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US scientists from the University of California at San Francisco (UCSF) have discovered a new pattern of brain activity that may contribute to the development of new treatments to treat disorders of the brain. Mood such as depression.
is based on studies in which participants rely on a functional magnetic resonance imaging (fMRI) scanner and look at upsetting images or listen to sad stories, reports the agency's Xinhua press.
Using computational algorithms, they adapted patterns of brain activity to the mood changes reported by patients and badyzed brain activity records in each patient in order to determine the mood patterns. identify intrinsic coherence networks (ICNs), which are brain groups. regions where their patterns of activity fluctuate at a common frequency.
The researchers found that changes in brain network activity were closely related to daily episodes 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 respectively with memory and negative emotions.
The researchers were able to identify a single signal almost completely explaining the depressive mood fits in the patients involved in the experiment.
The discovery suggests that the interactions between the amygdala and the hippocampus could be related to the recall of emotional memories, and that these activities were the most obvious. Vikaas Sohal, UCSF Neuroscientist,
The discovery of such an informative biomarker could help scientists develop new treatments to treat mood in people with a high level of activity. High anxiety, whose mood could then be subject to recall of emotionally charged memories. illness related to depression such as future depression.
The results of UCSF research were published in the journal Cell published earlier this week.
– IANS
mr / rt
(This story was not edited by Business Standard staff and is generated automatically from a syndicated feed.)
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