Transcript fahime_sheikhzadeh

Towards a unified model
of neocortex
laminar cortical circuits for vision and cognition
By:
Fahime Sheikhzadeh
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Outlines
• Why computational models
• A brief description about neocortex
• Towards a unified theory of neocortex:
laminar cortical circuits for vision and cogniton
• Conclusion
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Computational models
Why should one use computational models
to address questions in neuroscience?
• Dealing with complexity
• Checking conceptual models and revealing
assumptions
• Comparing and discovering hypotheses
• Suggesting fruitful areas for new
experiments
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Neocortex
• The neocortex is the outer layer of the
cerebral hemispheres
• In humans, 90% of the cerebral cortex is
neocortex.
• It made up of six layers,
labeled I to VI
• It is involved in higher functions such as
sensory perception, generation of motor
commands, spatial reasoning, conscious
thought and, in humans, language.
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Visual cortex
The visual cortex resides
in the occipital lobe of the
brain.
Sensory impulses travel
from the eyes via the optic
nerve to the visual cortex.
Over 50% of the neocortex of
the macaque monkey is devoted
to processing visual information
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Visual cortex areas
• V1 = striate visual cortex
• V2, V4, V5 (MT, MST) = prestriate visual
cortex
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Visual cortex areas
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Towards a unified
theory of neocortex:
laminar cortical circuits for
vision and cognition
Stephen Grossberg
Technical Report CAS/CNS TR-2006-2008
Invited article to appear in:
Book Title: “Computational Neuroscience: From Neurons to Theory
and Back Again”
Publisher: Elsevier, Amsterdam
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Abstract
LAMINART architecture unifies properties of
• visual development
• Learning
• perceptual grouping
• Attention
• 3D vision.
A key modeling theme: mechanisms which
enable development and learning to occur
in a stable way imply properties of adult
behavior
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Introduction
Researchers have tried to establish link between
brain and mind by the use of application of
classical concepts to the brain, like:
• hydraulic systems
• digital Computers
• Holograms
• control theory circuits
• Bayesian networks
None of these approaches has managed to
explicate the unique design principles and
mechanisms that characterize biological
intelligence.
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Computational paradigms of
modeling of brain and behavior
• Complementary Computing :
matching and learning processes within
the What and Where cortical streams
• Laminar Computing:
cerebral cortex is organized into layered
circuits which undergo characteristic
bottom-up, top-down, and horizontal
interactions
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Model
• Some visual processes and their
anatomical substrates that are being
modeled as part of a unified vision system
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LGN = Lateral Geniculate Nucleus
V1 = striate visual cortex
V2, V4, MT, MST = prestriate visual cortex
IT = inferotemporal cortex
PPC = posterior parietal cortex
PFC = prefrontal cortex.
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Laminar Computing by
Visual Cortex
Unifying;
(1) Adaptive Filtering: the developmental
and learning processes
(2) Grouping: the binding process
(3) Attention
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A New Way to Compute
Properties:
• A new type of hybrid between feedforward
and feedback computing
• A hybrid computing that simultaneously
realizes the stability of digital computing
and the sensitivity of analog computing
• The ability to self-stabilize development
and learning using the intracortical
feedback loop
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Attention Arises from Top-Down
Cooperative-Competitive Matching
• Provide only excitatory modulation to cells
in the on-center,
• Strongly inhibit cells in the off-surround.
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The Preattentive-Attentive Interface
and Object-Based Attention
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Stable Development and Learning
through Adaptive Resonance
• attentionally relevant stimuli are learned
• irrelevant stimuli are suppressed and
prevented from destabilizing existing
representations
There is a link between
attention and learning
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3D LAMINART model
• LAMINART model
• Non-laminar FACADE model
3D LAMINART
3D LAMINART model has clarified how the laminar
circuits of cortical areas V1, V2, and V4 are organized
for purposes of stereopsis, 3D surface perception,
and 3D figure-ground perception
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Conclusion
The family of LAMINART models now
allows us to understand as variations
of a shared cortical design brain
processes that seem to be totally
unrelated on the level of behavioral
function.
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References
• “TOWARDS A UNIFIED THEORY OF
NEOCORTEX: Laminar Cortical Circuits for
Vision and Cognition”, Stephen Grossberg, Boston
University. Invited article to appear in: Book Title:
“Computational Neuroscience: From Neurons to Theory and
Back Again”, Editors: Paul Cisek, Trevor Drew, and John
Kalaska, Publisher: Elsevier, Amsterdam Supported
• “Principles of Neural Science”, 4th_Edition,
Eric R. Kandel, James H. Schwartz, Thomas M. Jessell
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Thank u
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