Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model
Articolo
Data di Pubblicazione:
2024
Citazione:
Investigating the Impact of Local Manipulations on Spontaneous and Evoked Brain Complexity Indices: A Large-Scale Computational Model / G. Gaglioti, T.R. Nieus, M. Massimini, S. Sarasso. - In: APPLIED SCIENCES. - ISSN 2076-3417. - 14:2(2024), pp. 890.1-890.23. [10.3390/app14020890]
Abstract:
Brain complexity relies on the integrity of structural and functional brain networks, where
specialized areas synergistically cooperate on a large scale. Local alterations within these areas can
lead to widespread consequences, leading to a reduction in overall network complexity. Investigating
the mechanisms governing this occurrence and exploring potential compensatory interventions is a
pressing research focus. In this study, we employed a whole-brain in silico model to simulate the large-
scale impact of local node alterations. These were assessed by network complexity metrics derived
from both the model's spontaneous activity (i.e., Lempel–Ziv complexity (LZc)) and its responses to
simulated local perturbations (i.e., the Perturbational Complexity Index (PCI)). Compared to LZc,
local node silencing of distinct brain regions induced large-scale alterations that were paralleled
by a systematic drop of PCI. Specifically, while the intact model engaged in complex interactions
closely resembling those obtained in empirical studies, it displayed reduced PCI values across all local
manipulations. This approach also revealed the heterogeneous impact of different local manipulations
on network alterations, emphasizing the importance of posterior hubs in sustaining brain complexity.
This work marks an initial stride toward a comprehensive exploration of the mechanisms underlying
the loss and recovery of brain complexity across different conditions.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
brain complexity; whole-brain modeling; node silencing; perturbations; Lempel–Ziv complexity; Perturbational Complexity Index
Elenco autori:
G. Gaglioti, T.R. Nieus, M. Massimini, S. Sarasso
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