Biology subjects

Fougnie, D.

Publications and source records attributed to Fougnie, D..

6 recordsLinked to original sources

bioRxiv2026

Episodic memory rescues working memory via pattern separation, pattern completion, and predictive recall

Working memory is capacity-limited, but interactions with episodic memory may offset this constraint. We tested moment-by-moment contributions of episodic representations to working memory by combining the N-back and Mnemonic Similarity tasks. Thirty-one participants, undergoing eye-tracking, first encoded items in a one-back task, classifying them as "same" or "similar" to their predecessor. In a subsequent two-back task, mnemonic discrimination showed a graded, item-specific benefit of prior experience: performance was best for previously compared items, whereas recognition of identical repeats was unaffected. Successful discrimination of previously compared items was accompanied by greater pupil dilation, gradually emerging gaze patterns resembling those elicited by their similar pair-mate, and higher gaze-similarity between one-back and two-back target viewing. Diverging gaze patterns between pair-mates during one-back further predicted two-back discrimination. These findings challenge working memory's characterization as an isolated system, demonstrating how it recruits episodic computations - encoding distinct traces, predicting upcoming content, and reinstating it at retrieval.

neuroscience↗

bioRxiv2025

Probabilistic working memory representations in human cortex guide behavior

Models of working memory make fundamentally different commitments to the architecture of individual memories. Information-sparse models conceptualize individual memories single point estimates agnostic to meta-cognitive variables such a uncertainty. In contrast, information-rich models propose memories re encoded s probability distributions over feature space that embed memory uncertainty in the shape of the distribution To distinguish these accounts, constructed probability distributions of memory from participants iterative reports of motion direction each trial. Remarkably, the idiosyncratic shape of these distributions (e.g., asymmetry) single trials matched the shape of neural probability distributions decoded from fMRI patterns measured from occipital and parietal cortex. Consistent with information-rich models, the neural representation of n individual memory encodes mor than the memorized feature; its variance (i.e., width and asymmetry) encodes idiosyncrasies whose read-out predicts memory behavior.

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bioRxiv2022

Common neural mechanisms control attention and working memory

Although previous studies point to qualitative similarities between working memory (WM) and attention, the degree to which these two constructs rely on shared neural mechanisms remains unknown. Focusing on one such potentially shared mechanism, we tested the hypothesis that selecting an item within WM utilizes similar neural mechanisms as selecting a visible item via a shift of attention. We used fMRI and machine learning to decode both the selection among items visually available and the selection among items stored in WM in human subjects (both sexes). Patterns of activity in visual, parietal, and to a lesser extent frontal cortex predicted the locations of the selected items. Critically, these patterns were strikingly interchangeable; classifiers trained on data during attentional selection predicted selection from WM, and classifiers trained on data during selection from memory predicted attentional selection. Using models of voxel receptive fields, we visualized topographic population activity that revealed gain enhancements at the locations of the externally and internally selected items. Our results suggest that selecting among perceived items and selecting among items in WM share a common mechanism. This common mechanism, analogous to a shift of spatial attention, controls the relative gains of neural populations that encode behaviorally relevant information. Significance statementHow we allocate our attention to external stimuli that we see and to internal representations of stimuli stored in memory might rely on a common mechanism. Supporting this hypothesis, we demonstrated that not only could patterns of human brain activity predict which items were selected during perception and memory, but that these patterns were interchangeable during external and internal selection. Additionally, this generalized selection mechanism operates by changes in the gains of the neural populations both encoding attended sensory representations and storing relevant memory representations.

neuroscience↗

bioRxiv2022

Perception is Rich and Probabilistic

When we see a stimulus, e.g. a star-shaped object, our intuition is that we should perceive a single, coherent percept (even if it is inaccurate). But the neural processes that support perception are complex and probabilistic. Simple lines cause orientation-selective neurons across a population to fire in a probabilistic-like manner. Does probabilistic neural firing lead to non-probabilistic perception, or are the representations behind perception richer and more complex than intuition would suggest? To test this, we briefly presented a complex shape and had participants report the correct shape from a set of options. Rather than reporting a single value, we used a paradigm designed to encourage to directly report a representation over shape space--participants placed a series of Gaussian bets. We found that participants could report more than point-estimates of shape. The spread of responses was correlated with accuracy, suggesting that participants can convey a notion of relative imprecision. Critically, as participants placed more bets, the mean of responses show increased precision. The later bets were systematically biased towards the target rather than haphazardly placed around bet 1. These findings strongly indicate that participants were aware of more than just a point-estimate; Perceptual representations are rich and likely probabilistic.

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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.

neuroscience↗

bioRxiv2018

Humans incorporate trial-to-trial working memory uncertainty into rewarded decisions

In daily life, working memory plays an important role in action planning and decision-making. However, both the informational content of memory and how that information is used in decisions is poorly understood. To investigate this, we conducted a memory experiment where people not only reported an estimate of a remembered stimulus, but also made a rewarded decision designed to reflect memory uncertainty. Reported memory uncertainty is correlated with estimation error, showing people incorporate their trial-to-trial memory quality into rewarded decisions. Moreover, memory uncertainty can be combined with other sources of information; after we induced prior beliefs about stimuli probabilities, we found that estimates shifted towards more frequent colors, with the shift increasing with reported uncertainty. The data is best predicted by models where people incorporate their trial-to-trial memory uncertainty with potential rewards and prior beliefs, highlighting the importance of studying working memory as a process integrated with decision-making.

neuroscience↗