Systematic Review of Psychiatric Adverse Effects Induced by Chloroquine and Hydroxychloroquine: Case Reports and Population Studies.

OBJECTIVE: To perform a systematic review on the psychiatric adverse effects of chloroquine (CQ) and hydroxychloroquine (HCQ); to summarize what is known about psychiatric adverse effects of these drugs; to compare clinical trials, populational studies, and case report studies; and to increase awareness of the potential psychiatric adverse effects of these drugs. DATA SOURCES: A literature search of PubMed, Scopus, and Web of Science was performed to identify manuscripts published between December 1962 and June 2022. Search terms included CQ, HCQ, psychiatry, psychosis, depression, anxiety, bipolar disorder, delirium, and psychotic disorders. STUDY SELECTION AND DATA EXTRACTION: Relevant studies included reports of adverse effects after CQ or HCQ ingestion. DATA SYNTHESIS: The current literature presents evidence for a risk of short-term psychiatric adverse effects induced by either CQ or HCQ. However, the populational-level studies presented some limitations regarding the voluntary response in survey data, self-report adverse effects, and placebo group reporting similar symptoms to the case group. Thus, populational-level studies addressing the discussed limitations and the nature and extent of possible psychiatric adverse effects are needed. RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE: Most of the patients who developed such adverse effects did not report a family history of psychiatric disease. The frequency of psychiatric adverse effects depends on the patient's biological sex, age, and body mass index, but not on the drug dosage. CONCLUSIONS: Based on clinical trials and case reports, the current literature presents evidence for a risk of short-term psychiatric adverse effects induced by either drug.

Predicting memory from study-related brain activity.

To isolate brain activity that may reflect effective cognitive processes during the study phase of a memory task, cognitive neuroscientists commonly contrast brain activity during study of later-remembered versus later-forgotten items. This "subsequent memory effect" method has been described as identifying brain activity "predictive" of memory outcome. However, the modern field of machine learning distinguishes between descriptive analysis, subject to overfitting, and true prediction, that can classify untrained data. First, we tested whether classic event-related potential signals were, in fact, predictive of later old/new recognition memory (N = 62, 225 items/participant); this produced significant but small predictive success. Next, pattern classification of the multivariate spatiotemporal features of the single-trial EEG waveform also succeeded in predicting memory. However, the prediction was still small in magnitude. In addition, topographic maps suggested individual differences in sources of predictive activity. These findings suggest that, on average, brain activity, measured by EEG, during the study phase is only marginally predictive of subsequent memory. It is possible that this predictive approach will succeed better when other experimental factors known to influence memory outcome are also integrated into the models.NEW & NOTEWORTHY For both basic and applied reasons, an important goal is to identify brain activity present while people study materials that enable us to predict whether they will remember those materials. We show that this is possible with the conventional event-related potential "subsequent-memory-effect" signals as well as with machine learning classifiers, but only to a small degree. This is in line with behavioral research, which supports many determinants of memory apart from the cognitive processes during study.

A cross-species framework for investigating perceptual evidence accumulation.

Cross-species studies are important for a comprehensive understanding of brain functions. However, direct quantitative comparison of behaviors across species presents a significant challenge. To enable such comparisons in perceptual decision-making, we developed a synchronized evidence accumulation task for rodents and humans, by aligning mechanics, stimuli, and training. Rats, mice and humans readily learned the task and exhibited qualitatively similar performance. Quantitative model comparison revealed that all three species employed an evidence accumulation strategy, but differed in speed, accuracy, and key decision parameters. Human performance prioritized accuracy, whereas rodent performance was limited by internal time-pressure. Rats optimized reward rate, while mice appeared to switch between evidence accumulation and other strategies trial-to-trial. Together, these results reveal striking similarities and species-specific priorities in decision-making. Furthermore, the synchronized behavioral framework we present may facilitate future studies involving cross-species comparisons, such as evaluating the face validity of animal models of neuropsychiatric disorders. Highlights: Development of a free response evidence accumulation task for rats and miceSynchronized video game allows direct comparisons with humansRat, mouse and human behavior are well fit by the same decision modelsModel parameters reveal species-specific priorities in accumulation strategy.

Associative recognition without hippocampal associations.

Whereas both human and animal lesion and human neuroimaging studies have implicated the hippocampus in memory for associations, some studies find preserved associative memory following hippocampal damage. Starting with a classic summed similarity model of item recognition, we can account for associative recognition without assuming a specific hippocampally-mediated associative process. We add one key assumption: that one item can influence activation of another item's features. Feature-strength patterns, evaluated for each probe item individually, are then diagnostic of whether an item was paired with one item versus another. We suggest that feature-level inference, without explicit storage of associations, may play a critical role in associative recognition tasks. (PsycInfo Database Record (c) 2023 APA, all rights reserved).