Correlations enhance the behavioral readout of neural population activity in association cortex

Abstract

The spatiotemporal structure of activity in populations of neurons is critical for accurate perception and behavior. Experimental and theoretical studies have focused on "noise" correlations -trial-totrial covariations in neural activity for a given stimulus -as a key feature of population activity structure. Much work has shown that these correlations limit the stimulus information encoded by a population of neurons, leading to the widely-held prediction that correlations are detrimental for perceptual discrimination behaviors. However, this prediction relies on an untested assumption: that the neural mechanisms that read out sensory information to inform behavior depend only on a population's total stimulus information independently of how correlations constrain this information across neurons or time. Here we make the critical advance of simultaneously studying how correlations affect both the encoding and the readout of sensory information. We analyzed calcium imaging data from mouse posterior parietal cortex during two perceptual discrimination tasks. Correlations limited the ability to encode stimulus information, but (seemingly paradoxically) correlations were higher when mice made correct choices than when they made errors. On a singletrial basis, a mouse's behavioral choice depended not only on the stimulus information in the activity of the population as a whole, but unexpectedly also on the consistency of information across neurons and time. Because correlations increased information consistency, sensory information was more efficiently converted into a behavioral choice in the presence of correlations. Given this enhancedby-consistency readout, we estimated that correlations produced a behavioral benefit that compensated or overcame their detrimental information-limiting effects. These results call for a reevaluation of the role of correlated neural activity, and suggest that correlations in association cortex can benefit task performance even if they decrease sensory information.

Intersecting kinematic encoding and readout of intention in autism

“…To do so, we developed an analytic framework to directly model how information encoded in movement kinematics is read out with single-subject, single-trial resolution. Our formalism was inspired by recent mathematical advances in linking information encoding and readout in a neural population to inform single-trial behavior choices ( 17 , 18 ). Here we adapted this formalism to investigate how information is coded in movement kinematics (rather than in a neural population).…”

Context-dependent relationships between locus coeruleus firing patterns and coordinated neural activity in the anterior cingulate cortex

“…For example, an increase in correlations is considered a possible mechanism for connecting neural populations over a range of spatial and temporal scales ( Gray et al, 1989 ; Singer, 1999 ; Riehle et al, 1997 ). Some computational schemes can benefit from increases in correlated variability ( Abbott and Dayan, 1999 ; Singer and Gray, 1995 ; Gray, 1999 ; Kohn et al, 2016 ; Valente et al, 2021 ). However, an increase in correlations can also negatively impact the information coding capacity of a large neural population, particularly over longer integration windows ( Zohary et al, 1994 ; Bair et al, 2001 ; Averbeck et al, 2006 ; Renart et al, 2010 ; but also see Nirenberg and Latham, 2003 Moreno-Bote et al, 2014 , for alternative interpretations).…”

Developmental increase of inhibition drives decorrelation of neural activity

“…Both mouse models have similarly reduced E-I ratio in the mPFC superficial layers, that leads to analogously excessively reduced STTC values among spike trains. While in sensory areas correlation might limit information carrying capacity, in associative brain areas, like the mPFC, correlations are thought of improving signal readout, and increased correlations have been linked to improved behavioral performance 86 . This data lends support to the hypothesis that imbalances in E-I ratio might be a possible unifying framework for understanding the circuit dysfunction characterizing neuropsychiatric disorders 26,87,88 .…”