Manasij Venkatesh

This paper introduces a recurrent neural network-based framework to decode and predict individual differences in brain dynamics using fMRI data from movie-watching and experimental conditions.

The paper introduces an LSTM-based framework to analyze spatiotemporal brain dynamics from fMRI data, showing it can classify movie stimuli and predict individual traits.

This paper introduces a geodesic distance metric to compare functional connectivity matrices, achieving high participant identification accuracy and outperforming traditional methods.

The paper introduces reservoir computing for analyzing dynamic fMRI data, showing it can classify tasks and extract low-dimensional temporal trajectories with high accuracy.