Hamidreza Jamalabadi

The paper identifies neural correlates of interpersonal resilience, finding larger gray matter volume in the left supramarginal gyrus in individuals with secure attachment despite childhood maltreatment.

This paper evaluates hierarchical shallow piecewise-linear RNNs for modeling individual resting-state fMRI, finding they capture functional connectivity but have limited predictive power for phenotypic variables.

This study investigates the replicability of gray matter correlates of childhood maltreatment across three cohorts and finds no significant replication after controlling for depression.

The paper identifies neural markers of impending initial major depressive episodes by comparing converters, MDD patients, and healthy controls using voxel-wise gray matter volume analysis.

This paper introduces CaLLTiF, a causal discovery method for fMRI that improves accuracy and scalability, showing consistent causal patterns in human resting-state data.

This study investigates whole-brain causal connectivity during decoded neurofeedback and identifies network dynamics associated with performance differences.

This study examines how age and parenthood affect whole-brain controllability, finding that parenthood preserves controllability in mothers but not in men.

This paper investigates how cross-validation affects effect size estimation in brain-wide association studies and finds that cross-validation improves generalizability, especially in small samples.

The paper investigates how controllability metrics in subnetworks deviate from full networks and provides theoretical insights to address this bias.

This study investigates the effects of transcutaneous vagus nerve stimulation (tVNS) on brain signaling using fMRI, finding increased NTS activation but no changes in dynamic functional connectivity or gastric motility.

The paper examines how gray matter volume interacts with white matter connectivity to influence brain controllability, finding that gray matter has a significant impact in highly connected regions.

This study shows that EEG microstate parameters are associated with vigilance levels, with different effects on microstate class durations and transitions.