scholarly journals Reliable local dynamics in the brain across sessions are revealed by whole‐brain modeling of resting state activity

2019 ◽  
Author(s):  
Patricio Donnelly‐Kehoe ◽  
Victor M. Saenger ◽  
Nina Lisofsky ◽  
Simone Kühn ◽  
Morten L. Kringelbach ◽  
...  
Keyword(s):  
Resting State ◽  
Whole Brain ◽  
Local Dynamics ◽  
State Activity ◽  
Brain Modeling ◽  
The Brain

scholarly journals Task-Driven Activity Reduces the Cortical Activity Space of the Brain: Experiment and Whole-Brain Modeling

2015 ◽  
Vol 11 (8) ◽  
pp. e1004445 ◽  
Author(s):  
Adrián Ponce-Alvarez ◽  
Biyu J. He ◽  
Patric Hagmann ◽  
Gustavo Deco
Keyword(s):  
Cortical Activity ◽  
Activity Space ◽  
Whole Brain ◽  
Brain Modeling ◽  
The Brain

scholarly journals Closer to critical resting-state neural dynamics in individuals with higher fluid intelligence

2019 ◽  
Author(s):  
Takahiro Ezaki ◽  
Elohim Fonseca dos Reis ◽  
Takamitsu Watanabe ◽  
Michiko Sakaki ◽  
Naoki Masuda
Keyword(s):  
Resting State ◽  
Statistical Physics ◽  
Fluid Intelligence ◽  
Neural Dynamics ◽  
Whole Brain ◽  
Edge Of Chaos ◽  
Neural Computations ◽  
Show Evidence ◽  
Human Participants ◽  
The Brain

ABSTRACTAccording to the critical brain hypothesis, the brain is considered to operate near criticality and realize efficient neural computations. Despite the prior theoretical and empirical evidence in favor of the hypothesis, no direct link has been provided between human cognitive performance and the neural criticality. Here we provide such a key link by analyzing resting-state dynamics of functional magnetic resonance imaging (fMRI) networks at a whole-brain level. We develop a data-driven analysis method, inspired from statistical physics theory of spin systems, to map out the whole-brain neural dynamics onto a phase diagram. Using this tool, we show evidence that neural dynamics of human participants with higher fluid intelligence quotient scores are closer to a critical state, i.e., the boundary between the paramagnetic phase and the spin-glass (SG) phase. The present results are consistent with the notion of “edge-of-chaos” neural computation.

scholarly journals Awakening: Predicting external stimulation to force transitions between different brain states

2019 ◽  
Vol 116 (36) ◽  
pp. 18088-18097 ◽  
Author(s):  
Gustavo Deco ◽  
Josephine Cruzat ◽  
Joana Cabral ◽  
Enzo Tagliazucchi ◽  
Helmut Laufs ◽  
...  
Keyword(s):  
Fundamental Problem ◽  
Effective Connectivity ◽  
Brain State ◽  
Whole Brain ◽  
External Stimulation ◽  
Neuropsychiatric Diseases ◽  
Brain Modeling ◽  
Brain States ◽  
Definition Of ◽  
The Brain

A fundamental problem in systems neuroscience is how to force a transition from one brain state to another by external driven stimulation in, for example, wakefulness, sleep, coma, or neuropsychiatric diseases. This requires a quantitative and robust definition of a brain state, which has so far proven elusive. Here, we provide such a definition, which, together with whole-brain modeling, permits the systematic study in silico of how simulated brain stimulation can force transitions between different brain states in humans. Specifically, we use a unique neuroimaging dataset of human sleep to systematically investigate where to stimulate the brain to force an awakening of the human sleeping brain and vice versa. We show where this is possible using a definition of a brain state as an ensemble of “metastable substates,” each with a probabilistic stability and occurrence frequency fitted by a generative whole-brain model, fine-tuned on the basis of the effective connectivity. Given the biophysical limitations of direct electrical stimulation (DES) of microcircuits, this opens exciting possibilities for discovering stimulation targets and selecting connectivity patterns that can ensure propagation of DES-induced neural excitation, potentially making it possible to create awakenings from complex cases of brain injury.

scholarly journals Whole-Brain Dynamics in Aging: Disruptions in Functional Connectivity and the Role of the Rich Club

2020 ◽  
Author(s):  
Anira Escrichs ◽  
Carles Biarnes ◽  
Josep Garre-Olmo ◽  
José Manuel Fernández-Real ◽  
Rafel Ramos ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Functional Network ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Rich Club ◽  
Brain Functional Network ◽  
Age Related ◽  
Age Range ◽  
The Brain

Abstract Normal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state functional magnetic resonance imaging studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here, we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent signals to analyze resting-state fMRI data from 620 subjects divided into two groups (middle-age group (n = 310); age range, 50–64 years versus older group (n = 310); age range, 65–91 years). Applying the intrinsic-ignition framework to assess the effect of spontaneous local activation events on local–global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

Emerging concepts for the dynamical organization of resting-state activity in the brain

2010 ◽  
Vol 12 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Gustavo Deco ◽  
Viktor K. Jirsa ◽  
Anthony R. McIntosh
Keyword(s):  
Resting State ◽  
State Activity ◽  
The Brain

The brain and its resting state activity—Experimental and methodological implications

2010 ◽  
Vol 92 (4) ◽  
pp. 593-600 ◽  
Author(s):  
Georg Northoff ◽  
Niall W. Duncan ◽  
Dave J. Hayes
Keyword(s):  
Resting State ◽  
State Activity ◽  
The Brain

scholarly journals Whole-brain dynamics in aging: disruptions in functional connectivity and the role of the rich club

