Our results of whole brain, multivariate analysis of functional connectivity in schizophrenia indicate that when compared to healthy controls, patients with schizophrenia exhibit two distinct patterns of differences. Rather than showing uniformly increased or decreased connectivity, schizophrenia patients, when compared to controls, exhibit abnormally increased connectivity between the medial parietal and frontal lobes, and decreased connectivity between the medial parietal and temporal regions and between the temporal cortex bilaterally. Furthermore, these connectivity abnormalities show a differential relationship with patients’ clinical symptoms, in that the networks associated with sub-normal connectivity in the patient group are associated with the severity of patients’ positive symptoms, while networks associated with supra-normal connectivity in the patient group shows associations with the severity of patients’ negative and general symptoms. Taken together, these results suggest that abnormal patterns of functional connectivity are associated with schizophrenia clinical symptoms.
As discussed previously, the most frequently studied feature (network) identified in resting state fMRI data is the default mode network (DMN). According to various sources, it includes medial frontal (including anterior cingulate), parietal (including posterior cingulate, precuneus and inferior parietal) and medial temporal (including hippocampus) areas of the brain (Raichle et al., 2001
; Greicius et al., 2003
). The activation pattern (low-frequency fluctuations) within all the elements of this network seem to strongly correlate with each other, and network as a whole has been associated with spontaneous and task independent, internally generated thought processes (Fox et al., 2005
). It is further believed that the activation within this network is actively suppressed during the cognitive tasks, and that the degree of this suppression correlates with task performance (semantic recognition and semantic priming) (Jeong and Kubicki, 2010
). In schizophrenia, few similar observations have been made in relationship to the task performance, i.e. Whitfield-Gabrieli et al., (2009)
report anticorrelations between default-mode network and working memory performance, while Jeong and Kubicki (2010)
report anticorrelations between default-mode network and semantic processes in schizophrenia. Both those studies suggest that the decreased activation and poorer cognitive performance in schizophrenia might be partially related to increased activation/decreased suppression within the default-mode network.
Both increased (Zhou et al., 2010
) and decreased connectivity (Liang et al., 2006
; Bluhm et al., 2007
) in the default-mode network has been reported previously in patients with schizophrenia. The results of our study show that those previous results do not necessarily contradict each other. Instead, schizophrenia might, even at the level of each functional network, be associated with distinct patterns
of functional connectivity abnormalities, in which certain connections (i.e., parietal-temporal and the temporal cortices bilaterally) have subnormal levels of functional connectivity while others (i.e., parietal-frontal) show supra-normal connectivity.
Increased levels of activation within the anterior part of the default network in schizophrenia (which also overlap with the brain regions involved in executive function and attention) could potentially interact with the posterior connections (i.e., temporo-parietal), thereby decreasing their effective connectivity and potentially affecting important cognitive processes that would rely on such connectivity, such as early auditory (Javitt et al., 2003), or semantic (Nestor et al., 2003; Saykin et al., 1991
) processes. Furthermore, since the posterior and inferior temporal-parietal regions have been consistently implicated in the clinical symptoms of schizophrenia (specifically, in hallucinations and thought disorder (Woodruff et al., 1997
), it is possible that the functional connectivity disruptions between these regions, such as observed in the present study, as well as their correlations with hallucinations and delusions also observed here, directly reflect anatomical abnormalities reported in the literature, such as volume decreases in the STG, Heschl’s gyrus (associated with auditory hallucinations Bartha et al., 1990), and the amygdala-hippocampus complex (associated with thought disorder Shenton et al., 2001
), (for the review also see Buckley 2005). The second possibility is that decreased anatomical connectivity between temporal and posterior parietal regions (implicated by anatomical DTI studies reporting abnormalities in white matter integrity in the cingulum bundle and arcuate fasciculus (for the review, see (Kubicki et al., 2007
)), might decrease the inhibitory, “task related” input into the medial parietal region. This would further reflect in hyperactivation and hyperconnectivity within the frontal connections and attention deficits that are subserved by this connection, and are quite frequent in schizophrenia (as well as reflected by correlations with general and negative symptoms reported here). In addition to parieto-frontal and parieto-temporal connectivity abnormalities observed in our sample, our abnormal connectivity pattern also involved interhemispheric connections between temporal regions. Such abnormalities, even though not sufficiently understood, have been also suggested in multiple theories involving neurodevelopment and neurodegeneration in schizophrenia (Crow et al., 2007
), and further suggest necessity of involving connections between left and right hemisphere in all experimental models of schizophrenia.
It is worth mentioning that while our analysis exhibits a distinct prediction power, unlike PCA approaches, the results do not imply that the important connections belong to the same functional network. Since not all schizophrenia patients share the same clinical manifestations, functional signal fluctuations should be more variable within this group than within healthy controls. Our method is designed to find connections that consistently
differentiate patients and controls. Accordingly, in our previous, methodological publication (Venkataraman et al., 2010
), we demonstrated that Gini Importance, as opposed to univariate scores, remains consistent across cross-validation iterations, and significant connectivity features have reasonable predictive power in distinguishing those populations. We notice, however, that in current experiment, a small subset of subjects is still consistently misclassified. This suggests that functional connectivity differences between two populations are quite subtle. Additionally, since resting functional connectivity is not a well-understood phenomenon, the results may be confounded by external factors, which include anatomical variability in “white matter connectivity”, age, medication levels, etc. Once fully understood, accounting for these factors might vastly improve analytic power of functional connectivity experiments. It is worth recalling, however, that not only is schizophrenia a clinically inhomogeneous disease, but various anatomical and/or physiological disturbances might lead to the same clinical manifestation. This renders the search for a schizophrenia phenotype even more complex and difficult.