EEG resting-state large-scale brain network dynamics are related to depressive symptoms

AbstractBackgroundThe few previous studies on resting-state EEG microstates in depressive patients suggest altered temporal characteristics of microstates compared to those of healthy subjects. We tested whether resting-state microstate temporal characteristics could capture large-scale brain network dynamic activity relevant to depressive symptomatology.MethodsTo evaluate a possible relationship between the resting-state large-scale brain network dynamics and depressive symptoms, we performed EEG microstate analysis in patients with moderate to severe depression within bipolar affective disorder, depressive episode, and periodic depressive disorder, and in healthy controls.ResultsMicrostate analysis revealed six classes of microstates (A-F) in global clustering across all subjects. There were no between-group differences in the temporal characteristics of microstates. In the patient group, higher symptomatology on the Montgomery-Åsberg Depression Rating Scale, a questionnaire validated as measuring severity of depressive episodes in patients with mood disorders, correlated with higher occurrence of microstate A (Spearman’s rank correlation, r = 0.70, p < 0.01).ConclusionOur results suggest that the observed interindividual differences in resting-state EEG microstate parameters could reflect altered large-scale brain network dynamics relevant to depressive symptomatology during depressive episodes. These findings suggest the utility of the microstate analysis approach in an objective depression assessment.

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Altered EEG resting-state large-scale brain network dynamics in euthymic bipolar disorder patients

10.1101/668004 ◽

2019 ◽

Author(s):

Alena Damborská ◽

Camille Piguet ◽

Jean-Michel Aubry ◽

Alexandre G. Dayer ◽

Christoph M. Michel ◽

...

Keyword(s):

Bipolar Disorder ◽

Resting State ◽

Large Scale ◽

Network Dynamics ◽

Brain Network ◽

Network Activity ◽

Anxiety State ◽

Temporal Characteristics ◽

Functional Brain Network ◽

And Gender

AbstractBackgroundNeuroimaging studies provided evidence for disrupted resting-state functional brain network activity in bipolar disorder (BD). Electroencephalographic (EEG) studies found altered temporal characteristics of functional EEG microstates during depressive episode within different affective disorders. Here we investigated whether euthymic patients with BD show deviant resting-state large-scale brain network dynamics as reflected by altered temporal characteristics of EEG microstates.MethodsWe used high-density EEG to explore between-group differences in duration, coverage and occurrence of the resting-state functional EEG microstates in 17 euthymic adults with BD in on-medication state and 17 age- and gender-matched healthy controls. Two types of anxiety, state and trait, were assessed separately with scores ranging from 20 to 80.ResultsMicrostate analysis revealed five microstates (A-E) in global clustering across all subjects. In patients compared to controls, we found increased occurrence and coverage of microstate A that did not significantly correlate with anxiety scores.ConclusionOur results provide neurophysiological evidence for altered large-scale brain network dynamics in BD patients and suggest the increased presence of A microstate to be an electrophysiological trait characteristic of BD.

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EEG Resting-State Large-Scale Brain Network Dynamics Are Related to Depressive Symptoms

Frontiers in Psychiatry ◽

10.3389/fpsyt.2019.00548 ◽

2019 ◽

Vol 10 ◽

Cited By ~ 12

Author(s):

Alena Damborská ◽

Miralena I. Tomescu ◽

Eliška Honzírková ◽

Richard Barteček ◽

Jana Hořínková ◽

...

