Shared neurophysiological resources between exogenous and endogenous visuospatial attentional processes
Bibliographic record
Abstract
Abstract Prevailing accounts of visuospatial attention differentiate exogenous (involuntary shifts) from endogenous (voluntary control) orienting of attention. While these two forms of attentional processes are functionally separable, their interactions have been at the center of ongoing debates for more than two decades. One hypothesis is that exogenous and endogenous attention interfere because they share processing resources. Here, we confirm that endogenous attention alters exogenous attention processing, and examine the role of alpha-band neurophysiological activity in such interference events. We contrast the effects of exogenous attention across two experimental conditions: a single-cueing condition where exogenous attention is engaged alone, and a double-cueing condition where exogenous attention is concurrently engaged with endogenous attention. Our results show that the engagement of endogenous attention alters the emergence of exogenous attention across cue-related and target-related brain processes. Importantly, we also report that classifiers trained to decode exogenous attention from the power and phase of alpha-band brain activity in the single-cueing condition fail to do so in the doublecueing condition, where endogenous attention is also engaged. Taken together, our observations challenge the idea that exogenous attention operates independently from top-down processes and demonstrate that both forms of attention orienting engage shared brain processes, which constrain their interactions. Significance Statement Visuospatial attention is often dichotomized into top-down and bottom-up components: Top-down attention reflects slow voluntary shifts of attention orienting, while bottom-up attention is recruited by emerging demands from the environment. A large body of previous findings support the view that these two forms of attention orienting are functionally separable, with some interactions. The current study examines such interactions between top-down and bottom-up attention. Using electroencephalography (EEG) and multivariate pattern classification techniques, the researchers show that top-down attention interferes with the brain activity patterns of bottom-up attention. Moreover, machine learning classifiers trained to detect bottom-up attention based on brain activity in the alpha band (8-12 Hz), a marker of visuospatial attention, fail systematically when top-down attention is also engaged. The authors therefore conclude that both forms of visuospatial orienting are supported by overlapping processes that share brain resources.
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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 | 0.003 |
| 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 | 0.001 |
| 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".