inputs [excitatory sum, inhibitory normalize].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p362fig10.11 Final grouping: folded feedback, strongest enhanced on-center, weaker suppressed off-surround, interlaminar functional columns.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p363fig10.12 V2 repeats V1 circuitry at larger spatial scale.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p364fig10.13 6-to-4 decision circuit common to [BU adaptive filter, intracortical grouping, top-down intercortical attention].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p364fig10.14 Explanation: grouping and attention share the same modulatory decision circuit.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p367fig10.15 Attention protects target from masking stimulus.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p367fig10.16 Flankers can enhance or suppress targets.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p368fig10.17 Attention has greater effect on low contrast targets.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p368fig10.18 Texture reduces response to a bar: [iso-orientation, perpendicular] suppression.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p369fig10.19 Unconscious learning of motion direction, without [extra-foveal attention, awareness] of stimuli.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p371fig11.01 FACADE theory explains how the 3D boundaries and surfaces are formed to see the world in depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p372fig11.02 3D surface filling-in of [lightness, color, depth] by a single process: FACADE.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p373fig11.03 Both [contrast-specific binocular fusion, contrast-invariant boundary perception] are needed to see the world in depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p374fig11.04 Three processing stages of [monocular simple, complex] cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p374fig11.05 Contrast constraint on binocular fusion: only contrasts which are derived from the same objects in space are binoculary matched.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p375fig11.06 Binocular fusion by obligate cells in V1-3B when =[left,right] contrasts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p375fig11.07 3D LAMINART: [mo, bi]nocular simple cells binocularly fuse like image contrasts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p376fig11.08 Correspondance problem: How does the brain inhibit false matches. contrast constraint not enough.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p376fig11.09 V2 disparity filter solves correspondence problem: false matches suppressed by line-of-sight inhibition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p376fig11.10 3D LAMINART with disparity filter: 3D boundary representations via bipole grouping cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p377fig11.11 DaVinci stereopsis: monocular information and depth percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p378fig11.12 3D LAMINART: V2 monocular+binocular line of sight inputs -> depth perception.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p379fig11.13 3D LAMINART, DaVinci stereopsis (occlusion): emergent from simple mechanisms working together.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p380fig11.14 3D LAMINART, DaVinci stereopsis (polarity): same explanation as occlusion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p381fig11.15 DaVinci stereopsis variant of (Gillam, Blackburn, Nakayama 1999): same mechanisms.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p382fig11.16 DaVinci stereopsis of [3 narrow, one thick] rectangles: same explanation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p383fig11.17 Venetian blind effect: [left, right] eye matching bars.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p384fig11.18 Venetian blind effect: Surface[, -to-boundary] surface contour signals.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p385fig11.19 Dichoptic masking: [left, right] images have sufficiently different contrasts.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p385fig11.20 Dichoptic masking, Panum's limiting case: simplified version of Venetian blind effect.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p386fig11.21 Craik-O'Brien-Cornsweet Effect: 2D surface at a very near depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p387fig11.22 Julesz stereogram: boundaries with[out, ] surface contour feedback.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p388fig11.23 Sparse stereogram, large regions of ambiguous white: correct surface in depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p388fig11.24 depth-ambiguous feature contours: boundary groups lift to correct surface in depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p389fig11.25 Boundaries: not just edge detectors, or a shaded ellipse would look [flat, uniformly gray].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p390fig11.26 Multiple-scale depth-selective groupings determine perceived depth.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p391fig11.27 Multiple-scale grouping and size-disparity correlation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p391fig11.28 Ocular dominance columns, LGN mappings into layer 4C of V1.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p392fig11.29 3D vision figure-ground separation: multiple-scale, depth-selective boundary webs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p392fig11.30 How multiple scales vote for multiple depths, scale-to-depth and depth-to-scale maps.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p393fig11.31 LIGHTSHAFT model: determining depth-from-texture percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p393fig11.32 Kulikowski stereograms: binocular matching of out-of-phase [Gaussians, rectangles].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p394fig11.33 Kaufman stereogram: simultaneous fusion and rivalry.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p395fig11.34 3D LAMINART vs 7 other rivalry models: stable vision and rivalry.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p396fig11.35 Three properties of bipole boundary grouping in V2: boundaries oscillate with rivalry-inducing stimuli.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p397fig11.36 temporal dynamics of [rivalrous, coherent] boundary switching.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p398fig11.37 Simulation of the no swap baseline condition (Logothetis, Leopold, Sheinberg 1996).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p399fig11.38 Simulation of the swap condition of (Logothetis, Leopold, Sheinberg 1996).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p399fig11.39 Simulation of the eye rivalry data of (Lee, Blake 1999).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p400fig11.40 How do ambiguous 2D shapes contextually define a 3D object form.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p401fig11.41 3D LAMINART: [angle, disparity-gradient] cells learn 3D representations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p401fig11.42 hypothetical cortical hypercolumn: how [angle, disparity-gradient] cells may self-organize during development.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p402fig11.43 A pair of disparate images of a scene from the University of Tsukuba.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p402fig11.44 3D LAMINART disparities [5, 6, 8, 10, 11, 14]: images of objects in common depth planes.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p403fig11.45 SAR processing by multiple scales: reconstruction of a SAR image.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p405fig12.01 [What ventral, Where-How dorsal] cortical streams for [audition, vision].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p406fig12.02 Three S's of movement: Synergy formation, muscle Synchrony, volitional Speed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p407fig12.03 Motor cortical cells: vectors for [direction, length] of commanded movement.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p409fig12.04 VITE simulations: difference vector emergent from network interactions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p410fig12.05 VITE: velocity profile invariance [short, long] movements for same GO signal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p410fig12.06 Monkeys transform movement: 2 -> 10 o'clock target, 50 or 100 msec after activation of 2 o'clock target.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p411fig12.07 VITE: higher peak velocity due to target switching.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p411fig12.08 GO signals gate agonist-antagonist [difference, present position] vector processing stages.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p412fig12.09 Vector Associative Map: difference vector mismatch learning calibrates [target, present] position vectors.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p413fig12.10 VITE: cortical area [4,5] combine [trajectory, inflow] signals from [spinal cord, cerebellum] for [variable loads, obstacles].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p414fig12.11 [data, simulation]s from cortical areas 4 and 5 during a reach.