Rethinking the MS brain: Synaptic loss and computational modelling of brain networks.

Abstract

Extensive clinical and preclinical research over the past decades significantly improved our understanding of the immunopathogenesis of multiple sclerosis (MS) and highlighted how neuronal, axonal, and synaptic damage accompanies inflammatory processes since the earliest disease stages.1 It is still challenging, however, to decipher how such different factors interact and underpin the heterogeneity of MS clinical expression. Purely quantitative approaches, based on the evaluation of the extent of grey matter damage and demyelinating plaque burden, are sometimes contradicted by patterns of clinical-radiological dissociation, highlighting the relevance of individual coping mechanisms in each person with MS. Accordingly, new interpretative models are required to account for the heterogeneity of clinical phenotypes and manifestations in people with MS (PwMS). In this scenario, modern network science offers a different point of view. Brain networks can be considered as cost-efficient small-world networks, displaying high connectedness and efficient global integration, organized with hierarchical modularity and able to offer a proper balance between the segregation and integration of information.2 Structural or functional impairment of highly connected hubs may alter the function of the whole network, triggering compensatory changes in network activity that may represent maladaptive responses with progressive hub overload and hub failure.2 This interpretative model can be applied to different neurological disorders, with MS being a paradigmatic example, due to the presence of multifocal demyelinating lesions with a network ‘disconnecting’ effect3 and the more recent evidence of both functional and structural alterations of synaptic connections.4,5 In this issue, Huiskamp and colleagues6 provide a histological characterization of neuronal, excitatory and inhibitory synaptic densities in PwMS, testing through computational modelling how MS-related synaptic loss might affect brain network functioning. The authors found that excitatory and inhibitory synaptic densities were significantly reduced in the cortical layer VI of normal-appearing and demyelinated MS cortex, with respect to nonneurological controls. Interestingly, despite the fact that excitatory and inhibitory synapses were similarly reduced in normal-appearing MS cortex, the reduction was significantly larger for inhibitory synapses in demyelinated cortex. By testing such excitatory and inhibitory synaptic loss in a cortico-thalamic meanfield model that is thought to accurately mimic largescale brain dynamics, the authors show that inhibitory synapses impact network functioning more profoundly, leading to a disinhibitory increase in functional connectivity and neuronal activity. In this study, the authors translated histological findings on synaptic damage into macroscopic functional network analyses, showing that even slight changes in cortical excitatory and, especially, inhibitory synaptic densities can trigger significant network alterations due to an excitatory/inhibitory imbalance. The approach adopted by the authors allows us to overcome the simple observation of histological data and assess their functional consequences.