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Record W2013992327 · doi:10.1891/1933-3196.3.1.39

Present and Accounted For: Sensory Stimulation and Parietal Neuroplasticity

2009· article· en· W2013992327 on OpenAlexaff
Heather J. Pearson

Bibliographic record

VenueJournal of EMDR Practice and Research · 2009
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsSensory systemSensory stimulation therapyPosterior parietal cortexNeurosciencePsychologyStimulationNeglectNeuroplasticityParietal lobeCognitive psychologyPsychiatry

Abstract

fetched live from OpenAlex

There are commonalities between neurologic syndromes arising from lesions of the parietal cortex and psychiatric syndromes secondary to psychological trauma. Additionally some posttraumatic syndromes may reflect functional disruption of parietal areas. Directional or bilateral alternating peripheral sensory stimulation appear to assist in the amelioration of a wide range of clinical conditions, including the neglect syndrome and Posttraumatic Stress Disorder. It is posited that the stimulation may exert its effect through activation of parietal higher-order functions. The activation may result in an integration of sensory information and an updating of the current representation of person and space, which incorporates an awareness of current body reality, sense of self, and world view. It is hypothesized that the EMDR procedure is ideally constructed to facilitate parietal activation through multimodal sensory stimulation, attention and episodic memory retrieval and focus on internal and external body, space, and self. Further investigations and an integration of data between disciplines are suggested, in order to expand our range of effective treatments.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.001

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 head0.118
GPT teacher head0.429
Teacher spread0.310 · 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

Citations12
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of EMDR Practice and ResearchSame topicSpatial Neglect and Hemispheric DysfunctionFrench-language works237,207