Keyword(s):

Depressive Symptoms ◽

Resting State ◽

Large Scale ◽

Network Dynamics ◽

Brain Network

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An intervention for depressive symptoms using a commercial game in a mental health impatient setting. (Preprint)

10.2196/preprints.13890 ◽

2019 ◽

Author(s):

Pablo Rodrigo Guzman Cortez ◽

Matias Marzocchi ◽

Neus Freixa Fontanals ◽

Mercedes Balcells-Olivero

Keyword(s):

Mental Health ◽

Depressive Symptoms ◽

Health Outcomes ◽

Serious Games ◽

Rating Scale ◽

Depressive Symptomatology ◽

Pilot Test ◽

Potential Health ◽

Depressive Episodes ◽

Hamilton Rating Scale

BACKGROUND Computerized mental health interventions have shown evidence of their potential benefit for mental health outcomes in young users. All of the studied interventions available in the review and scientific literature can be classified as "serious games". Serious games are computerized interventions designed from the start with the objective of improving specific desired health outcomes. Moreover, there are reports of users experiencing subjective benefits in mental health after playing specific commercial games. These were games not intentionally made with a therapeutic objective in the design process. An example is the videogame "Journey", first released for the Playstation 3 console in 2012 which won "Game of the Year" in the 2013 D.I.C.E awards. The creator of the game describes the game as a short, 2-3-hour narrative experience in which the player goes through the "Hero's Journey" following a classic 3-part structure. There were more than 100 testimonials from players describing how the game helped them cope with psychological or personal issues. Some of them explicitly described recovering from depressive episodes through playing the game. OBJECTIVE To conduct a pilot test of the efficacy of the videogame Journey in reducing depressive symptoms in an acute impatient setting METHODS Depressive symptomatology was measured before and after the intervention using the Hamilton Rating Scale for Depression (HRSD) The intervention was conducted in an isolated room using a Playstation 3 console with the videogame "Journey" developed by Thatgamecompany. No internet access was allowed. The game was played over the course of 4 30-45 min sessions in a two week period. RESULTS The initial score in the Hamilton Rating Scale for Depression (HRSD) was 30, indicating a very severe depression. After the intervention the HRSD score was 10, showing a mild depression. CONCLUSIONS The Videogame Journey, a commercial game first available for the Playstation 3 console in 2012, was not created as a serious game with potential health benefits. Our pilot test is the first case report of a commercial game showing a potential effect in reducing depressive symptoms, which is consistent with the previous informal reports of users online.

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Altered Electroencephalographic Resting-State Large-Scale Brain Network Dynamics in Euthymic Bipolar Disorder Patients

Frontiers in Psychiatry ◽

10.3389/fpsyt.2019.00826 ◽

2019 ◽

Vol 10 ◽

Author(s):

Alena Damborská ◽

Camille Piguet ◽

Jean-Michel Aubry ◽

Alexandre G. Dayer ◽

Christoph M. Michel ◽

...

Keyword(s):

Bipolar Disorder ◽

Resting State ◽

Large Scale ◽

Network Dynamics ◽

Brain Network

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Brain network dynamics fingerprints are resilient to data heterogeneity

10.1101/2020.01.26.920637 ◽

2020 ◽

Author(s):

Tommaso Menara ◽

Giuseppe Lisi ◽

Fabio Pasqualetti ◽

Aurelio Cortese

Keyword(s):

Resting State ◽

Large Scale ◽

Brain Activity ◽

Network Dynamics ◽

Brain Network ◽

Fmri Data ◽

Dynamical Models ◽

Subject Specific ◽

Data Heterogeneity ◽

Data Collections

AbstractLarge multi-site neuroimaging datasets have significantly advanced our quest to understand brain-behaviour relationships and to develop biomarkers of psychiatric and neurodegenerative disorders. Yet, such data collections come at a cost, as the inevitable differences across samples may lead to biased or erroneous conclusions. Previous work has investigated this critical issue in resting-state functional magnetic resonance imaging (rs-fMRI) data in terms of effects on static measures, such as functional connectivity and brain parcellations. Here, we depart from prior approaches and utilize dynamical models to examine how diverse scanning factors in multi-site fMRI recordings affect our ability to infer the brain’s spatiotemporal wandering between large-scale networks of activity. Building upon this premise, we first confirm the emergence of robust subject-specific dynamical patterns of brain activity. Next, we exploit these individual fingerprints to show that scanning sessions belonging to different sites and days tend to induce high variability, while other factors, such as the scanner manufacturer or the number of coils, affect the same metrics to a lesser extent. These results concurrently indicate that we can recover the unique trajectories of brain activity changes in each individual, but also that our ability to infer such patterns is affected by how, where and when we try to do so.Author summaryWe investigate the important issue of data heterogeneity in large multi-site data collections of brain activity recordings. At a time in which appraising the source of variability in large datasets is gaining increasing attention, this study provides a novel point of view based on data-driven dynamical models. By employing subject-specific signatures of brain network dynamics, we find that certain scanning factors significantly affect the quality of resting-state fMRI data. More specifically, we first validate the existence of subject-specific brain dynamics fingerprints. As a proof of concept, we show that dynamical states can be estimated reliably, even across different datasets. Finally, we assess which scanning factors, and to what extent, influence the variability of such fingerprints.

