Our understanding of the neuropathology of schizophrenia has increased dramatically over the past decade. MRI findings now confirm structural brain abnormalities in schizophrenia. These findings have widened the scope of both clinical and basic science research and have led to an important research focus on the neurobiology of this disorder. MRI structural findings in schizophrenia include: (1) ventricular enlargement; (2) medial temporal lobe involvement (amygdala, hippocampus and parahippocampal gyrus); (3) STG involvement; (4) parietal lobe involvement (particularly the inferior parietal lobule and its subdivision into angular and supramarginal gyrus); as well as, (5) subcortical brain region involvement, including the cerebellum, basal ganglia, corpus callosum, thalamus, and CSP. The pattern and number of abnormalities are consistent with a disturbance of connectivity within and between brain regions, most likely neurodevelopmental in origin.
Several theories have been proposed in an attempt to understand the involvement of such a large number of abnormal brain regions in schizophrenia, many of which are likely highly functionally related. Andreasen and coworkers (1994a
), for example, suggest that the ‘cognitive dysmetria’ of schizophrenia can be explained by abnormalities in the thalamus and its connections with the cortex and cerebellum. Buchsbaum and colleagues (1990)
have focused on abnormalities in the frontal lobes, basal ganglia and temporal lobe connections. In contrast, Weinberger and coworkers (1992
; Weinberger, 1987
) describe schizophrenia as a neurodevelopmental encephalopathy and they propose a ‘disconnection model’ to explain how alterations in temporal lobe structures might interrupt connections between the temporo-limbic and prefrontal regions, and vice a versa. This model has been extended to basic science studies where these investigators have reported the effect of neonatal lesions on medial temporal lobe structures and their disruption of prefrontal cortical brain regions (Saunders et al., 1998
proposes that neurodevelopmental abnormalities in schizophrenia result from errors in synaptic pruning that occur at the onset of this disorder, during adolescence and early adulthood. Crow (1990a
) also invokes a neurodevelopmental explanation for schizophrenia but has focused on temporal lobe brain regions that are highly lateralized and important for language production. Our laboratory has also focused on temporal lobe abnormalities as being key to understanding the neuropathology of schizophrenia and we highlight damage to an interconnected neural network that is functionally important for language and associative links in memory as a fundamental defect in schizophrenia (e.g. Shenton et al., 1992
; McCarley et al., 1996
; Nestor et al., 1997
). And, finally, Pearlson et al. (1996)
highlights heteromodal association areas of the brain as being fundamental to the neuropathology of schizophrenia.
All of these theories have evolved from earlier theories of brain abnormalities in schizophrenia, though confirmation and then refinement was not possible until the application of in vivo neuroimaging techniques. This technology, in fact, has led to the most important discoveries of brain abnormalities in the history of research in schizophrenia. Future research studies will include characterizing basic mechanisms using molecular biology techniques and their application to post-mortem brain tissue, as well as animal models of lesions and their effect on interconnected brain regions. Such studies will likely advance our knowledge of the neural circuitry of the brain. Additionally, clinical studies will need to identify more homogeneous subject groups, evaluate early prenatal and birth history, and follow patients longitudinally from first onset of illness, throughout the life stages, in order to better inform our understanding of neurodevelopmental abnormalities and neurodegenerative changes in the brain.
Future research studies will also need to investigate brain abnormalities in high risk individuals such as family members of patients diagnosed with schizophrenia, as such investigations will likely further our understanding of the genetics of schizophrenia and perhaps suggest which insults or genes result in the development of schizophrenia. While some studies have been conducted in this area (e.g. Seidman et al., 1999
), more are needed. Moreover, an investigation of brain abnormalities in individuals diagnosed with schizotypal personality disorder, a disorder which is genetically linked to schizophrenia, will likely be fruitful as these individuals are genetically linked to schizophrenia but the symptoms are more attenuated, and they are not psychotic (e.g. Kendler et al., 1993
). And, while work in this area has begun (e.g. Dickey et al., 1999
; Siever, 1994
), further studies are needed. These individuals are of particular interest since they have generally not been exposed to neuroleptic medications nor have they experienced the effects of chronic hospitalization, both confounds in patients diagnosed with schizophrenia.
In terms of technical advances, the quality of in vivo images using MRI has dramatically increased over the past decade. For example, we are now able to evaluate nearly isotropic voxels in brain images (e.g. 1-mm 3). New segmentation algorithms have also been developed which facilitate the accuracy and speed with which brains can be segmented into gray matter, white matter, and CSF. It will be important for future studies to combine structural and functional measures.
Another important advance will be in measuring brain regions of interest. Specific regions of interest are still generally drawn manually and the process is quite labor intensive. Improvements will include techniques that utilize template driven segmentation based on techniques such as ‘warping’. For example, a brain atlas, with multiple segmented brain regions, will be ‘warped’ into new MRI data sets in order to delineate specific regions of interest (e.g. Anderson et al., 1998
; Collins et al., 1992
; Evans et al., 1991
; Gee et al., 1993
; Iosifescu et al., 1997
; Kikinis et al., 1996
; Shenton et al., 1995
; Tiede et al., 1993
). This approach will enable the segmentation of multiple regions of interest in a large number of subjects. Moreover, such an approach will be critical for investigating multiple brain regions in the same subjects rather than being limited to only a small subset of ROI for a given study. Investigators will also be able to evaluate intercorrelations among brain regions. By increasing both the number of brain ROIs and the number of subjects that can be analyzed in a given study, further links may also be made between structural brain abnormalities and clinical and cognitive measures.
