Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases

• Published in: Frontiers in aging neuroscience Vol. 14; p. 868342
• Main Authors: Monteverdi, Anita, Palesi, Fulvia, Costa, Alfredo, Vitali, Paolo, Pichiecchio, Anna, Cotta Ramusino, Matteo, Bernini, Sara, Jirsa, Viktor, Gandini Wheeler-Kingshott, Claudia A. M., D’Angelo, Egidio
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 05.08.2022
• Subjects: Alzheimer’s Disease; Amyotrophic Lateral Sclerosis; brain dynamics; excitatory/inhibitory balance; Frontotemporal Dementia; MRI; Neuroscience; Frontotemporal Dementia; Alzheimer’s Disease; Amyotrophic Lateral Sclerosis; connectivity; MRI; brain dynamics; excitatory/inhibitory balance
• ISSN: 1663-4365; 1663-4365
• DOI: 10.3389/fnagi.2022.868342

Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients’ excitation/inhibition profiles on neurodegenerative diseases including Alzheimer’s Disease, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. In this work, we used The Virtual Brain (TVB) simulation platform to simulate brain dynamics in healthy and neurodegenerative conditions and to extract information about the excitatory/inhibitory balance in single subjects. The brain structural and functional connectomes were extracted from 3T-MRI (Magnetic Resonance Imaging) scans and TVB nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. Simulations were performed including both cerebral and cerebellar nodes and their structural connections to explore cerebellar impact on brain dynamics generation. The potential for clinical translation of TVB derived biophysical parameters was assessed by exploring their association with patients’ cognitive performance and testing their discriminative power between clinical conditions. Our results showed that TVB biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer’s Disease and stronger N-methyl-D-aspartate (NMDA) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed us to perform an advanced analysis of patients’ conditions. In backward regressions, TVB-derived parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of TVB parameters and neuropsychological scores significantly improved the discriminative power between clinical conditions. Moreover, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. Importantly, the integration of cerebro-cerebellar loops in simulations improved TVB predictive power, i.e., the correlation between experimental and simulated functional connectivity in all pathological conditions supporting the cerebellar role in brain function disrupted by neurodegeneration. Overall, TVB simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.