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p415fig12.12 [VITE, FLETE, cerebellar, opponent muscle] model for trajectory formation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p416fig12.13 DIRECT model: Endogenous Random Generator learns volitional reaches.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p416fig12.14 DIRECT reaches [unconstrained, with TOOL, elbow@140°, blind].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p417fig12.15 From Seeing & Reaching (DIRECT) to Hearing & Speaking (DIVA): homologous circular reactions, [tool use, coarticulation].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p418fig12.16 Anatomy of DIVA model processing stages.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p419fig12.17 Auditory continuity illusion: backwards in time through noise, ART Matching Rule.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p420fig12.18 ARTSTREAM: auditory continuity illusion, stream as a spectral-pitch resonance.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p422fig12.19 ARTSTREAM: derive streams from [pitch, source direction].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p423fig12.20 SPINET: log polar spatial sound frequency spectrum to distinct auditory streams.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p424fig12.21 Pitch shifts with component shifts, pitch vs lowest harmonic number.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p424fig12.22 Decomposition of a sound in terms of three of its harmonics.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p425fig12.23 ARTSTREAM: auditory continuity illusion- continuity does not occur without noise.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p426fig12.24 Spectrograms of -ba- and -pa- show the transient and sustained parts of their spectrograms.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p428fig12.25 ARTSPEECH: auditory-articulatory feedback loop & imitative map, [auditory, motor] dimensionally consistent, motor theory of speech.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p430fig12.26 NormNet: speaker normalization via specializations of mechanisms for auditory streams.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p431fig12.27 ARTSTREAM & NormNet strip maps: variants of occular dominance columns in visual cortex.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p432fig12.28 SpaN: spatial representations of numerical quantities in the parietal cortex.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p433fig12.29 What stream: place-value [number map, language category]s; to Where stream: numerical strip maps.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p436fig12.30 cARTWORD: laminar speech model- future disambiguates past, resonanct wave propagates through time.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p436fig12.31 Working memory: temporal order STM is often imperfect, then stored in LTM.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p437fig12.32 Free recall bowed serial position curve.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p437fig12.33 Working memory models: item and order, or competitive queuing.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p438fig12.34 LTM Invariance Principle: [STM, LTM] new words must not cause catastrophic forgetting of subwords.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p439fig12.35 Normalization Rule: total activity of working memory has upper bound independent of number of items.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p439fig12.36 [Item, Order] working memories: [content-addressable categories, temporal order, [excitatory, inhibitory] recurrence, rehearsal wave.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p440fig12.37 Normalization Rule: primacy bow as more items stored.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p441fig12.38 LTM Invariance Principle: new events do not change the relative activities of past event sequences.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p442fig12.39 [LTM invariance, Normalization Rule] Shunt normalization -> STM bow.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p442fig12.40 [LTM Invariance, normalization, STM steady attention]: only [primacy, bowed] gradients of activity can be stored.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p443fig12.41 Neurophysiology of sequential copying: [primacy gradient, self-inhibition].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p444fig12.42 LIST PARSE: Laminar cortical model of working memory and list chunking.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p445fig12.43 LIST PARSE laminar Cognitive Working Memory in VPC, is homologous to visual LAMINART circuit.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p446fig12.44 LIST PARSE: immediate free recall experiments transposition errors, list length.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p447fig12.45 LIST PARSE: order errors vs serial position with extended pauses.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p448fig12.46 Masking Field working memory is a multiple-scale self-similar recurrent shunting on-center off-surround network.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p449fig12.47 Masking Field self-similar [recurrent inhibitory, top-down excitatory] signals to the item chunk working memory.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p452fig12.48 Perceptual integration of acoustic cues: [silence vs noise] durations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p453fig12.49 ARTWORD: acoustic cues, phonetic [features, WM], Masking Field unitized lists, gain control.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p453fig12.50 ARTWORD perception cycle: sequences-> chunks-> compete-> top-down expectations-> item working memory->  develops item-list resonance.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p454fig12.51 Resonant transfer: as silence interval increases, a delayed additional item can facilitate perception of a longer list.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p455fig12.52 cARTWORD dynamics 1-2-3: resonant activity in item and feature layers corresponds to conscious speech percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p456fig12.53 cARTWORD dynamics 1-silence-3: Gap in resonant activity of 1-silence-3 in [item, feature] layers corresponds to perceived silence.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p456fig12.54 cARTWORD dynamics: 1-noise-3: Resonance of 1-2-3 in [item, feature] layers  restores item 2.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p457fig12.55 cARTWORD dynamics 1-noise-5: Figures 12.[54, 55] future context can disambiguate past noisy sequences that are otherwise identical.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p459fig12.56 Rank information on the position of an item in a list using numerical hypercolumns in the prefrontal cortex.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p460fig12.57 lisTELOS for saccades: prototype to [store, recall] other [cognitive, spatial, motor] information.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p461fig12.58 lisTELOS shows [BG nigro-[thalamic, collicular], FEF, ITa, PFC, PNR-THAL, PPC, SEF, SC, V1, V4-ITp, Visual Cortex input] and [GABA].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p462fig12.59 TELOS: balancing reactive vs. planned movements.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p463fig12.60 Rank-related activity in PFC and SEF from two different experiments.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p464fig12.61 SEF saccades microstimulating electrode: spatial gradient of habituation alters order, but not which, saccades are performed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p464fig12.62 The most habituated position is foveated last: because stimulation spreads in all directions, saccade trajectories tend to converge.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p465fig12.63 lisTELOS and data: microstimulation biases selection so saccade trajectories converge toward a single location in space.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p467fig12.64 Some of the auditory cortical regions that respond to sustained or transient sounds.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p468fig12.65 [PHONET, ARTPHONE] linguistic properties: creates rate-invariant representations for variable-rate speech, paradoxical VC-CV category boundaries.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p469fig12.66 PHONET: relative duration of [consonant, vowel] pairs can [preserve, change] a percept.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p469fig12.67 PHONET [transient, sustained] cells that respond to certain [consonant transient, sustained vowel] sounds.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p471fig12.68 Mismatch vs resonant fusion: effect of silence interval length.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p473fig12.69 ART Matching Rule properties explain error rate and mean reaction time (RT) data from lexical decision experiments.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p474fig12.70 macrocircuit model to explain lexical decision task data.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p476fig12.71 Word frequency data model.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p481fig13.01 Cognitive-Emotional-Motor (CogEM): macrocircuit of [function, anatomy].