The effect of external stimulation on functional networks in the aging healthy human brain

Understanding the brain changes occurring during aging can provide new insights for developing treatments that alleviate or reverse cognitive decline. Neurostimulation techniques have emerged as potential treatments for brain disorders and to improve cognitive functions. Nevertheless, given the ethical restrictions of neurostimulation approaches, in silico perturbation protocols based on causal whole-brain models are fundamental to gaining a mechanistic understanding of brain dynamics. Furthermore, this strategy could serve as a more specific biomarker relating local activity with global brain dynamics. Here, we used a large resting-state fMRI dataset divided into middle-aged (N=310, aged < 65 years) and older adults (N=310, aged >= 65) to characterize brain states in each group as a probabilistic metastable substate (PMS) space, each with a probabilistic occurrence and frequency. Then, we fitted the PMS to a whole-brain model and applied in silico stimulations with different intensities in each node to force transitions from the brain states of the older group to the middle-age group. We found that the precuneus, a brain area belonging to the default mode network and the rich club, was the best stimulation target. These findings might have important implications for designing neurostimulation interventions to revert the effects of aging on whole-brain dynamics.

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

10.1101/2020.06.29.164343 ◽

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.

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Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states

NeuroImage ◽

10.1016/j.neuroimage.2017.12.009 ◽

2018 ◽

Vol 169 ◽

pp. 46-56 ◽

Cited By ~ 35

Author(s):

Gustavo Deco ◽

Joana Cabral ◽

Victor M. Saenger ◽

Melanie Boly ◽

Enzo Tagliazucchi ◽

...

Keyword(s):

In Silico ◽

Brain Dynamics ◽

Whole Brain ◽

Brain States

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

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1905534116 ◽

2019 ◽

Vol 116 (36) ◽

pp. 18088-18097 ◽

Cited By ~ 28

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.

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

Cerebral Cortex ◽

10.1093/cercor/bhaa367 ◽

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.

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Differentiating ADHD subtypes and simulation of in silico therapeutic neuronal excitation in a whole-brain nonlinear dynamic modelling frame-work

10.1101/2020.05.08.084491 ◽

2020 ◽

Author(s):

Behzad Iravani ◽

Artin Arshamian ◽

Peter Fransson ◽

Neda Kaboodvand

Keyword(s):

In Silico ◽

Dynamic Modelling ◽

Resting State Fmri ◽

Emotional Instability ◽

Whole Brain ◽

Individual Level ◽

Modelling Framework ◽

Building Models ◽

The Individual ◽

The Brain

ABSTRACTRecent advances in non-linear computational and dynamical modelling have opened up the possibility to parametrize dynamic neural mechanisms that drive complex behavior. Importantly, building models of neuronal processes is of key importance to fully understand disorders of the brain as it may provide a quantitative platform that is capable of binding multiple neurophysiological processes to phenotype profiles. In this study, we apply a newly developed adaptive frequency-based model of whole-brain oscillations to resting-state fMRI data acquired from healthy controls and a cohort of attention deficit hyperactivity disorder (ADHD) subjects. As expected, we found that healthy control subjects differed from ADHD in terms of attractor dynamics. However, we also found a marked dichotomy in neural dynamics within the ADHD cohort. Next, we classified the ADHD subgroup according to the level of distance of each individual’s empirical network from the two model-based simulated networks. Critically, the model was mirrored in the empirical behavior data with the two ADHD subgroups displaying distinct behavioral phenotypes related to emotional instability (i.e., depression and hypomanic personality traits). Finally, we investigated the applicability and feasibility of our whole-brain model in a therapeutic setting by conducting in silico excitatory stimulations to mimic clinical transcranial magnetic stimulation paradigms in ADHD. We tested the effect of stimulating any individual brain region on key network measures and its contribution in rectifying the brain dynamics to that of the healthy brain, separately for each ADHD subgroup. This showed that this was indeed possible for both subgroups. However, the current effect sizes were small suggesting that the stimulation protocol needs to be tailored at the individual level. These findings demonstrate the potential of this new modelling framework to unveil hidden neurophysiological profiles and establish tailored clinical interventions.

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Capturing the non-stationarity of whole-brain dynamics underlying human brain states

NeuroImage ◽

10.1016/j.neuroimage.2021.118551 ◽

2021 ◽

pp. 118551

Author(s):

J.A. Galadí ◽

S. Silva Pereira ◽

Y. Sanz Perl ◽

M.L. Kringelbach ◽

I. Gayte ◽

...

Keyword(s):

Human Brain ◽

Brain Dynamics ◽

Whole Brain ◽

Brain States

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Increased sensitivity to strong perturbations in a whole-brain model of LSD

10.1101/2021.01.05.425415 ◽

2021 ◽

Author(s):

