Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Neurosci Biobehav Rev. Author manuscript; available in PMC 2010 March 30.
Published in final edited form as:
PMCID: PMC2847441

A Role for White Matter Abnormalities in the Pathophysiology of Bipolar Disorder


Bipolar disorder is a chronically disabling psychiatric disorder characterized by manic states that is often interspersed with periods of depression whose neurobiology remains largely unknown. There is, however, increasing evidence that white matter (WM) abnormalities may play an important role in the neurobiology of the disorder. In this review we critically evaluate evidence for WM abnormalities in bipolar disorder obtained from neuroimaging, neuropathological, and genetic research. Increased rates of white matter hyperintensities, regional volumetric abnormalities, abnormal water diffusion along prefrontal-subcortical tracts, fewer oligodendrocytes in prefrontal WM, and alterations in the expression of myelin-and oligodendrocyte-related genes are among the most consistent findings. Abnormalities converge in the prefrontal WM and, in particular, tracts that connect prefrontal regions and subcortical gray matter structures known to be involved in emotion. Taken together, the evidence supports and clarifies a model of bipolar disorder that involves disconnectivity in regions implicated in emotion generation and regulation.

Keywords: bipolar disorder, white matter, diffusion tensor imaging

1. Introduction

Bipolar disorder (BD) is a serious affective illness that affects approximately 1.5% of the population (Angst, 1998; Narrow et al., 2002) and remains a leading worldwide cause of disability, morbidity, and mortality from suicide (Goodwin et al., 2007; Murray and Lopez, 1996). The disease is characterized by a recurrent and episodic course involving disturbances of mood, sleep, behavior, perception, and cognition (Goodwin and Jamison, 2007). BD has a spectrum presentation, with major subtypes of bipolar I and bipolar II, seemingly falling along a continuum of severity. According to current diagnostic categorization, patients with bipolar I disorder experience full mania, marked by symptoms of elated or irritable mood, reduced need for sleep, increased goal-directed activity, rapid speech, flight of ideas, and increased energy (DSM-IV, 1994). Additionally, in approximately 50% of bipolar I cases (DSM-IV, 1994), acute episodes are characterized by concurrent symptoms of psychosis, including auditory/visual hallucinations, and delusions that are typically focused around mood-congruent themes (i.e. religious preoccupations or manic beliefs in one’s own supernatural powers). Bipolar II patients have milder symptoms of mania which, by definition, do not involve psychosis, are typically shorter in duration, and do not significantly interfere with daily functioning. Both bipolar I and bipolar II subtypes experience intermittent major depressive episodes with sad mood, suicidal ideation, and changes in appetite, sleep, and energy, often interfering significantly with psychosocial functioning (DSM-IV, 1994). The notable heterogeneity in the clinical phenotype, including multiple subtypes (bipolar I, bipolar II) and several characteristics that are present only in a subgroup of patients (i.e. psychosis, cognitive impairment), complicate the attempts to elucidate the underlying pathophysiology of the illness.

Although the exact etiologies of bipolar disorder remain unknown, data from post-mortem, genetic, computed tomography (CT), positron emission tomography (PET), and magnetic resonance (MR) imaging studies provide evidence that brain abnormalities contribute to the disorder. The cause and significance of these abnormalities remain somewhat speculative, and findings are often contradictory. Recent models of BD (Adler et al., 2006b; Green et al., 2007; Lyoo et al., 2006; Phillips et al., 2003b; Phillips et al., 2008; Soares & Mann, 1997; Strakowski et al., 2005), however, suggest that the sometimes inconsistent and even contradictory findings involving abnormal brain anatomy, structure, and function may be understood within a framework of emotional dysregulation in circuits involving frontal cortical and limbic structures (Mayberg,1997). Several influential accounts of BD have suggested that the interplay between phylogenetically new cortical and phylogenetically old limbic regions is compromised in patients with BD and may be responsible for the core symptoms of the disease (Drevets et al., 1997; Mayberg et al., 1999; Strakowski et al., 2005). Dysregulation of various nodes in the limbic system may produce affective symptoms, including depression and mania. Limbic system structures include the amygdala, hippocampus and parahippocampal gyrus, ventral striatum, insula, anterior cingulate (ACC), and orbitofrontal cortex (OFC) (Mesulam and Guela,1988; Öngür and Price, 2000). The system is thought to reflect an evolutionary advance critical in the development of a distinctly mammalian CNS (MacLean,1990). The structures are involved in response to or appraisal of threat (amygdala), the integration of autonomic, affectively valenced information and behavioral “scripts,” especially as they relate to anticipated social outcome (ventral prefrontal cortex), autonomic processing, and affective and conflict monitoring (subgenual and dorsal cingulate). Because of reciprocal connectivity between these areas it is likely that both “top-down” and “bottom-up” dysfunction exists and brings about both the emotional dysregulation that characterizes the illness as well as the concomitant neurocognitive impairment that is common in BD

