Voluntary saccade inhibition deficits correlate with extended white-matter cortico-basal atrophy in Huntington's disease
Bibliographic record
Abstract
The ability to inhibit automatic versus voluntary saccade commands in demanding situations can be impaired in neurodegenerative diseases such as Huntington's disease (HD). These deficits could result from disruptions in the interaction between basal ganglia and the saccade control system. To investigate voluntary oculomotor control deficits related to the cortico-basal circuitry, we evaluated early HD patients using an interleaved pro- and anti-saccade task that requires flexible executive control to generate either an automatic response (look at a peripheral visual stimulus) or a voluntary response (look away from the stimulus in the opposite direction). The impairments of HD patients in this task are mainly attributed to degeneration in the striatal medium spiny neurons leading to an over-activation of the indirect-pathway thorough the basal ganglia. However, some studies have proposed that damage outside the indirect-pathway also contribute to executive and saccade deficits. We used the interleaved pro- and anti-saccade task to study voluntary saccade inhibition deficits, Voxel-based morphometry and Tract-based spatial statistic to map cortico-basal ganglia circuitry atrophy in HD. HD patients had voluntary saccade inhibition control deficits, including increased regular-latency anti-saccade errors and increased anticipatory saccades. These deficits correlated with white-matter atrophy in the inferior fronto-occipital fasciculus, anterior thalamic radiation, anterior corona radiata and superior longitudinal fasciculus. These findings suggest that cortico-basal ganglia white-matter atrophy in HD, disrupts the normal connectivity in a network controlling voluntary saccade inhibitory behavior beyond the indirect-pathway. This suggests that in vivo measures of white-matter atrophy can be a reliable marker of the progression of cognitive deficits in HD.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".