Control for a synchronization-desynchronization switch

Davis

Lucas

et al. 2016

Neuron

197

143

Summary In ~20 million people with drug-resistant epilepsy, focal seizures originating in dysfunctional brain networks will often evolve and spread to surrounding tissue, disrupting function in otherwise normal brain regions. To identify network control mechanisms that regulate seizure spread, we developed a novel tool for pinpointing brain regions that facilitate synchronization in the epileptic network. Our method measures the impact of virtually resecting putative control regions on synchronization in a validated model of the human epileptic network. By applying our technique to time-varying, functional networks, we identified brain regions whose topological role is synchronize or desynchronize the epileptic network. Our results suggest that greater antagonistic, push-pull interaction between synchronizing and desynchronizing brain regions better constrains seizure spread. These methods, while applied here to epilepsy, are generalizable to other brain networks, and have wide applicability in isolating and mapping functional drivers of brain dynamics in health and disease.

Section: Discussionmentioning

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Virtual Cortical Resection Reveals Push-Pull Network Control Preceding Seizure Evolution

Davis

Lucas

et al. 2016

Neuron

197

143

“…Using virtual cortical resection, we observed the presence of specific nodes whose placement in the wider network suggests their critical role in controlling synchronization and desynchronization in seizure dynamics. These key areas display antithetical potential for controlling activity dynamics, and therefore we speculate that they may employ an antagonistic, push-pull control mechanism similar to that described in theoretical work in other systems [25]. Mechanistically, synchronizing controllers theoretically pull the network towards a particular synchronous state, and, conversely, desynchronizing controllers push the network away from these states.…”

Section: Push-pull Control Titrates Network Synchronizabilitymentioning

confidence: 74%

“…Theoretical work in the fields of physics and engineering demonstrates that diffusion of dynamics through the network can be regulated through a push-pull control mechanism, where desynchronizing and synchronizing nodes operate antagonistically in a "tug-of-war". When synchronizing nodes exert greater push than desynchronizing nodes, synchronizability increases and dynamic processes may diffuse through the network more easily [25] (Fig. 1b).…”

Section: Introductionmentioning

confidence: 99%

Virtual cortical resection reveals push-pull network control preceding seizure evolution

Davis

Lucas

et al. 2016

Preprint

133

For ≈20 million people with drug-resistant epilepsy, recurring, spontaneous seizures have a devastating impact on daily life. The efficacy of surgical treatment for controlling seizures is hindered by a poor understanding of how some seizures spread to and synchronize surrounding tissue while others remain focal. To pinpoint network regions that regulate seizure evolution, we present a novel method to assess changes in synchronizability in response to virtually lesioning cortical areas in a validated computational network model. In human patients implanted with electrocorticographic sensors, we apply our virtual cortical resection technique to time-varying functional networks and identify control regions that synchronize or desynchronize cortical areas using an antagonistic push-pull control scheme to raise or lower synchronizability. Our results suggest that synchronizability before seizures predicts seizure evolution: in focal seizures, the strongest controllers are located outside seizure-generating areas. These methods,while applied here to epilepsy, are generalizable to other brain networks, and have wide applicability in isolating and mapping functional drivers of brain dynamics in health and disease. dynamic network neuroscience -epileptic network -synchronizability -push-pull control -diffusion -seizure evolution

“…One hypothesis from theoretical physics is that these networks employ a push-pull control strategy in which antagonistic desynchronizing and synchronizing nodes regulate the transfer of information through the network. 169 By analyzing the functional network topology of focal and distributed (clinically known as secondarily generalized) seizures, recent work demonstrates that desynchronizing and synchronizing brain regions antagonistically regulate the ability for seizures to synchronize network dynamics. 143 Thus, control strategies like push-pull control may be relevant for homeostatic regulation of (nonlinear) synchronization dynamics in the human brain.…”

Section: A Few Relevant Concepts and Toolsmentioning

confidence: 99%

A network engineering perspective on probing and perturbing cognition with neurofeedback

Bassett

Annals of the New York Academy of Sciences

2017

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition.