Facial Recognition and Visual Processing as We Age: Using the Thatcher Illusion with Famous and Non-Famous Faces
Bibliographic record
Abstract
This paper reports a study examining preferred visual processes in recognition of facial features in older vs younger age groups, using Thatcherised images of famous and non-famous people in the one study. The aims were to determine whether decline in visual system processing occurs increasingly as we grow older, and whether there is less decline in recognition of famous (or familiar) faces. Three groups (younger, middle-old and older) made up the sample of 73 people (aged 19-82 years). Visual decline in face recognition across the age groups was assessed based on the Thatcher illusion—using four famous and four non-famous faces either with normal features or with distorted features. The faces were presented one at a time on computer screen, and participants were asked to judge whether the face was distorted (eyes and/or mouth not aligned in relation to the face); in addition, time taken to decision (latency) was also measured. Decline was found in visual processing such that older individuals gave limited attention to facial details (processing faces holistically, with detail errors) and they took longer to decide. Whether the faces were famous or not did not have significant effects on the decisions and there was no interaction with age, though famous faces were given longer attention. Our visual system processes decline as we age in that we give less attention to details and more to holistic processing and so make more errors in recognition. Implications for treatment or amelioration of the effects are discussed.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".