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p483fig13.02 CogEM: motivated attention [closes cognitive-emotional feedback loop, focuses on relevant cues, blocks irrelevant cues].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p483fig13.03 CogEM: supported by anatomical connections [[sensory, orbitofrontal] cortices, amygdala].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p484fig13.04 Cognitive-Emotional resonance:  top-down feedback from the orbitofrontal cortex closes a feedback loop.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p484fig13.05 Classical conditioning: perhaps simplest kind of associative learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p485fig13.06 Classical conditioning: inverted-U vs InterStimulus Interval (ISI).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p485fig13.07 Paradigm of secondary conditioning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p486fig13.08 Blocking paradigm: cues lacking different consequences may fail to be attended.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p486fig13.09 Equally salient cues can be conditioned in parallel to an emotional consequence.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p486fig13.10 Blocking: both [secondary, attenuation of] conditioning at zero ISI.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p487fig13.11 CogEM : three main properties to explain how attentional blocking occurs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p488fig13.12 Motivational feedback and blocking.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p489fig13.13 CogEM and conditioning: positive ISI; inverted-U vs ISI.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p490fig13.14 Cognitive-Emotional circuit: for proper conditioning, sensory needs >= 2 processing stages.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p490fig13.15 CogEM is an ancient design that is found even in mollusks like Aplysia.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p492fig13.16 Polyvalent CS sampling and US-activated nonspecific arousal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p493fig13.17 Learning nonspecific arousal and CR read-out.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p494fig13.18 Learning to control nonspecific arousal and read-out of the CR: two stages of CS.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p494fig13.19 CogEM: secondary conditioning of [arousal, response], multiple [drive, input]s, motivational sets.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p496fig13.20 A single avalanche sampling cell can learn an arbitrary space-time pattern.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p497fig13.21 nonspecific arousal: primitive crayfish swimmerets, songbird pattern generator avalanche.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p498fig13.22 Adaptive filtering and Conditioned arousal: Towards Cognition, Towards Emotion.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p499fig13.23 Self-organizing avalanches [instars filter, serial learning, outstars read-out], Serial list learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p500fig13.24 Primary [excitatory, inhibitory] conditioning using opponent processes and their antagonistic rebounds.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p501fig13.25 Unbiased transducer in finite rate physical process: mass action by a chemical transmitter is the result.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p501fig13.26 Transmitter y [accumulation, release]:  y restored < infinite rate, evolution has exploited this.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p502fig13.27 Transmitter minor mathematical miracle [accumulation, release]: S*y = S*A*B div (A + S) (gate, mass action).png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p502fig13.28 Habituative transmitter gate: fast [increment, decrement]s of input lead to [overshoot, habituation, undershoot]s, Weber Law.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p503fig13.29 ON response to phasic ON input has Weber Law properties due to the habituative transmitter.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p504fig13.30 OFF-rebound transient due to phasic input offset: arousal level sets ratio ON vs OFF rebounds, Weber Law.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p504fig13.31 Behavioral contrast rebounds: decrease [food-> negative Frustration, shock-> positive Relief] reinforcers.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p505fig13.32 Behavioral contrast: [response suppression, antagonist rebound] both calibrated by shock levels.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p505fig13.33 Novelty reset- rebound to arousal onset: equilibrate to [I, J]; keep phasic input J fixed; interpret this equation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p506fig13.34 Novelty reset: rebound to arousal onset, reset of dipole field by unexpected event.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p506fig13.35 Shock [cognitive, emotional] effects: [reinforcer, sensory cue, expectancy].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p509fig13.36 Life-long learning: selective without [passive forgetting, associative saturation].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p510fig13.37 A disconfirmed expectation inhibits prior incentive, but is insufficient to prevent associative saturation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p510fig13.38 Dissociation of LTM read-[out, in]: dendritic action potentials as teaching signals, early predictions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p510fig13.39 Learn net dipole output pattern: [shunting competition, informational noise suppression] in affective gated dipoles, back-propagation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p512fig13.40 Conditioned excitor extinguishes: [learning, forgetting] phases, shock expectation disconfirmed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p513fig13.41 Conditioned inhibitor does not extinguish: [learn, forget] phases, same [CS, teacher] can be used.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p513fig13.42 Conditioned excitor extinguishes when expectation of shock is disconfirmed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p513fig13.43 Conditioned excitor extinguishes: expectation that -no shock- follows CS2 is NOT disconfirmed.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p514fig13.44 Analog of the COgEM model maps of [object X, proto-self], assembly of second-order map.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p519fig14.01 Coronal sections of prefrontal cortex.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p520fig14.02 pART [cognitive-emotional, working memory] dynamics: main brain [regions, connections].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p523fig14.03 MOTIVATOR model generalizes CogEM by including the basal ganglia: supports motivated attention for [, un]conditioned stimuli.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p524fig14.04 Basal ganglia circuit for dopaminergic Now Print signals from the substantia nigra pars compacta in response to unexpected rewards.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p530fig14.05 Visual [pop-out, search]-> reaction time experiments.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p531fig14.06 ARTSCENE: classification of scenic properties as texture categories.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p531fig14.07 ARTSCENE voting achieves even better prediction of scene type.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p532fig14.08 ARTSCENE: using [sequence, location]s of already experienced objects to predict [what, where] the desired object is.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p533fig14.09 ARTSCENE search [data, simulation]s for 6 pairs of images.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p540fig15.01 [Delay, trace conditioning] paradigms:  require a CS memory trace over the ISI.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p541fig15.02 nSTART hippocampal Cognitive-Emotional resonance: feeling of what happens, knowing causative event.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p541fig15.03 Timed responses from adaptively timed conditioning: Weber laws, inverted U as a function of ISI.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p542fig15.04 blinks of [nictitating membrane, eyelid] are adaptively timed: closure occurs at arrival of the US following the CS, obeys Weber Law.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p543fig15.05 Learning with two ISIs: each peak obeys Weber Law, strong evidence for spectral learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p543fig15.06 Circuit between [dentate granule, CA1 hippocampal pyramid] cells seems to compute spectrally timed responses.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p544fig15.07 Spectral timing: STM sensory representation-> Spectral activation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p544fig15.08 Habituative transmitter gate: spectral activities-> sigmoid signals-> gated by habituative transmitters.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p544fig15.09 Habituative transmitter gate: increases with accumulation, decreases from gated inactivation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p545fig15.10 A timed spectrum of gated sampling intervals.