Cited by 109Functional Brain Connectivity StudiesBipolar Disorder and TreatmentMental Health Research Topics

Dynamic functional connectivity in bipolar disorder is associated with executive function and processing speed: A preliminary study

Open access
Nguyen, Tanya T., Kovacevic, Sanja, Dev, Sheena I., Lu, Kun, Liu, Thomas T., Eyler, Lisa T.·2017·Neuropsychology

Abstract

OBJECTIVE: Disturbances in functional connectivity have been suggested to contribute to cognitive and emotion processing deficits observed in bipolar disorder (BD). Functional connectivity between medial prefrontal cortex (mPFC) and other brain regions may be particularly abnormal. The goal of the present study was to characterize the temporal dynamics of the default mode network (DMN) connectivity in BD and examine its association with cognition. METHOD: In a preliminary study, euthymic BD (n = 15) and healthy comparison (HC, n = 19) participants underwent resting-state functional MRI, using high-resolution sequences adapted from the Human Connectome Project, and completed neuropsychological measures of processing speed and executive function. A seed-based approach was used to measure DMN correlations in each participant, with regions of interest in the mPFC, posterior cingulate cortex (PCC), and lateral parietal cortex. Subsequently, to characterize temporal dynamics, correlational analyses between the mPFC and other DMN nodes were repeated using a sliding-window correlational analysis with subsets of the time series. RESULTS: When averaged across the entire scan, there were no group differences in overall connectivity strength between the mPFC and other regions of the DMN. However, dynamic connectivity between the mPFC and PCC was altered in BD, such that connectivity was less variable (i.e., more rigid) over time. Decreased connectivity variability was associated with slower processing speed and reduced cognitive set-shifting in BD patients. CONCLUSIONS: Variability in resting-state functional connectivity may be an index of internetwork flexibility that is reduced in BD and a correlate of ongoing cognitive impairment during periods of euthymia. (PsycINFO Database Record

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1037/neu0000317

Cites

68 of 68 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In depression, the precision might crash for positive priors, leading to hypo-learning and negativity.

    “In depression (the other pole), the precision might crash for positive priors, leading to the state described earlier of hypo-learning and negativity (68, 69).”

    From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [68]

    The Methods (Participants; page not provided) study euthymic bipolar I participants, and the Discussion (page not provided) addresses attention and connectivity dynamics. Neither those passages nor searches for positive-prior precision, hypo-learning, and depression-related learning address the proposed mechanism. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Nguyen, T. T., Kovacevic, S., Dev, S. I., Lu, K., Liu, T. T., & Eyler, L. T.
Affiliations
  • VA San Diego Healthcare System (US)
  • San Diego State University (US)
  • University of California San Diego (US)
Venue
Neuropsychology
Published
2017-01
Volume
31
Issue
1
Pages
73-83
ISSN
  • 0894-4105 (ISSN-L)
  • 1931-1559
OpenAlex
W2538606748
Cited by
109
References
67
Citations by year
2026: 6 · 2025: 8 · 2024: 11 · 2023: 11 · 2022: 7 · 2021: 33 · 2020: 17 · 2019: 7 · 2018: 6 · 2017: 3
FWCI
3.39
Type
journal article
Language
en
Open access
Locations
  • Neuropsychology (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • National Institutes of Health (5r01mh083968-05)
  • National Institute of Mental Health (R01-MH083968, T32MH019934)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
Keywords
bipolar disorder, dynamic functional connectivity, default mode network, medial prefrontal cortex, posterior cingulate cortex, processing speed, executive function, set-shifting, cognitive flexibility, euthymia, cognitive impairment
MeSH terms
Adult, Bipolar Disorder, Brain, Brain Mapping, Cognition, Cognition Disorders, Emotions, Female, Gyrus Cinguli, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Neuropsychological Tests, Parietal Lobe, Psychometrics, Reaction Time, Reference Values, Prefrontal Cortex, Executive Function

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review