Humans actively reconfigure neural task states

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Abstract

The ability to switch between different tasks is a core component of adaptive cognition, but a mechanistic understanding of this capacity has remained elusive. Longstanding questions over whether task switching requires active preparation remain hotly contested, in large part due to the difficulty of inferring preparatory dynamics from behavior or time-locked neuroimaging. We make progress on this debate by quantifying neural task representations using high-dimensional linear dynamical systems fit to human electroencephalographic recordings. We find that these dynamical systems have high predictive accuracy and reveal neural signatures of active preparation that are shared with task-optimized neural networks. These findings inform a classic debate about how we control our cognition, and offer a promising new paradigm for neuroimaging analysis.

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