Using fMRI to Identify Neuronal Mechanisms of Motion Detection Underlying Blindsight
Bibliographic record
Abstract
Research on the visually impaired offers a valuable model of functional brain plasticity by showing how sensory inputs reshape cortical activations. Following a unilateral post-chiasmatic lesion affecting the visual cortex, patients suffer a controlateral visual loss referred to as Homonymous Hemianopia. Nevertheless, these patients preserve the ability to unconsciously detect, localize and discriminate visual stimuli presented in their impaired visual field. To investigate this paradox, known as blindsight, we have conducted a study using brain imaging techniques to evaluate the structural and functional impact of such lesion in Homonymous Hemianopia patients. In doing so, we collected whole brain and sliced thalamic fMRI scan sequences during resting state and a motion detection task. Subjects with a right or left hemianopia underwent a series of visual tasks to correlate blindsight performances with neural activity. Accurate performance demonstrates their ability to unconsciously perceive motion presented in the blind hemifield and the presence of residual vision. When compared to neurotypical matched controls, we observed strong anatomical and functional differences as well as asymmetrical BOLD activations. As the main visual pathways were lesioned, these findings suggest that (1) sub-cortical pathways, including the superior colliculus projections to the middle temporal area as well as the new formed pathways absent in normal vision, are responsible for processing and relaying visual information; (2) white matter tracts of the still functioning areas increase in volume; (3) functional connectivity as a whole is modified as there is a bilateral activation of the middle temporal area as opposed to a controlateral activation in normal vision. This reorganization in the structure and function of the visual pathways correlates with behavioural changes, thus offering a plausible explanation for the blindsight phenomenon. Meeting abstract presented at VSS 2018
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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 | 0.000 |
| 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) | 0.001 | 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".