Biology subjects

Brady, T. F.

Publications and source records attributed to Brady, T. F..

6 recordsLinked to original sources

bioRxiv2025

Real-world objects scaffold visual working memory for features: Increased neural delay activity when colors are remembered as part of meaningful objects

Visual working memory is a core cognitive function that allows active storage of task-relevant visual information. Contrary to the common assumption that the capacity of this system is fixed with respect to a single feature dimension, recent research has shown that working memory performance for a simple visual feature - color - is improved when this feature is encoded as part of a real-world object relative to an unrecognizable scrambled object. Using EEG (N = 24), we here demonstrate that this performance benefit is supported by increased neural engagement during the retention period, as indexed by enlarged contralateral-delay-activity during maintenance. Furthermore, the pattern of neural activity across parietal-occipital electrodes was more stable across time, suggesting that real-world objects may support more robust memory representations. Finally, we report a novel fronto-central event-related potential that distinguishes between real-world objects and scrambled objects during encoding and maintenance processes. Overall, our results demonstrate that active visual working memory capacity for simple features is not fixed but can expand depending on what context these features are encoded in.

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bioRxiv2024

A 2D Gabor-wavelet baseline model out-performs a 3D surface model in scene-responsive cortex

Understanding 3D representations of spatial information, particularly in naturalistic scenes, remains a significant challenge in vision science. This is largely because of conceptual difficulties in disentangling higher-level 3D information from co-occurring features and cues (e.g., the 3D shape of a scene image is necessarily defined by "low-level" spatial frequency and orientation information). Recent work has employed newer models and analysis techniques that attempt to mitigate these difficulties within a model-comparison framework. For example, one such study reported 3D-surface features were uniquely present in areas OPA, PPA, and MPA/RSC (areas typically referred to as scene-selective), above and beyond a Gabor-wavelet baseline model. Here, we tested whether these findings generalized to a new stimulus set that, on average, dissociated static Gabor-wavelet baseline features from 3D scene-surface features. Surprisingly, we found evidence that a Gabor-wavelet baseline model--commonly thought of as a "low-level" or "2D" model--better fit voxel responses in areas OPA, PPA and MPA/RSC compared to a model with 3D-surface information. We highlight that this difference in results could be due to differences in the baseline conditions used across studies. These findings emphasize that much of the information in "scene-selective" regions--potentially even information about 3D surfaces--may be in the form of spatial frequency and orientation information often considered 2D or low-level. Disentangling lower-level and higher-level visual information is a continuing fundamental challenge for model-comparison approaches in visual cognition, and it motivates future work investigating which visual features could cue higher-level properties in our real-world visual experience--both within and beyond current model comparison frameworks. Author summaryTo gain a more complete picture of human visual processing, it is critical to understand the precise format of representations of naturalistic visual scenes. Recent work has approached this challenge by quantifying how much of our brain activity might be due to hypothesized characteristics of the stimuli being viewed. Here, we followed up on work finding that activity in scene-responsive regions of the brain is well predicted by information about the 3D configurations of major surfaces in viewed scenes, like walls and floors. In contrast to previous work, we found that our baseline condition--commonly thought of as "low-level" visual information--accounted for responses in these regions better than both of the 3D surface models that we tested. We highlight that this difference in results could be due to differences in the baseline conditions used across studies. However, our findings do not necessarily argue against the importance of these regions in encoding 3D surface information. Instead, they highlight the possibility that baseline models can perform well by virtue of covariation between low-level features like orientation and spatial frequency with higher-level properties like depth information. This motivates future work and/or new analysis frameworks to better characterize the interplay between hypothesized model features and the specific techniques used to quantify their relationship to neural representations.

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bioRxiv2020

Using a betting game to reveal the rich nature of visual working memories

When we ask people to hold a color in working memory, what do they store? Do they remember colors as point estimates (e.g. a particular shade of red) or are memory representations richer, such as uncertainty distributions over feature space? We developed a novel paradigm (a betting game) to measure the nature of working memory representations. Participants were shown a set of colored circles and, after a brief memory delay, asked about one of the objects. Rather than reporting a single color, participants placed multiple bets to create distributions in color space. The dispersion of bets was correlated with performance, indicating that participants internal uncertainty guided bet placement. Furthermore, relative to the first response, memory performance improved when averaging across multiple bets, showing that memories contain more information than can be conveyed in a single response. Finally, information about the item in memory was present in subsequent responses even when the first response would generally be classified as a guess or report of an incorrect item, suggesting that such failures are not all-or-none. Thus, memory representations are more than noisy point estimates; they are surprisingly rich and probabilistic.

