Gaze behaviour reveals the specification of competing reach movements under conditions of target uncertainty
Bibliographic record
Abstract
Recent influential theory suggests that when confronted with multiple potential reach targets, we maintain competing motor plans in parallel before deciding which one to execute (Cisek & Kalaska 2010). Although neurophysiological recordings from non-human primates have revealed results consistent with this controversial hypothesis (Cisek & Kalaska, 2005), unambiguous behavioural evidence remains sparse. Here we show, by exploiting the tendency of individuals to fixate an internal aimpoint when reaching to a single target under a visuomotor rotation (Rand & Rentsch, 2015), that gaze behaviour conveys details about the actions specified, but not necessarily executed, prior to target selection. Following a fixed preview period (2 or 4 s), either a single target or one of the two potential targets was filled in, signifying participants to initiate their reach. Targets were displayed on a visible ring and visuomotor rotations were applied to the targets, requiring participants to reach towards a location rotated away from the target to move the cursor from a central start position to the cued target. As expected, when only one target was presented, participants, in addition to fixating the visible target, reliably fixated an internal aimpoint during the preview period, indicative of movement planning. Critically, in two-target trials participants also fixated the aimpoints of the potential targets, as well as the visible targets during the preview period, indicating that they prepared competing reach movements prior to target selection. These findings provide compelling evidence for the influential, yet controversial idea that individuals specify, in advance of movement, competing motor plans under target uncertainty.Acknowledgments: Funded by NSERC and CIHR
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 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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".