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Record W2470787359 · doi:10.1155/2016/4806492

Maladaptive Plasticity in Aphasia: Brain Activation Maps Underlying Verb Retrieval Errors

2016· article· en· W2470787359 on OpenAlexaff
Kerstin Spielmann, E. Dana Durand, Karine Marcotte, Ana Inés Ansaldo

Bibliographic record

VenueNeural Plasticity · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology of Language and Bilingualism
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsAphasiaVerbPsychologyNeuroplasticityCognitive psychologyNeuroscienceNeuroimagingComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Anomia, or impaired word retrieval, is the most widespread symptom of aphasia, an acquired language impairment secondary to brain damage. In the last decades, functional neuroimaging techniques have enabled studying the neural basis underlying anomia and its recovery. The present study aimed to explore maladaptive plasticity in persistent verb anomia, in three male participants with chronic nonfluent aphasia. Brain activation maps associated with semantic verb paraphasia occurring within an oral picture-naming task were identified with an event-related fMRI paradigm. These maps were compared with those obtained in our previous study examining adaptive plasticity (i.e., successful verb naming) in the same participants. The results show that activation patterns related to semantic verb paraphasia and successful verb naming comprise a number of common areas, contributing to both maladaptive and adaptive neuroplasticity mechanisms. This finding suggests that the segregation of brain areas provides only a partial view of the neural basis of verb anomia and successful verb naming. Therefore, it indicates the importance of network approaches which may better capture the complexity of maladaptive and adaptive neuroplasticity mechanisms in anomia 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 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)0.000
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
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)0.0000.000

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 head0.068
GPT teacher head0.306
Teacher spread0.238 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2016
Admission routes1
Has abstractyes

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