Overall white matter changes: Histology and MRI

Initial attempts to quantify white matter changes were based on anatomical dissection and standard structural MRI. Historically, imaging techniques have not allowed detailed analysis of white matter in vivo, particularly at a cellular level, and so investigations have been predominately postmortem. However, postmortem studies carry with them a variety of methodological issues, such as the influence of postmortem interval and cause of death on the tissue, as well as the necessity of relying on previous diagnoses, that can seriously complicate interpretation of the data collected (Lewis, Reference Lewis2002). One finding from postmortem work has been a change in distribution of interstitial cells of the white matter (Akbarian, Reference Akbarian, Kim, Potkin, Hetrick, Bunney and Jones1996; Kirkpatrick, Reference Kirkpatrick, Conley, Kakoyannis, Reep and Roberts1999, Reference Kirkpatrick, Messias, Conley and Roberts2003). Interstitial neurons develop from the cortical subplate, which is a transitory structure present only during the second and third trimester and which plays a role in guiding the formation of cortical connections, possibly by dictating each cell's ultimate location. Normally the cells from the subplate undergo programmed cell death at the end of the third trimester and shortly after birth. The findings of changes in interstitial neuron distribution may indicate an imbalance in the factors initiating the cell death. Because of its critical role in migratory processes, any disturbance of the functioning of the subplate could lead to a disruption in the appropriate formation of cortical connections. Thus, this finding offers a potential mechanism for disruption of structural connectivity in the absence of gliosis or large-scale gross pathology.

As an alternative to histological and dissection studies, neuroimaging techniques have been applied to the investigation of white matter in living schizophrenic patients. However, although traditional MRI does allow a gross overview of the white matter, any abnormalities other than the overall size of the area are beyond the scope of this methodology. Traditional MRI cannot assess whether cells are in place but not properly connected, whether axons are disorganized, or whether normal functional cells have been replaced with other cells; in each case white matter volume may remain unchanged while functional connectivity may be fundamentally altered.

Many structural MRI studies have examined whole brain or lobar white matter volumes in patients with schizophrenia compared with controls. Breier and colleagues (1992) reported reduced bilateral prefrontal white matter volumes in patients with schizophrenia compared with controls. In addition, they reported that variation in prefrontal white matter volume correlated with right (but not left) amygdala and hippocampal volumes in the patients but not in the controls, which may be consistent with the idea of early hippocampus and amygdala damage, resulting in abnormal connectivity with the frontal lobe in patients with schizophrenia. This interpretation is also consistent with the finding that greater hippocampal pathology in schizophrenia is correlated with decreased prefrontal activity assessed using positron emission tomography (PET; Weinberger et al., Reference Weinberger, Berman, Suddath and Torrey1992). Similarly, Hulshoff Pol and colleagues (Reference Hulshoff Pol, Schnack, Bertens, van Haren, van der Tweel and Staal2002) found reduced white matter volume only in the prefrontal region in schizophrenia patients; there were no case–control differences in whole-brain white matter volumes. Specific tracts have also been investigated; for instance, decreases in the volume of the anterior limb of the internal capsule (connecting the medial dorsal thalamus and the frontal lobes) have been shown (Suzuki et al., Reference Suzuki, Nohara, Hagino, Kurokawa, Yotsutsuji and Kawasaki2002; Zhou et al., Reference Zhou, Suzuki, Hagino, Takahashi, Kawasaki and Nohara2003).

The relationship between gray and white matter volumes has also been investigated (Bartzokis et al., Reference Bartzokis, Nuechterlein, Lu, Gitlin, Rogers and Mintz2003). It was noted that in normal development across the life span (from late adolescence until midadulthood) there is a significant reduction in the gray/white matter ratio in the brain (Bartzokis et al., Reference Bartzokis, Beckson, Lu, Nuechterlein, Edwards and Mintz2001). In adolescence there is a period of substantial loss of gray matter (pruning), and then throughout adulthood, until the age of approximately 47, there is a normal increase in white matter. The combination of these events leads to a decrease in the gray/white matter ratio over time. In a cross-sectional study of schizophrenics and controls, it was found that the patients do not demonstrate this decrease in the way that normal subjects do; rather, the patients appear to fail to increase their white matter with age in the manner of the controls, and the deficit becomes more pronounced over time, making the gray matter deficit more apparent in younger subjects, whereas the white matter deficit becomes relatively larger with age (Bartzokis et al., Reference Bartzokis, Nuechterlein, Lu, Gitlin, Rogers and Mintz2003).

DTI assessments of white matter changes

A relatively new MRI technique, DTI, allows for a more detailed analysis of the integrity of the white matter tracts. The data collected in DTI are based on Brownian motion, the normal motion driven by thermal energy, of water molecules (Peled, Gudbjartsson, Westin, Kikinis, & Jolesz, Reference Peled, Gudbjartsson, Westin, Kikinis and Jolesz1998). If unobstructed, that motion has an equal likelihood of going in any direction (i.e., isotropic diffusion). Water molecules in the brain, however, are moving in an environment full of cell membranes, fibers, and other tissue components that limit their motion. In white matter tracts, the motion of the molecules is restricted by the myelinated axons and tends to move more easily in the direction along the axon than perpendicular to it, creating motion in an ellipsoid shape rather than a spherical one (i.e., anisotropic diffusion; see Figure 2). The shape of this ellipsoid can give information such as the degree of myelination, the average fiber diameter, and the similarity in the direction of the fibers within the tract. An index known as FA characterizes the eccentricity of the ellipsoid, and is interpreted as a measure of white matter integrity. The direction of the ellipsoid can give information about the orientation of fibers in that region, and it is possible to use tractography to follow fiber tracts through adjacent voxels with a common principle direction (Catani, Howard, Pajevic, & Jones, Reference Catani, Howard, Pajevic and Jones2002; Klingberg et al., Reference Klingberg, Vaidya, Gabrieli, Moseley and Hedehus1999). This procedure allows the tracing of anatomical connections between regions of interest, or the determination of whether the tracts themselves are appropriately placed and connected. With these capabilities, coupled with the ability to perform the technique in a standard MRI scanner over relatively short scan periods, DTI has become a very practical way to investigate structural integrity of fiber tracts in living subjects.

