Inferring the Dysconnection Syndrome in Schizophrenia: Interpretational Considerations on Methods for the Network Analyses of fMRI Data - Silverstein, Brian H.; Bressler, Steven L.; Diwadkar, Vaibhav A. (Frontiers in Psychiatry, 2016)
Schizophrenia has long been considered one of the most intractable of psychiatric conditions. Its etiology is likely polygenic, and its symptoms the result of complex network-level changes in neuronal activity. While easily identifiable by psychiatrists based on clear behavioral signs, the biological substrate of the disease remains poorly understood. Here we discuss current trends and key concepts in the theoretical framework surrounding schizophrenia, and critically discuss brain network approaches applied to neuroimaging data that can illuminate the correlates of the illness. We take the approach of generating a theoretical framework from early principles of brain function, neural units, and build to the highly relevant and practical perspective of network function. Next, we outline the strengths and limitations of several fMRI-based analytic methodologies for assessing in vivo brain network function, including undirected and directed functional connectivity and effective connectivity. The underlying assumptions of each approach for modeling fMRI data are treated in some quantitative detail, allowing for assessment of the utility of each for generating inferences about brain networks relevant to schizophrenia. fMRI and the analyses of fMRI signals provides a limited, yet vibrant platform from which to test specific hypotheses about brain network dysfunction in schizophrenia. Carefully considered and applied connectivity measures have the power to illuminate loss or change of function at the network level, thus providing insight into the underlying neurobiology which gives rise to the emergent symptoms seen in the altered cognition and behavior of schizophrenia patients.