A mathematical method, based on the interconnection of symptoms, could predict the probability of recovery from depression. This was stated by a study by the Istituto Superiore di Sanità published today by the journal Nature Mental Health. It is called network analysis and allows the measurement of so-called plasticity, i.e. the ability to modify brain activity and behavior in the prevention and treatment of psychiatric disorders.
“The objective was to demonstrate how plasticity can be measured mathematically by evaluating the strength of connectivity in the symptom network, i.e. the frequency with which the symptoms of depression change together – explains Igor Branchi, of the Reference Center for Behavioral Sciences and Mental Health of the Istituto Superiore di Sanità, which coordinated the study – The greater the synchrony of the variations of different symptoms, the higher the coherence (connectivity) of the system and the lower its plasticity: in this work it is demonstrated how configurations more connected are more difficult to modify than configurations in which the links between symptoms are less strong”.
To test the method, the researchers examined data from STAR*D, a study provided by the US National Institute of Mental Health, analyzing the improvement trajectory of more than 4,000 depressed individuals.
“The analysis – continues Branchi – demonstrated how the strength of the connectivity of the symptoms, measured at the beginning of the study, was weaker in the patients who subsequently showed greater plasticity, presenting a significant improvement (responders), compared to those who they would instead have shown a less noticeable improvement (non-responders)”.
This method therefore opens the way to new approaches in the prevention and treatment of major depressive disorder but “does not allow us to predict with certainty the future state of health of the individual which depends on a multitude of factors”, however allowing us to estimate the probability of change.
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