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p545fig15.11  Associative learning, gated steepest descent learning: output from each population is a doubly gated signal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p546fig15.12 Computer simulation of spectral learning: fastest with large sampling signals when the US occurs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p546fig15.13  Adaptive timing is a population property, random spectrum of rates achieves good collective timing.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p547fig15.14 [Un, ]expected non-occurences of goal: a predictive failure leads to: Orienting Reactions, Emotional- Frustration,  Motor- Explorator.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p547fig15.15  Expected non-occurrence of goal: some rewards are reliable but delayed in time, do not lead to orienting reactions.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p548fig15.16 Homolog between ART and CogEM model: complementary systems.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p548fig15.17 The timing paradox: want [accurate timing, to inhibit exploratory behaviour throught ISI].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p549fig15.18 Weber Law: reconciling accurate and distributed timing, different ISIs-  standard deviation = peak time, Weber law rule.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p549fig15.19 Conditioning, Attention, and Timing circuit: Hippocampus spectrum-> Amgdala orienting system-> neocortex motivational attention.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p550fig15.20 Adaptively timed Long Term Depression between parallel fibres and Purkinje cells-> movement gains within learned time interval.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p551fig15.21 Cerebellum: important cells types and circuitry.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p551fig15.22 Responses of a turtle retinal cone to brief flashes of light of increasing intensity.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p552fig15.23 Cerebellar biochemistry: mGluR supports adaptively timed conditioning at cerebellar Purkinje cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p556fig15.24 Cerebellar cortex responses: [data, model] short latency responses after lesioning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p557fig15.25 Computer simulations of adaptively timed [LTD at Purkinje cells, activation of cereballar nuclear cells].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p557fig15.26 Brain [region, process]s that contribute to autistic behavioral symptoms.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p559fig15.27 Spectrally timed SNc learning: brain [region, process]s release of dopaminergic signals, unexpected reinforcing.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p559fig15.28 Neurophysiological data and simulations of SNc responses.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p560fig15.29 Excitatory pathways that support activation of the SNc by a US and the conditioning of a CS to the US.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p560fig15.30 Inhibitory pathway: striosomal cells predict [timing, magnitude] of reward signal to cancel it.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p561fig15.31 Expectation timing: timing spectrum, striosomal cells delayed transient signals, gate [learning, read-out].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p561fig15.32 Inhibitory pathway expectation magnitude: is a negative feedback control system for learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p563fig15.33 MOTIVATOR: thalamocortical loops through basal ganglia.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p563fig15.34 Distinct basal ganglia zones for each loop.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p564fig15.35 GO signal to recurrent shunting OC-OS networks: control of the [fore, hind] limbs.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p565fig15.36 (a) FOVEATE: control of saccadic eye movements within the peri-pontine reticular formation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p566fig15.37 FOVEATE: steps in generation of a saccade.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p567fig15.38 Gated Pacemaker of [diurnal, nocturnal] circadian rythms: whether phasic light turns the pacemaker on or off.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p568fig15.39 MOTIVATOR hypothalamic gated dipoles: inputs, [object, value, object-value] categories, reward expectation filter.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p569fig15.40 GO and STOP movement signals: control by [direct, indirect] basal ganglia circuits.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p573fig16.01 Hippocampal place cells: discovery from rat [experimental chamber, neurophysiological recordings].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p574fig16.02 Neurophysiological recordings of 18 different place cell receptive fields.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p575fig16.03 Rat navigation: firing patterns of [hippocampal place, entrorhinal grid] cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p578fig16.04 Cross-sections of the hippocampal regions and the inputs to them.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p580fig16.05 GridPlaceMap hierarchy of SOMs with identical equations: learns 2D [grid, place] cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p581fig16.06 Trigonometry of spatial navigation: coactivation of stripe cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p582fig16.07 Stripe cells multiple [orientation, phase, scale]s: directionally-sensitive ring attractors, velocity, distance.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p582fig16.08 Evidence for stripe-like cells: entorhinal cortex data, Band Cells position from grid cell oscillatory interference.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p583fig16.09 GRIDSmap: stripe cells for rat trajectories, self-organizing map learned hexagonal grid cell receptive fields.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p583fig16.10 GRIDSmap embedded into hierarchy of SOMs: [angular head velocity, linear velocity] signals to place cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p584fig16.11 GRIDSmap learning of hexagonal grid fields, multiple phases per scale.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p584fig16.12 Temporal development of grid fields: orientations rotate to align with each other.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p585fig16.13 Hexagonal grid cell receptive fields: somewhat insensitive to [number, directional selectivities] of stripe cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p585fig16.14 GRIDSmap: Superimposed firing of stripe cells supports learning hexagonal grid.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p586fig16.15 Why is a hexagonal grid favored: stripe cells at intervals of 45 degrees, GRIDSmap does not learn, oscillatory interference does.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p586fig16.16 Grid-to-place SOM: formation of place cell fields via grid-to-place cell learning.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p587fig16.17 A refined analysis: SOM amplifies most frequent and energetic coactivations, stripe fields separated by [90°, 60°].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p588fig16.18 GridPlaceMap hierarchy of SOMs: coordinated learning of [grid, place, inomodal] cell receptive fields.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p589fig16.19 How does the spatial scale increase along the MEC dorsoventral axis.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p590fig16.20 Dorsoventral gradient in the rate of synaptic integration of MEC layer II stellate cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p590fig16.21 Frequency of membrane potential oscillations in grid cells decreases along the dorsoventral gradient of the MEC.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p591fig16.22 Dorsoventral [time constant, duration] gradients in AHP kinetics of MEC layer II stellate cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p591fig16.23 Spectral spacing model: map cells respond to stripe cell inputs of multiple scales, How do entorhinal cells solve the scale selection problem.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p592fig16.24 Parameter settings in the Spectral Spacing Model that were used in simulations.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p593fig16.25 Spectral Spacing Model equations for [STM, MTM, LTM].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p593fig16.26 Gradient of grid spacing along dorsoventral axis of MEC.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p594fig16.27 Gradient of field width along dorsoventral axis of MEC.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p595fig16.28 Peak and mean rates at different locations along DV axis of MEC.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p596fig16.29 Subthreshold membrane mV oscillations: decreasing Hz at different locations along DV axis of MEC.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p596fig16.30 Spatial phases of learned grid and place cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p597fig16.31 Multimodal place cell firing in large spaces.