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Xue, A. M.

Publications and source records attributed to Xue, A. M..

4 recordsLinked to original sources

Hippocampal patterns and associative memory: Distinct intracranial EEG temporal encoding patterns support memory

Episodic memory depends on neural representations encoded in the hippocampus. Experimental and computational evidence suggests that the hippocampus encodes pattern-separated representations that support later recall of episodic event elements. While extant data in humans predominantly focus on assaying the relationship between the similarity of spatial neural patterns at encoding and later memory performance, similarity of neural patterns in the temporal domain may also reveal encoding computations predictive of future memory. To examine how the similarity among temporal patterns of hippocampal activity during encoding relates to later episodic retrieval (associative cued recall and recognition memory), hippocampal activity was recorded from human participants (n=7) with implanted intracranial electrodes while they encoded arbitrary (A-B) paired-associates. Subsequent memory analyses first revealed that hippocampal high-frequency broadband power (HFB; 70-180Hz) was linked to a graded increase in memory strength; HFB power was greater during the encoding of pairs later correctly recalled relative to events later recognized and was lowest for events later forgotten. Second, and critically, subsequent memory analyses further revealed that more distinctive temporal patterns in the hippocampus during encoding -- indexed by the similarity of the HFB timeseries elicited by a given event to that elicited by other events -- were associated with superior subsequent memory performance. Finally, exploratory analyses revealed stimulus category effects on hippocampal HFB power during encoding and retrieval cuing. These results indicate that the temporal distinctiveness of hippocampal traces during encoding is important for subsequent retrieval of episodic event elements, consistent with theories that posit that pattern separation facilitates future remembering.

neuroscience↗

Strong mnemonic prediction errors increase cognitive control, attention, and arousal

Ongoing experience is continuously processed in the context of past events. Divergence between current experience and memory-based predictions (i.e., a mnemonic prediction error; MPE) is theorized to be a signal that encoding, as opposed to retrieval, should be prioritized. We asked how MPEs place demands on control and attention-related processes, and whether these demands differ as a function of prediction strength. We investigated these questions across two experiments, wherein we recorded scalp electroencephalography and/or pupillometry as 101 young human adults performed an associative memory task. Strong MPEs, more so than weak MPEs, increased physiological indices of cognitive control (frontal theta), attention (posterior alpha and pupil size), and arousal (pupil size). Greater cognitive control (frontal theta) during strong MPEs promoted better learning of prediction violating (i.e., unexpected) stimuli. Collectively, these findings reveal multiple pathways through which the mind and brain respond adaptively to violations of strong mnemonic predictions.

neuroscience↗

eyeris: A flexible, extensible, and reproducible pupillometry preprocessing framework in R

Pupillometry provides a non-invasive window into the mind and brain, particularly as a psychophysiological readout of autonomic and cognitive processes like arousal, attention, stress, and emotional states. Pupillometry research lacks a robust, standardized framework for data preprocessing, whereas in functional magnetic resonance imaging and electroencephalography, researchers have converged on tools such as fMRIPrep, EEGLAB and MNE-Python. Many established pupillometry preprocessing packages and workflows fall short of serving the goal of enhancing reproducibility, especially since most existing solutions lack designs based on Findability, Accessibility, Interoperability, and Reusability (FAIR) principles. To promote FAIR and open science practices for pupillometry research, we developed eyeris, a complete pupillometry preprocessing suite designed to be intuitive, modular, performant, and extensible (https://github.com/shawntz/eyeris). Out-of-the-box, eyeris provides a recommended preprocessing workflow and considers signal processing best practices for tonic and phasic pupillometry. Moreover, eyeris further enables open and reproducible science workflows, as well as quality control workflows by following a well-established file management schema and generating interactive output reports for both record keeping/sharing and quality assurance of preprocessed pupil data prior to formal analysis. Taken together, eyeris provides a robust all-in-one transparent and adaptive solution for high-fidelity pupillometry preprocessing with the aim of further improving reproducibility in pupillometry research.

neuroscience↗

Neural Representations of Food-Related Attributes in the Human Orbitofrontal Cortex in Health and Disease

Decisions about what to eat recruit the orbitofrontal cortex (OFC) and involve the evaluation of food-related attributes, such as taste and health. These attributes are utilized differently by healthy individuals and patients with disordered eating behavior, but it is unclear whether these attributes are decodable from activity in the OFC in both groups and whether neural representations of these attributes are differentially related to decisions about food. We used fMRI combined with behavioral tasks to investigate the representation of taste and health attributes in the human OFC and the role of these representations in food choices in healthy individuals and patients with anorexia nervosa (AN). We found that subjective ratings of tastiness and healthiness could be decoded from patterns of activity in the OFC in both groups. However, health-related patterns of activity in the OFC were more related to the magnitude of choice preferences among patients with AN than healthy individuals. These findings suggest that maladaptive decision-making in AN is associated with more consideration of health information represented by the OFC during deliberation about what to eat. Significance StatementAn open question about the orbitofrontal cortex (OFC) is whether it supports the evaluation of food-related attributes during deliberation about what to eat. We found that healthiness and tastiness information were decodable from patterns of neural activity in the OFC in both patients with anorexia nervosa (AN) and healthy controls. Critically, neural representations of health were more strongly related to choices in patients with AN, suggesting that maladaptive overconsideration of healthiness during deliberation about what to eat is related to activity in the OFC. More broadly, these results show that activity in the human OFC is associated with the evaluation of relevant attributes during value-based decision-making. These findings may also guide future research into the development of treatments for AN.

neuroscience↗