Understanding divergence: Placing developmental neuroscience in its dynamic context DOI Creative Commons
Duncan E. Astle,

Dani S. Bassett,

Essi Viding

et al.

Neuroscience & Biobehavioral Reviews, Journal Year: 2024, Volume and Issue: 157, P. 105539 - 105539

Published: Jan. 9, 2024

Neurodevelopment is not merely a process of brain maturation, but an adaptation to constraints unique each individual and the environments we co-create. However, our theoretical methodological toolkits often ignore this reality. There growing awareness that shift needed allows us study divergence behaviour across conventional categorical boundaries. argue in future must also incorporate developmental dynamics capture emergence those neurodevelopmental differences. This crucial step will require adjustments design methodology. If ultimate aim how, ultimately when, takes place then need analytic toolkit equal these ambitions. We over reliance on group averages has been conceptual dead-end with regard part because any differences are inevitably lost within average. Instead, approaches which themselves new, or simply newly applied context, may allow frameworks from groups individuals. Likewise, methods capable modelling complex dynamic systems understand emergent only possible at level interacting neural system.

Language: Английский

The physics of brain network structure, function and control DOI
Christopher W. Lynn, Danielle S. Bassett

Nature Reviews Physics, Journal Year: 2019, Volume and Issue: 1(5), P. 318 - 332

Published: March 27, 2019

Language: Английский

Citations

342
Computational network biology: Data, models, and applications DOI
Chuang Liu, Yifang Ma, Jing Zhao

et al.

Physics Reports, Journal Year: 2019, Volume and Issue: 846, P. 1 - 66

Published: Dec. 30, 2019

Language: Английский

Citations

181
From Maps to Multi-dimensional Network Mechanisms of Mental Disorders DOI Creative Commons
Urs Braun,

Axel Schaefer,

Richard F. Betzel

et al.

Neuron, Journal Year: 2018, Volume and Issue: 97(1), P. 14 - 31

Published: Jan. 1, 2018

Language: Английский

Citations

179
Brain network dynamics during working memory are modulated by dopamine and diminished in schizophrenia DOI Creative Commons
Urs Braun, Anais Harneit, Giulio Pergola

et al.

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: June 9, 2021

Abstract Dynamical brain state transitions are critical for flexible working memory but the network mechanisms incompletely understood. Here, we show that performance entails brain-wide switching between activity states using a combination of functional magnetic resonance imaging in healthy controls and individuals with schizophrenia, pharmacological fMRI, genetic analyses control theory. The stability relates to dopamine D1 receptor gene expression while influenced by D2 modulation. Individuals schizophrenia altered properties, including more diverse energy landscape decreased representations. Our results demonstrate relevance signaling steering whole-brain dynamics during link these processes pathophysiology.

Language: Английский

Citations

134
Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation DOI
Yuxiao Yang, Shaoyu Qiao, Omid G. Sani

et al.

Nature Biomedical Engineering, Journal Year: 2021, Volume and Issue: 5(4), P. 324 - 345

Published: Feb. 1, 2021

Language: Английский

Citations

116
Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape DOI Creative Commons
S. Parker Singleton, Andrea I. Luppi,

Robin Carhart‐Harris

et al.

Nature Communications, Journal Year: 2022, Volume and Issue: 13(1)

Published: Oct. 3, 2022

Psychedelics including lysergic acid diethylamide (LSD) and psilocybin temporarily alter subjective experience through their neurochemical effects. Serotonin 2a (5-HT2a) receptor agonism by these compounds is associated with more diverse (entropic) brain activity. We postulate that this increase in entropy may arise part from a flattening of the brain's control energy landscape, which can be observed using network theory to quantify required transition between recurrent states. Using states derived existing functional magnetic resonance imaging (fMRI) datasets, we show LSD reduce for state transitions compared placebo. Furthermore, across individuals, reduction correlates frequent increased dynamics. Through analysis incorporates spatial distribution 5-HT2a receptors (obtained publicly available positron emission tomography (PET) data under non-drug conditions), demonstrate an association reduced energy. Our findings provide evidence agonist allow facile temporally More broadly, receptor-informed model impact neuropharmacological manipulation on activity

Language: Английский

Citations

95
Linked patterns of symptoms and cognitive covariation with functional brain controllability in major depressive disorder DOI Creative Commons
Qian Li, Youjin Zhao,

Yongbo Hu

et al.

