Abstract Machine learning is an emerging tool in clinical psychology and neuroscience for
the individualized prediction of psychiatric symptoms. However, its application in non-clinical …

Dimensional models of psychopathology may provide insight into mechanisms underlying
comorbid depression and anxiety and improve specificity and sensitivity of neuroanatomical …

Trait anxiety is particularly a prone phenotype for the development of anxiety disorders and
depression. Studying the neural underpinnings of trait anxiety can further inform our …

Neuroscientific and psychological research posits that there are two transdiagnostic facets of
anxiety: anxious arousal and anxious apprehension. Though these two facets of anxiety are …

Background Major depressive and social anxiety disorders have a high comorbidity rate and
similar cognitive patterns. However, their unique and shared neuroanatomical …

Somatic complaints can be important features of an individual's expression of anxiety.
Anxiety-related traits are also risk factors for somatic symptoms. However, it is not known …

Generalized anxiety disorder (GAD) is a common condition characterized by excessive and
uncontrollable worry, along with its high comorbidity rates. Despite increasing efforts to …

Anxiety is a mental state characterized by an intense sense of tension, worry or
apprehension, relative to something adverse that might happen in the future. Researchers …

Background Dimensional approaches in highly prevalent psychiatric disorders like
depression or anxiety could lead to a better understanding of pathogenesis and advantages …

Understanding the relationship between brain measurements and behavioral performance
is an important step in developing approaches for early identification of any psychiatric …