Figure 2.

Isotropic and anisotropic diffusion, which are the basis of FA calculations used to calculate white matter integrity using DTI.

Initially, many DTI studies in schizophrenia assessed changes at the level of entire lobes or large cortical regions. These approaches have shown decreased FA in frontal (Buchsbaum et al., Reference Buchsbaum, Tang, Peled, Gudbjartsson, Lu and Hazlett1998; Hao et al., Reference Hao, Liu, Jiang, Gong, Liu and Tan2006; Kitamura et al., Reference Kitamura, Matsuzawa, Shioiri, Someya, Kwee and Nakada2005; Kumra et al., Reference Kumra, Ashtari, McMeniman, Vogel, Augustin and Becker2004; Lim et al., Reference Lim, Hedehus, Moseley, de Crespigny, Sullivan and Pfefferbaum1999; Minami et al., Reference Minami, Nobuhara, Okugawa, Takase, Yoshida and Sawada2003; Szeszko, Ardekani et al., Reference Szeszko, Ardekani, Ashtari, Kumra, Robinson and Sevy2005) and parietal lobes (Ardekani, Nierenberg, Hoptman, Javitt, & Lim, Reference Ardekani, Nierenberg, Hoptman, Javitt and Lim2003; Kyriakopoulos, Vyas, Barker, Chitnis, & Frangou, Reference Kyriakopoulos, Vyas, Barker, Chitnis and Frangou2008; Minami et al., Reference Minami, Nobuhara, Okugawa, Takase, Yoshida and Sawada2003). However, the affected subregions vary between studies, with some studies finding no patient–control differences (Foong et al., Reference Foong, Symms, Barker, Maier, Miller and Ron2002; Price, Bagary, Cercignani, Altmann, & Ron, Reference Price, Bagary, Cercignani, Altmann and Ron2005). Some of these discrepancies may be related to differences in registration techniques, as accurate registration is an ongoing issue for DTI studies. As new methods have emerged, it has been possible to obtain more subtle information about not only specific tracts or small regions implicated, but also about the relationship of changes in those regions with changes in cognition, symptomatology, and outcome.

One region of particular interest is the uncinate fasciculus, a tract providing connections between the temporal pole near the amygdala, and the orbitofrontal/ventrolateral prefrontal cortex (Petrides & Pandya, Reference Petrides, Pandya, Stuss and Knight2002). FA in the uncinate fasciculus has been shown to be reduced in patients with schizophrenia (Burns et al., Reference Burns, Job, Bastin, Whalley, Macgillivray and Johnstone2003; Kubicki et al., Reference Kubicki, Westin, Maier, Frumin, Nestor and Salisbury2002; Nakamura et al., Reference Nakamura, McCarley, Kubicki, Dickey, Niznikiewicz and Voglmaier2005; Nestor et al., Reference Nestor, Kubicki, Gurrera, Niznikiewicz, Frumin and McCarley2004; Price et al., Reference Price, Cercignani, Parker, Altmann, Barnes and Barker2008; Szeszko et al., Reference Szeszko, Robinson, Ashtari, Vogel, Betensky and Sevy2008) and schizotypal personality disorder (Nakamura et al., Reference Nakamura, McCarley, Kubicki, Dickey, Niznikiewicz and Voglmaier2005), a genetically related syndrome. Moreover, because of the regions it connects, this tract is of particular interest to emotional processing, and efforts have been made to determine the behavioral correlates of white matter changes in this tract. For example, decreased FA in this tract is associated with negative symptoms (Szeszko et al., Reference Szeszko, Robinson, Ashtari, Vogel, Betensky and Sevy2008) and with reduced executive functions (Kubicki et al., Reference Kubicki, Westin, Maier, Frumin, Nestor and Salisbury2002), verbal learning (Nakamura et al., Reference Nakamura, McCarley, Kubicki, Dickey, Niznikiewicz and Voglmaier2005; Szeszko et al., Reference Szeszko, Robinson, Ashtari, Vogel, Betensky and Sevy2008), and episodic memory (Nestor et al., Reference Nestor, Kubicki, Gurrera, Niznikiewicz, Frumin and McCarley2004), all cognitive constructs that would be expected to rely on coordinated communication between frontal and temporal lobes.

The cingulate gyrus is another region of interest based on functional imaging studies of patients with schizophrenia. It serves as a primary connection to the frontal lobes, which are compromised in schizophrenia, and is associated with a number of cognitive and affective processes that may be impaired in schizophrenia. FA is decreased in the anterior and posterior cingulate in schizophrenia (Fujiwara, Hirao, et al., Reference Fujiwara, Hirao, Namiki, Yamada, Shimizu and Fukuyama2007; Fujiwara, Namiki, et al., Reference Fujiwara, Namiki, Hirao, Miyata, Shimizu and Fukuyama2007; Kubicki et al., Reference Kubicki, Westin, Nestor, Wible, Frumin and Maier2003; Sun et al., Reference Sun, Wang, Cui, Breeze, Du and Wang2003; Wang et al., Reference Wang, Sun, Cui, Du, Wang and Zhang2004). Changes in FA in this region have been associated with positive symptom scores (Fujiwara, Namiki, et al., Reference Fujiwara, Namiki, Hirao, Miyata, Shimizu and Fukuyama2007), performance on the Wisconsin Card Sort Test, an index of executive function (Kubicki et al., Reference Kubicki, Westin, Nestor, Wible, Frumin and Maier2003) and performance on an attention task (Lim et al., Reference Lim, Ardekani, Nierenberg, Butler, Javitt and Hoptman2006).

