Long-term memory biases auditory spatial attention.
Bibliographic record
Abstract
Long-term memory (LTM) has been shown to bias attention to a previously learned visual target location. Here, we examined whether memory-predicted spatial location can facilitate the detection of a faint pure tone target embedded in real world audio clips (e.g., soundtrack of a restaurant). During an initial familiarization task, participants heard audio clips, some of which included a lateralized target (p = 50%). On each trial participants indicated whether the target was presented from the left, right, or was absent. Following a 1 hr retention interval, participants were presented with the same audio clips, which now all included a target. In Experiment 1, participants showed memory-based gains in response time and d'. Experiment 2 showed that temporal expectations modulate attention, with greater memory-guided attention effects on performance when temporal context was reinstated from learning (i.e., when timing of the target within audio clips was not changed from initially learned timing). Experiment 3 showed that while conscious recall of target locations was modulated by exposure to target-context associations during learning (i.e., better recall with higher number of learning blocks), the influence of LTM associations on spatial attention was not reduced (i.e., number of learning blocks did not affect memory-guided attention). Both Experiments 2 and 3 showed gains in performance related to target-context associations, even for associations that were not explicitly remembered. Together, these findings indicate that memory for audio clips is acquired quickly and is surprisingly robust; both implicit and explicit LTM for the location of a faint target tone modulated auditory spatial attention. (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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".