Abstract EN:

Posttraumatic stress disorder (PTSD) is a highly heterogeneous condition, ranging from individual traumatic incidents such as car accidents to national tragedies such as natural disasters. Every individual has a different depending on their personality and past experiences, especially regarding their tendency to depression. Hence the condition is better termed psychotrauma spectrum disorder (PSD). Its heterogeneity hinders reliable diagnosis, as detection is entirely dependent upon a clinician’s subjective impression and sensitivity to comorbidities and there is always the possibility of concealment. Yet early diagnosis is essential, as the earlier PSD is detected the more likely treatment will be successful. Furthermore, reliable biomarkers of PSD would allow for much more accurate detection and monitoring of progression. Here we propose a new computational approach building on our prior work on the early detection of Parkinson’s, Alzheimer’s and depression. We will use a new analysis tool, called the Brain Code (BC). This concept was developed to integrate many different kinds of data, for e.g. the often fragmented and incomplete outputs from body sensors that record balance, dexterity, postural, facial and vocal movements combined together with cognitive or clinical outputs such as the intentional or emotive content of speech. The Brain Code allows us to fit all these different data streams together in such a way as to compensate for the deficiencies of each individually. It can put disparate physiological and cognitive data into the same ‘coordinate system’, so that we will be able to develop a reliable quantitative ‘signature’ of PSD. These quantitative biomarkers will be designed so that they are useful for both physicians in a clinical setting and for communities affected by a large-scale traumatic event.