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Optimal trajectories of brain state transitions
2017
NeuroImage
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Here we address this question by drawing on recent advances in network control theory to model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. ...
Yet how white matter structure constrains how the brain transitions from one cognitive state to another remains unknown. ...
The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies. ...
doi:10.1016/j.neuroimage.2017.01.003
pmid:28088484
pmcid:PMC5489344
fatcat:pwabw2gevna5jbnsfakxxzmmee
Optimal Trajectories of Brain State Transitions
[article]
2017
arXiv
pre-print
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Yet how the organization of white matter architecture constrains how the brain transitions from one cognitive state to another remains unknown. ...
Drawing on recent advances in network control theory, we model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. ...
of how the activity in individual brain regions affects the trajectory of the brain as it transitions between states. ...
arXiv:1607.01706v3
fatcat:mx7meaktizeanfjjrdhgbd2rte
Brain network dynamics during working memory are modulated by dopamine and diminished in schizophrenia
2021
Nature Communications
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AbstractDynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. ...
The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and pharmacological modulation. ...
There was no involvement by the funding bodies at any stage of the study. ...
doi:10.1038/s41467-021-23694-9
pmid:34108456
fatcat:7hlyjkgo65hbzn2ebwibzm6gzy
Developmental increases in white matter network controllability support a growing diversity of brain dynamics
2017
Nature Communications
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This work reveals a possible mechanism of human brain development that preferentially optimizes dynamic network control over static network architecture. ...
We use a network representation of diffusion imaging data from 882 youth ages 8 to 22 to show that white matter connectivity becomes increasingly optimized for a diverse range of predicted dynamics in ...
The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies. ...
doi:10.1038/s41467-017-01254-4
pmid:29093441
pmcid:PMC5665937
fatcat:echxtaar2rablfmcotiq5jhqly
White Matter Network Architecture Guides Direct Electrical Stimulation Through Optimal State Transitions
[article]
2018
arXiv
pre-print
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We then use a targeted optimal control framework to solve for the optimal energy required to drive the brain to a given state. ...
In a first validation of our model, we find that the true pattern of white matter tracts can be used to more accurately predict the state transitions induced by direct electrical stimulation than the artificial ...
Author Declaration The authors declare no conflicts of interest. ...
arXiv:1805.01260v1
fatcat:wlz7mebpere5xan272vvrz7ohy
Quantifying brain state transition cost via Schrödinger Bridge
2021
Network Neuroscience
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We demonstrate correspondence between brain state transition cost and the difficulty of tasks. ...
However, this approach does not capture the stochasticity of neural systems, which is important for accurately quantifying brain state transition cost. ...
To quantify the efficiency of brain state transition, it would be interesting to compare empirical and optimal paths. ...
doi:10.1162/netn_a_00213
pmid:35356194
pmcid:PMC8959122
fatcat:nfpgvpx7mbf4reujsndno6ttt4
Quantifying brain state transition cost via Schrödinger's bridge
[article]
2021
bioRxiv
pre-print
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We demonstrate correspondence between brain state transition cost and the difficulty of tasks. ...
However, this approach does not capture the stochasticity of neural systems, which is important for accurately quantifying brain state transition cost. ...
To quantify the efficiency of brain state transition, it would be interesting to compare empirical and optimal paths. ...
doi:10.1101/2021.05.24.445394
fatcat:jijhmyrscveuhlf46o5krscemy
White Matter Network Architecture Guides Direct Electrical Stimulation Through Optimal State Transitions
[article]
2018
bioRxiv
pre-print
Preserved Fulltext
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We then use a targeted optimal control framework to solve for the optimal energy required to drive the brain to a given state. ...
In a first validation of our model, we find that the true pattern of white matter tracts can be used to more accurately predict the state transitions induced by direct electrical stimulation than the artificial ...
