Despite the critical role of self-disturbance in psychiatric diagnosis and treatment, its diverse behavioral manifestations remain poorly understood. This investigation aimed to elucidate unique patterns of self-referential processing in affective disorders and first-episode schizophrenia. A total of 156 participants (41 first-episode schizophrenia [SZ], 33 bipolar disorder [BD], 44 major depressive disorder [MDD], and 38 healthy controls [HC]) engaged in a self-referential effect (SRE) task, assessing trait adjectives for self-descriptiveness, applicability to mother, or others, followed by an unexpected recognition test. All groups displayed preferential self- and mother-referential processing with no significant differences in recognition scores. However, MDD patients showed significantly enhanced self-referential recognition scores and increased bias compared to HC, first-episode SZ, and BD. The present study provides empirical evidence for increased self-focus in MDD and demonstrates that first-episode SZ and BD patients maintain intact self-referential processing abilities. These findings refine our understanding of self-referential processing impairments across psychiatric conditions, suggesting that it could serve as a supplementary measure for assessing treatment response in first-episode SZ and potentially function as a discriminative diagnostic criterion between MDD and BD.
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http://dx.doi.org/10.1038/s41598-024-60498-5 | DOI Listing |
Nat Rev Neurosci
January 2025
Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
The brain is always intrinsically active, using energy at high rates while cycling through global functional modes. Awake brain modes are tied to corresponding behavioural states. During goal-directed behaviour, the brain enters an action-mode of function.
View Article and Find Full Text PDFConscious Cogn
December 2024
Faculty of Human-Environment Studies, Kyushu University, Fukuoka, Japan.
The aim of the current study was to investigate visual scan patterns for the self-face in infants with the ability to recognize themselves with a photograph. 24-month-old infants (N = 32) were presented with faces including the self-face in the upright or inverted orientation. We also measured infants' ability to recognize oneself in a mirror and with a photograph.
View Article and Find Full Text PDFMajor Depressive Disorder (MDD) poses a significant public health challenge due to its high prevalence and the substantial burden it places on individuals and healthcare systems. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) shows promise as a treatment for this disorder, although its mechanisms of action remain unclear. This study investigated whole-brain response patterns during rtfMRI-NF training to explain interindividual variability in clinical efficacy in MDD.
View Article and Find Full Text PDFBiol Psychiatry Cogn Neurosci Neuroimaging
December 2024
University of Arizona, SEMA Lab, Center for Consciousness Studies, Tuscon, AZ; Sanmai Technologies, PBC, Sunnyvale, CA.
Mindfulness has gained widespread recognition for its benefits to mental health, cognitive performance, and wellbeing. However, the multifaceted nature of mindfulness, encompassing elements like attentional focus, emotional regulation, and present-moment awareness, complicates its definition and measurement. A key component that may underlie its broad benefits is equanimity - the ability to maintain an open and non-reactive attitude toward all sensory experiences.
View Article and Find Full Text PDFBehav Res Methods
December 2024
CAP Team, Centre de Recherche en Neurosciences de Lyon - INSERM U1028 - CNRS UMR 5292 - UCBL - UJM, 95 Boulevard Pinel, 69675, Bron, France.
Artificial intelligence techniques offer promising avenues for exploring human body features from videos, yet no freely accessible tool has reliably provided holistic and fine-grained behavioral analyses to date. To address this, we developed a machine learning tool based on a two-level approach: a first lower-level processing using computer vision for extracting fine-grained and comprehensive behavioral features such as skeleton or facial points, gaze, and action units; a second level of machine learning classification coupled with explainability providing modularity, to determine which behavioral features are triggered by specific environments. To validate our tool, we filmed 16 participants across six conditions, varying according to the presence of a person ("Pers"), a sound ("Snd"), or silence ("Rest"), and according to emotional levels using self-referential ("Self") and control ("Ctrl") stimuli.
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