Startle-triggered responses indicate reticulospinal drive is larger for voluntary shoulder versus finger movements
Bibliographic record
Abstract
Recent primate studies have implicated a substantial role of reticulospinal pathways in the production of various voluntary movements. A novel way to assess the relative reticulospinal contributions in humans is through the use of a "StartReact" paradigm where a startling acoustic stimulus (SAS) is presented during a simple reaction time (RT) task. The StartReact response is characterized by short-latency triggering of a prepared response, which is attributed to increased reticulospinal drive associated with startle reflex activation. The current study used a StartReact protocol to examine differences in reticulospinal contributions between proximal and distal effectors by examining EMG onset latencies in lateral deltoid and first dorsal interosseous during bilateral shoulder or finger abduction. The magnitude of the StartReact effect, and thus relative reticulospinal drive, was quantified as the difference in RT between startle trials in which startle-reflex related EMG activation in the sternocleidomastoid (SCM) was present (SCM +) versus absent (SCM -). A significantly larger StartReact effect was observed for bilateral shoulder abduction versus bimanual finger abduction and a higher incidence of SCM + trials occurred in the proximal task. Additionally, both startle reflex and response-related EMG measures were larger on SCM + trials for the shoulder versus finger task. These results provide compelling novel evidence for increased reticulospinal activation in bilateral proximal upper-limb movements.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".