Involuntary orienting to visual and auditory stimuli elicits similar biasing mechanisms in early visual cortex to facilitate target processing
Bibliographic record
Abstract
A sudden visual or acoustic change in the environment can capture attention involuntarily and facilitate perceptual processing of a subsequent visual target at the same location. The behavioral consequences of this uni- and cross-modal cueing of attention have been well documented, but the underlying neural mechanisms and how they may differ depending on the modality of the cue remain elusive. Here we use EEG to directly compare the effects of visual and auditory cues on subsequent target processing and examine neural activity elicited by the cues themselves. Participants were presented with two Gabor patches at the same time (one to the left and one to the right of fixation) and were asked to indicate the orientation of the Gabor that appeared higher in contrast (cf., Carrasco et al., 2004). Prior to the presentation of these visual targets a non-predictive visual (Exp.1) or auditory (Exp.2) cue was presented at either the left or right location. Across both experiments we found that participants judged the Gabor patch on the cued side to have higher contrast (visual: t(19)=3.76, p=0.001; auditory: t(15)=4.07, p< 0.001), consistent with previous findings. Furthermore, in both cases, these behavioral effects were accompanied by a boost in early cortical processing beginning at 100ms post target onset (visual: p=0.00001; auditory: p=0.004) On trials where no targets were presented, visual and auditory cues elicited a slow positive deflection over contralateral visual cortex between 260 to 360ms post cue onset (visual: p< 0.0001; auditory: p< 0.0002). The time course of this cue-elicited neural biasing over visual areas matches the well-established time course of the behavioral benefits of exogenous cueing of attention. Overall, these results indicate that sudden events in the environment – regardless of sensory modality – cause reflexive shifts of attention that result in similar neural modulations in visual cortex. Meeting abstract presented at VSS 2018
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".