Researchers have identified two compounds derived from grapes that might help to treat those with major depressive disorder.
In a new study using rat models, researchers report adding a certain lactic acid bacteria to the diet can help to prevent a type of depression linked to an unhealthy lifestyle.
University of Edinburgh researchers report many genes linked to neuroticism are also linked to depression. The findings may help to develop more personalized treatments with depressive disorders.
Heart rate variability can indicate whether a person has bipolar disorder or major depression, a new study reports.
Researchers discover common and specific changes to the brain's gray matter in patients with major depressive disorder and social anxiety disorder.
Researchers have identified increased inflammatory activation markers in the brains of people with major depressive disorder who report suicidal ideations. The findings support recent research that anti-inflammatories may provide antidepressant effects for some patients.
A new study reports depressed people who responded to ketamine found their activity increased during earlier parts of the day. Researchers suggest clock gene machinery may be linked to the type of depression that responds to ketamine treatment.
A new study implicates serotonin 2c receptors with metabolic side effects caused by a common class of antipsychotic medications.
White matter integrity appears to be reduced in people with major depressive disorders, a new Scientific Reports study reveals.
Researchers have discovered a link between specific neural circuits to distinct behavioral symptoms of depression. The study, published in Cell, reports altering the networks helped to improve symptoms such as social withdrawal and helplessness.
Exposing depressed adolescents to positive and negative words elicited different effects in specific brain regions depending on the sex of the subject, a new Frontiers in Psychiatry study reports.
Researchers are utilizing neuroimaging data to identify brain patterns and predict depression with the help of machine learning.
