Task-evoked activity quenches neural correlations and variability across cortical areas
Open Access
- 3 August 2020
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLoS Computational Biology
- Vol. 16 (8), e1007983
- https://doi.org/10.1371/journal.pcbi.1007983
Abstract
Many large-scale functional connectivity studies have emphasized the importance of communication through increased inter-region correlations during task states. In contrast, local circuit studies have demonstrated that task states primarily reduce correlations among pairs of neurons, likely enhancing their information coding by suppressing shared spontaneous activity. Here we sought to adjudicate between these conflicting perspectives, assessing whether co-active brain regions during task states tend to increase or decrease their correlations. We found that variability and correlations primarily decrease across a variety of cortical regions in two highly distinct data sets: non-human primate spiking data and human functional magnetic resonance imaging data. Moreover, this observed variability and correlation reduction was accompanied by an overall increase in dimensionality (reflecting less information redundancy) during task states, suggesting that decreased correlations increased information coding capacity. We further found in both spiking and neural mass computational models that task-evoked activity increased the stability around a stable attractor, globally quenching neural variability and correlations. Together, our results provide an integrative mechanistic account that encompasses measures of large-scale neural activity, variability, and correlations during resting and task states. Statistical estimates of correlated neural activity and variability are widely used to characterize neural systems during different states. However, there is a conceptual gap between the use and interpretation of these measures between the human neuroimaging and non-human primate electrophysiology literature. For example, in the human neuroimaging literature, “functional connectivity” is often used to refer to correlated activity, while in the non-human primate electrophysiology literature, the equivalent term is “noise correlation”. In an effort to unify these two perspectives under a single theoretical framework, we provide empirical evidence from human functional magnetic resonance imaging and non-human primate mean-field spike rate data that functional connectivity and noise correlations reveal similar statistical patterns during task states. In short, we found that task states primarily quench neural variability and correlations in both data sets. To provide a theoretically rigorous account capable of explaining this phenomena across both data sets, we use mean-field dynamical systems modeling to demonstrate the deterministic relationship between task-evoked activity, neural variability and correlations. Together, we provide an integrative account, showing that task-evoked activity quenches neural variability and correlations in large-scale neural systems.Keywords
This publication has 71 references indexed in Scilit:
- Functional Network Organization of the Human BrainNeuron, 2011
- The organization of the human cerebral cortex estimated by intrinsic functional connectivityJournal of Neurophysiology, 2011
- Cortical state and attentionNature Reviews Neuroscience, 2011
- Measuring and interpreting neuronal correlationsNature Neuroscience, 2011
- Category-Selective Background Connectivity in Ventral Visual CortexCerebral Cortex, 2011
- Stimulus onset quenches neural variability: a widespread cortical phenomenonNature Neuroscience, 2010
- The Asynchronous State in Cortical CircuitsScience, 2010
- Attention improves performance primarily by reducing interneuronal correlationsNature Neuroscience, 2009
- The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?NeuroImage, 2009
- A component based noise correction method (CompCor) for BOLD and perfusion based fMRINeuroImage, 2007