ReviewSchizophrenia, neuroimaging and connectomics
Highlights
► Schizophrenia is a prototypical connectivity disorder. ► This article reviews imaging connectomic studies of schizophrenia. ► A primer on basic principles and methods of the field is provided. ► Key methodological issues in the literature are highlighted.
Introduction
Schizophrenia may be characterized as a prototypical disorder of brain connectivity. The very name implies a splitting (schizen) of the mind's (phren) normally integrated processes. This breakdown is evident in the disorder's clinical manifestations, including cognitive and affective deficits, positive symptoms such as delusions, hallucinations and thought disorder, and negative symptoms such as flattened affect and volitional disturbances. The link between these symptoms and brain connectivity was not lost on early writers; over a century ago, Wernicke first suggested that the disorder arose from pathology of the brain's association fibers (1906; Figs. 7C and D) and Bleuler, who coined the name schizophrenia, viewed a loosening of mental associations as a cardinal feature of the illness (1911/1950). The advent of modern neuroimaging techniques has provided an unprecedented capacity to test and extend these ideas via detailed mapping of brain network structure and dynamics. From the earliest in vivo demonstrations of brain abnormalities in people with schizophrenia (Ingvar and Franzen, 1974a, Ingvar and Franzen, 1974b, Johnstone et al., 1976), to the first study of connectivity disturbances in the disorder (Volkow et al., 1988), it did not take long before connectivity-based hypotheses of schizophrenia re-emerged; first in the form of the disconnection hypothesis laid out by Friston and Frith (1995), followed by subsequent variants (Andreasen et al., 1998, Bullmore et al., 1997, Friston, 1998, McGuire and Frith, 1996, Tononi and Edelman, 2000) and recently in more general characterizations of schizophrenia as a dysconnection disorder1 (Pettersson-Yeo et al., 2011, Stephan et al., 2006, Stephan et al., 2009).
In recent years, the study of connectivity abnormalities in schizophrenia has benefited greatly from rapid advances in the field of connectomics. Connectomics is an umbrella term that refers to scientific attempts to accurately map the set of neural elements and connections comprising the brain, collectively referred to as the human connectome, at either mico-, meso- or macro-scopic resolutions (Sporns, Sporns et al., 2005). The term connectome was initially invoked in reference to a structural description of the brain's physical wiring, but the concept has since been extended to include maps of the brain's functional interactions (e.g., Biswal et al., 2010), which are, by nature, more transient and state-dependent.
Imaging connectomics refers to the use of neuroimaging methods to map various properties of structural and functional brain connectivity, principally at macroscopic resolution. In a general sense, imaging connectomics encompasses the full range of neuroimaging investigations into brain connectivity, including region-of-interest and voxel-wise mapping approaches. In a more specific sense however, it refers to studies that aim to comprehensively map the large-scale architecture of the connectome by quantifying pair-wise interactions between large numbers of brain regions distributed throughout the cerebrum. Methodological advances have enabled construction of these connectomic maps with increasing detail, and their application to schizophrenia has led to novel insights into how the disorder affects distributed neural circuits. In this article, we critically evaluate this literature, focusing principally on studies using magnetic resonance imaging (MRI). We consider how this work has informed our understandings of two key aspects of connectomic disturbance in schizophrenia—altered inter-regional connectivity and altered brain network topology—and discuss its implications for pathophysiological models while highlighting important methodological issues. As a general orientation, we begin with a brief primer on the main principles and methods of imaging connectomics applied thus far. (For reviews of other types of connectivity studies in schizophrenia, see Ellison-Wright and Bullmore, 2009, Konrad and Winterer, 2008, Pettersson-Yeo et al., 2011).
Section snippets
A brief primer on connectomics
A central tenet of the connectomic endeavor is that brain connectivity can be succinctly described as a connectivity matrix, C, whose rows and columns correspond to different brain regions. The elements cij of C therefore index the degree of (structural or functional) interaction between regional pairs (Fig. 1). This representation allows quantification of different aspects of network connectivity and topology, facilitated through the application of graph theory, a rich mathematical framework
Brain network connectivity in schizophrenia
Most imaging connectomic studies of schizophrenia have investigated functional brain networks so our discussion is anchored on this work. In particular, we focus on four key issues in the literature; namely whether functional dysconnectivity in the disorder (1) is localized or diffuse, (2) abnormally increased or decreased, (3) state-dependent, and (4) has a structural basis.
Brain network topology in schizophrenia
The application of graph analytic techniques to MRI data allows the computation of a wide range of measures that characterize diverse topological properties of the human connectome. Extensive treatments of these measures, including formal definitions, have been provided elsewhere (Albert and Barabasi, 2002, Boccaletti et al., 2006, Newman, 2003, Rubinov and Sporns, 2010). In the following, we provide a conceptual overview of some of the key topological properties investigated in imaging
Conclusions
The studies reviewed here add to the already extensive literature documenting connectivity abnormalities in schizophrenia (Ellison-Wright and Bullmore, 2009, Konrad and Winterer, 2008, Pettersson-Yeo et al., 2011). The power of the imaging connectomic methods we have considered lies in their ability to provide relatively succinct, multidimensional characterizations of regional and whole-brain disturbances in brain network connectivity and topology. The findings suggest that schizophrenia is
Financial disclosures
ETB is employed half-time by GlaxoSmithKline. CP has received grant support from Janssen-Cilag, Eli Lilly, Hospira (Mayne), and Astra Zeneca. He has provided consultancy to Janssen-Cilag, Eli Lilly, Hospira (Mayne), Astra Zeneca, Pfizer, Schering Plough, and Lundbeck. He has undertaken investigator initiated studies supported by Eli Lilly, Hospira, Janssen Cilag and Astra Zeneca.
Acknowledgments
The authors thank Mary-Ellen Lynall and Aaron Alexander-Bloch for generously providing data and images to assist in generating some of the figures. AF was supported by a National Health and Medical Research Council CJ Martin Fellowship (ID: 454797). AZ is supported by a Melbourne Neuroscience Institute Fellowship and an Australian Research Council Research Fellow (APD; ID: DP0986320). CP was supported by a NHMRC Senior Principal Research Fellowship (ID: 628386) and NHMRC program grants (ID:
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