The majority of brain research in bipolar disorder has focused on the gray matter (GM). This is likely due to the fact that the white matter (WM), comprised of fiber tracts interconnecting cortical and subcortical GM, has been much more difficult to visualize and quantify than GM (see Figure 1). Alterations in WM tissue would likely have significant implications for the functioning of the brain as a whole, as it is the WM which serves as the circuitry and connective wiring of the brain. With the advent of techniques such as diffusion tensor imaging (DTI) and magnetic resonance spectroscopy (MRS) that allow for better quantification and characterization of the WM, it has become possible to move toward a connectivity-based model of brain abnormality that both supports and clarifies cortico-limbic models of emotional dysregulation.

Figure 1
Major white matter tracts

2. Models of BD

An abnormal relationship between the cortex and limbic structures as a basis for mood dysregulation was proposed by Mayberg (1997) as a general, adaptable framework for unipolar depression. Many recent reviews of neuroanatomical findings in BD suggest that this framework is useful for conceptualizing BD as well (Adler et al., 2006b; Bearden et al., 2001; Green et al., 2007; Haldane and Frangou, 2004; Lyoo et al., 2006; Phillips et al., 2003b; Phillips et al., 2008; Savitz and Drevets, 2009; Soares & Mann, 1997; Strakowski et al., 2005; Vawter et al., 2000). GM volumetric and metabolic abnormalities in regions such as the orbital frontal cortex, the subgenual anterior cingulate cortex, amygdala, hippocampus, striatum, and cerebellar vermis have been widely reported (see Savitz & Drevets, 2009 for a review) and suggest a pathophysiological mechanism that affects a wide network of structures.

Several researchers have proposed models that seek to define the specific networks that may be disrupted in BD (see Figure 2). The central feature of these models is deficient prefrontal modulation of subcortical and limbic structures. A disrupted anterior limbic network comprised of prefrontal-striatal-thalamic pathways as well as cerebellum and medial temporal limbic structures was proposed by Strakowski and colleagues (2005) as a model of BD. These authors proposed that abnormal modulation of the anterior limbic network by the prefrontal cortex may result in the mood dysregulation that characterizes the disorder. This model is consistent with findings of decreased modulatory control of the frontal cortex over the subcortical and temporal structures purported to be involved in mood regulation (e.g., Altshuler et al., 2005; Foland et al., 2008; Pavuluri et al., 2007). Subsequent models have generally built upon the notion of anterior limbic network disruption (Adler et al., 2006b; Green et al., 2007; Lyoo et al., 2006; Savitz and Drevets, 2009) and have incorporated additional altered networks.

Figure 2
Schematic representation of networks proposed to be disrupted in BD1

Phillips et al. (2008) have recently proposed a comprehensive neural model of BD that extends their previous work on both normal (Phillips et al., 2003a) and abnormal (Phillips et al., 2003b) emotion perception and regulation. This model focuses in particular on evidence that the OFC may serve as a mediator within the anterior limbic network between subcortical limbic regions involved in emotion perception and generation, and dorsal and lateral prefrontal regions involved in higher order processing of emotional information. In addition, the model proposes that the basis of mood dysfunction in BD may lie within circuits subserving automatic, as opposed to voluntary, emotional processes.

Subregions involved in automatic emotion regulation processes include the orbitofrontal cortex (OFC), subgenual anterior cingulate gyrus (sgACG), dorsal ACG and left rostral ACG, medial-dorsal PFC (MdPFC), and the hippocampus and parahippocampus. These GM regions have been extensively studied in BD, yet the WM connecting these regions has only recently become a focus of study. This is largely due to technological advances, such as diffusion tensor imaging (DTI), that allow for the quantification and visualization of WM fiber tracts. Recent evidence indicates that WM tracts connecting OFC and subcortical regions involved in emotion perception and generation are abnormal in BD (Figure 1). In this review we evaluate the evidence for WM abnormalities in the pathogenesis of BD from recently developed techniques, including DTI, and from other long-established methodologies to incorporate these findings into existing models.

