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      The Visual Callosal Connection: A Connection Like Any Other?

      review-article
      1 , 2 , *
      Neural Plasticity
      Hindawi Publishing Corporation

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          Abstract

          Recent work about the role of visual callosal connections in ferrets and cats is reviewed, and morphological and functional homologies between the lateral intrinsic and callosal network in early visual areas are discussed. Both networks selectively link distributed neuronal groups with similar response properties, and the actions exerted by callosal input reflect the functional topography of those networks. This supports the notion that callosal connections perpetuate the function of the lateral intrahemispheric circuit onto the other hemisphere. Reversible deactivation studies indicate that the main action of visual callosal input is a multiplicative shift of responses rather than a changing response selectivity. Both the gain of that action and its excitatory-inhibitory balance seem to be dynamically adapted to the feedforward drive by the visual stimulus onto primary visual cortex. Taken together anatomical and functional evidence from corticocortical and lateral circuits further leads to the conclusion that visual callosal connections share more features with lateral intrahemispheric connections on the same hierarchical level and less with feedback connections. I propose that experimental results about the callosal circuit in early visual areas can be interpreted with respect to lateral connectivity in general.

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          Most cited references178

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          The variable discharge of cortical neurons: implications for connectivity, computation, and information coding.

          Cortical neurons exhibit tremendous variability in the number and temporal distribution of spikes in their discharge patterns. Furthermore, this variability appears to be conserved over large regions of the cerebral cortex, suggesting that it is neither reduced nor expanded from stage to stage within a processing pathway. To investigate the principles underlying such statistical homogeneity, we have analyzed a model of synaptic integration incorporating a highly simplified integrate and fire mechanism with decay. We analyzed a "high-input regime" in which neurons receive hundreds of excitatory synaptic inputs during each interspike interval. To produce a graded response in this regime, the neuron must balance excitation with inhibition. We find that a simple integrate and fire mechanism with balanced excitation and inhibition produces a highly variable interspike interval, consistent with experimental data. Detailed information about the temporal pattern of synaptic inputs cannot be recovered from the pattern of output spikes, and we infer that cortical neurons are unlikely to transmit information in the temporal pattern of spike discharge. Rather, we suggest that quantities are represented as rate codes in ensembles of 50-100 neurons. These column-like ensembles tolerate large fractions of common synaptic input and yet covary only weakly in their spike discharge. We find that an ensemble of 100 neurons provides a reliable estimate of rate in just one interspike interval (10-50 msec). Finally, we derived an expression for the variance of the neural spike count that leads to a stable propagation of signal and noise in networks of neurons-that is, conditions that do not impose an accumulation or diminution of noise. The solution implies that single neurons perform simple algebra resembling averaging, and that more sophisticated computations arise by virtue of the anatomical convergence of novel combinations of inputs to the cortical column from external sources.
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            Feature-based attention influences motion processing gain in macaque visual cortex.

            Changes in neural responses based on spatial attention have been demonstrated in many areas of visual cortex, indicating that the neural correlate of attention is an enhanced response to stimuli at an attended location and reduced responses to stimuli elsewhere. Here we demonstrate non-spatial, feature-based attentional modulation of visual motion processing, and show that attention increases the gain of direction-selective neurons in visual cortical area MT without narrowing the direction-tuning curves. These findings place important constraints on the neural mechanisms of attention and we propose to unify the effects of spatial location, direction of motion and other features of the attended stimuli in a 'feature similarity gain model' of attention.
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              A quantitative map of the circuit of cat primary visual cortex.

              We developed a quantitative description of the circuits formed in cat area 17 by estimating the "weight" of the projections between different neuronal types. To achieve this, we made three-dimensional reconstructions of 39 single neurons and thalamic afferents labeled with horseradish peroxidase during intracellular recordings in vivo. These neurons served as representatives of the different types and provided the morphometrical data about the laminar distribution of the dendritic trees and synaptic boutons and the number of synapses formed by a given type of neuron. Extensive searches of the literature provided the estimates of numbers of the different neuronal types and their distribution across the cortical layers. Applying the simplification that synapses between different cell types are made in proportion to the boutons and dendrites that those cell types contribute to the neuropil in a given layer, we were able to estimate the probable source and number of synapses made between neurons in the six layers. The predicted synaptic maps were quantitatively close to the estimates derived from the experimental electron microscopic studies for the case of the main sources of excitatory and inhibitory input to the spiny stellate cells, which form a major target of layer 4 afferents. The map of the whole cortical circuit shows that there are very few "strong" but many "weak" excitatory projections, each of which may involve only a few percentage of the total complement of excitatory synapses of a single neuron.
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                Author and article information

                Journal
                Neural Plast
                Neural Plast
                NP
                Neural Plasticity
                Hindawi Publishing Corporation
                2090-5904
                1687-5443
                2013
                24 March 2013
                : 2013
                : 397176
                Affiliations
                1Brain Institute, University of Rio Grande do Norte, Av. Nascimento de Castro 2155, 59056-450 Natal, RN, Brazil
                2Max-Planck-Institute for Brain Research, Deutschordenstrasse 46, 60528 Frankfurt, Germany
                Author notes
                *Kerstin E. Schmidt: kschmidt@ 123456neuro.ufrn.br

                Academic Editor: Maurice Ptito

                Article
                10.1155/2013/397176
                3619632
                23634306
                0511224d-00e4-41d3-8da7-7c15c0156d46
                Copyright © 2013 Kerstin E. Schmidt.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 7 November 2012
                : 27 February 2013
                Categories
                Review Article

                Neurosciences
                Neurosciences

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