It is well known that visual cortical neurons respond vigorously to a limited range of stimulus orientations, while their primary afferent inputs, neurons in the lateral geniculate nucleus (LGN), respond well to all orientations. Mechanisms based on intracortical inhibition and/or converging thalamocortical afferents have previously been suggested to underlie the generation of cortical orientation selectivity; however, these models conflict with experimental data. Here, a 1:4 scale model of a 1700 microns by 200 microms region of layer IV of cat primary visual cortex (area 17) is presented to demonstrate that local intracortical excitation may provide the dominant source of orientation-selective input. In agreement with experiment, model cortical cells exhibit sharp orientation selectivity despite receiving strong iso-orientation inhibition, weak cross-orientation inhibition, no shunting inhibition, and weakly tuned thalamocortical excitation. Sharp tuning is provided by recurrent cortical excitation. As this tuning signal arises from the same pool of neurons that it excites, orientation selectivity in the model is shown to be an emergent property of the cortical feedback circuitry. In the model, as in experiment, sharpness of orientation tuning is independent of stimulus contrast and persists with silencing of ON-type subfields. The model also provides a unified account of intracellular and extracellular inhibitory blockade experiments that had previously appeared to conflict over the role of inhibition. It is suggested that intracortical inhibition acts nonspecifically and indirectly to maintain the selectivity of individual neurons by balancing strong intracortical excitation at the columnar level.

https://www.jneurosci.org/content/jneuro/15/8/5448.full.pdf

An emergent model of orientation selectivity in cat visual cortical simple cells

The analysis of visual motion plays a central role in biological systems. Sophisticated mechanisms for extracting and utilizing motion exist even in simple animals. For example, the frog has efficient ”bug detection” mechanisms that respond selectively to small, dark objects moving in its visual field [1]. The ordinary housefly can track moving objects and discover the relative motion between a target and its background, even when the two are indistinguishable in the absence of relative motion [2].

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The Measurement of Visual Motion

This investigation aims at exploring some of the functional consequences of single neurons containing active, voltage dependent channels for information processing. Assuming that the voltage change in the dendritic tree of these neurons does not exceed a few millivolts, it is possible to linearize the non-linear channel conductance. The membrane can then be described in terms of resistances, capacitances and inductances, as for instance in the small-signal analysis of the squid giant axon. Depending on the channel kinetics and the associated ionic battery the linearization yields two basic types of membrane: a membrane modeled by a collection of resistances and capacitances and membranes containing in addition to these components inductances. Under certain specified conditions the latter type of membrane gives rise to a membrane impedance that displays a prominent maximum at some nonzero resonant frequency fmax. We call this type of membrane quasi-active, setting it apart from the usual passive membrane. We study the linearized behaviour of active channels giving rise to quasi-active membranes in extended neuronal structures and consider several instances where such membranes may subserve neuronal function: 1. The resonant frequency of a quasi-active membrane increases with increasing density of active channels. This might be one of the biophysical mechanisms generating the large range over which hair cells in the vertebrate cochlea display frequency tuning. 2. The voltage recorded from a cable with a quasi-active membrane can be proportional to the temporal derivative of the injected current. 3. We modeled a highly branched dendritic tree (delta-ganglion cell of the cat retina) using a quasi-active membrane. The voltage attenuation from a given synaptic site to the soma decreases with increasing frequency up to the resonant frequency, in sharp contrast to the behaviour of passive membranes.(ABSTRACT TRUNCATED AT 400 WORDS)

Cable theory in neurons with active, linearized membranes.

Massively parallel (neural-like) networks are receiving increasing attention as a mechanism for expressing information processing models. By exploiting powerful primitive units and stability-preserving construction rules, various workers have been able to construct and test quite complex models, particularly in vision research. But all of the detailed technical work was concerned with the structure and behavior offixed networks. The purpose of this paper is to extend the methodology to cover several aspects of change and memory.

/pdf/dynamic-connections-in-neural-networks-15ormuua2h.pdf

Dynamic connections in neural networks

This article describes the implementation of a theory for the detection of intensity changes, proposed by Marr and Hildreth (Proc. R. Soc. London, Ser. B 207, 1980, 187–217). According to this theory, the image is first processed independently through a set of different size operators, whose shape is the Laplacian of a Gaussian, ▿2G(x, y). The loci, along which the convolution outputs cross zero mark the positions of intensity changes at different resolutions. These zero-crossings can be described by their position, slope of the convolution output across zero, and two-dimensional orientation. The set of descriptions from different operator sizes forms the input for later visual processes, such as stereopsis and motion analysis. There are close parallels between this theory and the early processing of information by the human visual system.

The detection of intensity changes by computer and biological vision systems

A model is proposed for the temporal characteristics of X- and Y-type responses of ganglion cells in the primate retina. The main suggestions of the model are: (I) The X-type temporal response is determined primarily by the delay between center and surround contributions. (II) The Y-type response is generated in the inner plexiform layer by a derivative-like operation on the bipolar cell's input, followed by a rectification in the convergence of these inputs onto the Y-ganglion-cell. (III) The derivative-like operation is obtained by recurrent inhibition in the dyad synaptic structure. The X- and Y-type responses predicted by the model, for a variety of stimuli, were examined and compared with available electrophysiological recordings. Finally, certain predictions derived from the model are discussed.

Jacob Richter

Papers

A model for the temporal organization of X- and Y-type receptive fields in the primate retina.