3. Evidence from Neuroimaging Studies

3.1 White Matter Hyperintensities

An increased number and/or severity of white matter hyperintensities (WMH), which are hyper-intense bright spots that may be detected in T2-weighted and fluid-attenuated inversion recovery (FLAIR) MR images, is one of the most consistently reported abnormalities in bipolar disorder (Ahn et al., 2004; Altshuler et al., 1995; Aylward et al., 1994; de Asis et al., 2006; Dupont et al., 1990; Dupont et al., 1995; Figiel et al., 1991; Gulseren et al., 2006; Kempton et al., 2008; Lloyd et al., 2009; Lyoo et al., 2002; McDonald et al., 1991; McDonald et al.,1999; Moore et al., 2001a; Moore et al., 2001b; Pillai et al., 2002; Regenold et al., 2008; Silverstone et al., 2003; Swayze et al., 1990; Tamashiro et al., 2008; Woods et al., 1995), although several negative reports have appeared (Botteron et al., 1995; Breeze et al., 2003; Brown et al., 1992; Chang et al., 2005; Dolan et al., 1990; Krabbendam et al., 2000; Lewine et al., 1995; López-Larson et al., 2002; Persuad et al., 1997; Sassi et al., 2003; Strakowski et al., 1993b; Zanetti et al., 2008). Regarding these negative findings, however, Ahn et al. (2004) have pointed out that studies using thinner MR imaging slices, a larger sample size, and that have rated the severity of WMH, in addition to their presence or absence according to an established rating scale, tend to produce more consistent, positive results. In adults with BD, there is evidence for an association between more severe WMH and a greater number of hospitalizations and poorer response to treatment (Moore et al., 2001b; but see Breeze et al., 2003).

Traditionally, WMH have been classified by location into those that occur in the periventricular space (known as periventricular WMH) or in the deep WM (deep WMH). In unipolar depression (UD) and BD, increased deep WMH, but not necessarily periventricular WMH, have been frequently noted (Ahn et al., 2004; de Asis et al., 2006; Figiel et al., 1991; McDonald et al., 1999; Moore et al., 2001b; Regenold et al., 2008; Thomas et al., 2002a; Thomas et al., 2002b), although the opposite has also been reported (Altshuler et al., 1995). An association between increased rates of periventricular WMH and previous suicide attempts among patients with affective disorders has been reported (Pompili et al., 2008), suggesting that periventricular WMH may be potential neurological markers of suicidal behavior. Increased deep WMH in UD and BD are generally localized in the deep prefrontal and frontal white matter, suggesting disruption in the tracts connecting fronto-cortical and subcortical regions (Aylward et al., 1994; de Asis et al., 2006; Lyoo et al., 2002) and provide support for a model of BD featuring disruption along these tracts.

There are several possible causes of WMH, including ischemia, demyelination, edema, and gliosis, and it has been difficult to determine which cause or combination of causes might underlie particular incidences of WMH in both healthy groups and in patients with BD. In healthy adults, the presence of WMH is generally associated with advanced age and increased cardiovascular risk factors such as hypertension (e.g. Kirkpatrick and Hayman, 1987; O’Brien et al., 2006). Given that there is an association between increased cardiovascular risk factors and BD, it is possible that a common process confers vulnerability to both vascular sequelae and some subtypes of BD. Dos Santos et al. (2008) have suggested that perhaps elevated serum homocysteine levels, which were correlated with functional decline in BD (Osher et al., 2004) are one aspect of this common process. Complicating this picture are findings of increased WMH in BD samples relative to control samples after controlling for cardiovascular risk factors (e.g. McDonald et al., 1991; McDonald et al., 1999), as well as in pediatric BD samples (Lyoo et al., 2002; Pillai et al., 2002) although negative results have also been reported (Botteron et al., 1995; Breeze et al., 2003; Chang et al., 2005). In elderly depressed subjects, deep WMH are thought to be primarily ischemic in origin (Thomas et al., 2002a; Thomas et al., 2002b), whereas in healthy elderly controls, this is not necessarily the case. Thomas and colleagues (2002a, 2002b) have proposed that a small degree of loss in perfusion with increased age is normal, but that in depressed elderly patients, this loss in perfusion may be more severe, leading to ischemia.

