Prevalence and Correlates of Eating Disorder Symptoms in Adolescents with Bipolar I Disorder.

Objective: To investigate the prevalence and correlates of eating disorder symptoms in adolescents with bipolar I disorder (BP I). Methods: We retrospectively collected a DSM-IV-TR-based diagnostic assessment of 179 adolescents with BP I and evaluated clinical variables in those with and without eating disorder symptoms. For comparison, we retrospectively evaluated eating disorder symptoms in adolescents with generalized anxiety disorder (GAD). Results: Thirty-six percent of adolescents with BP I experienced lifetime eating disorder symptoms; among comorbid adolescents, 74% reported eating disorder cognitions and 40% reported symptoms related to bingeing, 25% purging, and 17% restricting. BP I adolescents with (vs. without) eating disorder symptoms had higher Children's Depression Rating Scale-Revised scores (40.5 vs. 34.5; p < 0.001; effect size = 0.59) and were more likely to be female (75% vs. 45%; p < 0.001; odds ratio = 3.8). There were no differences in Young Mania Rating Scale scores (p = 0.70); lifetime presence of attention-deficit/hyperactivity disorder (p = 0.86) and alcohol (p = 0.59) or substance (p = 0.89) abuse/dependence symptoms; age of BP I onset (p = 0.14); inpatient hospitalization status at baseline (p = 0.53); presence of lifetime inpatient hospitalization (p = 0.64) or suicide attempt (p = 0.35); seriousness of suicidality (p = 0.86); body mass index (p = 0.48); and second-generation antipsychotic (SGA; p = 0.32) or non-SGA mood stabilizer (p = 0.09) use. Eating disorder cognitions (rather than behaviors) were higher in the GAD group (58%) compared with the BP I group (27%; p = 0.004). Limitations: A retrospective study is subject to recall bias and limits our understanding of the temporal relationship between eating disorder and mood symptoms. Conclusions: Eating disorder symptoms are frequently comorbid in adolescents with BP I. The comorbidity is associated with more severe depression but does not confer a more severe illness course.

High-dose armodafinil in treatment-refractory bipolar depression.

BACKGROUND: Bipolar depression is a serious neuropsychiatric disorder associated with a high risk of morbidity and suicidality. Standard antidepressants approved for treating major depressive disorder fail to exert efficacy in bipolar depression. Although 5 agents have been developed for the treatment of bipolar depression, treatment resistance is still observed in some patients, and requires off-label pharmacotherapy. Modafinil and armodafinil have been reported to improve treatment-resistant bipolar depression, but with inconsistent results. METHODS: We present a case of a 65-year-old woman with severe bipolar depression who failed to respond to electroconvulsive therapy and IV ketamine but later responded to high-dose armodafanil. RESULTS: The patient responded to high-dose armodafinil (gradually titrated to 1,000 mg/d) and achieved remission with good tolerability for 5 years. Recently, she contracted COVID-19 and developed muscular weakness. After a lengthy workup, we became concerned for myopathy as an adverse effect from armodafinil. The patient's dose of armodafinil was significantly reduced and she subsequently became very depressed and functionally disabled before improving again when armodafinil 1,000 mg/d was reinstated. CONCLUSIONS: We propose that some of the negative results seen in research of armodafinil for bipolar depression may be due to the use of low doses (100 to 200 mg/d), and higher doses may be needed for adequate response in treatment-resistant bipolar depression.

Disrupted object-scene semantics boost scene recall but diminish object recall in drawings from memory.

Humans are highly sensitive to the statistical relationships between features and objects within visual scenes. Inconsistent objects within scenes (e.g., a mailbox in a bedroom) instantly jump out to us and are known to catch our attention. However, it is debated whether such semantic inconsistencies result in boosted memory for the scene, impaired memory, or have no influence on memory. Here, we examined the relationship of scene-object consistencies on memory representations measured through drawings made during recall. Participants (N = 30) were eye-tracked while studying 12 real-world scene images with an added object that was either semantically consistent or inconsistent. After a 6-minute distractor task, they drew the scenes from memory while pen movements were tracked electronically. Online scorers (N = 1,725) rated each drawing for diagnosticity, object detail, spatial detail, and memory errors. Inconsistent scenes were recalled more frequently, but contained less object detail. Further, inconsistent objects elicited more errors reflecting looser memory binding (e.g., migration across images). These results point to a dual effect in memory of boosted global (scene) but diminished local (object) information. Finally, we observed that participants fixate longest on inconsistent objects, but these fixations during study were not correlated with recall performance, time, or drawing order. In sum, these results show a nuanced effect of scene inconsistencies on memory detail during recall.

THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images.

In recent years, the use of a large number of object concepts and naturalistic object images has been growing strongly in cognitive neuroscience research. Classical databases of object concepts are based mostly on a manually curated set of concepts. Further, databases of naturalistic object images typically consist of single images of objects cropped from their background, or a large number of naturalistic images of varying quality, requiring elaborate manual image curation. Here we provide a set of 1,854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language. Using these object concepts, we conducted a large-scale web image search to compile a database of 26,107 high-quality naturalistic images of those objects, with 12 or more object images per concept and all images cropped to square size. Using crowdsourcing, we provide higher-level category membership for the 27 most common categories and validate them by relating them to representations in a semantic embedding derived from large text corpora. Finally, by feeding images through a deep convolutional neural network, we demonstrate that they exhibit high selectivity for different object concepts, while at the same time preserving variability of different object images within each concept. Together, the THINGS database provides a rich resource of object concepts and object images and offers a tool for both systematic and large-scale naturalistic research in the fields of psychology, neuroscience, and computer science.