Correlation and partial correlation are often used to provide a characterisation of the network properties of the human brain, based on functional brain imaging data. However, for partial ...correlation, the choice of network nodes (brain regions) and regularisation parameters is crucial and not yet well explored. Here we assess a number of approaches by calculating how each approach performs when used to discriminate different ongoing states of brain activity. We find evidence that partial correlation matrices, when estimated with appropriate regularisation, can provide a useful characterisation of brain functional connectivity.
Many cognitive processes are challenging to study due to their scarce occurrence. Here we demonstrate how pattern recognition and brain imaging can enhance the study of such processes by providing ...fast, sensitive, and non-intrusive detection of these events. This can enable efficient experimental and clinical intervention. We focus on the study of traumatic events producing flashbacks associated with post-traumatic stress disorder (PTSD), using an experimental analogue of trauma (a traumatic film). These events are rare and challenging to reliably elicit in experimental settings. We show that a classifier can be built to predict, based upon brain response, which stimuli are likely to induce these rare flashbacks at the point of exposure. An ability to predict these stimuli makes possible the trialing of context-specific preventative clinical interventions. We present results from two independent datasets, outlining key analytic challenges.
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