MétaCan
Menu
← Back to cohort
Record W4381742096 · doi:10.2196/preprints.50030

The Effects of Exercise on Synaptic Plasticity in Individuals With Mild Cognitive Impairment: Protocol for a Pilot Intervention Study (Preprint)

2023· preprint· en· W4381742096 on OpenAlexaff
Karishma R. Ramdeo, Margaret Fahnestock, Martin J. Gibala, P. Ravi Selvaganapathy, Justin Lee, Aimee J. Nelson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSynaptic plasticityNeuroplasticityTranscranial magnetic stimulationPsychologyPhysical medicine and rehabilitationDementiaMedicineCognitive trainingCognitionNeurosciencePhysical therapyStimulationInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND Mild cognitive impairment (MCI) is a syndrome preceding more severe impairment characterized by dementia. MCI affects an estimated 15% to 20% of people older than 65 years. Nonpharmacological interventions including exercise are recommended as part of overall MCI management based on the positive effects of exercise on cognitive performance. Interval training involves brief intermittent bouts of exercise interspersed with short recovery periods. This type of exercise promotes cognitive improvement and can be performed in individuals with MCI. Synaptic plasticity can be assessed in vivo by the neurophysiological response to repetitive transcranial magnetic stimulation (rTMS). A method to assess synaptic plasticity uses an intermittent theta burst stimulation (iTBS), which is a patterned form of rTMS. Individuals with MCI have decreased responses to iTBS, reflecting reduced synaptic plasticity. It is unknown whether interval training causes changes in synaptic plasticity in individuals living with MCI. OBJECTIVE This research will determine whether interval training performed using a cycle ergometer enhances synaptic plasticity in individuals with MCI. The three aims are to (1) quantify synaptic plasticity after interval training performed at a self-determined intensity in individuals with MCI; (2) determine whether changes in synaptic plasticity correlate with changes in serum brain-derived neurotrophic factor, osteocalcin, and cognition; and (3) assess participant compliance to the exercise schedule. METHODS 24 individuals diagnosed with MCI will be recruited for assignment to 1 of the 2 equally sized groups: exercise and no exercise. The exercise group will perform exercise 3 times per week for 4 weeks. Synaptic plasticity will be measured before and following the 4-week intervention. At these time points, synaptic plasticity will be measured as the response to single-pulse TMS, reflected as the percent change in the average amplitude of 20 motor-evoked potentials before and after an iTBS rTMS protocol, which is used to induce synaptic plasticity. In addition, individuals will complete a battery of cognitive assessments and provide a blood sample from the antecubital vein to determine serum brain-derived neurotrophic factor and osteocalcin. RESULTS The study began in September 2023. CONCLUSIONS The proposed research is the first to assess whether synaptic plasticity is enhanced after exercise training in individuals with MCI. If exercise does indeed modify synaptic plasticity, this will create a new avenue by which we can study and manipulate neural plasticity in these individuals. CLINICALTRIAL ClinicalTrials.gov NCT05663918; https://clinicaltrials.gov/study/NCT05663918 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/50030

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.049
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0490.008

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 head0.069
GPT teacher head0.358
Teacher spread0.289 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicTranscranial Magnetic Stimulation Studies→French-language works237,207→