Rapid object recognition in the absence of conscious awareness
Bibliographic record
Abstract
The visual system has a remarkable capability to extract categorical information from complex natural scenes (Thorpe, Fize et al. 1996). To investigate whether rapid object recognition is limited to conscious perception, we recorded event-related potentials (ERPs) on both conscious and unconscious conditions. A continuous flash suppression (CFS) paradigm was used to ensure the target image was suppressed during the experiment (Tsuchiya and Koch 2005), in which the target was displayed in one eye to compete against flashed masks presented to the other eye. We equated the luminance and contrast of the images by using the SHINE toolbox to minimize potential low-level confounds in our study (Willenbockel, Sadr et al. 2010). In experiment 1, the duration of suppression was measured during CFS. We found animal images to be perceived earlier than non-animal under identical suppression masking (1666ms vs. 1728ms). This suggests a privileged processing of animal images exists even during suppression. In experiment 2, image contrast was adaptively controlled to ensure 50% of the images were seen during CFS. Subjects were to decide/guess the presence of an animal in the shown images. Accuracy was 77% vs. 49% for "seen" and "unseen", confirming subjects were truly unaware of "unseen" images. ERP results showed animal images induced bigger amplitude (150ms-350ms) than non-animal images on "seen" condition, but smaller amplitude than non-animal images on "unseen" condition (p(animal×seen) =0.034). The amplitude of animal images was significantly different between seen and unseen condition (p=0.011), but not for the non-animal images. The trial-by-trial correlation between seen/unseen condition and EEG amplitude for both animal and non-animal images is significant before 380ms (p<0.05). Our results indicate the brain has different responses on animal and distractor (non-animal) images even in unawareness, and the rapid processing of animal images might be different in conscious and unconscious conditions. Meeting abstract presented at VSS 2013
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 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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".