Adapting to change: The role of the right hemisphere in mental model building and updating.
Bibliographic record
Abstract
We recently proposed that the right hemisphere plays a crucial role in the processes underlying mental model building and updating. Here, we review the evidence we and others have garnered to support this novel account of right hemisphere function. We begin by presenting evidence from patient work that suggests a critical role for the right hemisphere in the ability to learn from the statistics in the environment (model building) and adapt to environmental change (model updating). We then provide a review of neuroimaging research that highlights a network of brain regions involved in mental model updating. Next, we outline specific roles for particular regions within the network such that the anterior insula is purported to maintain the current model of the environment, the medial prefrontal cortex determines when to explore new or alternative models, and the inferior parietal lobule represents salient and surprising information with respect to the current model. We conclude by proposing some future directions that address some of the outstanding questions in the field of mental model building and updating. (PsycINFO Database Record
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".