Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 118, Issue 3, Pages -Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.2021843118
Keywords
timescale hierarchy; behaving monkeys; somatosensory network; inherent time constants; primary somatosensory cortex
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Funding
- Direccion de Asuntos del Personal Academico de la Universidad Nacional Autonoma de Mexico [PAPIT-IN210819]
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The ability of cortical networks to integrate information from different sources is essential for cognitive processes. Different cortical areas may require different time-scales depending on their functional role, and this time scale hierarchy remains invariant across different task contexts.
The ability of cortical networks to integrate information from different sources is essential for cognitive processes. On one hand, sensory areas exhibit fast dynamics often phase-locked to stimulation; on the other hand, frontal lobe areas with slow response latencies to stimuli must integrate and maintain information for longer periods. Thus, cortical areas may require different time-scales depending on their functional role. Studying the cortical somatosensory network while monkeys discriminated between two vibrotactile stimulus patterns, we found that a hierarchical order could be established across cortical areas based on their intrinsic timescales. Further, even though subareas (areas 3b, 1, and 2) of the primary somatosensory (S1) cortex exhibit analogous firing rate responses, a clear differentiation was observed in their timescales. Importantly, we observed that this inherent timescale hierarchy was invariant between task contexts (demanding vs. nondemanding). Even if task context severely affected neural coding in cortical areas downstream to S1, their timescales remained unaffected. Moreover, we found that these time constants were invariant across neurons with different latencies or coding. Although neurons had completely different dynamics, they all exhibited comparable timescales within each cortical area. Our results suggest that this measure is demonstrative of an inherent characteristic of each cortical area, is not a dynamical feature of individual neurons, and does not depend on task demands.
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