Srikanth Ryali

This paper introduces MDSI-AVI, a framework for modeling whole-brain causal interactions in fMRI data, revealing new insights into working memory mechanisms.

The paper uses fMRI and a Bayesian Switching Dynamic Systems model to analyze brain states during encoding and post-encoding rest in children, showing how dynamic neural states predict episodic memory.

This paper validates an explainable AI framework to identify brain regions affected by excitation/inhibition imbalance using simulations and empirical data from autism.

The paper investigates the neuronal dynamics of the rodent default mode network and its interaction with the anterior insular cortex, revealing how salient stimuli modulate these networks.