AIMC Topic: Bipolar Disorder

Clear Filters Showing 11 to 20 of 116 articles

Early warning signals of bipolar relapse: Investigating critical slowing down in smartphone data.

Journal of affective disorders
BACKGROUND: Early warning signals (EWS) based on dynamical systems theory, such as increased autocorrelation (AR) and variance, may indicate impending mood episodes in bipolar disorder (BD). This study examines whether smartphone-based digital phenot...

Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.

Translational psychiatry
Psychosis poses substantial social and healthcare burdens. The analysis of speech is a promising approach for the diagnosis and monitoring of psychosis, capturing symptoms like thought disorder and flattened affect. Recent advancements in Natural Lan...

Different prefrontal cortex activity patterns in bipolar and unipolar depression during verbal fluency tasks based on functional near infrared spectroscopy study.

Scientific reports
This study aimed to investigate the functionality of the prefrontal cortex in patients with unipolar depression (UD) and bipolar depression (BD) using functional near-infrared spectroscopy (fNIRS) during a verbal fluency task (VFT). Additionally, it ...

Kcc-ReHo and Cohe-ReHo in bipolar disorder: their associated genes and potential for diagnosis and treatment prediction.

Neuropharmacology
The neural mechanisms underlying resting-state cerebral functional activity in bipolar disorder (BD) and the effects of pharmacotherapy on it remain unclear. This study investigated changes in local brain activity in BD patients (BDPs) following trea...

Covarying gray and white matter networks characterize schizophrenia and bipolar disorders on a continuum: A data fusion machine learning approach and a brain network analysis.

Journal of affective disorders
Schizophrenia (SZ) and Bipolar disorder (BD) share genetic and cerebral abnormalities, supporting an expanded continuum hypothesis. In this paper, we aim to better characterize differences and commonalities of gray and white matter features between S...

A multicentric study examining a deep-learning-based computer model for classifying bipolar disorder using retinal vascular images.

Journal of affective disorders
OBJECTIVES: Due to easy accessibility, the retina is considered a window to the brain. Recent studies have reported retinal vascular abnormalities in bipolar disorder. Deep learning analysis, an advanced computational approach, has been implemented i...

Differences in resting-state functional connectivity between depressed bipolar and major depressive disorder patients: A machine learning study.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Nearly 60 % of individuals with bipolar disorder (BD) are initially classified as major depressive disorder (MDD) patients, resulting in inappropriate drug treatment. Identifying reliable biomarkers for the differential diagnosis between MDD and BD p...

Multivariate brain morphological patterns across mood disorders: key roles of frontotemporal and cerebellar areas.

BMJ mental health
BACKGROUND: Differentiating major depressive disorder (MDD) from bipolar disorder (BD) remains a significant clinical challenge, as both disorders exhibit overlapping symptoms but require distinct treatment approaches. Advances in voxel-based morphom...

Machine learning for classification of pediatric bipolar disorder with and without psychotic symptoms based on thalamic subregional structural volume.

BMC psychiatry
BACKGROUND: The thalamus plays a crucial role in sensory processing, emotional regulation, and cognitive functions, and its dysregulation may be implicated in psychosis. The aim of the present study was to examine the differences in thalamic subregio...

Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review.

Journal of medical Internet research
BACKGROUND: Differentiating bipolar disorder (BD) from unipolar depression (UD) is essential, as these conditions differ greatly in their progression and treatment approaches. Digital phenotyping, which involves using data from smartphones or other d...