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Age of onset modulates resting‐state brain network dynamics in Friedreich Ataxia

Human Brain Mapping ◽

10.1002/hbm.25621 ◽

2021 ◽

Author(s):

Gilles Naeije ◽

Nicolas Coquelet ◽

Vincent Wens ◽

Serge Goldman ◽

Massimo Pandolfo ◽

...

Keyword(s):

Resting State ◽

Age Of Onset ◽

Network Dynamics ◽

Friedreich Ataxia ◽

Brain Network

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Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

Frontiers in Neuroinformatics ◽

10.3389/fninf.2015.00002 ◽

2015 ◽

Vol 9 ◽

Cited By ~ 30

Author(s):

Xerxes D. Arsiwalla ◽

Riccardo Zucca ◽

Alberto Betella ◽

Enrique Martinez ◽

David Dalmazzo ◽

...

Keyword(s):

Human Brain ◽

Real Time ◽

Large Scale ◽

Network Dynamics ◽

Brain Network ◽

Large Scale Simulation ◽

Time Interaction

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Living With Bipolar Disorder in the Time of Covid-19: Biorhythms During the Severe Lockdown in Cagliari, Italy, and the Moderate Lockdown in Tunis, Tunisia

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.634765 ◽

2021 ◽

Vol 12 ◽

Author(s):

Mauro Giovanni Carta ◽

Uta Ouali ◽

Alessandra Perra ◽

Azza Ben Cheikh Ahmed ◽

Laura Boe ◽

...

Keyword(s):

Bipolar Disorder ◽

Depressive Symptoms ◽

Rating Scale ◽

Biological Rhythms ◽

Short Term ◽

Female Age ◽

Future Studies ◽

Restrictive Measures ◽

Depressive Episodes ◽

Hamilton Rating Scale

Background: Restrictions during Covid-19 pandemic lockdown, in which rhythms of life have been compromised, can influence the course of bipolar disorder (BD). This study follows patients with bipolar disorder living in two geographically close cities (Cagliari and Tunis), but with different lockdown conditions: less severe in Tunis.Methods: Two cohorts were evaluated during lockdown (April 2020, t0) and 2 months later with lockdown lifted for a month (t1). Individuals were: over 18 years old without gender exclusion, BD I or II, in care for at least 1 year, received a clinical interview in the month before the start of the lockdown, stable clinically before the lockdown. The assessment was conducted by telephone by a psychiatrist or psychologist with good knowledge of patients. Diagnoses were made according to DSM-5 criteria. Depressive symptoms were collected through the Hamilton Rating Scale for Depression; cut-off 14 indicative of depressive episode. Circadian rhythms were measured using the BRIAN scale.Results: Forty individuals in Cagliari (70%female, age 48.57 ± 11.64) and 30 in Tunis (53.3% Female, age 41.8 ± 13.22) were recruited. In Cagliari at t0 45% had depressive episodes against none in Tunis, a similar difference appeared at t1. At t0 and t1 the Cagliari sample had more dysfunctional scores in the overall BRIAN scale and in the areas of sleep, activities and social rhythms; no differences were found in nutrition, both samples had predominantly nocturnal rhythm. In Cagliari at t0 and t1, the depressive sub-group showed more dysfunctional scores in the BRIAN areas sleep, activity, and nutrition. However, the differences in biological rhythms resulted, through ANCOVA analysis, independent of the co-presence of depressive symptoms.Discussion: A rigid lockdown could expose people with BD to depressive relapse through dysregulation of biological rhythms. The return to more functional rhythms did not appear 1 month after lockdown. The rekindling of the pandemic and the restoration of new restrictive measures will prevent, at least in the short term, the beneficial effect of a return to normality of the two cohorts.This was a limited exploratory study; future studies with larger samples and longer observational time are needed to verify the hypothesis.

