To develop effective brain decoding and stimulation control algorithms, we must first understand which regions of the brain show abnormal activity related to psychiatric illness. The TRANSFORM project conceives of this in terms of "transdiagnostic domains", a set of psychological constructs and associated behavioral tasks that collectively model a range of psychiatric disorders. Our neuroimaging team is composed of expert psychologists with long experience in task design, and they hold primary responsibility for designing our task batteries and the precise stimuli to be used to evoke brain activity.
Although TRANSFORM relies heavily on brain recordings taken during surgical procedures in humans, those recordings will always be limited in terms of which brain areas we can access and the number of patients who can volunteer. To ensure that we fully cover the whole brain, the Scan team is using the state-of-the-art neuro-imaging facilities at MGH's Athinoula A. Martinos Center for Biomedical Imaging to collect large-scale non-invasive data from the same patients who contribute to our invasive studies. Subjects are scanned with both fMRI (which has excellent spatial resolution) and MEG/EEG (excellent temporal resolution) to fully capture impairment across distributed neural networks. To merge these data and interpret them alongside our invasive recordings, the same team that produced world-class tools such as MNE-python, is working to build new data fusion and visualization engines, which we will make available as open-source toolkits for the neuroscience community.
Finally, to use the transdiagnostic battery as a clinical tool, we must understand the population norms. In addition to the epilepsy and movement disorders patients being recruited under other tasks, we will recruit and scan independent cohorts of healthy volunteers and psychiatric patients with a range of mood, anxiety, and impulse-control disorders. By comparing the behavioral patterns and neural activations in these cohorts to those of patients presenting for our clinical trials, we will be able to determine patient-specific patterns of network dysfunction and customize surgical targets for invasive therapies.