Investigating four pre-existing, publically available psychological and neurological data sets, researchers identify a network of brain areas that underlie psychiatric disorders including depression, anxiety, bipolar disorder, and schizophrenia.
Neurons in the anterior cingulate store social rank information to inform upcoming decisions. The findings could shed new light on social deficits associated with ASD and schizophrenia.
Area 32, a region of the anterior cingulate, balances activity from cognitive and emotional areas of the primate brain.
Neuroimaging study reveals social learning is represented in the anterior cingulate cortex, while direct learning is represented in the ventromedial prefrontal cortex. The two areas both interact with the striatum, which helps compute both reward prediction error and social prediction error.
When hippocampal firing rates are high before exposure to a learning task, people are better able to successfully encode memory. Findings suggest the hippocampus may have a "ready to encode" mode that facilitates memory recall.
Neuroimaging study reveals altered structural brain connectivity in patients with chronic and episodic migraines.
White matter tracts show increasing maturation with age from the back to the front of the brain. The maturations begin as a child reaches 9-12 years of age. The maturity correlates with a critical and formative period of development.
Neuroimaging reveals those who have spent more years studying have increased cortical thickness in the medial prefrontal cortex, anterior cingulate and orbitofrontal areas of the brain. Researchers also identified enhanced gene expression profiles in these brain regions that promote information processing and provide protection against some age-related neurodegenerative diseases.
A new neuroimaging study reveals the brains of teenage girls who self harm show similar features to adults with borderline personality disorder.
A new study reveals why, when the brain is faced with an overwhelming number of similar options, it struggles to make a decision.
A new meta-analysis of neuroimaging data reveals people with ASD process social and nonsocial rewards differently than those without an autism diagnosis.
Machine learning can predict, with significant accuracy, whether a person is a musician or not, based on fMRI data collected while subjects listened to music.
