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      Canonical correlations reveal co-variability between spike trains and local field potentials in area MT)

      abstract
      1 , 2 , 1 , 3 ,
      BMC Neuroscience
      BioMed Central
      24th Annual Computational Neuroscience Meeting: CNS*2015
      18-23 July 2015

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          Abstract

          Patterns of neuronal correlations can provide important clues about the structure of the underlying network and how it processes information. Several recent studies have found that neural population activity across a region can be explained in large part by a shared, low-dimensional signal [1-5]. Population-wide correlation is likely to influence the local field potential (LFP) - an epiphenomenon that reflects low-frequency, concerted neural activity from anatomically connected circuits. Here, we show that LFP and spike trains recorded simultaneously from the middle temporal (MT) area of the awake macaque indeed share population-wide correlation. We apply canonical correlation analysis (CCA) to 16 channels of LFP and 16 spike sorted neurons (from 12 channels) acquired at 50 ms temporal resolution during inter-trial intervals (when the monkey was free to make eye movements), as well as during performance of a perceptual decision-making task (when the monkey maintained fixation and discriminated the direction of visual motion). CCA finds instantaneous linear projections of the LFP that maximize the correlation to corresponding projections of the population spike trains. Previous studies have suggested using population spike rate as a proxy for the local network state [3,5]. Applied to our dataset, we obtain a correlation coefficient of -12% between population spike rate and the mean LFP during inter-trial interval segments. In contrast, we obtain pairs of canonical variables with corresponding canonical correlations 29%, 26%, and 21%. We then applied the extracted projections to the task-relevant motion stimulus integration window. We find that the correlation of the projections is maintained for the 1st (31%) and 3rd (18%) components, but drops significantly for the 2nd component (7%)-- indicating a task-specific decoupling of LFP and spikes in a subspace uncovered by CCA. Upon further analysis, each CCA projection showed a distinct stimulus encoding pattern in spike rate and LFP. We hypothesize that CCA projections reveal functional, virtual units of information processing. The LFP is an important source of information when neural activity is correlated. It can indicate the strength of correlations, and the common input giving rise to such correlations. Additionally, the LFP provides increased statistical power to analyses, especially in areas where large-scale recording is anatomically difficult. CCA is a simple technique that can reveal low-dimensional structure in the data, uncovering components which maximize covariability between LFP and spike trains within MT.

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          Most cited references4

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          Partitioning neuronal variability

          Responses of sensory neurons differ across repeated measurements. This variability is usually treated as stochasticity arising within neurons or neural circuits. However, some portion of the variability arises from fluctuations in excitability due to factors that are not purely sensory, such as arousal, attention, and adaptation. To isolate these fluctuations, we developed a model in which spikes are generated by a Poisson process whose rate is the product of a drive that is sensory in origin, and a gain summarizing stimulus-independent modulatory influences on excitability. This model provides an accurate account of response distributions of visual neurons in macaque LGN, V1, V2, and MT, revealing that variability originates in large part from excitability fluctuations which are correlated over time and between neurons, and which increase in strength along the visual pathway. The model provides a parsimonious explanation for observed systematic dependencies of response variability and covariability on firing rate.
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            State dependence of noise correlations in macaque primary visual cortex.

            Shared, trial-to-trial variability in neuronal populations has a strong impact on the accuracy of information processing in the brain. Estimates of the level of such noise correlations are diverse, ranging from 0.01 to 0.4, with little consensus on which factors account for these differences. Here we addressed one important factor that varied across studies, asking how anesthesia affects the population activity structure in macaque primary visual cortex. We found that under opioid anesthesia, activity was dominated by strong coordinated fluctuations on a timescale of 1-2 Hz, which were mostly absent in awake, fixating monkeys. Accounting for these global fluctuations markedly reduced correlations under anesthesia, matching those observed during wakefulness and reconciling earlier studies conducted under anesthesia and in awake animals. Our results show that internal signals, such as brain state transitions under anesthesia, can induce noise correlations but can also be estimated and accounted for based on neuronal population activity. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Gating of sensory input by spontaneous cortical activity.

              The activity of neural populations is determined not only by sensory inputs but also by internally generated patterns. During quiet wakefulness, the brain produces spontaneous firing events that can spread over large areas of cortex and have been suggested to underlie processes such as memory recall and consolidation. Here we demonstrate a different role for spontaneous activity in sensory cortex: gating of sensory inputs. We show that population activity in rat auditory cortex is composed of transient 50-100 ms packets of spiking activity that occur irregularly during silence and sustained tone stimuli, but reliably at tone onset. Population activity within these packets had broadly consistent spatiotemporal structure, but the rate and also precise relative timing of action potentials varied between stimuli. Packet frequency varied with cortical state, with desynchronized state activity consistent with superposition of multiple overlapping packets. We suggest that such packets reflect the sporadic opening of a "gate" that allows auditory cortex to broadcast a representation of external sounds to other brain regions.
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                Author and article information

                Contributors
                Conference
                BMC Neurosci
                BMC Neurosci
                BMC Neuroscience
                BioMed Central
                1471-2202
                2015
                4 December 2015
                : 16
                : Suppl 1
                : P194
                Affiliations
                [1 ]Center for Perceptual Systems, The University of Texas at Austin, Austin, TX 78712, USA
                [2 ]Department of Statistics and Grossman Center for the Statistics of Mind, Columbia University, New York, NY 10027, USA
                [3 ]Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, NY 11794, USA
                Article
                1471-2202-16-S1-P194
                10.1186/1471-2202-16-S1-P194
                4699160
                319831c9-6598-4878-ac1b-c18014f9a367
                Copyright © 2015 Yates et al.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                24th Annual Computational Neuroscience Meeting: CNS*2015
                Prague, Czech Republic
                18-23 July 2015
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                Neurosciences
                Neurosciences

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