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A Hidden Link between Subclinical Hypothyroidism and Depression: A literature Review

10.47363/jner/2021(1)101 ◽

2021 ◽

pp. 1-5

Author(s):

Sabitha Challa ◽

◽

Ahmed S Kabeil ◽

Bithiah Inyang ◽

Faisal J Gondal ◽

...

Keyword(s):

Depressive Symptoms ◽

Subclinical Hypothyroidism ◽

Rating Scale ◽

Serum Levels ◽

Younger Adults ◽

Normal Thyroid Function ◽

Low T3 ◽

The Central Nervous System ◽

Hypothalamic Pituitary Axis ◽

Depressive Episodes

The association between Subclinical hypothyroidism and Depression is recognised. It is found that patients with Thyroid disorders are more prone to develop depressive symptoms and depression may be accompanied by various subtle thyroid abnormalities. The most commonly documented abnormalities are elevated T4 levels, Low T3, elevated rT3, a blunted TSH response to TSH, Positive anti thyroid autoantibodies and elevated CSF TRH concentrations. It is also found that thyroid hormone supplements appear to accelerate and enhance the clinical response to antidepressants. It is found out that Depression is associated with changes in Hypothalamic-pituitary axis as thyroid hormones act on the central nervous system. Mild thyroid dysfunction causes depression in younger patients (<60 years old) diagnosed by depressive scale. It was found that differences in age group may cause depressive episodes. Depressive episodes such as anxiety and the risk of committing suicide are considerable factors that differ according to the age of the individuals.SCH was found to be associated with depression in the younger adults (<60 years old). The only difference between SCH and normal thyroid function is TSH.In depressive disorder and subclinical hypothyroidism sex differences have also been recognised. Association between subclinical hypothyroidism and Depression is assessed by various depressive scores such as Beck Depression Inventory and Hamilton depression rating scale. As Subclinical hypothyroidism is associated with low mood, Serum levels of TSH, FT3, FT4 and Hamilton depression, treatment with Levothyroxine showed significant decrease is TSH levels and Hamilton scores were decreased. Since the prevalence of depressive symptoms in hypothyroidism is high TSH cut-off levels is used,TSH cut off value for hypothyroidism is based on associated symptoms,TSH cut-off value is 2.5 MIU/L is optimal

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A Neuroeconomic Framework for Creative Cognition

10.31234/osf.io/5pqy6 ◽

2017 ◽

Author(s):

Hause Lin ◽

Oshin Vartanian

Keyword(s):

Decision Making ◽

Locus Coeruleus ◽

Large Scale ◽

Network Dynamics ◽

Brain Network ◽

Creative Cognition ◽

Decision Making Processes

Neuroeconomics is the study of the neurobiological bases of subjective preferences and choices. We present a novel framework that synthesizes findings from the literatures on neuroeconomics and creativity to provide a neurobiological description of creative cognition. It proposes that value-based decision-making processes and activity in the locus coeruleus-norepinephrine (LC-NE) neuromodulatory system underlie creative cognition, as well as the large-scale brain network dynamics shown to be associated with creativity. This framework allows us to re-conceptualize creative cognition as driven by value-based decision making, in the process providing several falsifiable hypotheses that can further our understanding of creativity, decision making, and brain network dynamics.

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