10 research outputs found
Unified developmental model of maps, complex cells and surround modulation in the primary visual cortex
For human and animal vision, the perception of local visual features can depend on
the spatial arrangement of the surrounding visual stimuli. In the earliest stages of visual
processing this phenomenon is called surround modulation, where the response of
visually selective neurons is influenced by the response of neighboring neurons. Surround
modulation has been implicated in numerous important perceptual phenomena,
such as contour integration and figure-ground segregation. In cats, one of the major
potential neural substrates for surround modulation are lateral connections between
cortical neurons in layer 2/3, which typically contains ”complex” cells that appear to
combine responses from ”simple” cells in layer 4C. Interestingly, these lateral connections
have also been implicated in the development of functional maps in primary
visual cortex, such as smooth, well-organized maps for the preference of oriented lines.
Together, this evidence suggests a common underlying substrate the lateral interactions
in layer 2/3—as the driving force behind development of orientation maps for
both simple and complex cells, and at the same time expression of surround modulation
in adult animals. However, previously these phenomena have been studied
largely in isolation, and we are not aware of a computational model that can account
for all of them simultaneously and show how they are related. In this thesis we resolve
this problem by building a single, unified computational model that can explain the
development of orientation maps, the development of simple and complex cells, and
surround modulation.
First we build a simple, single-layer model of orientation map development based
on ALISSOM, which has more realistic single cell properties (such as contrast gain
control and contrast invariant orientation tuning) than its predecessor. Then we extend
this model by adding layer 2/3, and show how the model can explain development of
orientation maps of both simple and complex cells. As the last step towards a developmental
model of surround modulation, we replace Mexican-hat-like lateral connectivity
in layer 2/3 of the model with a more realistic configuration based on long-range
excitation and short-range inhibitory cells, extending a simpler model by Judith Law.
The resulting unified model of V1 explains how orientation maps of simple and
complex cells can develop, while individual neurons in the developed model express
realistic orientation tuning and various surround modulation properties. In doing so,
we not only offer a consistent explanation behind all these phenomena, but also create
a very rich model of V1 in which the interactions between various V1 properties can
be studied. The model allows us to formulate several novel predictions that relate the variation of single cell properties to their location in the orientation preference maps
in V1, and we show how these predictions can be tested experimentally. Overall,
this model represents a synthesis of a wide body of experimental evidence, forming a
compact hypothesis for much of the development and behavior of neurons in the visual cortex
The emergence of functional microcircuits in visual cortex.
Sensory processing occurs in neocortical microcircuits in which synaptic connectivity is highly structured and excitatory neurons form subnetworks that process related sensory information. However, the developmental mechanisms underlying the formation of functionally organized connectivity in cortical microcircuits remain unknown. Here we directly relate patterns of excitatory synaptic connectivity to visual response properties of neighbouring layer 2/3 pyramidal neurons in mouse visual cortex at different postnatal ages, using two-photon calcium imaging in vivo and multiple whole-cell recordings in vitro. Although neural responses were already highly selective for visual stimuli at eye opening, neurons responding to similar visual features were not yet preferentially connected, indicating that the emergence of feature selectivity does not depend on the precise arrangement of local synaptic connections. After eye opening, local connectivity reorganized extensively: more connections formed selectively between neurons with similar visual responses and connections were eliminated between visually unresponsive neurons, but the overall connectivity rate did not change. We propose a sequential model of cortical microcircuit development based on activity-dependent mechanisms of plasticity whereby neurons first acquire feature preference by selecting feedforward inputs before the onset of sensory experience--a process that may be facilitated by early electrical coupling between neuronal subsets--and then patterned input drives the formation of functional subnetworks through a redistribution of recurrent synaptic connections
Unified developmental model of maps, complex cells and surround modulation in the primary visual cortex
For human and animal vision, the perception of local visual features can depend on the spatial arrangement of the surrounding visual stimuli. In the earliest stages of visual processing this phenomenon is called surround modulation, where the response of visually selective neurons is influenced by the response of neighboring neurons. Surround modulation has been implicated in numerous important perceptual phenomena, such as contour integration and figure-ground segregation. In cats, one of the major potential neural substrates for surround modulation are lateral connections between cortical neurons in layer 2/3, which typically contains ”complex” cells that appear to combine responses from ”simple” cells in layer 4C. Interestingly, these lateral connections have also been implicated in the development of functional maps in primary visual cortex, such as smooth, well-organized maps for the preference of oriented lines. Together, this evidence suggests a common underlying substrate the lateral interactions in layer 2/3—as the driving force behind development of orientation maps for both simple and complex cells, and at the same time expression of surround modulation in adult animals. However, previously these phenomena have been studied largely in isolation, and we are not aware of a computational model that can account for all of them simultaneously and show how they are related. In this thesis we resolve this problem by building a single, unified computational model that can explain the development of orientation maps, the development of simple and complex cells, and surround modulation. First we build a simple, single-layer model of orientation map development based on ALISSOM, which has more realistic single cell properties (such as contrast gain control and contrast invariant orientation tuning) than its predecessor. Then we extend this model by adding layer 2/3, and show how the model can explain development of orientation maps of both simple and complex cells. As the last step towards a developmental model of surround modulation, we replace Mexican-hat-like lateral connectivity in layer 2/3 of the model with a more realistic configuration based on long-range excitation and short-range inhibitory cells, extending a simpler model by Judith Law. The resulting unified model of V1 explains how orientation maps of simple and complex cells can develop, while individual neurons in the developed model express realistic orientation tuning and various surround modulation properties. In doing so, we not only offer a consistent explanation behind all these phenomena, but also create a very rich model of V1 in which the interactions between various V1 properties can be studied. The model allows us to formulate several novel predictions that relate the variation of single cell properties to their location in the orientation preference maps in V1, and we show how these predictions can be tested experimentally. Overall, this model represents a synthesis of a wide body of experimental evidence, forming a compact hypothesis for much of the development and behavior of neurons in the visual cortex.EThOS - Electronic Theses Online ServiceGBUnited Kingdo