In the search for brain markers of optimal attentional focus, the mainstream approach has been to first define attentional states based on behavioral performance, and to subsequently investigate "neural correlates" associated with these performance variations. However, this approach constrains the range of contexts in which attentional states can be operationalized by relying on overt behavior, and assumes a one-to-one correspondence between behavior and brain state. Here, we reversed the logic of these previous studies and sought to identify behaviorally-relevant brain states based solely on brain activity, agnostic to behavioral performance. In four independent datasets, we found that the same two brain states were dominant during a sustained attention task. One state was behaviorally optimal, with higher accuracy and stability, but a greater tendency to mind wander (State1). The second state was behaviorally suboptimal, with lower accuracy and instability (State2). We further demonstrate how these brain states were impacted by motivation and attention-deficit/hyperactivity disorder (ADHD). Individuals with ADHD spent more time in suboptimal State2 and less time in optimal State1 than healthy controls. Motivation overcame the suboptimal behavior associated with State2. Our study provides compelling evidence for the existence of two attentional states from the sole viewpoint of brain activity.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.neuroimage.2021.118072 | DOI Listing |
Int J Med Inform
January 2025
Department of Computer Science and Artificial Intelligence, University of Udine, 33100, Italy.
Background: Segmentation models for clinical data experience severe performance degradation when trained on a single client from one domain and distributed to other clients from different domain. Federated Learning (FL) provides a solution by enabling multi-party collaborative learning without compromising the confidentiality of clients' private data.
Methods: In this paper, we propose a cross-domain FL method for Weakly Supervised Semantic Segmentation (FL-W3S) of white blood cells in microscopic images.
Medicine (Baltimore)
January 2025
Department of Gastroenterology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China.
Inflammatory bowel disease is a chronic inflammatory condition predominantly affecting the intestines, encompassing both ulcerative colitis and Crohn disease (CD). As one of the most common gastrointestinal disorders, CD's pathogenesis is closely linked with the intestinal microbiota. Recently, fecal microbiota transplantation (FMT) has gained attention as a potential treatment for CD, with the effective reestablishment of intestinal microecology considered a crucial mechanism of FMT therapy.
View Article and Find Full Text PDFPLoS One
January 2025
School of Behavioral Sciences, The Academic College of Tel Aviv-Yafo, Tel Aviv, Israel.
Background: Occupational burnout, resulting from long-term exposure to work-related stressors, is a significant risk factor for both physical and mental health of employees. Most research on burnout focuses on routine situations, with less attention given to its causes and manifestations during prolonged national crises such as war. According to the Conservation of Resources theory, wartime conditions are associated with a loss of resources, leading to accelerated burnout.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Psychology, University of Surrey, Guildford, United Kingdom.
Background: Atypical interoception has been observed across multiple mental health conditions, including anxiety disorders and depression. Evidence suggests that not only pathological anxiety, but also heightened levels of state anxiety and stress are associated with interoceptive functioning. This study aimed to investigate the effects of the recent Coronavirus SARS-CoV-2 pandemic on self-reported interoception and mental health, and their relationship.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon.
In human activity-recognition scenarios, including head and entire body pose and orientations, recognizing the pose and direction of a pedestrian is considered a complex problem. A person may be traveling in one sideway while focusing his attention on another side. It is occasionally desirable to analyze such orientation estimates using computer-vision tools for automated analysis of pedestrian behavior and intention.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!