Brain imaging in schizophrenia
Negative symptoms are a particularly debilitating feature of schizophrenia. However, the neurobiological basis of these symptoms is poorly understood. Recent research points to widespread cortical thinning, white matter alterations and aberrant functional connectivity in patients with schizophrenia. Taken together, these findings suggest a neural dysfunction at the network level. An increased understanding of how this relates to negative symptoms is important, in order to eventually develop better treatments. Here, patients with schizophrenia and matched controls have undergone brain imaging with PET and MRI, including imaging of the dopamine system as well as structural and functional connectivity. In addition, a range of symptom ratings, and cognitive and neurophysiological measures haven been collected. In recent years, increased processing speed and memory capacity has made feasible the analysis of brain imaging data at the connectome level. These novel methods, although computationally intensive, are attractive in the context of schizophrenia research, given the widespread neurobiological alterations associated with the disorder. In this project, probabilistic tractography will be applied to diffusion tensor imaging data in order to compute connectivity matrices that can then be entered into computational models in order to predict blood oxygen level dependend (BOLD) signal as well as neurophysiological markers of the disease.