학술논문

Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition
Document Type
article
Source
Alzheimer’s Research & Therapy, Vol 16, Iss 1, Pp 1-16 (2024)
Subject
Dementia
Neurodegeneration
Biophysical modeling
Hyperexcitability
Variability
Gender
Neurosciences. Biological psychiatry. Neuropsychiatry
RC321-571
Neurology. Diseases of the nervous system
RC346-429
Language
English
ISSN
1758-9193
Abstract
Abstract Background The hypothesis of decreased neural inhibition in dementia has been sparsely studied in functional magnetic resonance imaging (fMRI) data across patients with different dementia subtypes, and the role of social and demographic heterogeneities on this hypothesis remains to be addressed. Methods We inferred regional inhibition by fitting a biophysical whole-brain model (dynamic mean field model with realistic inter-areal connectivity) to fMRI data from 414 participants, including patients with Alzheimer’s disease, behavioral variant frontotemporal dementia, and controls. We then investigated the effect of disease condition, and demographic and clinical variables on the local inhibitory feedback, a variable related to the maintenance of balanced neural excitation/inhibition. Results Decreased local inhibitory feedback was inferred from the biophysical modeling results in dementia patients, specific to brain areas presenting neurodegeneration. This loss of local inhibition correlated positively with years with disease, and showed differences regarding the gender and geographical origin of the patients. The model correctly reproduced known disease-related changes in functional connectivity. Conclusions Results suggest a critical link between abnormal neural and circuit-level excitability levels, the loss of grey matter observed in dementia, and the reorganization of functional connectivity, while highlighting the sensitivity of the underlying biophysical mechanism to demographic and clinical heterogeneities in the patient population.