SAN FRANCISCO – USA Researcher at the University of California San Francisco (UCSF) has found a new pattern of brain activity that can help develop new therapies in the future to treat mood disorders such as depression.
Most human brain research on mood diseases has claimed studies where participants reside in a functional magnetic resonance scanning (fMRI) scanner and look at disturbing images or listen to boring stories.
The researchers from the UCSF Weill Institute for Neurosciences recruited 21 patients with epilepsy who had had 40 to 70 electrodes implanted on the brain’s surface and into deeper structures in the brain to record brain activities for seven to ten days.
Using calculation algorithms, they matched patterns of brain activity to changes in patient reported mood and analyzed brain activity recordings of each patient to identify so-called native coherence networks (ICNs), which are groups of brain regions where t he activity patterns fluctuate in a common frequency.
The researchers found that changes in brain activity were strongly linked to daily challenges with low or depressed mood. The mood-related network was characterized by beta waves in hippocampus and amygdala, two deep brain regions that have long been correlated with memory and negative feelings.
The researchers were able to identify a single signal that explained almost completely bouts of depressive mood in the patients involved in the experiment.
The discovery suggests that interactions between amygdala and hippocampus can be linked to withdrawing emotional memories, and such activities were most apparent in people with high anxiety, whose mood could then be subject to recurrent emotional memories, said UCSF Neuroscience Vikaas Sohal.
The discovery of such a powerful informative biomarker can help researchers develop new therapies to treat mood related disease, such as depression in the future. [1
9659003] The results of UCSF research appeared in the magazine Cell published earlier this week.