Linking Visual Cortical Development to Visual Perception

Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI-97-20333); Office of Naval Research (N00014-95-1-0657

Linking Visual Development and Learning to Information Processing: Preattentive and Attentive Brain Dynamics

National Science Foundation (SBE-0354378); Office of Naval Research (N00014-95-1-0657

A Reaction-Diffusion Model to Capture Disparity Selectivity in Primary Visual Cortex

Decades of experimental studies are available on disparity selective cells in visual cortex of macaque and cat. Recently, local disparity map for iso-orientation sites for near-vertical edge preference is reported in area 18 of cat visual cortex. No experiment is yet reported on complete disparity map in V1. Disparity map for layer IV in V1 can provide insight into how disparity selective complex cell receptive field is organized from simple cell subunits. Though substantial amounts of experimental data on disparity selective cells is available, no model on receptive field development of such cells or disparity map development exists in literature. We model disparity selectivity in layer IV of cat V1 using a reaction-diffusion two-eye paradigm. In this model, the wiring between LGN and cortical layer IV is determined by resource an LGN cell has for supporting connections to cortical cells and competition for target space in layer IV. While competing for target space, the same type of LGN cells, irrespective of whether it belongs to left-eye-specific or right-eye-specific LGN layer, cooperate with each other while trying to push off the other type. Our model captures realistic 2D disparity selective simple cell receptive fields, their response properties and disparity map along with orientation and ocular dominance maps. There is lack of correlation between ocular dominance and disparity selectivity at the cell population level. At the map level, disparity selectivity topography is not random but weakly clustered for similar preferred disparities. This is similar to the experimental result reported for macaque. The details of weakly clustered disparity selectivity map in V1 indicate two types of complex cell receptive field organization

Modeling the self-organization of color selectivity in the visual cortex

How does the visual cortex represent and process color? Experimental evidence from macaque monkey suggests that cells selective for color are organized into small, spatially separated blobs in V1, and stripes in V2. This organization is strikingly different from that of orientation and ocular dominance maps, which consist of large, spatially contiguous patterns. In this dissertation, a self-organizing model of the early visual cortex is constructed using natural color image input. The modeled V1 develops realistic color-selective receptive fields, ocular dominance stripes, orientation maps, and color-selective regions, while the modeled V2 also creates realistic colorselective and orientation-selective neurons. V1 color-selective regions are generally located in the center of ocular dominance stripes as they are in biological maps; the model predicts that color-selective regions become more widespread in both cortical regions when the amount of color in the training images is increased. The model also predicts that in V1 there are three types of color-selective regions (red-selective, greenselective, and blue-selective), and that a unique cortical activation pattern exists for each of the HSV colors. In both V1 and V2, when regions of different color-selectivity are located nearby, bands of color form with gradually changing color preferences. The model also develops lateral connections between cells that are selective for similar orientations, matching previous experimental results, and predicts that cells selective for color primarily connect to other cells with similar chromatic preferences. Thus the model replicates the known data on the organization of color preferences in V1 and V2, provides a detailed explanation for how this structure develops and functions, and leads to concrete predictions to test in future experiments.Computer Science

Stable learning of functional maps in self-organizing spiking neural networks with continuous synaptic plasticity

This study describes a spiking model that self-organizes for stable formation and maintenance of orientation and ocular dominance maps in the visual cortex (V1). This self-organization process simulates three development phases: an early experience-independent phase, a late experience-independent phase and a subsequent refinement phase during which experience acts to shape the map properties. The ocular dominance maps that emerge accommodate the two sets of monocular inputs that arise from the lateral geniculate nucleus (LGN) to layer 4 of V1. The orientation selectivity maps that emerge feature well-developed iso-orientation domains and fractures. During the last two phases of development the orientation preferences at some locations appear to rotate continuously through ±180° along circular paths and referred to as pinwheel-like patterns but without any corresponding point discontinuities in the orientation gradient maps. The formation of these functional maps is driven by balanced excitatory and inhibitory currents that are established via synaptic plasticity based on spike timing for both excitatory and inhibitory synapses. The stability and maintenance of the formed maps with continuous synaptic plasticity is enabled by homeostasis caused by inhibitory plasticity. However, a prolonged exposure to repeated stimuli does alter the formed maps over time due to plasticity. The results from this study suggest that continuous synaptic plasticity in both excitatory neurons and interneurons could play a critical role in the formation, stability, and maintenance of functional maps in the cortex

