Moguilner, SebastianHerzog, RubénSanz Perl, YonatanMedel, VicenteCruzat, JosefinaCoronel, CarlosKringelbach, MortenDeco, GustavoIbáñez, AgustínTagliazucchi, Enzo2025-05-142025-05-142024Moguilner S, Herzog R, Sanz Perl Y, Medel V, Cruzat J, Coronel C, et al. Biophysical models applied to dementia patients reveal links between geographical origin, gender, disease duration, and loss of neural inhibition. Alzheimers Res Ther. 2024;16:79. DOI: 10.1186/s13195-024-01449-01758-9193http://hdl.handle.net/10230/70390Includes supplementary materials for the online appendix.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.application/pdfeng© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s13195-024-01449-0DementiaNeurodegenerationBiophysical modelingVariabilityGenderHeterogeneityHyperexcitabilityinfo:eu-repo/semantics/openAccess