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Record W3107099117 · doi:10.1073/pnas.2013231117

Poststroke acute dysexecutive syndrome, a disorder resulting from minor stroke due to disruption of network dynamics

2020· article· en· W3107099117 on OpenAlexaboutno aff
Elisabeth B. Marsh, Christian Brodbeck, R. Llinás, Dania Mallick, Joshua P. Kulasingham, Jonathan Z. Simon, Rodolfó R. Llinás

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersJohns Hopkins UniversityAmerican Heart Association
KeywordsDysexecutive syndromeFusiform gyrusTemporal lobeStroke (engine)MagnetoencephalographyMontreal Cognitive AssessmentInterquartile rangeNeuroscienceCognitionFunctional magnetic resonance imagingPsychologyAudiologyCardiologyLesionMedicineInternal medicinePathologyNeuropsychologyCognitive impairmentElectroencephalography

Abstract

fetched live from OpenAlex

= 0.005), and patient reaction times were increased. The amplitude of activation was significantly lower after infarct and demonstrated a pattern of temporal dispersion independent of stroke location. Differences were prominent in the fusiform gyrus and lateral temporal lobe. The pattern suggests that distributed network dysfunction may be responsible. Additionally, controls were able to modulate their cerebral activity based on task difficulty. In contrast, stroke patients exhibited the same low-amplitude response to all stimuli. Group differences remained, to a lesser degree, 6 mo later; while MoCA scores and reaction times improved for patients. This study suggests that function is a globally distributed property beyond area-specific functionality and illustrates the need for longer-term follow-up studies to determine whether abnormal activation patterns ultimately resolve or another mechanism underlies continued recovery.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.042
GPT teacher head0.292
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations14
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of Sciences→Same topicFunctional Brain Connectivity Studies→French-language works237,207→