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Record W3209788662 · doi:10.32598/bcn.2021.1425.4

COVID-19 and the Brain: A Psychological and Resting-state Functional Magnetic Resonance Imagin (fMRI) Study of the Whole-brain Functional Connectivity

2021· article· en· W3209788662 on OpenAlexaboutno aff
Mohammad Niroumand Sarvandani, Javad Sheikhi Koohsar, Raheleh Rafaiee, Maryam Saeedi, Seyedeh Masoumeh Seyedhosseini Tamijani, Hamed Ghazvini, Hossein Sheibani

Bibliographic record

VenueBasic and Clinical Neuroscience Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
FundersShahroud University of Medical Sciences
KeywordsFunctional magnetic resonance imagingResting state fMRIFunctional connectivityCoronavirus disease 2019 (COVID-19)Magnetic resonance imagingNeurosciencePsychologyMedicineBrain mappingPathologyRadiology

Abstract

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Introduction: Coronavirus-2019 (COVID-19) spreads rapidly worldwide and causes severe acute respiratory syndrome. The current study aims to evaluate the relationship between the whole-brain functional connections in a resting state and cognitive impairments in patients with COVID-19 compared to the healthy control group. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) and Montreal cognitive assessment (MoCA) data were obtained from 29 patients of the acute stage of COVID-19 on the third day of admission and 20 healthy controls. Cross-correlation of the mean resting-state signals was determined in the voxels of 23 independent components (IC) of brain neural circuits. To assess cognitive function and neuropsychological status, MoCA was performed on all participants. The relationship between rs-fMRI information, neuropsychological status, and paraclinical data was analyzed. Results: The COVID-19 group got a lower mean MoCA score and showed a significant reduction in the functional connectivity of the IC14 (P<0.001) and IC38 (P<0.001) regions compared to the controls. The increase in functional connectivity was observed in the COVID-19 group compared to the controls at baseline in the default mode network (DMN) IC00 (P<0.001) and dorsal attention network (DAN) IC08 (P<0.001) regions. Furthermore, the alternation of functional connectivity in the mentioned ICs was significantly correlated with the mean MoCA scores and inflammatory parameters, i.e. erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP). Conclusion: Functional connectivity abnormalities in four brain neural circuits are associated with cognitive impairment and increased inflammatory markers in patients with COVID-19. Highlights: The patients with coronavirus-2019 (COVID-19) got a lower mean Montreal cognitive assessment (MoCA) score.The patients with COVID-19 showed significant reduction in the functional connectivity of the IC14 and IC38 regions.The patients with COVID-19 showed significant increase of functional connectivity in the default mode network (DMN) IC00 and dorsal attention network (DAN) IC08 regions.Alternation of functional connectivity was significantly correlated with the mean MoCA scores and ESR and CRP. Plain Language Summary: The researcher aimed at assessing cognitive impairments and investigating the whole-brain functional connectivity using resting state fMRI in patients with COVID-19 compared with healthy control group. The result showed That COVID-19 group got a lower mean cognitive score and showed a significant reduction in the functional connectivity of the IC14 and IC38 regions of brain compared with controls. Also, the increase of functional connectivity was observed in the COVID-19 group compared with controls at baseline in the default mode network (DMN) and dorsal attention network (DAN) regions of brain. Moreover, Functional connectivity abnormalities in four brain neural circuits associated with cognitive impairment and increased inflammatory markers in patients with COVID-19.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.046
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.381
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2021
Admission routes1
Has abstractyes

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