Zsigmond Tamás Kincses

This study investigates how dorsolateral prefrontal cortex (DLPFC) intervention affects the retrieval of statistical knowledge using rTMS, finding enhanced access to statistical regularities with bilateral DLPFC suppression.

This study develops a multi-center machine learning model using gray matter cortical thickness to predict individual pain sensitivity, achieving a moderate predictive performance.

The paper identifies a resting-state brain connectivity pattern predictive of individual pain sensitivity without painful stimulation.

The paper investigates cerebrocerebellar circuit anomalies in a prenatal valproate model of autism using MRI and immunohistology, finding altered BOLD responses and reduced Purkinje cell numbers.