Dynamical Signatures of Structural Connectivity Damage to a Model of the Brain Posed at Criticality

Abstract

Synchronization of brain activity fluctuations is believed to represent communication between spatially distant neural processes. These inter-areal functional interactions develop in the background of a complex network of axonal connections linking cortical and sub-cortical neurons, termed the human "structural connectome".Theoretical considerations and experimental evidence support the view that the human brain can be modeled as a system operating at a critical point between ordered (sub-critical) and disordered (super-critical) phases. Here, we explore the hypothesis that pathologies resulting from brain injury of different etiology are related to the model of a critical brain. For this purpose, we investigate how damage to the integrity of the structural connectome impacts on the signatures of critical dynamics. Adopting a hybrid modeling approach combining an empirical weighted network of human structural connections with a conceptual model of critical dynamics, we show that lesions located at highly transited connections progressively displace the model towards the subcritical regime. The topological properties of the nodes and links are of less importance when considered independently of their weight in the network. We observe that damage to midline hubs such as the middle and posterior cingulate cortex is most crucial for the disruption of criticality in the model. However, a similar effect can be achieved by targeting less transited nodes and links whose connection weights add up to an equivalent amount. This implies that brain pathology does not necessarily arise due to insult targeted at well-connected areas and that inter-subject variability could obscure lesions located at non-hub regions. Finally, we discuss the predictions of our model in the context of clinical studies of traumatic brain injury and neurodegenerative disorders.3

Homeostatic plasticity and emergence of functional networks in a whole-brain model at criticality

“…In particular, most of the models have developed indexes that are able to distinguish between different groups of subjects (e.g. healthy vs. stroked) using as input an average connectome obtained from many individuals and comparing the model output with average group properties 43 , 87 . However, a prerequisite for theoretical models to be significant in terms of translational neuroscience, and thus possibly informative for therapeutic intervention, is to provide individual-level markers (or “brain signatures”) that reliably predict cognitive and behavioral performance not only at the group level but also be adapted and tailored to the specific patient.…”

“…A recent paper by Haimovici et al . 43 investigated the effect of artificial lesions on the signatures of criticality of the network dynamics. Lesions were simulated by removing nodes/links of an averaged group level structural empirical matrix, targeting nodes/links according to a given network centrality and also in a random way.…”

“…In this phase, only those nodes with the strongest connections will determine the signal flow in the network. In between of these two phases a phase transition occurs at T = T c where brain activities have oscillatory behaviors, and long-range temporal correlations in their envelope 15 , 43 . As shown in 15 the size of the second largest cluster is a suitable quantity to characterize the phase transition and it happens at the corresponding value of T where 〈 S 2 〉 is maximal (see also 72 ).…”

“…As shown in 15 the size of the second largest cluster is a suitable quantity to characterize the phase transition and it happens at the corresponding value of T where 〈 S 2 〉 is maximal (see also 72 ). In addition to the second cluster size, the peak in the standard deviation, σ ( A ), may also be used to infer the critical transition 43 .…”

“…From a theoretical point of view, a recent work by Haimovici et al . 43 has quantified the way synthetic lesions may impact the large-scale dynamical signatures of the (HTC) critical dynamics at a group level. Synthetic lesions are able to push the system out of the critical state towards a sub-critical state, which is characterized by decreased levels of neural fluctuations.…”