Patients with schizophrenia have decreased hippocampal volumes (Nelson, Saykin, Flashman, & Riordan, Reference Nelson, Saykin, Flashman and Riordan1998) as well as reduced overall temporal lobe gray matter volumes (Gur et al., Reference Gur, Turetsky, Cowell, Finkelman, Maany and Grossman2000) and impairments in cognitive functions mediated by the medial temporal lobe such as episodic memory (Saykin et al., Reference Saykin, Gur, Gur, Mozley, Mozley and Resnick1991). FA reductions in patients with schizophrenia have been observed in the hippocampus (White et al., Reference White, Kendi, Lehericy, Kendi, Karatekin and Guimaraes2007) and the temporal lobes (Schlosser et al., Reference Schlosser, Nenadic, Wagner, Gullmar, von Consbruch and Kohler2007), although negative findings exist (Begre et al., Reference Begre, Federspiel, Kiefer, Schroth, Dierks and Strik2003). Further, associations between decreased FA in the hippocampus with decreased verbal declarative memory performance (Lim et al., Reference Lim, Ardekani, Nierenberg, Butler, Javitt and Hoptman2006), and decreased FA in the fornix with decreased episodic memory performance (Nestor et al., Reference Nestor, Kubicki, Kuroki, Gurrera, Niznikiewicz and Shenton2007), have been reported. White matter changes have been shown to be present even in the first episode of schizophrenia (Begre et al., Reference Begre, Federspiel, Kiefer, Schroth, Dierks and Strik2003; Federspiel et al., Reference Federspiel, Begre, Kiefer, Schroth, Strik and Dierks2006; Hao et al., Reference Hao, Liu, Jiang, Gong, Liu and Tan2006; Price et al., Reference Price, Bagary, Cercignani, Altmann and Ron2005; Szeszko, Ardekani, et al., Reference Szeszko, Ardekani, Ashtari, Kumra, Robinson and Sevy2005), suggesting that they occur during development and are not secondary to the disease or its treatment. Recently, our group has begun to assess changes in DTI measures prior to the onset of schizophrenia, in an ultra high-risk (UHR) population. In a cross-sectional investigation, the hippocampus and temporal tracts have shown a very interesting pattern across adolescence and young adulthood in which healthy controls increase FA with age, while high-risk subjects fail to show the same increase. This pattern may indicate that the differences in some white matter tracts that are observable in adult schizophrenia patients arise gradually as a part of an abnormal process of white matter development in adolescence (Karlsgodt, Niendam, et al., Reference Karlsgodt, Niendam, van Erp, Poldrack, Nuechterlein and Cannon2008).

One white matter tract emerging as a point of particular interest given its role in supporting working memory is the superior longitudinal fasciculus (SLF), which is a primary connection linking the frontal and parietal lobes (Petrides & Pandya, Reference Petrides, Pandya, Stuss and Knight2002). The frontal and parietal cortices are critical for working memory (Chafee & Goldman-Rakic, Reference Chafee and Goldman-Rakic2000; Paulesu, Frith, & Frackowiak, Reference Paulesu, Frith and Frackowiak1993), and cellular activity in these regions during working memory processing has been shown to be coordinated (Chafee & Goldman-Rakic, Reference Chafee and Goldman-Rakic1998), suggesting that these regions function as a working memory network. Patients with schizophrenia show impairments in working memory (Lee & Park, Reference Lee and Park2005), and working memory deficits have been proposed to be a core feature of the illness, as they are associated with other cognitive processes (Silver, Feldman, Bilker, & Gur, Reference Silver, Feldman, Bilker and Gur2003), symptomatology (Goldman-Rakic, Reference Goldman-Rakic1994), and functional outcomes (Green, Reference Green1996). Moreover, the pattern of maturation of the white matter tracts between the frontal and parietal lobe regions correlates both with the pattern of maturation of working memory capacity and functional activation (Klingberg, Reference Klingberg2006), linking intact working memory performance to integrity of the entire circuit. Finally, FA in the SLF has been shown to be decreased in patients with schizophrenia (Federspiel et al., Reference Federspiel, Begre, Kiefer, Schroth, Strik and Dierks2006; Karlsgodt, van Erp, et al., Reference Karlsgodt, van Erp, Poldrack, Bearden, Nuechterlein and Cannon2008; Szeszko et al., Reference Szeszko, Robinson, Ashtari, Vogel, Betensky and Sevy2008).

This relatively new body of work using DTI as a measure to investigate abnormalities in schizophrenia has been growing rapidly. It is an important area to expand upon, given DTI's ability to investigate white matter microstructure in vivo longitudinally, and given that this safe, repeatable procedure enables study of the functional behavioral correlates of changes in connectivity during normal and abnormal brain development.

MRI of disrupted development in schizophrenia

Modern imaging findings have well established that schizophrenia is associated with structural brain abnormalities, with the most consistent findings being enlarged ventricles and reduced medial temporal, superior temporal, and prefrontal gray matter volumes (Pantelis et al., Reference Pantelis, Yucel, Wood, Velakoulis, Sun and Berger2005; Shenton, Dickey, Frumin, & McCarley, Reference Shenton, Dickey, Frumin and McCarley2001). Cross-sectional neuroimaging studies have shown gray matter volume deficits not only in established but also in prodromal (Borgwardt et al., Reference Borgwardt, McGuire, Aston, Berger, Dazzan and Gschwandtner2007; Pantelis et al., Reference Pantelis, Velakoulis, McGorry, Wood, Suckling and Phillips2003) and early stages of schizophrenia (Shenton et al., Reference Shenton, Dickey, Frumin and McCarley2001), suggesting that structural abnormalities exist at least in part before the onset of illness. Furthermore, abnormal brain asymmetry and cortical folding, signs of relatively early developmental deviations, have been found in schizophrenia patients (Nakamura, Nestor, et al., Reference Nakamura, Nestor, McCarley, Levitt, Hsu and Kawashima2007; Yucel et al., Reference Yucel, Stuart, Maruff, Velakoulis, Crowe and Savage2001). These findings are in accordance with the early neurodevelopmental model of schizophrenia (Weinberger, Reference Weinberger1995). At the same time, accumulating longitudinal neuroimaging data suggest that brain volume changes in schizophrenia are not restricted to early developmental stages, but may be progressive around the time of onset of frank symptoms (for a review, see Pantelis et al., Reference Pantelis, Yucel, Wood, Velakoulis, Sun and Berger2005), in line with the late developmental hypothesis of the illness.

