Humans With Traumatic Brain Injuries Show Place-Learning Deficits in Computer-Generated Virtual Space
Bibliographic record
Abstract
Spatial learning and memory has been linked to the hippocampus and temporal lobes and though these areas are often damaged in traumatic brain injury (TBI), spatial learning deficits after TBI have not received much attention. In the present study, a virtual environment was used to challenge people with TBI to solve a task comparable to the Morris water maze, which in turn has been shown to be highly sensitive to hippocampal and frontal lobe dysfunction in laboratory animals. A regular computer monitor was used to present 12 participants with TBI and 12 age- and sex-matched comparison participants with a computer-generated, three-dimensional "virtual arena maze," consisting of a large round arena within a very large square room. Participants were required to learn the place of an invisible target on the floor of the room based solely on distal cues on the walls of the room. Eight of the 12 participants with moderate to severe TBI showed substantial place-learning deficits in comparison to the uninjured participants. Performance in the virtual environment correlated with self-reported frequency of wayfinding problems in everyday life and with scores on a test of episodic memory, the Rivermead Behavioural Memory Task. These data confirm that deficits in spatial learning and memory follow TBI, and suggest that the virtual arena maze may provide a new method for objectively assessing them.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".