2020 ◽  
Author(s):  
Anira Escrichs ◽  
Carles Biarnes ◽  
Josep Garre-Olmo ◽  
José Manuel Fernández-Real ◽  
Rafel Ramos ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Rich Club ◽  
Brain Functional Network ◽  
Age Related ◽  
Age Range ◽  
The Brain

AbstractNormal aging causes disruptions in the brain that can lead to cognitive decline. Resting-state fMRI studies have found significant age-related alterations in functional connectivity across various networks. Nevertheless, most of the studies have focused mainly on static functional connectivity. Studying the dynamics of resting-state brain activity across the whole-brain functional network can provide a better characterization of age-related changes. Here we employed two data-driven whole-brain approaches based on the phase synchronization of blood-oxygen-level-dependent (BOLD) signals to analyze resting-state fMRI data from 620 subjects divided into two groups (‘middle-age group’ (n=310); age range, 50-65 years vs. ‘older group’ (n=310); age range, 66-91 years). Applying the Intrinsic-Ignition Framework to assess the effect of spontaneous local activation events on local-global integration, we found that the older group showed higher intrinsic ignition across the whole-brain functional network, but lower metastability. Using Leading Eigenvector Dynamics Analysis, we found that the older group showed reduced ability to access a metastable substate that closely overlaps with the so-called rich club. These findings suggest that functional whole-brain dynamics are altered in aging, probably due to a deficiency in a metastable substate that is key for efficient global communication in the brain.

scholarly journals A METHOD FOR INTEGRATIVE ANALYSIS OF LOCAL AND GLOBAL BRAIN DYNAMICS

2021 ◽  
Author(s):  
Robyn L. Miller ◽  
Victor M Vergara ◽  
Vince Calhoun
Keyword(s):  
Resting State ◽  
Network Connectivity ◽  
High Dimensional ◽  
Group Differences ◽  
Brain Dynamics ◽  
Whole Brain ◽  
Time Resolved ◽  
Localized Patterns ◽  
Global Brain ◽  
The Brain

The most common pipelines for studying time-varying network connectivity in resting state functional magnetic resonance imaging (rs-fMRI) operate at the whole brain level, capturing a small discrete set of 'states' that best represent time-resolved joint measures of connectivity over all network pairs in the brain. This whole-brain hidden Markov model (HMM) approach 'uniformizes' the dynamics over what is typically more than 1000 pairs of networks, forcing each time-resolved high-dimensional observation into its best-matched high-dimensional state. While straightforward and convenient, this HMM simplification obscures functional and temporal nonstationarities that could reveal systematic, informative features of resting state brain dynamics at a more granular scale. We introduce a framework for studying functionally localized dynamics that intrinsically embeds them within a whole-brain HMM frame of reference. The approach is validated in a large rs-fMRI schizophrenia study where it identifies group differences in localized patterns of entropy and dynamics that help explain consistently observed differences between schizophrenia patients and controls in occupancy of whole-brain dFNC states more mechanistically.

scholarly journals Large-scale intrinsic connectivity is consistent across varying task demands

2018 ◽  
Author(s):  
Paulina Kieliba ◽  
Sasidhar Madugula ◽  
Nicola Filippini ◽  
Eugene P. Duff ◽  
Tamar R. Makin
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Brain Activation ◽  
Whole Brain ◽  
Activation Patterns ◽  
Intrinsic Connectivity ◽  
Connectivity Patterns ◽  
Brain Functional Connectivity ◽  
The Brain

AbstractMeasuring whole-brain functional connectivity patterns based on task-free (‘restingstate’) spontaneous fluctuations in the functional MRI (fMRI) signal is a standard approach to probing habitual brain states, independent of task-specific context. This view is supported by spatial correspondence between task- and rest-derived connectivity networks. Yet, it remains unclear whether intrinsic connectivity observed in a resting-state acquisitions is persistent during task. Here, we sought to determine how changes in ongoing brain activation, elicited by task performance, impact the integrity of whole-brain functional connectivity patterns. We employed a ‘steadystates’ paradigm, in which participants continuously executed a specific task (without baseline periods). Participants underwent separate task-based (visual, motor and visuomotor) or task-free (resting) steady-state scans, each performed over a 5-minute period. This unique design allowed us to apply a set of traditional resting-state analyses to various task-states. In addition, a classical fMRI block-design was employed to identify individualized brain activation patterns for each task, allowing to characterize how differing activation patterns across the steady-states impact whole-brain intrinsic connectivity patterns. By examining correlations across segregated brain regions (nodes) and the whole brain (using independent component analysis), we show that the whole-brain network architecture characteristic of the resting-state is robustly preserved across different steady-task states, despite striking inter-task changes in brain activation (signal amplitude). Subtler changes in functional connectivity were detected locally, within the active networks. Together, we show that intrinsic connectivity underlying the canonical resting-state networks is relatively stable even when participants are engaged in different tasks and is not limited to the resting-state.New and NoteworthyDoes intrinsic functional connectivity (FC) reflect the canonical or transient state of the brain? We tested the consistency of the intrinsic connectivity networks across different task-conditions. We show that despite local changes in connectivity, at the whole-brain level there is little modulation in FC patterns, despite profound and large-scale activation changes. We therefore conclude that intrinsic FC largely reflects the a priori habitual state of the brain, independent of the specific cognitive context.

scholarly journals Decreased integration and information capacity in stroke measured by whole brain models of resting state activity

Brain ◽  
2017 ◽  
Vol 140 (4) ◽  
pp. 1068-1085 ◽  
Author(s):  
Mohit H. Adhikari ◽  
Carl D. Hacker ◽  
Josh S. Siegel ◽  
Alessandra Griffa ◽  
Patric Hagmann ◽  
...  
Keyword(s):  
Resting State ◽  
Information Capacity ◽  
Whole Brain ◽  
State Activity ◽  
Brain Models
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