Investigating the Effects of Glucose and Sweet Taste on Corticospinal and Intracortical Excitability
Bibliographic record
Abstract
Transcranial magnetic stimulation (TMS) is commonly used to measure corticospinal and intracortical excitability in basic and clinical neuroscience. However, the effect of glucose on TMS-based measures is not well defined, despite a potentially impactful influence on precision and reliability. Here, a double-blinded placebo-controlled study was used to test the effects of glucose on two commonly used TMS measures: short-interval intracortical inhibition (SICI), and the area under the motor evoked potential recruitment curves (AURC). SICI and AURC are thought to reflect inhibitory (GABAergic) and excitatory (glutamatergic) neurotransmission respectively. Healthy males (N=18) each participated in four sessions. Session 1 involved TMS familiarization and acquisition of an individualized blood glucose response curve. During sessions 2, 3 and 4, dependent measures were taken before (T0) and twice after (T1 & T2) drinking 300 mL of solution containing glucose (75 g), sucralose-sweetened placebo (control for sweetness) or plain water (control for time). The T1 and T2 measurements were started 5 minutes prior to the blood glucose peak observed during Session 1. Blood glucose and mean arterial pressure (MAP) were also monitored. Sucralose, but not water or glucose increased AURC and none of the treatments altered SICI. There was no association between blood glucose level and TMS measures, but in all three conditions MAP rose after consumption of the drink. There was a positive correlation between the rise in blood pressure and the relative increase in AURC at the higher stimulus intensities. Eleven participants returned for a fifth session to quantify the smallest detectible change in the AURC measurements and it was confirmed that significant changes were real while non-significant differences in measurement means fell within the range of expected measurement error. This study also suggests a relationship between corticospinal excitability and autonomic tone. Additional investigation is required to understand the mediating factors of this association.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".