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bioRxiv2018

Episodic Memory Can Replace Active Storage in Visual Working Memory

Humans have remarkable visual long-term memory abilities, capable of storing thousands of objects with significant detail. However, it remains unknown how such memory is utilized during the short-term maintenance of information. Specifically, if people have a previously encoded memory for an item, how does this affect subsequent working memory for that same item? Here, we demonstrate people can quickly and accurately make use of visual long-term memories and therefore maintain less perceptual information actively in working memory. We assessed how much perceptual information is actively maintained in working memory by measuring neural activity during the delay period of a working memory task using electroencephalography. We find that despite maintaining less perceptual information in working memory when long-term memory representations are available, there is no decrement in memory performance. This suggests under certain circumstances people can dynamically disengage working memory maintenance and instead use long-term memories when available. However, this does not mean participants always utilize long-term memory. In a follow-up experiment, we introduced additional perceptual interference into working memory and found participants actively maintained items in working memory even when they had existing long-term memories available. These results clarify the kinds of conditions under which long-term and working memory operate. Specifically, working memory is engaged when new information is encountered or perceptual interference is high. Visual long-term memory may otherwise be rapidly accessed and utilized in lieu of active perceptual maintenance. These data demonstrate the interactions between working memory and long-term memory are more dynamic and fluid than previously thought.

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bioRxiv2018

The role of meaning in visual memory: Face-selective brain activity predicts memory for ambiguous face stimuli

How people process images is known to affect memory for those images, but these effects have typically been studied using explicit task instructions to vary encoding. Here, we investigate the effects of intrinsic variation in processing on subsequent memory, testing whether recognizing an ambiguous stimulus as meaningful (as a face vs. as shape blobs) predicts subsequent visual memory even when matching the perceptual features and the encoding strategy between subsequently remembered and subsequently forgotten items. We show that single trial EEG activity can predict whether participants will subsequently remember an ambiguous Mooney face image (e.g., an image that will sometimes be seen as a face and sometimes not be seen as a face). In addition, we show that a classifier trained only to discriminate between whether participants perceive a face vs. non-face can generalize to predict whether an ambiguous image is subsequently remembered. Furthermore, when we examine the N170, an ERP index of face processing, we find that images that elicit larger N170s are more likely to be remembered than those that elicit smaller N170s, even when the exact same image elicited larger or smaller N170s across participants. Thus, images processed as meaningful - in this case as a face-during encoding are better remembered than identical images that are not processed as a face. This provides strong evidence that understanding the meaning of a stimulus during encoding plays a critical role in visual memory.\n\nSignificance StatementIs visual memory inherently visual or does meaning and other conceptual information necessarily play a role even in memory for detailed visual information? Here we show that its easier to remember an image when its processed in a meaningful way -- as indexed by the amount of category-specific brain activity it elicits. In particular, we use single-trial EEG activity to predict whether an image will be subsequently remembered, and show that the main driver of this prediction ability is whether or not an image is seen as meaningful or non-meaningful. This shows that the extent to which an image is processed as meaningful can be used to predict subsequent memory even when controlling for perceptual factors and encoding strategies that typically differ across images.

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bioRxiv2018

Psychological Scaling Reveals a Single Parameter Framework For Visual Working Memory

Almost all models of visual memory implicitly assume that errors in mnemonic representations are linearly related to distance in stimulus space. Here, we show that neither memory nor perception are appropriately scaled in stimulus space; instead, they are based on a transformed similarity representation that is non-linearly related to stimulus space. This result calls into question a foundational assumption of extant models of visual working memory. Once psychophysical similarity is taken into account, aspects of memory that have been thought to demonstrate a fixed working memory capacity of ~3-4 items and to require fundamentally different representations -- across different stimuli, tasks, and types of memory -- can be parsimoniously explained with a unitary signal detection framework. These results have significant implications for the study of visual memory and lead to a substantial reinterpretation of the relationship between perception, working memory and long-term memory.

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