More recently, late-onset BD has been associated with increased rates and severity of deep frontal WMH, suggesting that BD as well as UD may be a consequence of the interaction between advanced age and ischemia (Takahashi et al., 2008; Tamashiro et al., 2008; Zanetti et al, 2007). Tamashiro et al. (2008) have recently demonstrated that late-onset BD is associated with an increased number and severity of deep WMH relative to both healthy controls and, interestingly, age-matched early-onset BD patients, suggesting that late-onset BD is particularly associated with deep WMH and is likely to be a distinct subtype of the disorder. Some groups (e.g., Zanetti et al., 2007) have proposed that late-onset BD characterized by deep frontal WMH indicates that vascular mania may be a distinct clinical entity analogous to vascular depression (Alexopoulos et al., 1997). It may be that vascular depression and vascular mania are the result of similar ischemic processes that disrupt white matter tracts.

Inconsistent reports of laterality effects have been reported, with some studies reporting an excess of left-sided deep frontal WMH occurring in BD subjects relative to controls (Lloyd et al., 2009) and others reporting an excess of right-sided deep WMH (Gulseren et al., 2006). The WMH of unaffected siblings of patients with BD were investigated in one small study; results indicated that BD patients had increased WMH relative to their siblings and to controls, but that both the patient group and the sibling group had predominantly right-sided lesions relative to the control group, who tended to have more left-sided lesions (Gulseren et al., 2006). The investigation of unaffected siblings is a crucial but as yet relatively understudied line of research in characterizing the endophenotypic character of WMH in BD.

The presence and severity of WMH in healthy, elderly samples has been found to be correlated with decreased performance on a range of cognitive tasks (Gunning-Dixon & Raz, 2000), and this correlation has been reported in younger BD adults with WMH as well (Dupont et al., 1990; Dupont et al., 1995 but see Krabbendam et al., 2000). Although the etiology of WMH is not yet understood, research has provided evidence that the presence of WMH indicates disruption in the WM fiber (Leuchter et al., 1994; Soares and Mann, 1997; Taylor et al., 2001). More specifically, some types of WMH may be indicative of early localized demyelination (Hajek et al., 2005).

An inverse correlation between WMH and intracellular pH, as well as a positive correlation between WMH and an elevated phosphodiester peak, has been reported in a sample of euthymic, drug-free BD patients (Kato et al., 1998). The authors noted that these metabolic abnormalities arose not from the WMH themselves, which were generally mild, but from the surrounding, normal-appearing tissue. This finding provides empirical support for the hypothesis that WMH are markers of a generalized neuropathophysiologic process in at least a subsample of BD patients. Although the significance of decreased intracellular pH is not clear, the authors proposed that it may signify an ischemia-induced excess of lactate in the tissue surrounding WMH; alternatively, they suggested that it may indicate an alteration in the Na+/H+ exchanger (Kato et al., 1998).

Increased deep WMH have been found to distinguish patients with BD from patients with schizophrenia (SCZ) as well as from healthy controls (Regenold et al., 2008) This same study found significant correlations between deep WMH volume and cerebrospinal fluid (CSF) concentrations of both sorbitol and fructose in the BD group, but not in the SCZ or control groups. Taken together with evidence that diabetes mellitus is associated with BD, this study indicates that abnormalities in glucose metabolism are associated with BD, or at least the subset of BD patients who exhibit WMH. Abnormal glucose metabolism was also found to be associated with a measure of treatment resistance in this sample. In a subsequent study, this group demonstrated that a sample of BD and SCZ patients exhibited increased CSF lactate concentrations relative to a control group (Regenold et al., 2009). The authors suggest that this finding provides further evidence for abnormal glucose metabolism in at least a subset of patients with BD and SCZ and points specifically to mitochondrial dysfunction, a mechanism of psychiatric disease, and BD in particular, that has been receiving much attention in recent years (Kato & Kato, 2000; Quiroz et al., 2008; Shao et al., 2008; Stork & Renshaw, 2005). Further investigation is required to evaluate the possible connections between WMH, BD, and mitochondrial dysfunction, a line of research that appears to be promising in identifying subtypes of BD that may respond to metabolic therapy as well as elucidating the pathophysiology of this disorder.

