Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state

Papadopoulos, Lia; Lynn, Christopher W.; Battaglia, Demian; Bassett, Danielle S.

doi:10.1371/journal.pcbi.1008144

Cited by 35 publications

(64 citation statements)

References 144 publications

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“…In a nonlinear system the exact same perturbation can lead to different effects in different dynamical states and since the FC clearly depends on the dynamical state of the system, the effects of a local perturbation can be dependent on FC rather than on SC. Once again, computational simulations of virtual brain models informed by empirical SC information but augmented with nonlinear brain dynamics confirm the validity of our prediction [216]. Virtual brain models tuned to regimes maximizing the degeneracy of their 'dynome', sampled via a noise-driven exploration, also succeed in qualitatively reproducing the switching 'chronnectome' observed in resting state fMRI [217].…”

Section: Application To Neurosciencesupporting

confidence: 70%

Two classes of functional connectivity in dynamical processes in networks

Voutsa

Battaglia

Bracken

et al. 2021

J. R. Soc. Interface.

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The relationship between network structure and dynamics is one of the most extensively investigated problems in the theory of complex systems of recent years. Understanding this relationship is of relevance to a range of disciplines—from neuroscience to geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity, SC) with a (network) representation of the dynamics (functional connectivity, FC). Here, we show that one can distinguish two classes of functional connectivity—one based on simultaneous activity (co-activity) of nodes, the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processes—excitations, regular and chaotic oscillators—and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in geomorphology, ecology, systems biology, neuroscience and socio-ecological systems. Seeing the organisation of dynamical processes in a network either as governed by co-activity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.

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Section: Application To Neurosciencesupporting

confidence: 70%

Two classes of functional connectivity in dynamical processes in networks

Voutsa

Battaglia

Bracken

et al. 2021

J. R. Soc. Interface.

Self Cite

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“…In contrast, the brain exhibits a rich set of dynamics encompassing many other types of behaviors. Numerical simulation studies have sought to understand how such rich dynamics, occurring atop a complex network, respond to perturbative signals such as stimulation Papadopoulos, Lynn, Battaglia, & Bassett, 2020). Yet, to more formally bring control-theoretic models closer to such dynamics and associated responses, the framework must be generalized…”

Section: Generalizations To Time-varying and Nonlinear Systemsmentioning

confidence: 99%

Models of communication and control for brain networks: distinctions, convergence, and future outlook

Srivastava¹,

Nozari²,

Kim³

et al. 2020

Network Neuroscience

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Recent advances in computational models of signal propagation and routing in the human brain have underscored the critical role of white matter structure. A complementary approach has utilized the framework of network control theory to better understand how white matter constrains the manner in which a region or set of regions can direct or control the activity of other regions. Despite the potential for both of these approaches to enhance our understanding of the role of network structure in brain function, little work has sought to understand the relations between them. Here, we seek to explicitly bridge computational models of communication and principles of network control in a conceptual review of the current literature. By drawing comparisons between communication and control models in terms of the level of abstraction, the dynamical complexity, the dependence on network attributes, and the interplay of multiple spatiotemporal scales, we highlight the convergence of and distinctions between the two frameworks. Based on the understanding of the intertwined nature of communication and control in human brain networks, this work provides an integrative perspective for the field and outlines exciting directions for future work.

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“…Variability in the baseline brain state may have impacted the consistency of the stimulation responses in our data set. Even the stimulation response within a session has been repeatedly found to depend on the underlying brain state [ 24 – 26 ]. This finding is corroborated here since consistency was found to be anti-correlated with both the difference in baseline mean band power and difference in memory task which can be understood as a difference in brain state ( figure 6(D) ).…”

Section: Discussionmentioning

confidence: 99%

Band power modulation through intracranial EEG stimulation and its cross-session consistency

et al. 2020

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Objective. Direct electrical stimulation of the brain through intracranial electrodes is currently used to probe the epileptic brain as part of pre-surgical evaluation, and it is also being considered for therapeutic treatments through neuromodulation. In order to effectively modulate neural activity, a given neuromodulation design must elicit similar responses throughout the course of treatment. However, it is unknown whether intracranial electrical stimulation responses are consistent across sessions. The objective of this study was to investigate the within-subject, cross-session consistency of the electrophysiological effect of electrical stimulation delivered through intracranial electroencephalography (iEEG). Approach. We analysed data from 79 epilepsy patients implanted with iEEG who underwent brain stimulation as part of a memory experiment. We quantified the effect of stimulation in terms of band power modulation and compared this effect from session to session. As a reference, we made the same measurements during baseline periods. Main results. In most sessions, the effect of stimulation on band power could not be distinguished from baseline fluctuations of band power. Stimulation effect was consistent in a third of the session pairs, while the rest had a consistency measure not exceeding the baseline standards. Cross-session consistency was highly correlated with the degree of band power increase, and it also tended to be higher when the baseline conditions were more similar between sessions. Significance. These findings can inform our practices for designing neuromodulation with greater efficacy when using direct electrical brain stimulation as a therapeutic treatment.

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Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state

Cited by 35 publications

References 144 publications

Two classes of functional connectivity in dynamical processes in networks

Two classes of functional connectivity in dynamical processes in networks

Models of communication and control for brain networks: distinctions, convergence, and future outlook

Band power modulation through intracranial EEG stimulation and its cross-session consistency

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