Early Warning Signals in psychopathology

Early warning signals are indicators that some (major) change is about to happen. In almost all situations the indicators are obtained from (multiple) time series. Research into such indicators in climatology and engineering has met with some success. Such indicators of large changes in mental health would obviously be useful in psychopathology. However, it has been shown that simply applying standard techniques for indicators of large changes to any kind of system will often fail, i.e., it may fail to indicate a change when it is coming, but more often it will indicate change when it is not coming. To avoid such mistakes in early warning signals, we propose a framework using network theory to determine the type of indicators of large (qualitative) changes in psychopathology. In this framework we require assumptions about the type of network (relations between variables) and how the network is affected by external influences (big and small events in life). Applying this framework narrows down the type of indicators that are useful to function as early warning signals. We then focus, using the network framework, to determining extreme values. There are strong connections between the fields of extreme value theory and dynamical systems. The connections between these fields can be used to obtain early warning signals.