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Core Findings With Reported Statistics

Twenty-six adults completed a two-day design alternating instrumental visual detection (Phase A) with audiovisual sound localisation (Phase B), in which target and non-target flashes flanked a brief sound at 3°, 6°, or 9° disparity. Targetward localisation bias increased linearly with disparity (F(1,25,653)=5.35, p=0.021), with model-estimated biases of 0.35°, 0.68°, and 0.81° at the three disparities — all reliably above zero after Holm correction Behavioral localisation bias results.

This bias propagated through the full decision cascade: an early target-specific saccade-rate contrast (0.131–0.328 s, cluster p<0.001), a sustained Phase B gaze displacement toward the target (0.229–1.000 s, cluster p<0.001), trajectory AUC increasing with disparity (F(1,50)=35.73, p=2.37e-7), and more target-directed than non-target-directed changes-of-mind (12.70% vs 10.32%, t(25)=4.21, p=1.42e-4) Oculomotor and trajectory evidence.

Critical Assessment

Strengths: Multi-measure convergence (reports, saccades, gaze, trajectories, CoMs), physically matched target/non-target stimuli with counterbalanced colors, participant-specific baseline corrections for motor noise, and preregistered-quality statistical control (mixed models, cluster permutation, multiple-comparison correction). The claim that gaze biases cannot explain the perceptual effect is plausible because flashes lasted only 100 ms, before saccades could alter visual input Authors note gaze did not alter input.

Weaknesses and blind spots: The behavioral disparity effect on Absolute bias is modest (p=0.021, linear F on ~25,653 trial-level observations), so it is statistically fragile relative to the trajectory effect. All participants were young healthy adults; only one learning procedure (speeded detection) and one task were tested. The neural mechanism is unmeasured — inference that learned relevance 'reweights sensory inputs' during integration is interpretive, not directly observed. Because the target side was always opposite the non-target at equal disparity, demand/expectancy cannot be fully excluded without a condition where the learned target is absent. Data are promised on the Radboud Data Repository but the DOI was not yet live at extraction, limiting independent verification. The study also tests instrumental learning only; the authors themselves note that Pavlovian reward learning may or may not produce the same reweighting Authors flag reward-learning generalization gap.

What would change the conclusion: A replication with a target-absent control condition, or failure of the bias to reproduce under equal luminance/salience controls, would undermine the learned-relevance interpretation; a direct neural measurement in multisensory cortex showing precision-like weighting modulation would strengthen it. Confidence: moderate — internally consistent multi-measure evidence, but small effect at the report level and no neural grounding yet.

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 BGPT Paper Review

Study Novelty

First direct demonstration that instrumentally learned visual relevance reweights multisensory integration, extending value-driven attention work beyond oculomotor capture to perceptual inference; conceptually fresh but adjacent to precision-weighting literature.

Scientific Quality

Rigorous multi-measure design, corrected statistics, and matched stimuli; limited by modest behavioral effect size (p=0.021), no target-absent demand control, no neural measurement, and data repository DOI not yet live.

Study Generality

Single task, single learning procedure, healthy young adults only; generality to other learning regimes, populations, and modalities remains untested by the authors' own admission.

Study Usefulness

Advances multisensory integration theory by showing learned priority acts as a weighting factor beyond precision; practical applications are indirect (attention/perception research design).

Study Reproducibility

Detailed methods, standard software pipelines, and promised Radboud Data Repository access; however, the persistent DOI was not yet public at review time.

Explanatory Depth

Provides converging behavioral/oculomotor/motor readouts spanning the inference cascade, but lacks neural-level mechanistic evidence for how learned relevance alters sensory weighting.