Beatrice M. Jobst ◽

Selen Atasoy ◽

Adrián Ponce-Alvarez ◽

Ana Sanjuán ◽

Leor Roseman ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

External Perturbation ◽

Brain Regions ◽

Lysergic Acid ◽

Functional Magnetic Resonance ◽

Resonance Imaging ◽

Whole Brain ◽

Response Diversity ◽

Brain States ◽

The Brain

AbstractLysergic acid diethylamide (LSD) is a potent psychedelic drug, which has seen a revival in clinical and pharmacological research within recent years. Human neuroimaging studies have shown fundamental changes in brain-wide functional connectivity and an expansion of dynamical brain states, thus raising the question about a mechanistic explanation of the dynamics underlying these alterations. Here, we applied a novel perturbational approach based on a whole-brain computational model, which opens up the possibility to externally perturb different brain regions in silico and investigate differences in dynamical stability of different brain states, i.e. the dynamical response of a certain brain region to an external perturbation. After adjusting the whole-brain model parameters to reflect the dynamics of functional magnetic resonance imaging (fMRI) BOLD signals recorded under the influence of LSD or placebo, perturbations of different brain areas were simulated by either promoting or disrupting synchronization in the regarding brain region. After perturbation offset, we quantified the recovery characteristics of the brain area to its basal dynamical state with the Perturbational Integration Latency Index (PILI) and used this measure to distinguish between the two brain states. We found significant changes in dynamical complexity with consistently higher PILI values after LSD intake on a global level, which indicates a shift of the brain’s global working point further away from a stable equilibrium as compared to normal conditions. On a local level, we found that the largest differences were measured within the limbic network, the visual network and the default mode network. Additionally, we found a higher variability of PILI values across different brain regions after LSD intake, indicating higher response diversity under LSD after an external perturbation. Our results provide important new insights into the brain-wide dynamical changes underlying the psychedelic state - here provoked by LSD intake - and underline possible future clinical applications of psychedelic drugs in particular psychiatric disorders.HighlightsNovel offline perturbational method applied on functional magnetic resonance imaging (fMRI) data under the effect of lysergic acid diethylamide (LSD)Shift of brain’s global working point to more complex dynamics after LSD intakeConsistently longer recovery time after model perturbation under LSD influenceStrongest effects in resting state networks relevant for psychedelic experienceHigher response diversity across brain regions under LSD influence after an external in silico perturbation

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Stuck in a State of Inattention? Functional Hyperconnectivity as an Indicator of Disturbed Intrinsic Brain Dynamics in Adolescents With Concussion: A Pilot Study

ASN NEURO ◽

10.1177/1759091417753802 ◽

2018 ◽

Vol 10 ◽

pp. 175909141775380 ◽

Cited By ~ 7

Author(s):

Angela M. Muller ◽

Naznin Virji-Babul

Keyword(s):

Diffusion Tensor Imaging ◽

Pilot Study ◽

Resting State ◽

Diffusion Tensor ◽

Brain Dynamics ◽

Public Health Issue ◽

Brain Correlates ◽

Brain States ◽

The Brain ◽

Structural Brain

Sports-related concussion in youth is a major public health issue. Evaluating the diffuse and often subtle changes in structure and function that occur in the brain, particularly in this population, remains a significant challenge. The goal of this pilot study was to evaluate the relationship between the intrinsic dynamics of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) and relate these findings to structural brain correlates from diffusion tensor imaging in a group of adolescents with sports-related concussions ( n = 6) and a group of healthy adolescent athletes ( n = 6). We analyzed rs-fMRI data using a sliding windows approach and related the functional findings to structural brain correlates by applying graph theory analysis to the diffusion tensor imaging data. Within the resting-state condition, we extracted three separate brain states in both groups. Our analysis revealed that the brain dynamics in healthy adolescents was characterized by a dynamic pattern, shifting equally between three brain states; however, in adolescents with concussion, the pattern was more static with a longer time spent in one brain state. Importantly, this lack of dynamic flexibility in the concussed group was associated with increased nodal strength in the left middle frontal gyrus, suggesting reorganization in a region related to attention. This preliminary report shows that both the intrinsic brain dynamics and structural organization are altered in networks related to attention in adolescents with concussion. This first report in adolescents will be used to inform future studies in a larger cohort.

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Hierarchical disruption in the cortex of anesthetized monkeys as a new signature of consciousness loss

10.1101/2020.06.04.133538 ◽

2020 ◽

Author(s):

Camilo Miguel Signorelli ◽

Lynn Uhrig ◽

Morten Kringelbach ◽

Bechir Jarraya ◽

Gustavo Deco

Keyword(s):

Neural Activity ◽

Resting State ◽

Resting State Fmri ◽

Hierarchical Organization ◽

Brain Dynamics ◽

Depth Of Anesthesia ◽

Functional Changes ◽

Cortical Hierarchy ◽

Brain States ◽

Structure Similarity

AbstractAnesthesia induces a reconfiguration of the repertoire of functional brain states leading to a high function-structure similarity. However, it is unclear how these functional changes lead to loss of consciousness. Here we suggest that the mechanism of conscious access is related to a general dynamical rearrangement of the intrinsic hierarchical organization of the cortex. To measure cortical hierarchy, we applied the Intrinsic Ignition analysis to resting-state fMRI data acquired in awake and anesthetized macaques. Our results reveal the existence of spatial and temporal hierarchical differences of neural activity within the macaque cortex, with a strong modulation by the depth of anesthesia and the employed anesthetic agent. Higher values of Intrinsic Ignition correspond to rich and flexible brain dynamics whereas lower values correspond to poor and rigid, structurally driven brain dynamics. Moreover, spatial and temporal hierarchical dimensions are disrupted in a different manner, involving different hierarchical brain networks. All together suggest that disruption of brain hierarchy is a new signature of consciousness loss.

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A METHOD FOR INTEGRATIVE ANALYSIS OF LOCAL AND GLOBAL BRAIN DYNAMICS

10.1101/2021.05.18.444698 ◽

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.

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