Recent longitudinal studies using high-resolution MRI and advanced image analysis techniques have demonstrated progressive volume loss in various brain regions in schizophrenia patients. In a series of first-episode schizophrenia follow-up studies, DeLisi, Sakuma, Maurizio, Relja, and Hoff (Reference DeLisi, Sakuma, Maurizio, Relja and Hoff2004) and colleagues found accelerated lateral ventricular expansion over a 10-year period. Accelerated progressive ventricular expansion in patients at various stages of illness has also been reported by other researchers (Garver, Nair, Christensen, Holcomb, & Kingsbury, Reference Garver, Nair, Christensen, Holcomb and Kingsbury2000; Nair et al., Reference Nair, Christensen, Kingsbury, Kumar, Terry and Garver1997; Nakamura, Salisbury, et al., Reference Nakamura, Salisbury, Hirayasu, Bouix, Pohl and Yoshida2007). Progressive frontal volume loss was reported initially by Gur and colleagues (1998) in first-episode/chronic patients and subsequently replicated in several other studies (Ho et al., Reference Ho, Andreasen, Nopoulos, Arndt, Magnotta and Flaum2003; Lieberman et al., Reference Lieberman, Tollefson, Charles, Zipursky, Sharma and Kahn2005; Mathalon, Sullivan, Lim, & Pfefferbaum, Reference Mathalon, Sullivan, Lim and Pfefferbaum2001; Nakamura, Salisbury, et al., Reference Nakamura, Salisbury, Hirayasu, Bouix, Pohl and Yoshida2007; Rapoport et al., Reference Rapoport, Giedd, Blumenthal, Hamburger, Jeffries and Fernandez1999; Sun et al., in press; Thompson et al., Reference Thompson, Vidal, Giedd, Gochman, Blumenthal and Nicolson2001; van Haren et al., Reference van Haren, Pol, Schnack, Cahn, Brans and Carati2008). Excessive volume loss in the whole temporal lobe has been reported in several studies (Nakamura, Salisbury, et al., Reference Nakamura, Salisbury, Hirayasu, Bouix, Pohl and Yoshida2007; Rapoport et al., Reference Rapoport, Giedd, Blumenthal, Hamburger, Jeffries and Fernandez1999), and this finding seems largely attributable to changes in the superior temporal gyrus (Kasai, Shenton, Salisbury, Hirayasu, Lee, et al., Reference Kasai, Shenton, Salisbury, Hirayasu, Lee and Ciszewski2003; Kasai, Shenton, Salisbury, Hirayasu, Onitsuka, et al., Reference Kasai, Shenton, Salisbury, Hirayasu, Onitsuka and Spencer2003; Thompson et al., Reference Thompson, Vidal, Giedd, Gochman, Blumenthal and Nicolson2001).

The profile of brain volume decline in schizophrenia relative to the normal developmental profile was recently examined in a longitudinal study by our group in collaboration with the Melbourne group (Sun, Stuart, et al., in press). We applied cortical pattern matching (Thompson et al., Reference Thompson, Hayashi, de Zubicaray, Janke, Rose and Semple2003) in combination with fMRI of the brain structural image evaluation using normalization of atrophy (SIENA) to repeated MRI scans in first-episode schizophrenia patients and healthy controls, mapping local brain surface contractions throughout the lateral cortical surface. Significantly greater prefrontal surface contraction was found in patients compared with controls, consistent with previous findings of frontal progression mentioned above. More interestingly, patients and healthy controls demonstrated very similar anatomical patterns of brain surface contractions, both showing prominent prefrontal contraction, with that of the former group exaggerated in both magnitude and spatial extent (see Figure 3). Further analyses demonstrated that the surface contraction observed in prefrontal regions was driven by changes in gray matter volume. The similarity of surface contraction patterns between normal and diseased cohorts nicely fits the prediction of the hypothesis of synaptic overpruning in schizophrenia (Feinberg, Reference Feinberg1982; McGlashan & Hoffman, Reference McGlashan and Hoffman2000), indicating the involvement of late developmental deviations in the neuropathophysiology of schizophrenia.

Figure 3.

Maps of the average brain surface contraction rates and p-maps for comparison of first-episode schizophrenia patients versus healthy controls.

MRI of disease onset: Prodromal states

Despite the mentioned findings, the major difficulties in interpreting the longitudinal brain changes as primary pathological processes in schizophrenia are the inevitable existence of confounding factors secondary to the illness, which include long-term illness, medications, or fluctuation of symptoms. Even in longitudinal studies following first-episode patients, the reported duration of illness in the majority of studies were over 1 year at intake (Pantelis et al., Reference Pantelis, Yucel, Wood, Velakoulis, Sun and Berger2005), and antipsychotics were generally administered to control psychotic symptoms. All these factors are likely to bring changes to brain structures, and for ethical and practical reasons, these factors cannot be controlled in patients.

One strategy to address these questions is to identify individuals who are at heightened risk for developing psychosis because of mental state change and/or family history of psychosis, and to track brain changes from the premorbid stage to the onset of illness (Cannon et al., Reference Cannon, van Erp, Bearden, Loewy, Thompson and Toga2003; Johnstone et al., Reference Johnstone, Abukmeil, Byrne, Clafferty, Grant and Hodges2000; McGorry, Yung, & Phillips, Reference McGorry, Yung and Phillips2003). When some of these individuals experience a frank onset during follow-up, brain changes occurring around the time of onset can be assessed. This approach aims to observe brain changes at a very early prodromal stage, before full-blown psychosis emerges, thereby avoiding confounding factors related to long-term treatment and illness chronicity (Cannon et al., Reference Cannon, van Erp, Bearden, Loewy, Thompson and Toga2003). Indeed, if exaggerated brain volume loss is found during the prodromal phase of the illness, these changes may be involved in the onset of the disorder.