Recent evidence suggests that valproate therapy may attenuate the formation of WMH by activating the Notch signaling pathway, a cascade which plays an important role in cell fate determination and vasculogenesis (Yuan et al., 2009). This research grew out of the realization that WMH are quite similar in appearance to the lesions associated with the cerebral autosomal dominant arteriopathy with subcorticial infarcts and leukoencephalopathy (CADASIL) syndrome, a hereditary stroke disorder marked by changes in mood, progressive dementia, migraine, and stroke (e.g., Chabriat et al., 1995; Joutel et al., 1996; Yuan et al., 2009). CADASIL is now known to be caused by mutations in Notch3 that ultimately lead to the progressive deterioration of vascular smooth muscle cells in the brain. It may be that the WMH seen in a subset of BD patients are a result of a less severe alteration in the Notch pathway. Given this speculation, it is interesting to note that valproate, commonly used to treat BD, has been shown to be related to the attenuation of Notch signaling abnormalities (Yuan et al., 2009).

It is important to note that WMH are nonspecific factors that do not appear to be present in all BD patients, and that any consistent and unique characteristics of the subsample of BD patients with WMH remain to be elucidated. Increased WMH have been demonstrated in BD I relative to BD II (Altshuler et al., 1995) and in poor outcome relative to good outcome BD (Moore et al., 2001b; Regenold et al., 2008), although the majority of studies have not assessed these characteristics or have not found such correlations. Although the exact cause and significance of WMH in general and in BD specifically are not currently known, the reported preponderance of WMH in BD is a strong indication that WM abnormalities are present in the disorder, and that they appear most robust in WM comprising frontocortico-limbic pathways.

3.2 Structural MR Imaging Studies

Studies that have assessed WM through structural volumetric imaging have provided evidence of subtle abnormalities in patients with BD compared to healthy volunteers. Some investigators reported a non-significant trend toward reduced cerebral WM in patients with bipolar disorder compared to controls (Strakowski et al., 1993a; Rosso et al., 2007), and, interestingly, reported an association between gross WM volume and amgydala volume in first-episode patients, but not in controls (Rosso et al., 2007). The majority of traditional volumetric studies that have sought to measure total cerebral WM volume in BD have reported no differences between BD samples and controls (Atmaca et al., 2007; Beyer et al., 2009; Brambilla et al., 2001; Lim et al 1999; Sassi et al., 2002; Zipursky et al.,1997), although there have been some findings to the contrary (Davis et al., 2004). Studies that have used methods that are sensitive to regional differences in WM volume, such as voxel-based morphometry (VBM) and region-of-interest (ROI) analyses have produced mixed results, however (see Table 1).

Table 1
Volumetric Studies of White Matter in Bipolar Disorder

Voxel-based morphometry allows for the examination of differences in tissue volume and/or density throughout the brain without restricting analyses to pre-defined regions (Ashburner and Friston, 2000). Using this methodology, several groups have reported regional WM deficits in BD samples relative to controls (Bruno et al., 2004; Farrow et al., 2005; McDonald et al., 2005; McIntosh et al., 2005; Stanfield et al., 2009) whereas others have not found any differences (Lyoo et al., 2004; Sarnicola et al., 2009). Volumetric deficits have been found in frontal and parietal WM in first-episode patients relative to controls (Farrow et al., 2005), and in distributed regions throughout the brain in chronic BD samples (McDonald et al., 2005). Several studies have reported reductions in WM density in patients compared to controls in prefrontal WM (Bruno et al., 2004; McIntosh et al., 2005; Stanfield et al., 2009) although there have been negative reports as well (Lyoo et al., 2004). Some groups have found that WM volume reductions are restricted to familial BD (McIntosh et al., 2005).

Subregional investigations of WM volume have reported deficits in bilateral superior temporal gyrus in pediatric BD (Chen et al., 2004) and in prefrontal WM in an adult BD sample (Haznedar et al., 2005). These latter findings are in contrast to those of Lopéz-Larson and colleagues (2002), in which no volumetric differences were found in prefrontal or paracingulate WM between patients and controls.