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p597fig16.32 Model fits data about grid cell development in juvenile rats:  grid [score increases, spacing flat].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p598fig16.33 Model fits [place, grid, directional] cell data about grid cell development in juvenile rats:  [spatial information, inter-trial stability] vs postnatal day.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p598fig16.34 spiking GridPlaceMap: generates theta-modulated place and grid cell firing, unlike the rate-based model.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p599fig16.35 anatomically overlapping grid cell modules: effects of [different modules in one animal, DV location, response rate].png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p600fig16.36 entorhinal-hipppocampal system: ART spatial category learning system, place cells as spatial categories.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p602fig16.37 Hippocampal inactivation by muscimol disrupts grid cells.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p603fig16.38 Role of hippocampal feedback in maintaining grid fields, muscimol inhibition.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p605fig16.39 Disruptive effects of MS inactivation in MEC.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p607fig16.40 Effects of medial septum (MS) inactivation on grid cells: data, simulations, gridness.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p611fig16.41 back-propagating action potentials, recurrent inhibitory interneurons: control learning, regulate rythm- read-out is dissociated from read-in.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p612fig16.42 Macrocircuit of the main SOVEREIGN subsystems: visual, motor.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p613fig16.43 SOVEREIGN [visual form, motion processing] stream mechanisms.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p613fig16.44 SOVEREIGN[target position, difference] vectors, volitional GO computations] to control decision-making and action.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p614fig16.45 [distance, angle] computations learn dimensionally-consistent [visual, motor] information for [decision, action]s.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p615fig16.46 SOVEREIGN uses homologous processing stages to model the [What, Where] cortical streams, motivational mechanisms.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p615fig16.47 SOVEREIGN: multiple parallel READ circuits, sensory-drive heterarchy amplifies motivationally favored option.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p616fig16.48 SOVEREIGN tests using virtual reality 3D rendering of a cross maze.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p616fig16.49 SOVEREIGN  animat converted inefficient exploration into an efficient direct learned path to the goal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p617fig16.50 Spectral Spacing models of [perirhinal what, parahippocampal where] inputs, fused in the hippocampus.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p627tbl17.01 Homologs between [reaction-diffusion, recurrent shunting cellular network] models of development.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p628fig17.01 A hydra.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p628fig17.02 how different [cut, graft]s of the normal Hydra may [, not] lead to the growth of a new head.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p629fig17.03 How an initial morphogenetic gradient may be contrast enhanced to exceed the threshold for head formation.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p630fig17.04 Morphogenesis: use cellular models vs [chemical, fluid] reaction-diffusion models.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p631fig17.05 How a blastula develops into a gastrula.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/p634fig17.06 How binary cells with a Gaussian distribution of output thresholds generates a sigmoidal population signal.png
/home/bill/web/Neural nets/TrNNs_ART/images- captioned/pxvifig00.01 Macrocircuit of the visual system.png
/home/bill/web/Neural nets/TrNNs_ART/Introduction.html
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/home/bill/web/ProjMajor/History/Ukraine-Russia/Mearsheimer 2015 Europe dependence on Russian gas.png
/home/bill/web/ProjMajor/History/Ukraine-Russia/Mearsheimer 2015 Ukraine 2015 survey join EU or [Russia, Belarus, Kazakhstan].png
/home/bill/web/ProjMajor/History/Ukraine-Russia/Mearsheimer 2015 Ukraine 2015 survey join NATO.png
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/home/bill/web/ProjMajor/Icebreaker/
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/home/bill/web/ProjMajor/Lies, Damned Lies, and Scientists/Howell C3 Chapter - Suggestions for science, policy, and society.pdf
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https://kyivindependent.com/national/us-warns-that-russia-could-attack-ukraine-at-any-moment/
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https://kyivindependent.com/national/weekend-news-wrap-up-2/
https://kyivindependent.com/national/west-urges-ukraine-to-complete-key-judicial-anti-corruption-reforms-quickly/
https://kyivindependent.com/national/what-we-know-about-biden-putin-call-on-threatening-invasion-of-ukraine/
https://kyivindependent.com/national/what-we-know-about-british-tank-killers-likely-sent-to-ukraine/
https://kyivindependent.com/national/what-we-know-about-polish-anti-aircraft-weapons-sent-to-ukraine/
https://kyivindependent.com/national/what-we-know-about-us-bunker-busters-sent-to-ukraine/
https://kyivindependent.com/national/where-russia-is-attacking-ukraine-today-feb-25/
https://kyivindependent.com/national/white-house-russia-was-preparing-evacuation-from-kyiv-embassy-amid-rising-tensions/
https://kyivindependent.com/national/white-house-us-will-not-pressure-ukraine-to-grant-autonomy-to-donbas/
https://kyivindependent.com/national/who-can-and-cant-join-ukraines-new-territorial-defense-force/
https://kyivindependent.com/national/why-nord-stream-2-is-centerpiece-of-ukraine-crisis-with-russia-explainer/
https://kyivindependent.com/national/why-russia-wants-autonomy-for-occupied-donbas-explainer/
https://kyivindependent.com/national/will-russia-launch-large-scale-war-or-limited-invasion-analysis-of-3-popular-scenarios/
https://kyivindependent.com/national/world-bank-study-reveals-effects-of-global-warming-on-ukraines-agriculture-forests/
https://kyivindependent.com/national/world-bank-to-give-ukraine-150-million-for-covid-19-vaccination-drive/
https://kyivindependent.com/national/world-bank-to-lend-300-million-euros-to-back-reforms-mitigate-pandemic-in-ukraine/
https://kyivindependent.com/national/world-reacts-to-kremlin-escalation-with-sanctions/
https://kyivindependent.com/national/yellow-quarantine-zone-restrictions-will-be-tightened-as-of-dec-6/
https://kyivindependent.com/national/yermak-travels-to-paris-meets-normandy-format-advisors-amid-russian-escalation/
https://kyivindependent.com/national/yermak-ukraine-proposes-trilateral-talks-with-us-russia/
https://kyivindependent.com/national/zelensky-addresses-nation-as-russia-re-invades/
https://kyivindependent.com/national/zelensky-announces-trilateral-partnership-between-ukraine-poland-uk/
https://kyivindependent.com/national/zelensky-biden-discuss-security-diplomacy-aid-to-ukraine/
https://kyivindependent.com/national/zelensky-biden-hold-talks-on-potential-russian-invasion/
https://kyivindependent.com/national/zelensky-calls-on-other-countries-media-to-not-cause-fear-about-russian-escalation/
https://kyivindependent.com/national/zelensky-gathers-european-support-in-brussels-ahead-of-eastern-partnership-summit/
https://kyivindependent.com/national/zelensky-in-munich-demands-security-guarantees-calls-for-preemptive-sanctions-against-russia/
https://kyivindependent.com/national/zelensky-issues-decree-to-bolster-ukraines-military/
https://kyivindependent.com/national/zelensky-responds-to-biden-there-are-no-minor-incursions/
https://kyivindependent.com/national/zelenskys-full-speech-at-munich-security-conference/
https://kyivindependent.com/news-archive/
https://kyivindependent.com/opinion/alexander-query-macrons-ill-timed-bluff-puts-ukraine-at-risk/
https://kyivindependent.com/opinion/allan-pagh-kristensen-fight-against-corruption-requires-comprehensive-reforms/
https://kyivindependent.com/opinion/amy-knight-on-ukraine-nato-and-more-russias-vladimir-putin-lives-in-an-alternative-reality/
https://kyivindependent.com/opinion/anatoly-motkin-ukraine-will-become-a-role-model-for-eurasian-it-markets/
https://kyivindependent.com/opinion/andrew-danieri-the-new-ukraine-needs-a-new-census/
https://kyivindependent.com/opinion/andrew-fink-putins-anti-democratic-crusade/
https://kyivindependent.com/opinion/andriy-boytsun-ukrainian-state-owned-enterprises-weekly/
https://kyivindependent.com/opinion/andriy-guck-no-fly-zone-is-what-ukraine-urgently-needs-to-save-civilians-and-cities/
https://kyivindependent.com/opinion/andriy-shevchenko-putin-wont-stop-at-ukraine/
https://kyivindependent.com/opinion/anna-myroniuk-i-lost-my-home-to-putin-once-now-it-can-happen-again/
https://kyivindependent.com/opinion/anne-applebaum-the-reason-putin-would-risk-war/
https://kyivindependent.com/opinion/aura-sabadus-will-putin-deploy-his-energy-weapons-against-europe/