Although only a few longitudinal studies of high-risk individuals have appeared, their results corroborate the notion of preonset brain volume decline. In a 1-year follow-up study, Pantelis and colleagues (2003) examined brain changes in a cohort at UHR of psychosis determined by both state and trait criteria. They found progressive gray matter loss in left inferior frontal, medial temporal, and cerebellar regions and left and right cingulate regions in the high-risk individuals who later converted to psychosis (converters). In a 2-year follow-up study on individuals at high risk of schizophrenia for familial reasons, Job Whalley, Johnstone, and Lawrie (Reference Job, Whalley, Johnstone and Lawrie2005) reported gray matter loss in the temporal lobes, the right frontal lobe, and right parietal lobe in the high-risk subjects (converters and nonconverters), and left temporal and right cerebellar gray matter loss in the converters. However, no significant differences in brain volume changes were observed in either study in the comparisons of converters versus nonconverters. Furthermore, factors shared by the groups that could cause brain changes (e.g., transient psychotic states, drug use, and normal developmental factors) were not controlled, and therefore the question of whether progressive changes differ among converters, nonconverters, and healthy controls was not answered conclusively.

We recently reported on brain surface contraction in an expanded sample of the UHR cohort examined by Pantelis and colleagues (2003), using cortical pattern matching (Thompson et al., Reference Thompson, Hayashi, de Zubicaray, Janke, Rose and Semple2003) in combination with SIENA (Sun, Phillips, et al., in press). In a direct between-group comparison, converters showed a significantly greater surface contraction rate in right prefrontal regions when directly compared to nonconverters. This result largely excludes the possibility that progressive brain volume changes observed in schizophrenia/psychosis are due to long-term medication or illness chronicity, and strongly suggests that progression is a primary pathological process in psychosis and schizophrenia that possibly leads to the onset of full-blown symptoms. In addition, the brain surface contractions in the converters resembled the patterns found in healthy controls and first-episode schizophrenia patients in the above-mentioned study from our group (Sun, Stuart, et al., in press), indicating the continuous involvement of deviations of normal brain development in the pathology of schizophrenia from prodromal stages to early years of illness.

The high anatomical correlation between differential rates of surface contraction in homologous brain regions between healthy individuals, UHR converters, and schizophrenia patients suggests that more pronounced synaptic pruning occurs in regions that experience greater normal developmental changes in the late adolescent/early adult period. This finding may provide an explanation of the apparent differential involvement of prefrontal cortical changes in schizophrenia. The prefrontal region experiences the most pronounced developmental changes during late adolescence and early adulthood, and it is the region where anatomical and physiological changes have been most consistently observed in schizophrenia. In addition, this brain region plays a central role in working memory, executive function and other higher order cognitive functions, all of which are impaired in schizophrenia. It is also the prefrontal region that shows signs of reduced neuronal connectivity in postmortem studies (Glantz & Lewis, Reference Glantz and Lewis2000; Selemon et al., Reference Selemon, Rajkowska and Goldman-Rakic1995; Selemon, Rajkowska, & Goldman-Rakic, Reference Selemon, Rajkowska and Goldman-Rakic1998). Cortical mapping in twins discordant for schizophrenia shows both genetic and disease-specific influences on gray matter deficits in the prefrontal region (Cannon, Thompson, et al., Reference Cannon, Thompson, van Erp, Toga, Poutanen and Huttunen2002), and several susceptibility genes for schizophrenia have been associated with prefrontal structural and functional abnormalities (Cannon et al., Reference Cannon, Hennah, van Erp, Thompson, Lonnqvist and Huttunen2005; Egan et al., Reference Egan, Goldberg, Kolachana, Callicott, Mazzanti and Straub2001). It is conceivable that excessive synaptic pruning in schizophrenia results from inherited variations in genes that are involved in the normal pruning process, suggesting the testable hypothesis that progressive brain changes are associated with schizophrenia-related gene variations. In this regard, the disrupted in schizophrenia 1 (DISC1) gene is a promising candidate, as it has been linked to prefrontal gray matter deficit in schizophrenia (Cannon et al., Reference Cannon, Hennah, van Erp, Thompson, Lonnqvist and Huttunen2005).

Emotion and symptoms of schizophrenia

We know that complex structural changes occur across development and with the gradual onset of schizophrenia. The ramifications of these impairments in neural connectivity can be more easily conceptualized by considering the effects on complex functions that are known to rely on interconnected and communicating regions. For example, socioemotional information processing is a complex cognitive function that is reliant on a network of regions, which is disrupted in schizophrenia. Blunted emotional expression and avolition (diminished interest in work, social, or other goal-directed activities), are included among the negative symptoms, and are central characteristics of schizophrenia (American Psychiatric Association, 2000). Such symptoms tend to be pervasive and stable over time (Fenton & McGlashan, Reference Fenton and McGlashan1991) and are strongly associated with social or occupational functional impairment (Green, Kern, Braff, & Mintz, Reference Green, Kern, Braff and Mintz2000; Sayers, Curran, & Mueser, Reference Sayers, Curran and Mueser1996). Emotion processing is integrally related to social behavior as it facilitates both relationships and reciprocal communication. The basis of the social impairments associated with schizophrenia may be due to core social information processing deficits and, by extension, deficits in processing of emotion information (Penn, Corrigan, Bentall, Racenstein, & Newman, Reference Penn, Corrigan, Bentall, Racenstein and Newman1997).

