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Network Hyperconnectivity and Altered Saccadic Response Suggests Impairments in Visuomotor Skills Following Mild Traumatic Brain injury : a Study of Post-Trauma Vision Syndrome

2017· other· en· W6889852972 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTraumatic brain injurySaccadic maskingAffect (linguistics)Eye movementPoison controlPerception

Abstract

fetched live from OpenAlex

Network hyperconnectivity and altered saccadic response suggests impairments in visuomotor skills following mild traumatic brain injury: A study of post-trauma vision syndrome Nicole S. Coverdale1, Allen A. Champagne1, Matti D. Allen2, Don C. Brien1, Juan Fernandez-Ruiz3, Jessica M. Trier2, Douglas J. Cook1,41.tCentre for Neuroscience Studies, Queenu2019s University, Kingston, ON, Canada 2.tDepartment of Physical Medicine and Rehabilitation, Queenu2019s University, Kingston, ON, Canada3.tDepartamento de Fisiologu00eda, Facultad de Medicina, Universidad NacionalAutu00f3noma de Mu00e9xico, Ciudad de Mu00e9xico, Mu00e9xico4.tDepartment of Surgery, Queenu2019s University, Kingston, ON, CanadaBackgroundA subset of mild traumatic brain injury (mTBI) patients experience prolonged symptoms that negatively affect quality of life. In particular, some patients report specific problems with vision and balance that can be termed post-trauma vision syndrome (PTVS), including binocular vision dysfunction, photophobia, balance impairment, and other visual symptoms such as objects appearing to move. PTVS is thought to be related to dysfunction relative to focal and ambient visual processing, but little is understood about its pathophysiology. In this study, we combined resting state analyses and eye tracking to characterize differences in network connectivity and eye movements between adults with mTBI and PTVS, and healthy age- and sex-matched controls.MethodsThirteen adults were recruited to participate in this study (n=7 mTBI, 5F, 48 uf0b1 13 years, 869 uf0b1 470 days since injury; n=6 controls, 4F, 45 uf0b1 14 years). Patients were included if they had a normal MRI or CT scan, and a physician had diagnosed them as having symptoms consistent with PTVS. A dual echo pseudocontinuous arterial spin labelling sequence was performed and blood oxygen level dependent (BOLD) data were extracted from the second echo for resting state analysis. Following pre-processing of the BOLD resting images, an independent component analysis was used to identify the spatial distribution of the network of interests, which were then clustered into nodes of interests (NOI). Mean regional BOLD timeseries were extracted for each node, and correlated across NOIs, and between networks. In addition to imaging data, eye tracking was performed during a pro- and anti-saccade protocol where the colour of the central fixation point indicated whether a pro- or anti-saccade should be performed. Complete eye tracking data was obtained on a subset of participants who completed the MRI (6 mTBI and 4 controls), in order to evaluate oculomotor skills, between the groups. ResultsCompared to controls, the mTBI group had increased functional connectivity between nodes in the sensorimotor, salience, visuospatial, and high visual networks. Reaction time for voluntary saccades in the anti-saccade task was also significantly increased in the mTBI group, compared to controls (350 uf0b1 83 ms in mTBI versus 226 uf0b1 24 ms in control; p=0.02). ConclusionsResting state network connectivity was altered in mTBI patients with a specific set of vision and balance problems, compared to healthy controls. Also, we identified behavioural changes, observable in anti-saccade reaction time, which suggests that bottom-up oculomotor processing is intact in this mTBI population, while top-down output is impaired. These results suggest that mTBI-related alterations in vision and balance affect top-down oculomotor responses, and resting state networks related to sensation, salience and high order visual processing. Further recruitment of mTBI patients will allow us to establish possible correlations between behavioral outcomes and resting state networks.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0360.018
Science and technology studies0.0010.001
Scholarly communication0.0040.021
Open science0.0090.012
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.060
GPT teacher head0.385
Teacher spread0.325 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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