Brain Stem Pursuit Pathways: Dissociating Visual, Vestibular, and Proprioceptive Inputs During Combined Eye-Head Gaze Tracking
Bibliographic record
Abstract
Eye-head (EH) neurons within the medial vestibular nuclei are thought to be the primary input to the extraocular motoneurons during smooth pursuit: they receive direct projections from the cerebellar flocculus/ventral paraflocculus, and in turn, project to the abducens motor nucleus. Here, we recorded from EH neurons during head-restrained smooth pursuit and head-unrestrained combined eye-head pursuit (gaze pursuit). During head-restrained smooth pursuit of sinusoidal and step-ramp target motion, each neuron's response was well described by a simple model that included resting discharge (bias), eye position, and velocity terms. Moreover, eye acceleration, as well as eye position, velocity, and acceleration error (error = target movement - eye movement) signals played no role in shaping neuronal discharges. During head-unrestrained gaze pursuit, EH neuron responses reflected the summation of their head-movement sensitivity during passive whole-body rotation in the dark and gaze-movement sensitivity during smooth pursuit. Indeed, EH neuron responses were well predicted by their head- and gaze-movement sensitivity during these two paradigms across conditions (e.g., combined eye-head gaze pursuit, smooth pursuit, whole-body rotation in the dark, whole-body rotation while viewing a target moving with the head (i.e., cancellation), and passive rotation of the head-on-body). Thus our results imply that vestibular inputs, but not the activation of neck proprioceptors, influence EH neuron responses during head-on-body movements. This latter proposal was confirmed by demonstrating a complete absence of modulation in the same neurons during passive rotation of the monkey's body beneath its neck. Taken together our results show that during gaze pursuit EH neurons carry vestibular- as well as gaze-related information to extraocular motoneurons. We propose that this vestibular-related modulation is offset by inputs from other premotor inputs, and that the responses of vestibuloocular reflex interneurons (i.e., position-vestibular-pause neurons) are consistent with such a proposal.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".