The developmental emergence of emotional processing deficits is of particular interest, as emotional and social skills, particularly those involving self-regulation and expressivity, continue to develop into adolescence (Campos, Frankel, & Camras, Reference Campos, Frankel and Camras2004; Casey, Giedd, & Thomas, Reference Casey, Giedd and Thomas2000). The ability to regulate emotional reactivity is likely supported by maturation of frontal lobe regions such as the anterior cingulate and medial prefrontal cortex (Fuster, Reference Fuster2002; Posner & Rothbart, Reference Posner and Rothbart1998). This regulatory capacity may have important ramifications; regulatory skills in adolescence have been associated with increased resilience to adverse events (Buckner, Mezzacappa, & Beardslee, Reference Buckner, Mezzacappa and Beardslee2003), a finding that may inform investigations about different effects of environmental factors on at risk adolescents. It is possible that the excessive pruning or impaired myelination believed to occur in schizophrenia might interfere with the normal development of these emotional and social functions. The reliance of emotional processing on a widespread network of interactive regions makes it particularly vulnerable to even subtle insult in any implicated region or the connections between them. Consistent with this vulnerability, poor social role functioning, deficient social skills, and inadequate support networks are among the earliest reliable indicators of the disorder, consistently reported in pre-illness, prodromal, and recent-onset cases (Horan, Subotnik, Snyder, & Nuechterlein, Reference Horan, Subotnik, Snyder and Nuechterlein2006; Pinkham, Penn, Perkins, Graham, & Siegel, Reference Pinkham, Penn, Perkins, Graham and Siegel2007). Accordingly, social and role functioning have increasingly become high priority targets for assessment and treatment, especially in at-risk individuals and at early stages of the disorder (e.g., Cornblatt et al., Reference Cornblatt, Auther, Niendam, Smith, Zinberg and Bearden2007; Mueser & Bond, Reference Mueser and Bond2000).

Disruption of emotional processing in schizophrenia

Emotion processing is complex and involves several stages (e.g., Phillips, Drevets, Rauch, & Lane, Reference Phillips, Drevets, Rauch and Lane2003): appraisal, the identification of a stimulus as salient or self-significant (Campos et al., Reference Campos, Frankel and Camras2004; LeDoux, Reference LeDoux2000); experience, the production of a specific affective state (i.e., “feeling”) in response to an emotional stimulus (Phillips et al., Reference Phillips, Drevets, Rauch and Lane2003); expression, the conveyance (either verbal or nonverbal) of information regarding our affective state to others; and regulation, modulation and/or inhibition of this set of processes that is important for the contextual appropriateness of our affective states and subsequent behavior (e.g., Ochsner & Gross, Reference Ochsner and Gross2005). The impairments in perception of emotional and social stimuli observed in schizophrenia could implicate deficits in any of these areas. For example, individuals with schizophrenia have difficulty identifying emotional faces and affective prosody (Edwards, Pattison, Jackson, & Wales, Reference Edwards, Pattison, Jackson and Wales2001; Kohler, Reference Kohler2004). Likewise, flat affect or blunted emotional expressivity is a hallmark of the disorder (Shtasel et al., Reference Shtasel, Gur, Gallacher, Heimberg, Cannon and Gur1992), although impaired emotional expression is not necessarily concordant with reduced emotional experience (Berenbaum & Oltmanns, Reference Berenbaum and Oltmanns1992; Kring, Kerr, Smith, & Neale, Reference Kring, Kerr, Smith and Neale1993).

It is important that deficits in basic emotion perception may easily extend to impaired perception of social signals in general (e.g., Aghevli, Blanchard, & Horan, Reference Aghevli, Blanchard and Horan2003; Hooker & Park, Reference Hooker and Park2002). Deficits in theory of mind, the ability to appreciate the mental states of others, and empathy are commonly reported in patients (Lee, Farrow, Spence, & Woodruff, Reference Lee, Farrow, Spence and Woodruff2004). This coupling of impaired social cognition and perception may be critical to the interpersonal problems associated with schizophrenia (Brune, Reference Brune2005; Sergi et al., Reference Sergi, Rassovsky, Widmark, Reist, Erhart and Braff2007). Behavioral findings to date indicate that the full picture of socioemotional processing deficits in schizophrenia is anything but simple. Elucidating the complex neurobiological mechanisms and interacting brain regions implementing such processes is critical to a complete understanding of these deficits.

Neural bases of emotional processing

Extant literature on the neural correlates of emotion processing consistently implicates a network of subcortical brain regions as the seat of the emotional response (e.g., Burgdorf & Panksepp, Reference Burgdorf and Panksepp2006). It is this reliance on a group of interacting regions that make this domain an interesting probe of disrupted connectivity. Specifically, the amygdaloid complex is critical for automatic evaluation of incoming stimuli from primary sensory processing regions (via the thalamus) as well as cortical sensory association areas with which it has bidirectional connections (Aggleton, Reference Aggleton1993). The amygdala has been implicated as a site of primary appraisal of highly salient (e.g., fearful or threatening) stimuli in particular, but may also be influenced by and exert influence on perceptual, attentional, and memory functions of the cortex (for a review, see LeDoux, Reference LeDoux2000) and play a key role in the coordination of behavioral, neuroendocrine, and autonomic nervous system responses to threatening stimuli via efferent projections to the hypothalamus and brainstem (Holland & Gallagher, Reference Holland and Gallagher1999; Posner, Reference Posner2001). In line with the complexity of its reciprocal connections, research suggests that the amygdala may also play a role in processing predictive social signals, and as such, aids in resolving broad-spectrum biologically relevant associative ambiguities (Whalen et al., Reference Whalen, Shin, McInerney, Fischer, Wright and Rauch2001).

In addition to the fear response, positive emotional systems have also become an established area of inquiry (Seligman & Csikszentmihalyi, Reference Seligman and Csikszentmihalyi2000), and these are thought to rely on a complex network as well. Burgdorf and Panksepp (Reference Burgdorf and Panksepp2006) characterize two distinct classes of positive affect subserved by partially overlapping neuroanatomical networks as revealed by animal models and PET studies in humans: an appetitive (e.g., reward seeking) system involving the ventral striatal dopamine system and a consummatory system (e.g., hedonic tastes) involving the opiate and GABA system in the ventral striatum and orbital frontal cortex. Given the well-established role of dopamine dysregulation in schizophrenia (Davis, Kahn, Ko, & Davidson, Reference Davis, Kahn, Ko and Davidson1991), these data suggest important avenues for further research. PET and single-photon emission computerized tomography studies may be particularly suited for providing valuable information about various catecholamine and opioid neurotransmitter (NT) receptor characteristics and synaptic NT concentrations (Posner, Reference Posner2001). For example, several PET studies with converging evidence from rodent and nonhuman primate work implicate interactions between the amygdala and orbitofrontal cortex in reward expectancy and appetitive learning (see Holland & Gallagher, Reference Holland and Gallagher2004, for a review).

