Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture

Abstract

17Complex cognitive functions such as working memory and decision-making require information 18 maintenance over many timescales, from transient sensory stimuli to long-term contextual cues. 19While theoretical accounts predict the emergence of a corresponding hierarchy of neuronal 20 timescales, direct evidence in the human cortex is lacking. Here, we use a novel computational 21 approach to infer neuronal timescales from human intracranial recordings and find that 22 timescales gradually increase along the principal sensorimotor-to-association axis. Cortex-wide 23 transcriptomic analysis further shows a direct alignment between timescales and expression of 24 excitation-and inhibition-related genes, as well as genes specific to voltage-gated 25 transmembrane ion transporters. Finally, neuronal timescales are functionally dynamic: 26 prefrontal cortex timescales expand during working memory maintenance and predict individual 27 performance, while cortex-wide timescales compress with aging. Thus, neuronal timescales 28 follow cytoarchitectonic gradients across the human cortex, and are relevant for cognition in 29both short-and long-terms, bridging microcircuit physiology with macroscale dynamics and 30 behavior. 31 32One-sentence summary 33Human cortical timescales is associated with synaptic and ion channel genes, lengthens with 34 working memory maintenance, and shortens in aging. 35

Topographic gradients of intrinsic dynamics across neocortex

“…linear autocorrelation; nonlinear autocorrelation; automutual information). Short-lag autocorrelation measures load positively, while long-lag autocorrelation measures load negatively, consistent with the notion that autocorrelation decays with increasing time lag [41,84,92] (Figure 3-figure supplement 1). For PC2, we observe strong contributions from measures of distribution shape, captured by measures of distributional entropy (e.g.…”

“…These micro-architectural properties -increasingly measured directly from histology or inferred from other measurements, such as microarray gene expression -provide a unique opportunity to relate circuit architecture to temporal dynamics and computation. Indeed, multiple studies have focused on how intrinsic timescales vary in relation to microscale and macroscale attributes [41,62,72,84,92,102]. The primary functional consequence of this hierarchy of * bratislav.misic@mcgill.ca timescales is thought to be a hierarchy of temporal receptive windows: time windows in which a newly arriving stimulus will modify processing of previously presented (i.e.…”

A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power

“…Coherence (and Granger causality) entails that the spectral energy from a sending region is focused in a specific frequency band and that the synaptic activity in a receiver has a relatively strong contribution from a sender at the coherent frequency. There are prominent differences between brain areas in the distribution of spectral energy and its modulation by behavior, which may reflect increases in intrinsic timescales across hierarchical levels (Murray et al, 2014;Gao et al, 2020;Buzsa ´ki, 2006;Siegel et al, 2012). Hence, the unique power-spectral profiles of different brain areas will automatically give rise to large-scale inter-areal coherence and Granger-causality patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.…”

Topographic gradients of intrinsic dynamics across neocortex

“…For a neuronal population, the confluence of local properties and global connectivity shapes both the generation of local rhythms, as well as the propensity to communicate with other populations. Numerous studies, mainly using electrophysiological recordings, suggest that intrinsic timescales systematically vary over the cortex [32,51,61,71]. The primary functional consequence of this hierarchy of timescales is thought to be a hierarchy of temporal receptive windows: time windows in which a newly arriving stimulus will modify processing of previously presented information [7,15,16,43,48,50].…”