Face-selective activation in the middle fusiform gyrus in a patient with acquired prosopagnosia: abnormal modulation for face identity
Bibliographic record
Abstract
We recently reported bilateral face-preferential activation in the middle fusiform gyrus (mFG) and in the superior temporal sulcus (STS) of patient DF, who has severe acquired prosopagnosia and object agnosia but who is able to discriminate a face from an object (Steeves et al., 2006). Further, DF showed no face-preferential activation in the inferior occipital gyrus (IOG) in either hemisphere, which is near her lateral occipital lesions (LO). Identical face-preferential activation in the right mFG was also reported in the acquired prosopagnosic patient PS, who has lesions in the left mFG and right IOG (Rossion et al., 2003). However unlike neurologically-intact individuals, PS did not show release from adaptation to face identity in this area (Schiltz et al., 2006). Here, we tested DF for face identity-specific modulation using event-related fMR adaptation. In a passive design, DF viewed pairs of same and different faces and objects (1000 ms each, separated by 500 ms with 7500 ms ITI) and the task was to identify face-object trials. In an active 1-back matching design, DF viewed pairs of same and different faces. As before, DF showed face-preferential activation in both left and right mFG and STS. Contrary to healthy controls, in both designs the activation in these regions did not show the expected pattern of adaptation recovery with different face identities. Consistent with her behavioural performance, DF's cortical face networks do not appear to process face identity. Comparing patients PS and DF puts forth a solid case— they have different lesion patterns within the face-preferential cortical network but both have intact right mFG and a common lesion in the right IOG. In both cases, face-selectivity and face detection can operate with an intact right mFG but modulation for face identity within this region appears to be affected by the loss of the right IOG.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".