Moving toward a cohesive structural network model of emotion, several researchers have theorized that conscious perception of emotion may involve the recognition in working memory (implicating dorsolateral prefrontal cortex, orbitofrontal cortex, and anterior cingulate) of an immediately present stimulus that triggers both long-term explicit memories (involving diffuse cortical regions) and amygdala activation (LeDoux, Reference LeDoux1989, Reference LeDoux2000). Similarly, emotion regulation strategies such as attentional control and cognitive reappraisal are clearly processes of cognition–emotion interactions that may depend upon distinct neural systems acting in concert (e.g., Ochsner & Gross, Reference Ochsner and Gross2005; see also Lazarus, Reference Lazarus1991). Specifically, prefrontal and cingulate regions may exert inhibitory influence upon subcortical structures (Green & Malhi, Reference Green and Malhi2006), possibly mediated by medial prefrontal cortex (Lane et al., Reference Lane, Reiman, Bradley, Lang, Ahern and Davidson1997; Ochsner, Bunge, Gross, & Gabrieli, Reference Ochsner, Bunge, Gross and Gabrieli2002). Several neuroimaging studies have found decreased amygdalar activation with a corresponding increased right hemispheric ventrolateral prefrontal activation during affective labeling (Hariri, Bookheimer, & Mazziotta, Reference Hariri, Bookheimer and Mazziotta2000; Hariri, Mattay, Tessitore, Fera, & Weinberger, Reference Hariri, Mattay, Tessitore, Fera and Weinberger2003; Lieberman et al., Reference Lieberman, Eisenberger, Crockett, Tom, Pfeifer and Way2007), suggesting a potential brain mechanism for emotion regulation involving multiple interacting systems (see also Keightley et al., Reference Keightley, Winocur, Graham, Mayberg, Hevenor and Grady2003). Given this interactive inhibitory relationship, disruption in either of these regions or the white matter tracts connecting them could give rise to emotional processing deficits.

Our limited understanding of the neural networks involved in emotion processing clearly highlights an area that requires further research, and this need is especially evident as we try to translate our knowledge into explication of the possible neural underpinnings of deficits in social cognition in schizophrenia. As outlined previously, structural analyses of schizophrenia patients consistently reveal overall reductions in brain volume and cortical gray matter (Lawrie & Abukmeil, Reference Lawrie and Abukmeil1998; Mueser & McGurk, Reference Mueser and McGurk2004). These regions include areas implicated in the socioemotional circuitry, including the frontal lobes, amygdala, hippocampus, and thalamus (Andreasen et al., Reference Andreasen, Flashman, Flaum, Arndt, Swayze and O'Leary1994; Byne et al., Reference Byne, Buchsbaum, Mattiace, Hazlett, Kemether and Elhakem2002; Wright et al., Reference Wright, Rabe-Hesketh, Woodruff, David, Murray and Bullmore2000). In addition to gray matter changes specific to areas relevant to emotional processing, there is evidence for impaired connectivity between these regions. First, structural imaging provides evidence that decreases in prefrontal white matter volumes correlates with amygdala and hippocampal volumes in patients (Breier et al., Reference Breier, Buchanan, Elkashef, Munson, Kirkpatrick and Gellad1992) as well as findings that greater hippocampal pathology correlates with decreased prefrontal activity (Weinberger et al., Reference Weinberger, Berman, Suddath and Torrey1992). Second, there are DTI findings of decreased FA in schizophrenia patients in several relevant brain regions, including the prefrontal cortex (Buchsbaum et al., Reference Buchsbaum, Tang, Peled, Gudbjartsson, Lu and Hazlett1998; Hao et al., Reference Hao, Liu, Jiang, Gong, Liu and Tan2006; Kitamura et al., Reference Kitamura, Matsuzawa, Shioiri, Someya, Kwee and Nakada2005; Kumra et al., Reference Kumra, Ashtari, McMeniman, Vogel, Augustin and Becker2004; Lim et al., Reference Lim, Hedehus, Moseley, de Crespigny, Sullivan and Pfefferbaum1999; Minami et al., Reference Minami, Nobuhara, Okugawa, Takase, Yoshida and Sawada2003; Szeszko, Ardekani, et al., Reference Szeszko, Ardekani, Ashtari, Kumra, Robinson and Sevy2005), temporal lobe regions (Schlosser et al., Reference Schlosser, Nenadic, Wagner, Gullmar, von Consbruch and Kohler2007; White et al., Reference White, Kendi, Lehericy, Kendi, Karatekin and Guimaraes2007), and frontotemporal tracts such as the uncinate fasciculus (Burns et al., Reference Burns, Job, Bastin, Whalley, Macgillivray and Johnstone2003; Kubicki et al., Reference Kubicki, Westin, Maier, Frumin, Nestor and Salisbury2002; Nakamura et al., Reference Nakamura, McCarley, Kubicki, Dickey, Niznikiewicz and Voglmaier2005; Nestor et al., Reference Nestor, Kubicki, Gurrera, Niznikiewicz, Frumin and McCarley2004; Price et al., Reference Price, Cercignani, Parker, Altmann, Barnes and Barker2008; Szeszko et al., Reference Szeszko, Robinson, Ashtari, Vogel, Betensky and Sevy2008). Third, given the relationship of negative symptoms and socioemotional functioning, the correlation of decreased FA in the uncinate fasciculus to negative symptoms (Szeszko et al., Reference Szeszko, Robinson, Ashtari, Vogel, Betensky and Sevy2008) indicates that associations between emotional processing and uncinate integrity may be of interest.

