Diverse coupling of neurons to populations in sensory cortex

Abstract

A large population of neurons can in principle produce an astronomical number of distinct firing patterns. In cortex however, these patterns lie in a space of lower dimension1-4, as if individual neurons were “obedient members of a huge orchestra”5. Here we use recordings from the visual cortex of mouse and monkey to investigate the relationship between individual neurons and the population, and to establish the underlying circuit mechanisms. We show that neighbouring neurons can differ in their coupling to the overall firing of the population, ranging from strongly coupled “choristers” to weakly coupled “soloists”. Population coupling is largely independent of sensory preferences, and it is a fixed cellular attribute, invariant to stimulus conditions. Neurons with high population coupling are more strongly affected by non-sensory behavioural variables such as motor intention. Population coupling reflects a causal relationship, predicting a neuron’s response to optogenetically-driven increases in local activity. Moreover, population coupling indicates synaptic connectivity: a neuron’s population coupling, measured in vivo, predicted subsequent in vitro estimates of the number of synapses received from its neighbours. Finally, population coupling provides a compact summary of population activity: knowledge of the population couplings of N neurons predicts a substantial portion of their N2 pairwise correlations. Population coupling therefore represents a novel, simple measure that characterises each neuron’s relationship to a larger population, explaining seemingly complex network firing patterns in terms of basic circuit variables.

Stimulus-dependent spiking relationships with the EEG

“…While the present study and numerous previous results (Churchland et al 2010;Smith and Kohn 2008;Smith and Sommer 2013) point to a distinct change in state that occurs when an external stimulus perturbs the network, more subtle changes can occur because of shifts in attention (Cohen and Maunsell 2009;Mitchell et al 2009), learning over time (Gu et al 2011;Jeanne et al 2013), and contextual modulation (Snyder et al 2014). A pair of recent studies have highlighted the diversity of how neurons couple with populations (Okun et al 2015) and the dynamic changes in that coupling over time (Scholvinck et al 2015). Our results fit solidly into the context of this literature, demonstrating that the presence of a stimulus changes how neurons link to the population and affects the diversity of their coupling to global oscillations as measured by the EEG or LFP.…”

Endogenous Sequential Cortical Activity Evoked by Visual Stimuli

“…3J, 5H, 6H ), indicating that a subset of neurons remains stable over long time periods. Recently, it has been shown that strongly coupled neurons remain stable during sensory stimuli or spontaneous activity, supporting the idea of a finite repertory of stable microcircuit motifs (Okun et al, 2015). The stability of specific groups of neurons opens the possibility of manipulating targeted populations using optogenetics with single-cell resolution.…”

“…3K, 5I, 6I ), suggesting that they could encode different aspects of visual stimuli, the spatiotemporal environment, or the context as a whole. Because in primary visual cortex, interneurons have broad orientation properties (Kerlin et al, 2010) and high population coupling (Okun et al, 2015), they could have a pivotal role in the orchestration of neuronal ensembles.…”

Distinct timescales of population coding across cortex

“…We tested whether coupling was due to global population changes 28,29 or to coordinated activity in small neuronal groups 30 by comparing the performance of variants of the coupled model. We compared coupled models that included as coupling predictors only the mean population activity or the activity of factorized subsets of cells.…”