A detailed model of the primary visual pathway in the cat: comparison of afferent excitatory and intracortical inhibitory connection schemes for orientation selectivity

In order to arrive at a quantitative understanding of the dynamics of cortical neuronal networks, we simulated a detailed model of the primary visual pathway of the adult cat. This computer model comprises a 5 degrees x 5 degrees patch of the visual field at a retinal eccentricity of 4.5 degrees and includes 2048 ON- and OFF-center retinal beta-ganglion cells, 8192 geniculate X-cells, and 4096 simple cells in layer IV in area 17. The neurons are implemented as improved integrate-and-fire units. Cortical receptive fields are determined by the pattern of afferent convergence and by inhibitory intracortical connections. Orientation columns are implemented continuously with a realistic receptive field scatter and jitter in the preferred orientations. We first show that realistic ON-OFF-responses, orientation selectivity, velocity low-pass behaviour, null response, and responses to spot stimuli can be obtained with an appropriate alignment of geniculate neurons converging onto the cortical simple cell (Hubel and Wiesel, 1962) and in the absence of intracortical connections. However, the average receptive field elongation (length to width) required to obtain realistic orientation tuning is 4.0, much higher than the average observed elongation. This strongly argues for additional intracortical mechanisms sharpening orientation selectivity. In the second stage, we simulated five different inhibitory intracortical connection patterns (random, local, sparse-local, circular, and cross-orientation) in order to investigate the connection specificity necessary to achieve orientation tuning. Inhibitory connection schemes were superimposed onto Hubel and Wiesel-type receptive fields with an elongation of 1.78. Cross-orientation inhibition gave rise to different horizontal and vertical orientation tuning curves, something not observed experimentally. A combination of two inhibitory schemes, local and circular inhibition (a weak form of cross-orientation inhibition), is in good agreement with observed receptive field properties. The specificity required to establish these connections during development is low. We propose that orientation selectivity is caused by at least three different mechanisms (“eclectic” model): a weak afferent geniculate bias, broadly tuned cross-orientation inhibition, and some iso-orientation inhibition. The most surprising finding is that an isotropic connection scheme, circular inhibition, in which a cell inhibits all of its postsynaptic target cells at a distance of approximately 500 microns, enhances orientation tuning and leads to a significant directional bias. This is caused by the embedding of cortical cells within a columnar structure and does not depend on our specific assumptions

Modeling direction selectivity of simple cells in striate visual cortex within the framework of the canonical microcircuit

Nearly all models of direction selectivity (DS) in visual cortex are based on feedforward connection schemes, where geniculate input provides all excitatory synaptic input to both pyramidal and inhibitory neurons. Feedforward inhibition then suppresses feedforward excitation for nonoptimal stimuli. Anatomically, however, the majority of asymmetric, excitatory, synaptic contacts onto cortical cells is provided by other cortical neurons, as embodied in the Canonical Microcircuit of Douglas and Martin (1991). In this view, weak geniculate input is strongly amplified in the preferred direction by the action of intracortical excitatory connections, while in the null direction inhibition reduces geniculate-induced excitation. We investigate analytically and through biologically realistic computer simulations the functioning of a cortical network based on massive excitatory, cortico-cortical feedback. The behavior of this network is compared to physiological data as well as to the behavior of a purely feedforward model of DS based on nonlagged input. Our model explains a number of puzzling features of direction selective simple cells, including the small somatic input conductance changes that have been measured experimentally during stimulation in the null direction, and the persistence of DS while fully blocking inhibition in a single cell. Although the operation at the heart of our network is amplification, the network passes the linearity test of (Jagadeesh et al., 1993). We make specific predictions concerning the effect of selective blockade of cortical inhibition on the velocity-response curve

