MedWire News: The identification of neural activity patterns in response to facial expressions of emotion may help in the diagnoses of mental illness, say researchers.
Janaina Mourão-Miranda (University College London, UK) and team found that brain activity patterns in response to images of happy and neutral faces differed significantly in patients with mood disorders compared with mentally healthy individuals.
"Pattern recognition approaches offer the potential to help clinicians not only discriminate healthy from unwell individuals but also discriminate among patients with different psychiatric illnesses," said co-author Mary Phillips (University of Pittsburgh, Pennsylvania, USA) in a press statement.
"This approach can ultimately help improve diagnosis of those psychiatric illnesses that are often extremely difficult to accurately diagnose using current clinical criteria. This can be important for determining the best course of treatment for a patient."
The findings come from a study of 18 depressed patients with bipolar I disorder, 18 depressed patients with recurrent unipolar depression matched for depression severity, age, and illness duration, and 18 age- and gender-matched mentally healthy individuals.
All of the participants underwent functional magnetic resonance imaging scans while performing a task in which they were asked to distinguish between happy and neutral faces.
The researchers found that a pattern recognition software program was able to distinguish between responses to happy versus neutral faces more accurately in controls than in both groups of mood disorder patients.
This suggests that mood disorder patients have abnormal responses to happy faces when compared with neutral stimuli.
Furthermore, the accuracy of the programme in distinguishing between responses to the two stimuli was significantly lower for bipolar than unipolar disorder patients.
"These findings indicate that pattern recognition approaches can be used to identify abnormal brain activity patterns in patient populations and have promising clinical utility as techniques that can help to discriminate between patients with different psychiatric illnesses," concludes the team in Bipolar Disorders.
Phillips added: "These approaches may also have wider future use in identifying abnormal patterns of brain activity in patient populations that can predict their likely response to different treatments and the risk of future psychiatric illness in individuals."
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