The Principle of Optimal Control in Brain State Transitions By positing a model for optimal brain state transitions, we relate expected energy expenditures to a change in the probability with which a pattern ...
doi:10.1101/313304
fatcat:2zmd2cuidzbibgvktcbpwobt4m
Metastable Resting State Brain Dynamics
2019
Frontiers in Computational Neuroscience
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of system's trajectories into metastable states using recurrence grammars. ...
Metastability refers to the fact that the state of a dynamical system spends a large amount of time in a restricted region of its available phase space before a transition takes place, bringing the system ...
and associates to optimal brain structures, thus resolving the function-structure of the so-called resting state networks (RSNs) (Raichle et al., 2001; Fox et al., 2005; Diez et al., 2015; Smitha et ...
doi:10.3389/fncom.2019.00062
pmid:31551744
pmcid:PMC6743347
fatcat:xotgseqzpbghxi7dk7erjc2csy
White Matter Network Architecture Guides Direct Electrical Stimulation through Optimal State Transitions
2019
Cell Reports
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Optimizing direct electrical stimulation for the treatment of neurological disease remains difficult due to an incomplete understanding of its physical propagation through brain tissue. ...
We find statistically significant shared variance between the predicted activity state transitions and the observed activity state transitions. ...
The views, opinions, and/or findings contained in this material are those of the authors and should not be interpreted as representing the official views or policies of the Department of Defense or the ...
doi:10.1016/j.celrep.2019.08.008
pmid:31484068
pmcid:PMC6849479
fatcat:yc244nlscjf5zojszaynn5c6xq
Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor function, and diminished in schizophrenia
[article]
2019
bioRxiv
pre-print
Preserved Fulltext
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The file type is application/pdf.
Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. ...
The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and pharmacological modulation. ...
There was no involvement by the funding bodies at any stage of the study. We thank Oliver ...
doi:10.1101/679670
fatcat:7l3r4bku45d7xdyhnvjwgrx23e
Delimiting subterritories of the human subthalamic nucleus by means of microelectrode recordings and a Hidden Markov Model
2009
Movement Disorders
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The sensorimotor region of the STN (seemingly the preferred location for STN DBS) lies dorsolaterally, in a region also marked by distinct beta (13-30 Hz) oscillations in the parkinsonian state. ...
Fifty-six MER trajectories were used, obtained from 21 PD patients who underwent bilateral STN DBS implantation surgery. ...
at the Hadassah (PATH) committee of London. ...
doi:10.1002/mds.22674
pmid:19533755
fatcat:swtvvymk4rh2zbjyfnsxsmk5wq
A practical guide to methodological considerations in the controllability of structural brain networks
[article]
2019
arXiv
pre-print
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Predicting how the brain can be driven to specific states by means of internal or external control requires a fundamental understanding of the relationship between neural connectivity and activity. ...
optimal control energy. ...
The optimal control energy additionally constrains the size of the state trajectory. (Right) Control strategies potentially examining all possible state transitions (dashed arrows). ...
arXiv:1908.03514v1
fatcat:ovcrpjr2gvd3pa3vg4zm6h6gwy
Optimization of energy state transition trajectory supports the development of executive function during youth
2020
eLife
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Our results reveal a mechanism by which structural networks develop during adolescence to reduce the theoretical energetic costs of transitions to activation states necessary for executive function. ...
activate the fronto-parietal system through the control of multiple brain regions given existing structural network topology. ...
(a) The activation profiles of all 27 brain regions of the fronto-parietal system 1393 during an optimal trajectory from the baseline state to the final state. ...
doi:10.7554/elife.53060
pmid:32216874
pmcid:PMC7162657
fatcat:k2ouoi7wrjgklfjmyliaemqhxu
Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands
2020
Communications Biology
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A diverse set of white matter connections supports seamless transitions between cognitive states. ...
However, it remains unclear how these connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. ...
First, we hypothesized that the brain is optimized to support the observed brain states and state transitions with relatively little energy. ...
doi:10.1038/s42003-020-0961-x
pmid:32444827
fatcat:rs7ldiqujvfn3i4kyha3vvciqe
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