Biology subjects

Vickery, T. J.

Publications and source records attributed to Vickery, T. J..

4 recordsLinked to original sources

bioRxiv2025

Neural correlates of boundary extension during visual imagination

People typically remember seeing a greater expanse of a scene than was visible in a studied close-up (boundary extension, BE). Multivoxel pattern analysis was used to test the neural correlates of BE. Classifiers were trained using a whole-brain searchlight method to discriminate between close-up and wider-angle versions of 16 scenes during repeated perceptual exposures. Earlier, each subject studied either the close or wide version of each scene and then visually imagined it from memory. If a brain region reflects BE, then unlike classification during perception, visual images of close views should sometimes be misclassified as wide (capturing false memory beyond the view), whereas visual images of wide views should be correctly classified. BE-consistent patterns during imagery were found in high-level visual regions, including posterior superior parietal cortex. This pattern did not reflect a brain-wide bias toward better classification of wider-angle views: the pattern reversed (better classification of close views) in the early visual cortex, presenting a novel distinction between early and late visual representations in imagery. We propose that this method reflects active maintenance of boundary-extended scene representations in memory and that it holds promise as a general purpose tool for decoding false memory in the brain.

neuroscience↗

bioRxiv2020

Reward impacts visual statistical learning

Humans automatically detect and remember regularities in the visual environment--a type of learning termed visual statistical learning (VSL). Many aspects of learning from reward resemble statistical learning in respects, yet whether and how reward learning impacts VSL is largely unexamined. In two studies, we found that reward contingencies affect VSL, with high-value associated with stronger behavioral and neural signatures of such learning than low-value images. In Experiment 1, participants learned values (high or low) of images through a trial-and-error risky choice task. Unbeknownst to them, images were paired as four types--High-High, High-Low, Low-High, and Low-Low. In subsequent recognition and reward memory tests, participants chose the more familiar of two pairs (a target and a foil) and recalled the value of images. We found better recognition when the first images of pairs have high-values, with High-High pairs showing the highest recognition rate. In Experiment 2, we provided evidence that brain responses were affected by both value and statistical contingencies. When we compared responses between the high-value first image and the low-value first image, greater activation in regions that included inferior frontal gyrus, anterior cingulate gyrus, hippocampus, among other regions were found. These findings were driven by the interaction between statistically structured information and reward--the same value contrast yielded no regions for second-image contrasts and for singletons. Our results suggested that the powerful allocation of attention in response to the high-value first image potentially enables better memory for statistically learned pairs and reward information than low-value first image.

neuroscience↗

bioRxiv2018

Not-so-working memory: Drift in fMRI pattern representations during maintenance predicts errors in a visual working memory task

Working memory (WM) is critical to many aspects of cognition, but it frequently fails. Much WM research has focused on capacity limits, but even for single, simple features, the fidelity of individual representations is limited. Why is this? We used fMRI and a pattern-based index of \"representational drift\" to investigate how ongoing changes in brain activity patterns throughout the WM maintenance period predicted performance, using a delayed-match-to-sample task for a single item with a single critical feature: orientation. In trials where the target and probe stimuli matched, participants incorrectly reported more non-matches when their activity patterns drifted away from the target. In trials where the target and probe did not match, participants incorrectly reported more matches when their activity patterns drifted towards the probe. Our results suggest that WM errors are not simply due to unstructured noise, but also drift within representation space that can be indexed by neuroimaging.

neuroscience↗

bioRxiv2018

Oculomotor capture reveals trial-by-trial neural correlates of attentional guidance by contents of visual working memory

Evidence from attentional and oculomotor capture, contingent capture, and other paradigms suggests that mechanisms supporting human visual working memory (VWM) and visual attention are intertwined. Features held in VWM bias guidance toward matching items even when those features are task irrelevant. However, the neural basis of this interaction is underspecified. Prior examinations using fMRI have primarily relied on coarse comparisons across experimental conditions that produce varying amounts of capture. To examine the neural dynamics of attentional capture on a trial-by-trial basis, we applied an oculomotor paradigm that produced discrete measures of capture. On each trial, subjects were shown a memory item, followed by a blank retention interval, then a saccade target that appeared to the left or right. On some trials, an irrelevant distractor appeared above or below fixation. Once the saccade target was fixated, subjects completed a forced-choice memory test. Critically, either the target or distractor could match the feature held in VWM. Although task irrelevant, this manipulation produced differences in behavior: participants were more likely to saccade first to an irrelevant VWM-matching distractor compared with a non-matching distractor - providing a discrete measure of capture. We replicated this finding while recording eye movements and scanning participants brains using fMRI. To examine the neural basis of oculomotor capture, we separately modeled the retention interval for capture and non-capture trials within the distractor-match condition. We found that frontal activity, including anterior cingulate cortex and superior frontal gyrus regions, differentially predicted subsequent oculomotor capture by a memory-matching distractor. Other regions previously implicated as involved in attentional capture by VWM-matching items showed no differential activity across capture and no-capture trials, even at a liberal threshold. Our findings demonstrate the power of trial-by-trial analyses of oculomotor capture as a means to examine the underlying relationship between VWM and attentional guidance systems.

neuroscience↗