Abstract
Complex cognitive functions such as working memory and decision-making require the maintenance of information over many timescales, from transient sensory stimuli to long-term contextual cues1. However, while theoretical accounts predict that a corresponding hierarchy of neuronal timescales likely emerges as a result of graded variations in recurrent synaptic excitation2–4, direct evidence in the human cortex is lacking. This limits our ability to study how other cytoarchitectural and cell-intrinsic features shape the temporal patterns of cortical activity5–7, and whether neuronal timescales are dynamic and relevant for human cognition. Here, we use a novel computational approach to infer neuronal timescales from intracranial recordings and construct a continuous gradient across the human cortex. We find that timescales increase along the principal sensorimotor-to-association axis7–9, where higher-order association areas have longer neuronal timescales. These measurements reflect transmembrane current fluctuations and scale with single-unit spiking timescales across the macaque cortex10. Cortexwide transcriptomic analysis11–13 in humans confirms direct alignment between timescales and expression of excitation- and inhibition-related genes, but further identifies genes specifically related to voltage-gated transmembrane ion transporters. Finally, neuronal timescales are functionally dynamic: prefrontal cortex timescales expand during working memory maintenance and predict individual performance, while cortex-wide timescales compress with aging. Thus, neuronal timescales follow cytoarchitectonic gradients across the human cortex, and are relevant for cognition in both short- and long-terms, bridging microcircuit physiology with macroscale dynamics and behavior.
Data availability All data analyzed in this manuscript are from open data sources. All code used for all analyses and plots are publicly available on GitHub at https://github.com/rdqao/field-echos and https://github.com/rudyvdbrink/surface_projection. See Extended Data Table 1 and 2.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Competing interests: the authors declare no competing interests.