Roxana Zeraati

The paper analyzes intrinsic neural timescales across the entire mouse brain, revealing spatial patterns and a multiscale architecture of timescale diversity.

The paper shows that bifurcations in cortical space create functional modules for specific cognitive tasks, with timescale patterns matching experimental observations.

The paper measures intrinsic timescales in the visual cortex during attention tasks and finds they change with attention and spatial connectivity.

This paper introduces a Bayesian framework for estimating timescales from dynamic processes, showing it outperforms standard methods on synthetic and primate cortex data.