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Record W2728881252

Paired Associative Plasticity in Human Motor Cortex

2013· dissertation· en· W2728881252 on OpenAlexfundno aff
Behzad Elahi

Bibliographic record

VenueTSpace (University of Toronto) · 2013
Typedissertation
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsNeuroscienceMotor cortexAssociative propertyPlasticityPsychologyNeuroplasticityCognitive scienceCognitive psychologyPhysicsMathematics
DOInot available

Abstract

fetched live from OpenAlex

This thesis consists of four chapters. In this thesis we explored associative plasticity of human motor cortex with the use of noninvasive transcranial magnetic stimulation (TMS). Paired Associative Stimulation (PAS) has grown in popularity because of its potential clinical applications. We used TMS techniques in combination with electromyographic (EMG) measurements to study cortical excitability and kinematic features of arm movement. This work has focused in a cohesive approach to answer certain fundamental questions about a) the rules of cortical plasticity and mechanism of PAS, b) the interaction between the state of neuronal excitability at the targeted cortical network and the effects of PAS, and c) translation of these effects into obvious measurable kinematic changes starting from network level changes and ending up with the behavioral modulation of arm movement. First we explored the role of GABAergic intracortical networks and intracortical facilitation on modulation of cortical excitability by showing for the first time that PAS can be conditioned by these inhibitory and facilitatory intracortical networks. Next, using standard indirect approaches utilizing peripheral EMG measures, we showed a graded excitability response for the PAS technique and showed that interactions of PAS with motor learning depends on the degree as well as the state of cortical excitability. Rules governing the interactions of brain stimulation techniques and motor learning are important because brain stimulation techniques can be used to modify, improve or disrupt motor adaptation and skill learning with great potential for clinical applications such as facilitation of recovery after stroke. TMS provide us with a unique opportunity to study the rules of plasticity at a systems level, which is a combination of synaptic and nonsynaptic (metaplastic) changes. These changes can occur either in the direction to limit the physiological range of neuronal functioning (homeostatic) or against the direction established state of neurons.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0070.001

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 head0.025
GPT teacher head0.290
Teacher spread0.265 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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