Coverage, Continuity and Visual Cortical Architecture

The primary visual cortex of many mammals contains a continuous representation of visual space, with a roughly repetitive aperiodic map of orientation preferences superimposed. It was recently found that orientation preference maps (OPMs) obey statistical laws which are apparently invariant among species widely separated in eutherian evolution. Here, we examine whether one of the most prominent models for the optimization of cortical maps, the elastic net (EN) model, can reproduce this common design. The EN model generates representations which optimally trade of stimulus space coverage and map continuity. While this model has been used in numerous studies, no analytical results about the precise layout of the predicted OPMs have been obtained so far. We present a mathematical approach to analytically calculate the cortical representations predicted by the EN model for the joint mapping of stimulus position and orientation. We find that in all previously studied regimes, predicted OPM layouts are perfectly periodic. An unbiased search through the EN parameter space identifies a novel regime of aperiodic OPMs with pinwheel densities lower than found in experiments. In an extreme limit, aperiodic OPMs quantitatively resembling experimental observations emerge. Stabilization of these layouts results from strong nonlocal interactions rather than from a coverage-continuity-compromise. Our results demonstrate that optimization models for stimulus representations dominated by nonlocal suppressive interactions are in principle capable of correctly predicting the common OPM design. They question that visual cortical feature representations can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure

Towards a Unified Theory of Neocortex: Laminar Cortical Circuits for Vision and Cognition

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of pre-attentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

Always returning: feedback and sensory processing in visual cortex and thalamus

[Abstract] Feedback projections are an integral part of the mammalian visual system. Although it is tempting to relegate them to a subsidiary role in visual processing, because their supposed latency and lag might appear to be unfavourable for an involvement in fast processing, this is a dangerous simplification. Certainly for the world in motion, feedback from higher motion areas can influence the transfer of ascending input when, or even before, the input arrives. Here, we consider the circuit formed by layer 6 feedback cells in the visual cortex and how this straddles the retinothalamic and thalamocortical transfer of visual input. We discuss its links to feedback from the cortical motion area MT (V5), and suggest that motion perception involves a dynamic interplay between MT, V1 and the thalamus. This review is part of the TINS special issue on The Neural Substrates of Cognition

Towards building a more complex view of the lateral geniculate nucleus: Recent advances in understanding its role

The lateral geniculate nucleus (LGN) has often been treated in the past as a linear filter that adds little to retinal processing of visual inputs. Here we review anatomical, neurophysiological, brain imaging, and modeling studies that have in recent years built up a much more complex view of LGN . These include effects related to nonlinear dendritic processing, cortical feedback, synchrony and oscillations across LGN populations, as well as involvement of LGN in higher level cognitive processing. Although recent studies have provided valuable insights into early visual processing including the role of LGN, a unified model of LGN responses to real-world objects has not yet been developed. In the light of recent data, we suggest that the role of LGN deserves more careful consideration in developing models of high-level visual processing

Topographic plasticity in primary visual cortex is mediated by local corticocortical connections

The placement of monocular laser lesions in the adult cat retina produces a lesion projection zone (LPZ) in primary visual cortex (V1) in which the majority of neurons have a normally located receptive field (RF) for stimulation of the intact eye and an ectopically located RF ( displaced to intact retina at the edge of the lesion) for stimulation of the lesioned eye. Animals that had such lesions for 14 - 85 d were studied under halothane and nitrous oxide anesthesia with conventional neurophysiological recording techniques and stimulation of moving light bars. Previous work suggested that a candidate source of input, which could account for the development of the ectopic RFs, was long-range horizontal connections within V1. The critical contribution of such input was examined by placing a pipette containing the neurotoxin kainic acid at a site in the normal V1 visual representation that overlapped with the ectopic RF recorded at a site within the LPZ. Continuation of well defined responses to stimulation of the intact eye served as a control against direct effects of the kainic acid at the LPZ recording site. In six of seven cases examined, kainic acid deactivation of neurons at the injection site blocked responsiveness to lesioned-eye stimulation at the ectopic RF for the LPZ recording site. We therefore conclude that long-range horizontal projections contribute to the dominant input underlying the capacity for retinal lesion-induced plasticity in V1