Anderson, B. A. | Search bioRxiv

bioRxiv2024

Reliably Measuring Learning-Dependent Distractor Suppression with Eye Tracking

In the field of psychological science, behavioral performance in computer-based cognitive tasks often exhibits poor reliability. The absence of reliable measures of cognitive processes contributes to non-reproducibility in the field and impedes investigation of individual differences. Specifically in visual search paradigms, response time-based measures have shown poor test-retest reliability and internal consistency across attention capture and distractor suppression, but one study has demonstrated the potential for oculomotor measures to exhibit superior reliability. Therefore, in this study, we investigated three datasets to compare the reliability of learning-dependent distractor suppression measured via distractor fixations (oculomotor capture) and latency to fixate the target (fixation times). Our findings reveal superior split-half reliability of oculomotor capture compared to that of fixation times regardless of the critical distractor comparison, with the reliability of oculomotor capture in most cases falling within the range that is acceptable for the investigation of individual differences. We additionally find that older adults have superior oculomotor reliability compared with young adults, potentially addressing a significant limitation in the aging literature of high variability in response time measures due to slower responses. Our findings highlight the utility of measuring eye movements in the pursuit of reliable indicators of distractor processing and the need to further test and develop additional measures in other sensory domains to maximize statistical power, reliability, and reproducibility.

neuroscience↗

bioRxiv2021

Neural Correlates of Value-Driven Spatial Attention

Reward learning has been shown to habitually guide spatial attention to regions of a scene. However, the neural mechanisms that support this bias in spatial orienting are unknown. In the present study, participants learned to orient to a particular quadrant of a scene (high-value quadrant) to maximize monetary gains. This learning was scene-specific, with the high-value quadrant varying across different scenes. During a subsequent test phase, participants were faster at identifying a target if it appeared in the high-value quadrant (valid), and initial saccades were more likely to be made to the high-value quadrant. fMRI analyses during the test phase revealed learning-dependent priority signals in the bilateral caudate tail and superior colliculus, frontal eye field, substantia nigra, and insula, paralleling findings concerning feature-based value-driven attention. In addition, ventral regions typically associated with scene selective and spatial information processing, including the hippocampus, parahippocampal gyrus, and temporo-occipital cortex, were also implicated. Taken together, our findings offer new insights into the neural architecture subserving value-driven attention, both extending our understanding of nodes in the attention network previously implicated in feature-based value-driven attention and identifying a ventral network of brain regions implicated in rewards influence on scene-dependent spatial orienting.

neuroscience↗