Principles underlying the development and organization of feature maps in the visual cortex

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, February 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (leaves 139-142).A fundamental question in neuroscience is how sensory information is represented in the brain. In particular, what principles guide the spatial organization of neurons with regard to their receptive field properties, and how is this organization established mechanistically? The visual cortex serves as a model area to address these questions, but whether general principles can explain the layouts of cortical maps, such as those of visual space and of specific response features, remains unresolved. We find that in primary visual cortex of ferret, the layout of each map is inter-dependent with that of the others. First, we find a strong anisotropy in the visual map, such that receptive field positions change more rapidly along one axis of cortex; and importantly, along the axis where visual space changes rapidly, the feature maps of orientation, ocular dominance, and spatial frequency change slowly. Second, orientation, ocular dominance, and spatial frequency maps have local spatial relationships with each other: in areas of cortex where one feature changes rapidly, the other features change more slowly. Each of these relationships are well-explained by a dimension-reduction model of cortex.(cont.) This suggests that the constraints which drive map formation in the model, continuity (representing each feature smoothly across cortex) and coverage uniformity (representing each feature combination to an equal extent), may play a central role in determining the functional organization of visual cortex. To explore the mechanisms giving rise to the map relationships, we alter the expression of one feature map early in development and measure the impact on the layouts of the remaining maps. We find that alteration of the ocular dominance map, due to neonatal monocular enucleation, does not prevent the formation of the orientation and spatial frequency maps, but it does alter their spatial relationships. The highest gradient regions of the spatial frequency map have a stronger tendency to avoid high gradient orientation regions, and the contours of the two maps have a greater tendency to cross orthogonally. The results are consistent with the predictions of a dimension-reduction model for removing a feature map, suggesting that as a result of altered input patterns, the cortex can rearrange over the time scale of development according to a dimension-reduction strategy.by Brandon J. Farley.Ph.D

A geometric model of multi-scale orientation preference maps via Gabor functions

In this paper we present a new model for the generation of orientation preference maps in the primary visual cortex (V1), considering both orientation and scale features. First we undertake to model the functional architecture of V1 by interpreting it as a principal fiber bundle over the 2-dimensional retinal plane by introducing intrinsic variables orientation and scale. The intrinsic variables constitute a fiber on each point of the retinal plane and the set of receptive profiles of simple cells is located on the fiber. Each receptive profile on the fiber is mathematically interpreted as a rotated Gabor function derived from an uncertainty principle. The visual stimulus is lifted in a 4-dimensional space, characterized by coordinate variables, position, orientation and scale, through a linear filtering of the stimulus with Gabor functions. Orientation preference maps are then obtained by mapping the orientation value found from the lifting of a noise stimulus onto the 2-dimensional retinal plane. This corresponds to a Bargmann transform in the reducible representation of the $\text{SE}(2)=\mathbb{R}^2\times S^1$ group. A comparison will be provided with a previous model based on the Bargman transform in the irreducible representation of the $\text{SE}(2)$ group, outlining that the new model is more physiologically motivated. Then we present simulation results related to the construction of the orientation preference map by using Gabor filters with different scales and compare those results to the relevant neurophysiological findings in the literature

Cortical Maps

In this article, we review functional organization in sensory cortical regions-how the cortex represents the world. We consider four interrelated aspects of cortical organization: (1) the set of receptive fields of individual cortical sensory neurons, (2) how lateral interaction between cortical neurons reflects the similarity of their receptive fields, (3) the spatial distribution of receptive-field properties across the horizontal extent of the cortical tissue, and (4) how the spatial distributions of different receptive-field properties interact with one another. We show how these data are generally well explained by the theory of input-driven self-organization, with a family of computational models of cortical maps offering a parsimonious account for a wide range of map-related phenomena. We then discuss important challenges to this explanation, with respect to the maps present at birth, maps present under activity blockade, the limits of adult plasticity, and the lack of some maps in rodents. Because there is not at present another credible general theory for cortical map development, we conclude by proposing key experiments to help uncover other mechanisms that might also be operating during map development