Gulshan Kumar

This study uses fMRI and MVPA to decode neural responses to real words and pseudowords, finding shape associations in both language and visual regions.

The paper uses representational similarity analysis and machine learning to identify acoustic parameter combinations linked to iconicity in pseudowords across different meaning domains.

The paper links individual variability in perception to neural dynamics by analyzing EEG data and proposing a biophysical model of brain network interactions.

This study uses EEG and computational modeling to explain inter-individual and inter-trial variability in cross-modal perception by analyzing brain connectivity patterns and neuronal interactions.