https://kyivindependent.com/opinion/bohdan-vitvitsky-disarming-putins-history-weapon/
https://kyivindependent.com/opinion/brian-whitmore-while-the-world-watches-ukraine-putin-is-quietly-occupying-belarus/
https://kyivindependent.com/opinion/center-for-defense-strategies-what-putins-watershed-decision-means-for-ukraine-world-analysis/
https://kyivindependent.com/opinion/editorial-sanction-russia-now/
https://kyivindependent.com/opinion/editorial-western-allies-should-do-more-for-ukraine-to-correct-their-past-mistakes/
https://kyivindependent.com/opinion/eugene-czolij-a-no-fly-zone-needs-to-be-enforced-now-over-ukraines-airspace/
https://kyivindependent.com/opinion/eugene-czolij-canadas-package-to-ukraine-to-ensure-peace-is-missing-a-crucial-piece/
https://kyivindependent.com/opinion/eugene-czolij-expelling-russia-from-swift-must-now-be-done-swiftly/
https://kyivindependent.com/opinion/eugene-czolij-it-is-in-natos-best-interests-to-help-ukraine-secure-its-airspace/
https://kyivindependent.com/opinion/eugene-czolij-nato-member-countries-are-targets-of-putins-military-aggression-and-must-act-accordingly-in-ukraine/
https://kyivindependent.com/opinion/eugene-czolij-still-not-too-late-for-germany-to-honor-its-commitment-to-ukraine/
https://kyivindependent.com/opinion/eugene-czolij-the-budapest-memorandum-reality-check/
https://kyivindependent.com/opinion/eugene-czolij-the-us-must-show-leadership-in-countering-putins-imperial-ambitions/
https://kyivindependent.com/opinion/eugene-czolij-the-west-must-act-now/
https://kyivindependent.com/opinion/eugene-czolij-ukraine-is-embodiment-of-true-values-of-eu-member-state-eu-must-grant-it-membership-now/
https://kyivindependent.com/opinion/eugene-czolij-west-must-decisively-enforce-basic-principles-of-un-charter-for-global-peace-security/
https://kyivindependent.com/opinion/glen-grant-ukraine-stands-firm-despite-russian-offensive/
https://kyivindependent.com/opinion/group-of-authors-understanding-confronting-russian-aggression-toward-ukraine/
https://kyivindependent.com/opinion/gyunduz-mamedov-ukraine-must-hold-iran-to-justice-over-flight-ps752/
https://kyivindependent.com/opinion/gyunduz-mamedov-ukraine-needs-to-strengthen-effective-prosecution-of-war-crimes/
https://kyivindependent.com/opinion/harley-balzer-dont-believe-putins-propaganda-sanctions-are-hurting-russia/
https://kyivindependent.com/opinion/illia-ponomarenko-even-if-russia-attacks-ukraines-fall-is-not-predestined/
https://kyivindependent.com/opinion/illia-ponomarenko-is-russia-really-about-to-invade-ukraine/
https://kyivindependent.com/opinion/james-batchik-doug-klain-its-time-for-europe-to-defend-ukraine-and-itself/
https://kyivindependent.com/opinion/james-rogers-is-britain-now-ukraines-closest-ally/
https://kyivindependent.com/opinion/joe-varner-abandoning-ukraine-means-surrendering-the-rules-based-liberal-world-order/
https://kyivindependent.com/opinion/john-e-herbst-how-kazakhstan-could-shift-putins-calculus-on-ukraine/
https://kyivindependent.com/opinion/kurt-volker-dont-let-russia-fool-you-about-minsk-agreements/
https://kyivindependent.com/opinion/lubomyr-luciuk-when-it-comes-to-ukraines-national-security-vladimir-putin-has-already-won/
https://kyivindependent.com/opinion/lukasz-adamski-putins-ukraine-playbook-echoes-the-tactics-of-russian-imperialism/
https://kyivindependent.com/opinion/marco-levytsky-why-is-canada-so-reluctant-to-provide-lethal-arms-to-ukraine/
https://kyivindependent.com/opinion/michael-bociurkiw-checkmate-putin-has-the-west-cornered/
https://kyivindependent.com/opinion/michael-bociurkiw-for-putin-kazakhstan-is-a-domino-too-big-to-fall/
https://kyivindependent.com/opinion/michael-bociurkiw-ukrainians-are-wondering-if-their-comedian-turned-president-can-handle-the-world-stage/
https://kyivindependent.com/opinion/michael-khodarkovsky-what-is-next-for-russia/
https://kyivindependent.com/opinion/mychailo-wynnyckyj-ukrainian-voices-are-missing-from-the-drama-over-ukraines-future/
https://kyivindependent.com/opinion/nataliia-steblyna-everyone-is-important-in-the-war-against-putin/
https://kyivindependent.com/opinion/nato-member-states-must-provide-ukraine-with-fighter-jets-without-further-delay/
https://kyivindependent.com/opinion/oksana-bashuk-hepburn-dictatorship-and-isolationism-dont-work-in-the-21st-century/
https://kyivindependent.com/opinion/oksana-bashuk-hepburn-how-to-ensure-putins-withdrawal-from-ukraine/
https://kyivindependent.com/opinion/oksana-bashuk-hepburn-minsk-is-flawed-new-peace-plan-needed/
https://kyivindependent.com/opinion/oksana-bashuk-hepburn-to-win-in-diplomacy-take-the-advantage/
https://kyivindependent.com/opinion/oksana-bashuk-hepburn-why-is-putin-still-in-charge-of-the-wests-agenda/
https://kyivindependent.com/opinion/oleg-sukhov-us-should-sanction-these-2-symbols-of-ukraines-corruption/
https://kyivindependent.com/opinion/oleksandr-pankieiev-the-west-must-stand-together-on-russian-aggression/
https://kyivindependent.com/opinion/olena-goncharova-canada-must-stand-on-guard-for-ukraine/
https://kyivindependent.com/opinion/olena-goncharova-please-remember-ukraine-is-not-the-ukraine-and-why-it-matters-now/
https://kyivindependent.com/opinion/osnat-lubrani-uns-approach-to-combating-gender-based-violence-in-ukraine/
https://kyivindependent.com/opinion/osnat-lubrani-un-will-continue-to-deliver-for-all-ukrainians-leaving-no-one-behind/
https://kyivindependent.com/opinion/pavel-felgenhauer-russia-and-nato-locked-in-high-risk-standoff-in-mediterranean-and-black-seas/
https://kyivindependent.com/opinion/pavel-felgenhauer-russian-troops-deploy-to-belarus-with-fanfare/
https://kyivindependent.com/opinion/pavlo-lodyn-putins-aggression-and-the-threat-of-environmental-catastrophe-in-europe/
https://kyivindependent.com/opinion/peter-dickinson-putin-escalates-his-ukraine-war-with-recognition-of-separatist-republics/
https://kyivindependent.com/opinion/robert-a-mcconnel-talk-wont-deter-putin-heres-what-west-can-do/
https://kyivindependent.com/opinion/sergey-fursa-these-sanctions-need-to-be-imposed-against-russia-immediately/
https://kyivindependent.com/opinion/stanislav-aseyev-russias-bluff-of-the-century-will-there-be-a-war/
https://kyivindependent.com/opinion/timothy-ash-putin-is-preparing-for-war/
https://kyivindependent.com/opinion/timothy-ash-putin-the-gambler-may-have-gone-too-far-to-back-down/
https://kyivindependent.com/opinion/timothy-ash-ukraine-has-much-stronger-macro-better-able-to-endure-russian-aggression/
https://kyivindependent.com/opinion/timothy-ash-what-kazakhstans-protests-mean-for-the-global-economy/
https://kyivindependent.com/opinion/timothy-ash-what-kazakhstan-unrest-means-for-ukraine-amid-upcoming-us-russia-security-talks/
https://kyivindependent.com/opinion/timothy-snyder-putins-case-for-invading-ukraine-rests-on-phony-grievances-and-ancient-myths/
https://kyivindependent.com/opinion/ukrainian-state-owned-enterprises-weekly-issue-56/
https://kyivindependent.com/opinion/ukrainian-state-owned-enterprises-weekly-issue-57/
https://kyivindependent.com/opinion/ukrainian-state-owned-enterprises-weekly-issue-60/
https://kyivindependent.com/opinion/ukrainian-state-owned-enterprises-weekly-issue-64/
https://kyivindependent.com/opinion/ukrainian-state-owned-enterprises-weekly-special-issue-top-2021-events/
https://kyivindependent.com/opinion/un-must-impose-a-no-fly-zone-over-ukraine/
https://kyivindependent.com/opinion/veronika-melkozerova-how-looming-russian-invasion-changed-lives-of-ukrainians/
https://kyivindependent.com/opinion/victor-tregubov-are-you-a-foreigner-who-wants-to-help-ukraine-heres-how/
https://kyivindependent.com/opinion/victor-tregubov-plunging-into-icy-water-on-epiphany-isnt-an-old-ukrainian-tradition-its-russian/
https://kyivindependent.com/opinion/vladimir-kara-murza-its-not-just-the-west-that-opposes-putins-war-on-ukraine-a-lot-of-russians-do-too/
https://kyivindependent.com/opinion/yevhen-fedchenko-western-sanctions-must-target-putins-propagandists/
https://kyivindependent.com/opinion/yuri-polakiwsky-a-lend-lease-agreement-as-a-way-forward-for-ukraine/
https://kyivindependent.com/podcasts/media-in-progress-ep-1-our-fight-for-independent-journalism-in-ukraine/
https://kyivindependent.com/podcasts/media-in-progress-ep-2-whats-in-a-name/
https://kyivindependent.com/podcasts/media-in-progress-ep-3-who-what-where/
https://kyivindependent.com/podcasts/media-in-progress-ep-4-with-you-on-our-side/
https://kyivindependent.com/podcasts/media-in-progress-ep-5-will-russia-invade-again/
https://kyivindependent.com/podcasts/media-in-progress-ep-6-popular-protest-inter-elite-feuds-or-russian-intervention-whats-going-on-in-kazakhstan/
https://kyivindependent.com/podcasts/media-in-progress-ep-7-company-culture-what-can-make-or-break-a-team/
https://kyivindependent.com/podcasts/media-in-progress-ep-8-can-independent-media-be-sustainable-we-want-to-prove-it-can/
https://kyivindependent.com/podcasts/questions-about-russias-war-against-ukraine-with-defense-reporter-illia-ponomarenko/
https://kyivindependent.com/politics/anti-corruption-body-medvedchuk-failed-to-declare-2-68-million-in-assets/
https://kyivindependent.com/politics/constitutional-court-delays-swearing-in-judges-appointed-by-zelensky/
https://kyivindependent.com/politics/court-rules-not-to-arrest-poroshenko/
https://kyivindependent.com/politics/detectives-try-to-summon-poroshenko-may-charge-him-in-medvedchuk-case/
https://kyivindependent.com/politics/foreign-minister-dmytro-kuleba-accuses-russia-of-trying-to-kill-normandy-format-peace-talks/
