Basilis Zikopoulos

The paper develops a neural model to study how excitation/inhibition imbalance affects visual motion perception in Alzheimer's disease, finding that increased excitation and decreased inhibition reduce illusion representation.

This paper introduces a novel method using the rotating tilted lines illusion to estimate population receptive fields, showing it can approximate fMRI results and detect visual processing abnormalities in neurological conditions.

This study uses computational modeling to compare thalamocortical circuit dynamics between rodents and primates, revealing species-specific differences in neural synchrony, sleep spindles, and potential implications for neuropsychiatric disorders.

This study uses explainable 3D CNNs to identify regional and network-level biomarkers in early Parkinson's MRIs linked to symptom progression.

This study uses 3D CNNs to analyze structural MRI data from ASD patients, identifying consistent brain region and network changes linked to phenotypic heterogeneity and clinical scores.

The paper develops an AI model that classifies white matter regions in ASD and CTR brains with high accuracy, highlighting axon pathology differences.

The paper shows that cortical circuit principles predict the progression of tauopathy in CTE by aligning p-tau pathology with laminar connection patterns in human brains.

The paper uses a neural model to study how changes in excitatory and inhibitory subfields affect spatial frequency sensitivity in schizophrenia patients, finding differences between medicated and unmedicated groups.

This study proposes a neural model to investigate how altered excitation/inhibition and feedback levels in schizophrenia affect visual illusion perception.

The paper develops a primate-specific computational model of thalamocortical circuits to simulate sleep spindles and investigates how core and matrix connectivity ratios affect spindle dynamics.

The paper introduces a computational method to identify a cortical spectrum in rhesus macaques using histological and MRI data, showing it is robust across methods.