Jijun Wang

This study uses dynamic meta-networking to identify distinct network correlates of positive and negative formal thought disorder in schizophrenia, showing treatment-related normalization.

This paper develops and validates a scalp-based MRI-guided method for personalized TMS targeting, showing comparable performance to neuronavigation systems.

This study identifies an anhedonia-related damage network through functional connectivity analysis and transcriptomic profiling, showing its predictive value for TMS treatment efficacy.

This study investigates hippocampal circuitry impairments in schizophrenia, finding deficits in pattern separation and completion linked to memory dysfunction and delusions, with antipsychotic treatment showing normalization of neural activity.

This study investigates metacognition in macaques using confidence proxies and computational models, finding BA46d's time-sensitive role in metacognitive processes.

The paper shows that the intrinsic topographic hierarchy of self, consisting of internal, external, and mental layers, exists during rest and tasks, and converges with dynamic measures.

The paper examines resting-state fMRI data from high-risk individuals to determine if abnormal functional connectivity in the dentate nuclei precedes psychosis onset.

This study investigates conflict processing in schizophrenia using N2 and frontal midline theta, finding that FMθ, not N2, is impaired in SZ during conflict tasks.

The paper identifies methylomic changes in peripheral blood lymphocytes of schizophrenia prodromal and first-episode patients compared to healthy controls in a Chinese Han population.

This paper investigates the role of the parietal memory network in auditory hallucinations using longitudinal data from schizophrenia patients and finds decreased connectivity in this network correlates with hallucination severity and predicts treatment response.

This study examines how spatial smoothing and model order in ICA affect the segregation of the parietal memory network and default mode network in fMRI data.