EBioMedicine, Journal Year: 2024, Volume and Issue: 106, P. 105255 - 105255

Published: July 19, 2024

Controllability analysis is an approach developed for evaluating the ability of a brain region to modulate function in other regions, which has been found be altered major depressive disorder (MDD). Both symptoms and cognitive impairments are prominent features MDD, but case-control differences controllability between MDD controls can not fully interpret contribution both clinical cognition linked patterns among them MDD.

Language: Английский

Citations

23
Colloquium: Control of dynamics in brain networks DOI Creative Commons
Evelyn Tang, Danielle S. Bassett

Reviews of Modern Physics, Journal Year: 2018, Volume and Issue: 90(3)

Published: Aug. 14, 2018

The ability to effectively control brain dynamics holds great promise for the enhancement of cognitive function in humans, and betterment their quality life. Yet, successfully controlling neural systems is challenging, part due immense complexity large set interactions that can drive any single change. While we have gained some understanding neurons, large-scale -- networks multiply interacting components remains poorly understood. Efforts address this gap include construction tools networks, mostly adapted from dynamical theory. Informed by current opportunities practical intervention, these theoretical contributions provide models draw a wide array mathematical approaches. We present intriguing recent developments effective strategies dynamic also describe potential mechanisms underlie such processes. review efforts general neurophysiological processes with implications development function, as well altered medical contexts anesthesia administration, seizure suppression, deep-brain stimulation Parkinson's disease. conclude forward-looking discussion regarding how emerging results network especially approaches deal nonlinear or more realistic trajectories transitions could be used directly pressing questions neuroscience.

Language: Английский

Citations

153
Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands DOI Creative Commons
Eli J. Cornblath, Arian Ashourvan,

Jason Z. Kim

et al.

Communications Biology, Journal Year: 2020, Volume and Issue: 3(1)

Published: May 22, 2020

A diverse set of white matter connections supports seamless transitions between cognitive states. However, it remains unclear how these guide the temporal progression large-scale brain activity patterns in different Here, we analyze brain's trajectories across a single time point from functional magnetic resonance imaging data acquired during resting state and an n-back working memory task. We find that specific sequences are modulated by load, associated with age, related to task performance. Using diffusion-weighted same subjects, apply tools network control theory show linear spread along constrains probabilities at rest, while stimulus-driven visual inputs explain observed Overall, results elucidate structural underpinnings cognitively developmentally relevant spatiotemporal dynamics.

Language: Английский

Citations

135
White Matter Network Architecture Guides Direct Electrical Stimulation through Optimal State Transitions DOI Creative Commons
Jennifer Stiso, Ankit N. Khambhati, Tommaso Menara

et al.

Cell Reports, Journal Year: 2019, Volume and Issue: 28(10), P. 2554 - 2566.e7

Published: Sept. 1, 2019

Optimizing direct electrical stimulation for the treatment of neurological disease remains difficult due to an incomplete understanding its physical propagation through brain tissue. Here, we use network control theory predict how spreads white matter influence spatially distributed dynamics. We test theory's predictions using a unique dataset comprising diffusion weighted imaging and electrocorticography in epilepsy patients undergoing grid stimulation. find statistically significant shared variance between predicted activity state transitions observed transitions. then optimal framework posit testable hypotheses regarding which states structural properties will efficiently improve memory encoding when stimulated. Our work quantifies role that architecture plays guiding dynamics offers empirical support utility explaining brain's response

Language: Английский

Citations

133