Vaibhav Tripathi

The paper examines sensory-WM gradients in frontal cortex, finding that sensory and working memory regions overlap and form gradients rather than sharp boundaries.

The paper examines interactions between sensory-biased and supramodal working memory networks using fMRI data from human participants, finding asymmetry in connectivity during auditory versus visual tasks.

This paper shows that brain networks can be precisely mapped within individuals using only task data, producing results similar to resting-state data.

The paper identifies cortical regions linked to the ventral striatum (VS) using functional connectivity MRI, showing its preferential correlation with the Salience network including dorsolateral prefrontal cortex.

This paper introduces a model-free method, Temporal Synchronization Analysis, to detect nonlinear brain activations in fMRI data across multiple cognitive tasks.

This paper quantifies how hair and skin characteristics affect fNIRS signal quality and provides recommendations to improve inclusivity in fNIRS studies.

This study uses fMRI to compare brain connectivity in meditators and novices during Yoga Nidra, finding distinct DMN decoupling in meditators linked to their practice experience.

This paper extends connectome fingerprinting to predict individual cerebellar activity from resting-state functional connectomes, showing greater precision than group averages.

The paper examines the relationship between alpha and beta peak frequencies from MEG and functional connectivity between the Default Mode and Dorsal Attention Networks using fMRI in two datasets.

This study analyzes EEG data from 43 subjects practicing Sudarshan Kriya Yoga, showing changes in alpha, theta, delta waves, and aperiodic signals across different meditation phases.

The paper investigates DMN dynamics across tasks and finds low synchronization in task-negative regions and weak task-positive regions across subjects and trials.