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      Linear Transformation of Thalamocortical input by Intracortical Excitation

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          Abstract

          Neurons in thalamorecipient layers of sensory cortices integrate thalamocortical and intracortical inputs. Although their functional properties can be inherited from the convergence of thalamic inputs, the roles of intracortical circuits in thalamocortical transformation of sensory information remain unclear. Here, by reversibly silencing intracortical excitatory circuits with optogenetic activation of parvalbumin-positive inhibitory neurons in mouse primary visual cortex, we compared visually-evoked thalamocortical input with total excitation in the same layer 4 pyramidal neurons. We found that intracortical excitatory circuits preserve the orientation and direction tuning of thalamocortical excitation, with a linear amplification of thalamocortical signals by about threefold. The spatial receptive field of thalamocortical input is slightly elongated, and is expanded by intracortical excitation in an approximately proportional manner. Thus, intracortical excitatory circuits faithfully reinforce the representation of thalamocortical information, and may influence the size of the receptive field by recruiting additional inputs.

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          Most cited references52

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          Highly selective receptive fields in mouse visual cortex.

          Genetic methods available in mice are likely to be powerful tools in dissecting cortical circuits. However, the visual cortex, in which sensory coding has been most thoroughly studied in other species, has essentially been neglected in mice perhaps because of their poor spatial acuity and the lack of columnar organization such as orientation maps. We have now applied quantitative methods to characterize visual receptive fields in mouse primary visual cortex V1 by making extracellular recordings with silicon electrode arrays in anesthetized mice. We used current source density analysis to determine laminar location and spike waveforms to discriminate putative excitatory and inhibitory units. We find that, although the spatial scale of mouse receptive fields is up to one or two orders of magnitude larger, neurons show selectivity for stimulus parameters such as orientation and spatial frequency that is near to that found in other species. Furthermore, typical response properties such as linear versus nonlinear spatial summation (i.e., simple and complex cells) and contrast-invariant tuning are also present in mouse V1 and correlate with laminar position and cell type. Interestingly, we find that putative inhibitory neurons generally have less selective, and nonlinear, responses. This quantitative description of receptive field properties should facilitate the use of mouse visual cortex as a system to address longstanding questions of visual neuroscience and cortical processing.
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            Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex.

            Neurons in the cerebral cortex are organized into anatomical columns, with ensembles of cells arranged from the surface to the white matter. Within a column, neurons often share functional properties, such as selectivity for stimulus orientation; columns with distinct properties, such as different preferred orientations, tile the cortical surface in orderly patterns. This functional architecture was discovered with the relatively sparse sampling of microelectrode recordings. Optical imaging of membrane voltage or metabolic activity elucidated the overall geometry of functional maps, but is averaged over many cells (resolution >100 microm). Consequently, the purity of functional domains and the precision of the borders between them could not be resolved. Here, we labelled thousands of neurons of the visual cortex with a calcium-sensitive indicator in vivo. We then imaged the activity of neuronal populations at single-cell resolution with two-photon microscopy up to a depth of 400 microm. In rat primary visual cortex, neurons had robust orientation selectivity but there was no discernible local structure; neighbouring neurons often responded to different orientations. In area 18 of cat visual cortex, functional maps were organized at a fine scale. Neurons with opposite preferences for stimulus direction were segregated with extraordinary spatial precision in three dimensions, with columnar borders one to two cells wide. These results indicate that cortical maps can be built with single-cell precision.
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              Connectivity reflects coding: a model of voltage-based STDP with homeostasis.

              Electrophysiological connectivity patterns in cortex often have a few strong connections, which are sometimes bidirectional, among a lot of weak connections. To explain these connectivity patterns, we created a model of spike timing-dependent plasticity (STDP) in which synaptic changes depend on presynaptic spike arrival and the postsynaptic membrane potential, filtered with two different time constants. Our model describes several nonlinear effects that are observed in STDP experiments, as well as the voltage dependence of plasticity. We found that, in a simulated recurrent network of spiking neurons, our plasticity rule led not only to development of localized receptive fields but also to connectivity patterns that reflect the neural code. For temporal coding procedures with spatio-temporal input correlations, strong connections were predominantly unidirectional, whereas they were bidirectional under rate-coded input with spatial correlations only. Thus, variable connectivity patterns in the brain could reflect different coding principles across brain areas; moreover, our simulations suggested that plasticity is fast.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nat. Neurosci.
                Nature neuroscience
                1097-6256
                1546-1726
                3 September 2013
                11 August 2013
                September 2013
                01 March 2014
                : 16
                : 9
                : 10.1038/nn.3494
                Affiliations
                [1 ]Zilkha Neurogenetic Institute, University of Southern California, Los Angeles, CA 90089, USA
                [2 ]Department of Cell and Neurobiology, University of Southern California, Los Angeles, CA 90089, USA
                [3 ]Department of Physiology and Biophysics, University of Southern California, Los Angeles, CA 90089, USA
                [4 ]Graduate Programs, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA
                Author notes
                [* ]Correspondence should be addressed to: H.W.Tao, htao@ 123456usc.edu
                Article
                NIHMS507217
                10.1038/nn.3494
                3855439
                23933750
                27f35a89-b833-4bb2-afee-54d6c096cc4d

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                History
                Funding
                Funded by: National Eye Institute : NEI
                Award ID: R21 EY022478 || EY
                Funded by: National Eye Institute : NEI
                Award ID: R01 EY019049 || EY
                Funded by: National Institute on Deafness and Other Communication Disorders : NIDCD
                Award ID: R01 DC008983 || DC
                Categories
                Article

                Neurosciences
                Neurosciences

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