Gustavo Patow

This study links receptor profiles and cortical excitability to acute and long-term stroke outcomes using patient-specific whole-brain models.

The paper examines how meningioma and glioma tumors affect brain connectivity resilience, finding meningioma shows higher functional connectivity preservation despite structural damage, while glioma shows more balanced damage with worse cognitive outcomes.

The paper uses computational whole-brain models to show that perilesional excitability predicts long-term motor recovery after stroke, but not acute impairment.

This study examines how meningiomas and gliomas affect brain dynamics using resting-state fMRI, finding distinct disruptions in dynamical complexity metrics between the two tumor types.

This study develops a personalized fMRI analysis pipeline for disorders of consciousness, identifying connectivity and local parameters as biomarkers for diagnosis and prognosis.

This study examines brain dynamics across women's reproductive stages using fMRI and machine learning, finding that brain dynamics decline at menopause and that combining brain dynamics with hormone levels improves stage classification.

This study uses off-equilibrium fluctuation-dissipation theorem to analyze brain dynamics in Alzheimer's disease, finding increased deviations in MCI and decreased deviations in AD, suggesting potential biomarkers for early detection.

This study uses intrinsic ignition analysis on rs-fMRI data to show reduced dynamical complexity and node-metastability in Alzheimer's disease, linked to Amyloid-β and tau pathology.

This study models the differential effects of Amyloid-Beta and Tau on neuronal activity in Alzheimer's Disease, finding A{beta} dominance in early stages and Tau dominance in later stages.