The modulation of neural gain facilitates a transition between functional segregation and integration in the brain

  title={The modulation of neural gain facilitates a transition between functional segregation and integration in the brain},
  author={James M. Shine and Matthew J. Aburn and Michael Breakspear and Russell A. Poldrack},
Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain pushed the network through an abrupt dynamical… 
Transitions in information processing dynamics at the whole-brain network level are driven by alterations in neural gain
This study demonstrates that the gain-mediated phase transition is characterized by a shift in the underlying dynamics of neural information processing, and suggests that the constraints imposed by the ascending arousal system constrain low-dimensional modes of information processing within the brain.
Transitions in brain-network level information processing dynamics are driven by alterations in neural gain
The results suggest that the modulation of neural gain via the ascending arousal system may fundamentally alter the information processing mode of the brain, which in turn has important implications for understanding the biophysical basis of cognition.
Diffuse neural coupling mediates complex network dynamics through the formation of quasi-critical brain states
It is established that modulating the balance between local and diffuse synaptic coupling in a thalamocortical model subtends the emergence of quasi-critical brain states that act to flexibly transition the brain between unique modes of information processing.
Cholinergic neuromodulation of inhibitory interneurons facilitates functional integration in whole-brain models
This work considers a Jansen & Rit whole-brain model in a network interconnected using a human connectome, and studies the influence of the cholinergic and noradrenergic neuromodulatory systems on the segregation/integration balance.
Homeostatic plasticity and emergence of functional networks in a whole-brain model at criticality
This work shows that normalization of the node’s excitatory input improves the correspondence between simulated neural patterns of the model and various brain functional data, and suggests that the inclusion of homeostatic principles lead to more realistic brain activity consistent with the hallmarks of criticality.
Human cognition involves the dynamic integration of neural activity and neuromodulatory systems
It is found that neuronal activity converged onto a low-dimensional manifold that facilitates the execution of diverse task states and advance the understanding of functional brain organization by emphasizing the interface between neural activity, neuromodulatory systems, and cognitive function.
The dynamic basis of cognition: an integrative core under the control of the ascending neuromodulatory system
It is shown that large-scale neuronal activity converges onto a low dimensional manifold that facilitates the dynamic execution of diverse task states and advances the understanding of functional brain organization by emphasizing the interface between low dimensional neural activity, network topology, neuromodulatory systems and cognitive function.
Neuromodulatory Influences on Integration and Segregation in the Brain
  • J. Shine
  • Biology, Psychology
    Trends in Cognitive Sciences
  • 2019
Structural determinants of dynamic fluctuations between segregation and integration on the human connectome
This study examines the contributions of network features to dynamic fluctuations by constructing rewired surrogate connectome in which network features of interest are selectively preserved, and by assessing the magnitude of fluctuations simulated with these surrogates.
Whole-brain modeling explains the context-dependent effects of cholinergic neuromodulation
The results confirm that cholinergic neuromodulation promotes functional segregation in a context-dependent fashion, and suggest that this segregation is suited for simple visual-attentional tasks.


Rethinking segregation and integration: contributions of whole-brain modelling
The brain regulates information flow by balancing the segregation and integration of incoming stimuli to facilitate flexible cognition and behaviour and recent whole-brain computational modelling approaches have enabled us to start assessing the effect of input perturbations on brain dynamics in silico.
The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition
It is confirmed that the human brain has the remarkable ability to reconfigure its large-scale organization dynamically in response to current cognitive demands and that interpreting reconfiguration in terms of network segregation and integration may shed light on the optimal network structures underlying successful cognition.
Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations
This work explores the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection and discusses the findings in relation to psychiatric disorders and the future of connectomics.
Dynamic models of large-scale brain activity
Evidence supports the view that collective, nonlinear dynamics are central to adaptive cortical activity and aberrant dynamic processes appear to underlie a number of brain disorders.
A measure for brain complexity: relating functional segregation and integration in the nervous system.
A measure, called neural complexity (CN), that captures the interplay between functional segregation and functional integration in brains of higher vertebrates and may prove useful in analyzing complexity in other biological domains such as gene regulation and embryogenesis.
Towards the virtual brain: network modeling of the intact and the damaged brain.
A unifying theoretical framework is discussed that explains how structured spatio-temporal resting state patterns emerge from noise driven explorations of unstable or stable oscillatory states and the consequences of network manipulations to understand some of the brain's dysfunctions.
Key role of coupling, delay, and noise in resting brain fluctuations
In numerical simulation, the dynamics of a simplified cortical network using 38 noise-driven (Wilson–Cowan) oscillators, which in isolation remain just below their oscillatory threshold are studied, indicating the presence of stochastic resonance and high sensitivity to changes in diffuse feedback activity.
Structural and Functional Brain Networks: From Connections to Cognition
It is concluded that the emergence of dynamic functional connectivity, from static structural connections, calls for formal (computational) approaches to neuronal information processing that may resolve the dialectic between structure and function.
Noise during Rest Enables the Exploration of the Brain's Dynamic Repertoire
It is shown that comparable resting state networks emerge from a stability analysis of the network dynamics using biologically realistic primate brain connectivity, although anatomical information alone does not identify the network.