https://kyivindependent.com/politics/kyiv-administration-sues-subway-contractor-for-using-state-funds-to-make-a-buck/
https://kyivindependent.com/politics/lawyers-say-zelensky-illegally-appointed-constitutional-court-judges/
https://kyivindependent.com/politics/media-zelenskys-chief-of-staff-throws-secretive-birthday-celebration-at-state-residence/
https://kyivindependent.com/politics/nato-believes-russian-military-buildup-near-ukraines-border-is-not-a-bluff/
https://kyivindependent.com/politics/ngos-call-on-zelensky-not-to-appoint-corrupt-judges/
https://kyivindependent.com/politics/parliament-passes-anti-akhmetov-tax-law-that-raises-iron-ore-rents-triples-carbon-tax/
https://kyivindependent.com/politics/police-us-citizen-ordered-killing-of-agriculture-minister-over-business-grudge/
https://kyivindependent.com/politics/poroshenko-returns-to-ukraine-where-he-faces-arrest/
https://kyivindependent.com/politics/poroshenko-trial-prosecution-asks-for-37-million-bail-judges-deliberate-for-11-hours-without-result/
https://kyivindependent.com/politics/president-volodymyr-zelensky-leads-by-10-in-new-poll/
https://kyivindependent.com/politics/president-zelenskys-speech-to-parliament-what-you-need-to-know/
https://kyivindependent.com/politics/pro-kremlin-lawmaker-pays-bail-for-odesa-mayor-trukhanov/
https://kyivindependent.com/politics/rfezm@(m@z5-intelligence-agents-involved-with-wagnergate-had-their-passports-revoked/
https://kyivindependent.com/politics/selection-panel-launches-judicial-reform/
https://kyivindependent.com/politics/state-guard-administration-denies-firing-servicemen-for-not-shooting-down-journalists-drone/
https://kyivindependent.com/politics/state-investigation-bureau-opens-probe-into-famous-journalist-days-after-he-argues-with-zelensky-on-tv/
https://kyivindependent.com/politics/thousands-of-protesters-demand-zelenskys-resignation/
https://kyivindependent.com/politics/ukraines-judicial-reform-explained/
https://kyivindependent.com/politics/west-promises-consequences-if-russia-invades-ukraine/
https://kyivindependent.com/politics/who-is-murayev-a-man-uk-exposes-as-potential-leader-of-kremlins-coup/
https://kyivindependent.com/politics/why-is-ukraine-still-missing-a-chief-anti-corruption-prosecutor/
https://kyivindependent.com/politics/zelensky-holds-5-hour-press-marathon-with-handpicked-media/
https://kyivindependent.com/politics/zelensky-leads-presidential-poll-with-23-5-poroshenko-polls-second/
https://kyivindependent.com/politics/zelensky-partys-lawmaker-reportedly-caught-taking-bribe/
https://kyivindependent.com/politics/zelenskys-party-lawmaker-buys-nationwide-television-channel/
https://kyivindependent.com/politics/zelenskys-party-member-expelled-after-bribe-attempt-exposure/
https://kyivindependent.com/regional/occrp-how-kazakhstans-leader-of-the-nation-controls-vast-assets-through-charitable-foundations-investigation/
https://kyivindependent.com/tech/german-based-tech-company-avenga-buys-ukrainian-outsourcer-perfectial/
https://kyivindependent.com/tech/glovo-acquires-ukrainian-grocery-delivery-zakaz-ua/
https://kyivindependent.com/tech/government-launches-new-digital-services-including-pension-and-subsidy-registration/
https://kyivindependent.com/tech/grammarly-becomes-most-expensive-ukrainian-tech-startup-with-13-billion-valuation/
https://kyivindependent.com/tech/grammarly-founders-become-billionaires-richer-than-oligarchs-kolomoisky-pinchuk/
https://kyivindependent.com/tech/mate-academy-startup-raises-1-9-million-from-ukrainian-european-investors/
https://kyivindependent.com/tech/ministry-of-digital-transformation-partners-with-apple-to-conduct-2023-census/
https://kyivindependent.com/tech/new-app-to-help-victims-report-domestic-abuse/
https://kyivindependent.com/tech/over-50-it-companies-join-ukraines-special-economic-zone-diia-city-in-its-first-days/
https://kyivindependent.com/tech/rocket-with-ukrainian-engine-launches-french-military-satellites-into-orbit/
https://kyivindependent.com/tech/tech-in-2021-ukrainian-startups-go-public-partner-with-elon-musk-raise-millions/
https://kyivindependent.com/tech/thousands-of-ukrainians-use-passwords-that-take-seconds-to-hack/
https://kyivindependent.com/tech/ukraine-imposes-additional-taxes-on-foreign-tech-what-changes-for-google-facebook-users/
https://kyivindependent.com/tech/ukraines-wearable-transcribing-device-raises-111000-on-kickstarter/
https://kyivindependent.com/tech/ukrainian-becomes-worlds-top-online-gamer/
https://kyivindependent.com/tech/ukrainian-company-creates-new-year-light-show-for-burj-khalifa-in-dubai/
https://kyivindependent.com/tech/ukrainian-developed-orty-named-one-of-worlds-top-food-tech-startups-in-2021/
https://kyivindependent.com/tech/ukrainian-sports-tech-startup-raises-6-million-in-cryptocurrency-offering/
https://kyivindependent.com/tech/ukrainian-startup-awesomic-attracts-2-million-to-expand-its-designer-marketplace/
https://kyivindependent.com/tech/ukrainian-startup-mysat-raises-9700-on-kickstarter-to-develop-satellite-kit/
https://kyivindependent.com/tech/ukrainian-startup-pibox-raises-400000-in-toronto/
https://kyivindependent.com/tech/ukrainian-startup-reface-partners-with-warner-bros-to-promote-new-films/
https://kyivindependent.com/tech/us-giant-chipmaker-qualcomm-acquires-ukrainian-startup-augmented-pixels/
https://kyivindependent.com/tech/zelensky-signs-diia-city-bill-that-changes-taxation-for-tech-firms/
https://kyivindependent.com/uncategorized/13-border-guards-were-killed-defending-ukraines-zmiinyi-island-snake-island-in-the-black-sea/
https://kyivindependent.com/uncategorized/14342/
https://kyivindependent.com/uncategorized/a-9-story-residential-building-in-bucha-was-hit-by-a-russian-strike-casualties-are-unknown/
https://kyivindependent.com/uncategorized/air-raid-alerts-go-off-in-almost-every-region-of-ukraine/
https://kyivindependent.com/uncategorized/air-raid-sirens-activated-in-kyiv-as-multiple-reports-suggest-that-russian-forces-are-about-to-conduct-heavy-airstrikes-and-rocket-attacks-against-the-city/
https://kyivindependent.com/uncategorized/a-large-column-of-russian-vehicles-is-pushing-into-the-city-of-sumy-from-the-side-of-khimprom/
https://kyivindependent.com/uncategorized/a-loud-explosion-was-heard-in-kyiv-center-at-2-54-p-m/
https://kyivindependent.com/uncategorized/a-missile-strikes-an-apartment-building-in-chernihiv/
https://kyivindependent.com/uncategorized/anders-aslund-putin-has-seriously-wounded-ukraines-economy-without-firing-a-single-shot/
https://kyivindependent.com/uncategorized/a-number-of-cities-and-towns-in-ukraine-including/
https://kyivindependent.com/uncategorized/a-russian-rocket-hit-police-headquarters-in-kharkiv-unian-news-agency-reports/
https://kyivindependent.com/uncategorized/atb-supermarkets-located-underground-are-opened-as-bomb-shelters/
https://kyivindependent.com/uncategorized/a-warehouse-of-kyivenergo-capitals-energy-generating-company-was-set-on-fire/
https://kyivindependent.com/uncategorized/belarus-will-renounce-its-non-nuclear-and-neutral-status-allowing-russia-to-place-nuclear-weapons-on-its-territory-as-a-result-of-the-referendum-held-today/
https://kyivindependent.com/uncategorized/biden-us-department-of-justice-is-assembling-a-task-force-to-go-after-the-crimes-of-russian-oligarchs-and-corrupt-russian-leaders/
https://kyivindependent.com/uncategorized/biden-we-will-join-our-allies-in-closing-our-airspace-to-russian-planes/
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https://www.ukrinform.net/rubric-ato/3424251-russia-preparing-provocation-at-zaporizhia-npp-galushchenko.html
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https://www.ukrinform.net/rubric-ato/3424325-ukrainian-military-destroyed-column-of-enemy-equipment-in-kharkiv-region.html
https://www.ukrinform.net/rubric-ato/3424328-russia-to-bear-responsibility-for-exposing-world-to-nuclear-danger-kuleba.html
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https://www.ukrinform.net/rubric-ato/3424351-since-war-began-58-civilians-killed-288-injured-in-donetsk-region.html
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https://www.ukrinform.net/rubric-ato/3424521-russian-invaders-launch-over-50-attacks-on-kharkiv-over-past-day.html
https://www.ukrinform.net/rubric-ato/3424539-three-days-to-capture-kharkiv-russian-pow-confesses-he-was-sent-not-to-exercises.html
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https://www.ukrinform.net/rubric-ato/3424555-9-people-including-3-children-killed-in-russias-shelling-of-zhytomyr-region.html
https://www.ukrinform.net/rubric-ato/3424564-enemy-missile-destroyed-in-sky-over-zhytomyr-region.html
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https://www.ukrinform.net/rubric-ato/3424600-zelensky-almost-all-russian-troops-amassed-for-invasion-have-entered-ukraine.html
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https://www.ukrinform.net/rubric-ato/3424719-council-of-europe-condemns-russias-aggression-against-ukraine.html
https://www.ukrinform.net/rubric-ato/3424729-nato-secretary-general-warns-russia-away-from-attacking-supply-lines-supporting-ukraine.html
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https://www.ukrinform.net/rubric-ato/3424835-zelensky-to-address-canadian-parliament.html
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https://www.ukrinform.net/rubric-ato/3424880-iaea-no-critical-impact-on-safety-after-power-loss-at-chornobyl-npp.html
https://www.ukrinform.net/rubric-ato/3424907-civilians-evacuated-from-izium-under-russian-shelling.html
https://www.ukrinform.net/rubric-ato/3424931-kuleba-calls-for-providing-ukraine-with-aircraft-after-air-strike-hit-maternity-hospital-in-mariupol.html
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https://www.ukrinform.net/rubric-ato/3424974-at-least-17-people-injured-after-russian-air-strike-hit-maternity-hospital.html
https://www.ukrinform.net/rubric-ato/3424986-over-40000-women-and-children-evacuated-from-all-over-ukraine-in-one-day.html
https://www.ukrinform.net/rubric-ato/3424998-russian-invaders-fired-on-people-who-were-trying-to-leave-chernihiv.html
https://www.ukrinform.net/rubric-ato/3425032-defense-ministry-enemy-suffers-significant-losses-near-borodianka-and-makariv.html
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https://www.ukrinform.net/rubric-ato/3425124-russian-invaders-shelling-ukrainian-positions-in-mykolaiv-regional-administration.html
https://www.ukrinform.net/rubric-ato/3425127-fighting-in-luhansk-region-abates-not-for-a-minute.html
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https://www.ukrinform.net/rubric-ato/3425149-president-pause-in-closure-of-sky-over-ukraine-has-already-become-deadly.html
https://www.ukrinform.net/rubric-ato/3425154-everything-that-occupiers-doing-with-mariupol-is-beyond-atrocities-zelenskys-address-full-text.html
https://www.ukrinform.net/rubric-ato/3425171-zelenska-entire-britain-from-ordinary-citizens-to-royal-family-supports-ukraine.html
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https://www.ukrinform.net/rubric-ato/3425210-zelensky-ready-for-compromises-not-betrayal-of-ukraine.html
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https://www.ukrinform.net/rubric-ato/3425250-sumy-region-preparing-three-humanitarian-corridors-for-march-10.html
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https://www.ukrinform.net/rubric-ato/3425271-russia-could-freeze-war-at-some-stage-rather-than-end-it-bellingcat-reporter.html
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https://www.ukrinform.net/rubric-ato/3425347-ukrainian-army-hits-five-enemy-tanks-near-kyiv-denysenko.html
https://www.ukrinform.net/rubric-ato/3425359-russian-warships-retreat-from-odesa-to-crimea.html
https://www.ukrinform.net/rubric-ato/3425370-kuleba-cavusoglu-agree-on-steps-to-end-russias-war-against-ukraine.html
https://www.ukrinform.net/rubric-ato/3425395-situation-in-chernobyl-very-dangerous-for-both-europe-and-russia-podoliak.html
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https://www.ukrinform.net/rubric-ato/3425439-ukraine-opens-humanitarian-corridors-vereshchuk-names-seven-routes.html
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https://www.ukrinform.net/rubric-ato/3425493-zelensky-scholz-discuss-assistance-to-ukraine-sanctions-against-russia.html
https://www.ukrinform.net/rubric-ato/3425517-ukrainian-military-captured-thousands-of-russian-soldiers-adviser-to-interior-minister.html
https://www.ukrinform.net/rubric-ato/3425528-buses-leave-zaporizhzhia-to-evacuate-people-from-mariupol.html
https://www.ukrinform.net/rubric-ato/3425576-humanitarian-cargo-returns-to-zaporizhzhia-as-mariupol-blocked-for-evacuation.html
https://www.ukrinform.net/rubric-ato/3425589-ukrainian-armed-forces-destroyed-iskander-division-in-chernihiv-region.html
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https://www.ukrinform.net/rubric-ato/3425623-humanitarian-corridors-open-only-in-sumy-region-adviser-to-interior-minister.html
https://www.ukrinform.net/rubric-ato/3425653-russian-propagandists-will-be-brought-to-justice-for-complicity-in-war-crimes-zelensky.html
https://www.ukrinform.net/rubric-ato/3425663-71-children-killed-over-100-injured-since-russia-attacks-ukraine.html
https://www.ukrinform.net/rubric-ato/3425667-zelensky-after-our-victory-we-will-rebuild-everything-destroyed-by-enemy.html
https://www.ukrinform.net/rubric-ato/3425668-about-2000-people-being-evacuated-from-izium-presidents-office.html
https://www.ukrinform.net/rubric-ato/3425672-kuleba-lavrov-was-not-authorized-to-make-decisions-at-meeting-in-antalya.html
https://www.ukrinform.net/rubric-ato/3425690-media-releases-putins-party-gag-orders-for-russian-mps.html
https://www.ukrinform.net/rubric-ato/3425725-russian-invaders-have-already-shelled-63-hospitals-killing-five-health-workers.html
https://www.ukrinform.net/rubric-ato/3425737-kuleba-russia-must-immediately-withdraw-troops-from-chornobyl-and-zaporizhzhia-npps.html
https://www.ukrinform.net/rubric-ato/3425746-zelensky-informs-johnson-macron-about-russias-new-crimes-against-ukraine.html
https://www.ukrinform.net/rubric-ato/3425758-1-killed-in-severodonetsk-3-wounded-in-rubizhne-in-aggressors-shelling.html
https://www.ukrinform.net/rubric-ato/3425772-ukraine-suggests-that-osce-iaea-missions-be-located-at-nuclear-power-plants.html
https://www.ukrinform.net/rubric-ato/3425783-enemy-fires-two-missiles-on-airport-in-dnipropetrovsk-region.html
https://www.ukrinform.net/rubric-ato/3425801-invaders-mine-coast-of-kakhovka-reservoir.html
https://www.ukrinform.net/rubric-ato/3425828-russian-invaders-could-blow-up-ammonia-depots-in-kharkiv-region.html
https://www.ukrinform.net/rubric-ato/3425840-duda-icc-prosecutors-collecting-evidence-of-russian-crimes-among-ukrainian-refugees-in-poland.html
https://www.ukrinform.net/rubric-ato/3425862-ukrainian-forces-down-enemy-su25-fighter-jet.html
https://www.ukrinform.net/rubric-ato/3425898-russian-air-strike-hits-town-near-kyiv-amid-evacuation-of-civilians.html
https://www.ukrinform.net/rubric-ato/3425905-ukraine-army-holds-back-invaders-in-all-directions-invaders-suffering-significant-losses-general-staff.html
https://www.ukrinform.net/rubric-ato/3425923-russias-defense-ministry-diplomacy-fail-to-speak-in-one-voice-when-lying-about-bombing-mariupol-maternity-hospital.html
https://www.ukrinform.net/rubric-ato/3425955-putins-plans-fail-so-he-must-stop-war-against-ukraine-borrell.html
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https://www.ukrinform.net/rubric-ato/3426018-mariupol-besieged-but-ukrainians-fighting-for-it-donetsk-regional-administration.html
https://www.ukrinform.net/rubric-ato/3426029-more-than-1000-more-people-evacuated-from-irpin.html
https://www.ukrinform.net/rubric-ato/3426032-russians-fire-uragan-systems-on-nizhyn-killing-at-least-two-people.html
https://www.ukrinform.net/rubric-ato/3426064-invaders-have-already-destroyed-and-damaged-over-400-infrastructure-facilities-in-donetsk-region.html
https://www.ukrinform.net/rubric-ato/3426089-more-than-38000-people-evacuated-through-humanitarian-corridors-today.html
https://www.ukrinform.net/rubric-ato/3426100-reznikov-number-of-civilians-killed-by-aggressors-exceeds-number-of-military-fallen-in-fighting.html
https://www.ukrinform.net/rubric-ato/3426129-russias-war-in-ukraine-will-have-negative-effect-on-entire-global-economy-imf.html
https://www.ukrinform.net/rubric-ato/3426135-nsdc-secretary-ukraine-was-preparing-for-war-against-russia-but-did-not-expect-attack-from-belarus.html
https://www.ukrinform.net/rubric-ato/3426142-zelensky-russian-troops-have-a-clear-order-to-hold-mariupol-hostage.html
https://www.ukrinform.net/rubric-ato/3426149-russian-invaders-kill-former-secretary-at-brovary-city-council-mayor.html
https://www.ukrinform.net/rubric-ato/3426155-zelensky-sees-ukraines-membership-in-eu-as-final-exam-for-europe.html
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https://www.ukrinform.net/rubric-ato/3426166-ukraines-defense-forces-holding-back-russias-advance-in-all-directions-general-staff.html
https://www.ukrinform.net/rubric-ato/3426171-kuleba-duda-discuss-support-for-ukraines-eu-membership.html
https://www.ukrinform.net/rubric-ato/3426201-ukraine-army-destroyed-two-columns-of-enemy-vehicles-and-10-air-targets-over-past-day.html
https://www.ukrinform.net/rubric-ato/3426209-ukraine-at-osce-several-diplomatic-institutions-come-under-aggressors-fire.html
https://www.ukrinform.net/rubric-ato/3426215-greece-to-take-some-ukrainian-refugees-from-poland.html
https://www.ukrinform.net/rubric-ato/3426232-number-of-child-refugees-from-ukraine-exceeds-1m-unicef.html
https://www.ukrinform.net/rubric-ato/3426245-us-congress-passes-136b-in-emergency-aid-for-ukraine-and-its-allies.html
https://www.ukrinform.net/rubric-ato/3426247-several-explosions-heard-in-lutsk-city.html
https://www.ukrinform.net/rubric-ato/3426250-about-215000-citizens-returned-to-ukraine-from-abroad.html
https://www.ukrinform.net/rubric-ato/3426258-eu-leaders-say-yes-to-ukrainian-eurointegration-lithuanian-president-assures.html
https://www.ukrinform.net/rubric-ato/3426269-enemy-trying-to-introduce-system-of-commandants-offices-in-kherson-region.html
https://www.ukrinform.net/rubric-ato/3426282-ukrainians-show-extraordinary-courage-in-fight-against-putins-war-us-vice-president.html
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https://www.unicef.org/press-releases/statement-unicef-executive-director-catherine-russell-reported-attack-against
https://www.un.org/press/en/2022/db220310.doc.htm
https://www.un.org/press/en/2022/db220310.doc.htm 
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https://www.voanews.com/a/russia-imposed-court-in-crimea-sentences-rfezm@(m@zjournalist-yesypenko-to-six-years-in-prison/6444162.html
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