Functional neuroimaging has been used as a probe of emotional processing deficits in patients; however, the existing literature is sparse and has yet to be organized into a coherent framework. Several fMRI studies have shown abnormal amygdalar activation in response to emotional faces in individuals with schizophrenia (Gur et al., Reference Gur, Loughead, Kohler, Elliott, Lesko and Ruparel2007; Kosaka et al., Reference Kosaka, Omori, Murata, Iidaka, Yamada and Okada2002). Williams and colleagues (Reference Williams, Das, Liddell, Olivieri, Peduto and David2007) found that facial expressions of fear, anger, and disgust abnormally increased autonomic arousal in patients (assessed via skin conductance response) but concurrent fMRI activity of the amygdala, insula, and anterior cingulate cortex were decreased compared to healthy controls. Taylor Phan, Britton, and Liberzon (Reference Taylor, Phan, Britton and Liberzon2005) found reduced fMRI activity in the amygdala and ventral striatum in response to both positive and aversive stimuli in patients with schizophrenia versus controls, although their prediction that these differences may be related to increased “tonic” activity in these regions in patients was not wholly supported. Future studies explicitly addressing the basis of socioemotional processing deficits by assessing functional connectivity of brain regions associated with each of the areas of emotion perception, expression, and regulation are needed, as are studies directly addressing white matter connections as related to such deficits.

Neuroimaging investigations of candidate genes

A number of risk genes for schizophrenia have been investigated using neuroimaging techniques to examine their effects on neural developmental processes, and their relationship to phenotypes associated with schizophrenia. Here we will briefly review a subset of these genes that have been investigated with respect to neuroimaging, development, and connectivity.

Genetic and environmental interaction

It is generally accepted that the effects of variations in any single gene are not likely to be highly influential in the disease process. Rather, genetic influences in schizophrenia and all other psychiatric illnesses do not directly alter the phenotype in a simple Mendelian manner, but are complex (multigenetic) in nature, such that a large network of small genetic variations may add and interact to produce the disruption of neural architecture that is behaviorally expressed as the schizophrenia syndrome.

Some of the developmental disruptions observed in patients with schizophrenia appear influenced by environmental rather than genetic factors. The most consistently reported environmental risk factors affecting early developmental processes in schizophrenia are obstetric complications (Clarke, Harley, & Cannon, Reference Clarke, Harley and Cannon2006). For example, hypoxic events appear to be among some of the most influential obstetric complications in the development of schizophrenia (Cannon, van Erp, et al., Reference Cannon, van Erp, Rosso, Huttunen, Lonnqvist and Pirkola2002). Fetal hypoxia has been found in several studies to both confer risk for schizophrenia and contribute to the brain abnormalities commonly associated with the early neurodevelopmental disturbances seen in probands (Buka, Tsuang, & Lipsitt, Reference Buka, Tsuang and Lipsitt1993; Dalman et al., Reference Dalman, Thomas, David, Gentz, Lewis and Allebeck2001; Murray et al., Reference Murray, Sham, Van Os, Zanelli, Cannon and McDonald2004; van Erp et al., Reference van Erp, Saleh, Rosso, Huttunen, Lonnqvist and Pirkola2002; Zornberg, Buka, & Tsuang, Reference Zornberg, Buka and Tsuang2000). The hippocampus in particular appears to be most influenced by environmental factors in schizophrenia and is highly vulnerable to hypoxic events (van Erp et al., Reference van Erp, Saleh, Rosso, Huttunen, Lonnqvist and Pirkola2002). Family studies have supported the idea of a gene–environment interaction, indicating that obstetric complications are most predictive of schizophrenia later in life, only in individuals who have a strong family history of psychosis (Cannon et al., Reference Cannon, Rosso, Hollister, Bearden, Sanchez and Hadley2000). In addition, many of the genes that have been implicated in the developmental process in schizophrenia, including BDNF, COMT, DTNBP1, NRG1, and RGS4, are also highly influenced by hypoxic events (Schmidt-Kastner, van Os, Steinbusch, & Schmitz, Reference Schmidt-Kastner, van Os, Steinbusch and Schmitz2006).

Later development is susceptible to environmental factors as well. There are a number of environmental risk factors that may not have clearly defined mechanisms, but that have been shown to contribute to risk for psychosis. These include life stress, immigrant status, living in an urban environment, and substance abuse (McDonald & Murray, Reference McDonald and Murray2000). One example getting much recent attention is cannabis use, which often begins during adolescence, and which may increase risk for schizophrenia (Arseneault, Cannon, Witton, & Murray, Reference Arseneault, Cannon, Witton and Murray2004; Veling, Mackenbach, van Os, & Hoek, Reference Veling, Mackenbach, van Os and Hoek2008). Gene–environment interactions with cannabis are beginning to be explored, but it is not yet clear the degree to which an interaction exists or with what particular genes cannabis may interact (Caspi et al., Reference Caspi, Moffitt, Cannon, McClay, Murray and Harrington2005; Veling et al., Reference Veling, Mackenbach, van Os and Hoek2008; Zammit et al., Reference Zammit, Spurlock, Williams, Norton, Williams and O'Donovan2007).

Taken together, these considerations suggest that for some, the genetic susceptibility to schizophrenia may only “come on-line” and result in the accompanying developmental disturbances when an individual is exposed to specific environmental influences. The exploration of how the environmental and genetic factors combine to influence normal developmental processes is an important direction of future research. Also important is exploring the differences between people who have similar risk factors but have differences in clinical or functional outcome. There may be differences in resilience to early insults based on either baseline differences that make the brain more robust or differences in plasticity, enabling it to better withstand insults (Cicchetti & Blender, Reference Cicchetti and Blender2006). Exploring these issues may bring us closer to understanding the complex interplay of events that unfold across development to lead to schizophrenia.