Design principles of columnar organization in visual cortex

Visual space is represented by cortical cells in an orderly manner. Only little variation in the cell behavior is found with changing depth below the cortical surface, that is, all cells in a column with axis perpendicular to the cortical plane have approximately the same properties (Hubel and Wiesel 1962, 1963, 1968). Therefore, the multiple features of the visual space (e.g., position in visual space, preferred orientation, and orientation tuning strength) are mapped on a two-dimensional space, the cortical plane. Such a dimension reduction leads to complex maps (Durbin and Mitchison 1990) that so far have evaded an intuitive understanding. Analyzing optical imaging data (Blasdel 1992a, b; Blasdel and Salama 1986; Grinvald et al. 1986) using a theoretical approach we will show that the most salient features of these maps can be understood from a few basic design principles: local correlation, modularity, isotropy, and homogeneity. These principles can be defined in a mathematically exact sense in the Fourier domain by a rather simple annulus-like spectral structure. Many of the models that have been developed to explain the mapping of the preferred orientations (Cooper et al. 1979; Legendy 1978; Linsker 1986a, b; Miller 1992; Nass and Cooper 1975; Obermayer et al. 1990, 1992; Soodak 1987; Swindale 1982, 1985, 1992; von der Malsburg 1973; von der Malsburg and Cowan 1982) are quite successful in generating maps that are close to experimental maps. We suggest that this success is due to these principles, which are common properties of the models and of biological maps

Functional Specialization of eye-specific visual pathways into higher visual cortex

The brain is able to construct a visual representation of the world by parallel processing of cortical neurons that prefer increasingly complex stimuli. One way the visual cortex has accomplished parallel processing is by creating functionally organized modules that are tuned to unique features and linking them in multiple processing stages of cortex. For example, primary visual cortex (V1) sends functionally distinct information to higher visual areas (HVAs), which are more specialized in their processing of spatiotemporal information. Inherently coupled to this process is the convergence of eye-specific inputs in visual cortex. Shifting the eye-specific tuning of neurons in primary visual cortex by monocular deprivation in early life is known to disrupt tuning for spatial frequency in adulthood. Combining space and time better characterizes the segregation of HVAs. To begin to understand if eye-specific responses could be linked to tuning properties important for the segregation of HVAs, we characterized eye-specific spatiotemporal tuning of layer 2/3 excitatory cells within the binocular zone of V1 and two HVAs grouped into the putative ventral and dorsal streams, LM and PM, using two-photon GCaMP6s imaging of awake mice. An asymmetry was found at the level of V1, such that responses driven primarily by the contralateral eye were biased towards high spatial frequencies, low speeds, cardinal directions, and were more direction selective than binocular or ipsilateral eye-driven responses. Eye-specific inputs in V1 are tuned to different speeds and also have different degrees of speed tuning, where contralateral eye inputs are more speed tuned than ipsilateral eye inputs. The proportions of eye-specific neurons of LM and PM matched the expected preferences based on eye-specific spatial frequency tuning found at the level of V1. A similar contralateral bias for distinct features, most notably, spatiotemporal tuning, was found within LM and PM, linking neurons with similar eye-specific preferences to their tuning for early feature detectors important for stream specialization. To determine if V1 sends eye-specific functionally distinct information to HVAs, we injected AAV-Syn-GCaMP6s into the binocular zone of V1 and imaged the afferents that targeted either LM or PM. We found that V1 afferents to LM and PM were distinct in their distributions for ocular dominance, suggesting that eye-specific projections from V1 to HVAs contribute to their functional specificity. To determine if the functional specialization of HVAs depend upon eye-specific developmental mechanisms, we deprived mice of visual experience through the contralateral eye (CMD) during the ocular dominance critical period and assessed eye-specific spatiotemporal tuning of V1, LM and PM in adulthood. We found that CMD diminished the functional specificity of V1, LM and PM, resulting in areas without differentiated spatiotemporal preferences. Moreover, the eye-specific functional segregation was also disrupted with CMD. Altogether, our data demonstrates that the maturation of higher visual areas is dependent on proper binocular visual experience and suggests that the functional specialization of eye-specific responses could be an efficient routing mechanism to differentiate higher visual areas

View-Invariant Object Category Learning, Recognition, and Search: How Spatial and Object Attention Are Coordinated Using Surface-Based Attentional Shrouds

Air Force Office of Scientific Research (F49620-01-1-0397); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

Synaptic rewiring in neuromorphic VLSI for topographic map formation

A generalised model of biological topographic map development is presented which combines both weight plasticity and the formation and elimination of synapses (synaptic rewiring) as well as both activity-dependent and -independent processes. The question of whether an activity-dependent process can refine a mapping created by an activity-independent process is investigated using a statistical approach to analysingmapping quality. The model is then implemented in custom mixed-signal VLSI. Novel aspects of this implementation include: (1) a distributed and locally reprogrammable address-event receiver, with which large axonal fan-out does not reduce channel capacity; (2) an analogue current-mode circuit for Euclidean distance calculation which is suitable for operation across multiple chips; (3) slow probabilistic synaptic rewiring driven by (pseudo-)random noise; (4) the application of a very-low-current design technique to improving the stability of weights stored on capacitors; (5) exploiting transistor non-ideality to implement partially weightdependent spike-timing-dependent plasticity; (6) the use of the non-linear capacitance of MOSCAP devices to compensate for other non-linearities. The performance of the chip is characterised and it is shown that the fabricated chips are capable of implementing the model, resulting in biologically relevant behaviours such as activity-dependent reduction of the spatial variance of receptive fields. Complementing a fast synaptic weight change mechanism with a slow synapse rewiring mechanism is suggested as a method of increasing the stability of learned patterns