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US scientists from the University of California at San Francisco (UCSF) have discovered a new pattern of brain activity likely to contribute to the development of new treatments to treat mood disorders. such as depression.
Most research on mood disorders in the human brain is based on studies in which participants rely on a functional magnetic resonance imaging (fMRI) scanner and look at heartbreaking images or listen to stories. sad, reports the Xinhua news agency.
Using computational algorithms, they adapted patterns of brain activity to mood changes reported by patients and analyzed brain activity records in each patient to identify the symptoms. Intrinsic coherence networks (ICNs), which are groups of brain regions where their activity patterns fluctuate at a common frequency.
The researchers found that changes in brain network activity were closely related to daily moods of low or depressed mood.
The mood-related network was characterized by beta waves in the hippocampus and amygdala, two deep brain regions that have long been correlated with memory and negative emotions, respectively.
The researchers were able to identify a single signal explaining almost completely the depressive mood fits in the patients involved in the experiment.
The discovery suggests that interactions between the amygdala and the hippocampus could be related to reminding of emotional memories, and that these activities were more evident in people with high anxiety levels, whose Mood could then be subject to the impact of recalling emotionally charged memories, UCSF said. neuroscientist Vikaas Sohal.
The discovery of such an informative biomarker could help scientists develop new treatments to treat mood diseases such as depression.
The results of the UCSF research were published in the journal Cell published earlier this week.
–IANS
mr / rt
(This story has not been changed by Business Standard staff and is generated automatically from a syndicated feed.)
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