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      Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

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          Abstract

          A large-scale laminar network model sheds light on frequency-dependent interactions in the primate cortex.

          Abstract

          Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

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          Most cited references40

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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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            Selective gating of visual signals by microstimulation of frontal cortex.

            Several decades of psychophysical and neurophysiological studies have established that visual signals are enhanced at the locus of attention. What remains a mystery is the mechanism that initiates biases in the strength of visual representations. Recent evidence argues that, during spatial attention, these biases reflect nascent saccadic eye movement commands. We examined the functional interaction of saccade preparation and visual coding by electrically stimulating sites within the frontal eye fields (FEF) and measuring its effect on the activity of neurons in extrastriate visual cortex. Here we show that visual responses in area V4 could be enhanced after brief stimulation of retinotopically corresponding sites within the FEF using currents below that needed to evoke saccades. The magnitude of the enhancement depended on the effectiveness of receptive field stimuli as well as on the presence of competing stimuli outside the receptive field. Stimulation of non-corresponding FEF representations could suppress V4 responses. The results suggest that the gain of visual signals is modified according to the strength of spatially corresponding eye movement commands.
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              A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortex.

              We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for "temporal receptive windows" that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or electroencephalography/magnetoencephalography) by taking into account inter-areal heterogeneity.
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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                November 2016
                16 November 2016
                : 2
                : 11
                : e1601335
                Affiliations
                [1 ]Center for Neural Science, New York University (NYU), New York, NY 10003, USA.
                [2 ]Department of Psychiatry, Yale School of Medicine, New Haven, CT 06511, USA.
                [3 ]Stem Cell and Brain Research Institute, INSERM U846, Bron, France.
                [4 ]Université de Lyon, Université Lyon I, Lyon, France.
                [5 ]NYU–East China Normal University Institute for Brain and Cognitive Science, NYU Shanghai, Shanghai, China.
                Author notes
                [* ]Corresponding author. Email: xjwang@ 123456nyu.edu
                Author information
                http://orcid.org/0000-0003-3124-8474
                Article
                1601335
                10.1126/sciadv.1601335
                5262462
                28138530
                c10f332a-8152-4bee-af89-3de096476c6d
                Copyright © 2016, The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

                History
                : 12 June 2016
                : 20 October 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000006, Office of Naval Research;
                Award ID: ID0ED3AG12440
                Award ID: N00014-13-1-0297
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: ID0EYCBG12441
                Award ID: R01MH062349
                Award Recipient :
                Funded by: STCSM;
                Award ID: ID0ENJBG12442
                Award ID: 14JC1404900
                Award Recipient :
                Funded by: STCSM;
                Award ID: ID0EAQBG12443
                Award ID: 15JC1400104
                Award Recipient :
                Funded by: ANR;
                Award ID: ID0ETWBG12444
                Award ID: ANR-11-BSV4-501
                Award Recipient :
                Funded by: LABEX CORTEX;
                Award ID: ID0E51BG12445
                Award ID: ANR-11-LABX-0042
                Award Recipient :
                Funded by: ANR;
                Award ID: ID0EJ6BG12446
                Award ID: ANR-11-IDEX-0007
                Award Recipient :
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Neuroscience

                large-scale brain model,cortical layers,neural oscillations,granger causality,visual hierarchy,gamma,alpha

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