Other methods for investigating brain regions in MR data sets, which will be important in future studies, include the use of: (1) artificial neural networks (e.g. Magnotta et al., 1999
); (2) landmark based shape analysis (e.g. Arndt et al., 1996
; Bookstein, 1991
; Buckley et al.,1999
; Casanova et al.,1990
; Corson et al.,1999a
; DeQuardo et al., 1996
; Tibbo et al., 1998
); (3) surface parametrization techniques for shape extraction (e.g. Brechbühler et al., 1995
; Narr et al., 2000
); (4) skeletonization techniques for extracting shape (e.g. Frumin et al., 1998
; Golland et al., 1999
; Golland and Grimson, 2000
; Näf et al., 1996
; Pizer et al., 1998
); and (5) high dimensional transformations to extract shape (e.g. Csernansky et al., 1998
; Haller et al., 1997
). Image averaging (e.g. Andreasen et al., 1994a
; Wolkin et al., 1998
), and voxel based approaches may also be important in future studies defining brain regions (see Pearlson and Marsh, 1999
for a review of the latter approaches).
A focus on shape deformations of brain regions, as opposed to only volume measures, may also provide important information relevant to neurodevelopmental theories of schizophrenia, because such deformations may be associated with neurodevelopmental abnormalities. Support for this hypothesis comes from Van Essen (1997)
who has shown that the course of development in cortical-cortical and subcortical-cortical connections determines their pattern of growth and shape.
Another area likely to receive attention in future studies is the evaluation of white matter abnormalities. Many studies have reported gray matter abnormalities in schizophrenia, but few have reported white matter changes. White matter is harder to define and to evaluate using conventional MRI as it appears uniform and homogeneous. MR brain diffusion tensor imaging (DTI), however, is a new technique that has recently been developed for use with humans which makes it possible to investigate white matter more closely. This technique has been used to evaluate changes in the brain following acute stroke (e.g. Le Bihan et al., 1986
; Maier et al., 1998
; Moseley et al., 1990
; Warach et al., 1992
). It has also been used to evaluate brain tumors (e.g. Le Bihan et al., 1986
; Hajnal et al., 1991
) and normal and abnormal white matter via diffusion anisotropy (Chien et al., 1990
; Doran et al., 1990
; Douek et al., 1991
; Le Bihan, 1995
; Peled et al., 1998
With respect to white matter, MR brain diffusion tensor imaging is well suited for evaluating white matter because water diffusion is restricted by the physical characteristics of the fiber tracts. There are currently only a small number of studies of schizophrenia using this technique. Specifically, Buchsbaum and colleagues (1998)
reported diminished anisotropic diffusion in the right inferior prefrontal region in six schizophrenic patients. A study by Lim et al. (1999)
reported reduced anisotropy, indicative of reduced white matter integrity in schizophrenic patients compared to controls. Finally, Foong and colleagues (2000b)
reported decreased anisotropy in the splenium of the corpus callosum in patients with schizophrenia. shows an example of MR diffusion tensor imaging which highlights the corpus callosum fibers. These fibers appear as a dense array of tensors that indicate white matter fiber tracts.
Fig. 6 MR brain diffusion tensor image map of a normal control subject. The diffusion tensor map is displayed as eigenvectors with the blue lines representing the direction of the in-plane components of each eigenvector which correspond to the largest eigenvalue. (more ...)
DTI may also be combined with magnetization transfer imaging, which makes possible the indirect estimation of protons bound to myelin and cell membranes of white matter (e.g. Foong et al., 2000a
). The magnetization transfer ratio (MTR), which reflects the exchange of magnetization between bound protons and free water, is thought to index myelin and axonal integrity. Thus MTR, in combination with DTI, can help to address further specific white matter anomalies which will likely lead to a new understanding of disrupted connectivity in schizophrenia.
Last, and perhaps the greatest recent advance in MRI technology, is functional MRI. One of the most important changes in the last few years has been to move from examining isolated brain regions to examining interconnected neural networks which are likely impaired in schizophrenia (e.g. Andreasen, 1997
; Weinberger, 1996
; Weinberger et al., 1996
). This move has been significant with the advent of fMRI technology which affords the opportunity to evaluate both brain structure and function more closely. And indeed, many laboratories are developing fMRI technology, which is rapidly changing and evolving, and which has already led to a wealth of new information concerning brain structure and function. [See review by Weinberger et al. (1996)
]. fMRI is particularly useful when there is a simultaneous focus on understanding the relationship between normal cognition and functional and neuroanatomical connections. The next decade will likely witness an explosion of new research from interdisciplinary teams of physicists, cognitive neuroscientists, neuroscientists, psychologists, and psychiatrists, which will likely lead to a greater understanding of the brain mechanisms responsible for observed structural abnormalities in schizophrenia.