The most-studied WM subregion in BD is the corpus callosum (CC), the largest WM tract that connects the two hemisheres of the brain. Among studies that have measured the volume of the CC in BD samples relative to controls, most have found that the CC is smaller in BD (Arnone et al., 2008; Atmaca et al., 2007; Brambilla et al., 2003; Coffman et al., 1990 but see Hauser et al., 1989; Walterfang et al., 2009b). A recent study found that lithium-naïve BD patients had significantly less CC area than lithium-treated BD patients as well as controls, suggesting that CC deficits may be ameliorated by lithium treatment (Walterfang et al., 2009a). This study also found that length of illness was negatively correlated with CC midbody area among the entire BD group. Several groups have found decreased CC signal intensity in adult (Brambilla et al., 2004) and pediatric (Caetano et al., 2008) BD samples. A decrease in CC signal intensity may reflect an increase in water content in these regions, which in turn may result from decreased myelination. Yasar and colleagues (2006) found a decrease in the circularity of the splenium of the CC in a sample of pediatric patients with BD relative to controls, suggesting that CC abnormalities begin early in the course of the disorder and, given the preponderance of evidence for adult CC abnormalities, are likely to progress.

Recent work has been directed at identifying neuroanatomic correlates of genetic risk for BD, and WM abnormalities have consistently emerged as endophenotypes. In a study that investigated patients with bipolar disorder and their unaffected twins, both members of the twin pair were found to have a decrease in left hemisphere WM volume relative to controls (Kieseppä et al., 2003). McDonald and colleagues (2004) found that genetic risk for developing BD was significantly associated with WM volume deficits throughout the brain, including in bilateral prefrontal regions. Negative reports have also appeared (McIntosh et al., 2006). Recently, van der Schot et al. (2009) demonstrated that a lobar WM decrease in BD is genetically mediated, thus supporting the hypothesis that WM abnormalities are involved in the pathophysiology of BD.

Taken together, the evidence suggests that WM abnormalities appear to exist in BD, but are more likely to reflect subtle alterations in contrast to gross volumetric abnormalities. These subtle alterations may require more sensitive imaging techniques to better understand their role in the neurobiology of BD.

3.3 Magnetic Resonance Spectroscopy Studies

Magnetic resonance spectroscopy (MRS) is a specialized form of MRI in which the chemical properties of the tissue are analyzed, in addition to the structural properties. Specifically, MRS provides measures of concentrations of various metabolites in brain tissue. The large variation in techniques and approaches in MRS imaging makes it difficult to compare the results of individual studies; at the same time, the variation in techniques allows for a wide range of positive and negative findings that are potentially reconciled by the fact that experimental designs differ so greatly. To date, relatively few MRS studies have been carried out in bipolar disorder, and those that have been conducted have tended to focus on GM structures.

Of the few studies that have used MRS to investigate WM directly, many have reported negative results for WM abnormalities in patients with bipolar disorder (Blasi et al., 2004; Friedman et al., 2004; Frye et al., 2007), although GM abnormalities are frequently found (Stoll et al., 2000) (see Table 2). Dager and colleagues (2004) found that choline, creatine, N-acetyl aspartate, myoinositol, and lactate concentrations were unchanged in the frontal and parietal WM of unmedicated BD patients. Unmedicated BD II patients demonstrated an elevation in glutamate, glutamine, and GABA (measured aggregately as Glx) in frontal WM relative to controls, although unmedicated BD I patients did not show this elevation (Dager et al., 2004). This group also found that, across participants, depression scores on the Hamilton Depression Rating Scale (Hamilton, 1960) were inversely correlated with WM concentrations of creatine and phosphocreatine.

Table 2
Magnetic Resonance Spectroscopy Studies of White Matter in Bipolar Disorder

A higher concentration of glutamate/glutamine has been reported in orbital-lateral WM in patients with BD I experiencing either a manic or a mixed episode relative to controls (Cecil et al., 2002). Although the clinical significance of this finding is not yet understood, the authors point out that the concentration of these amino acids was significantly negatively correlated with duration of valproate therapy. This finding is consistent with reports that both lithium and valproate increase the reuptake of glutamate (Dixon et al., 1997;1998). It is not clear how this result may relate to that of Dager et al. (2004), in which unmedicated patients with BD II but not BD I demonstrated elevated Glx in frontal WM. It may be that an increased concentration of amino acids in the prefrontal WM is an underlying substrate of some types of BD. Consistent with this idea, Öngür et al. (2008) recently reported evidence for an elevated glutamine/glutamate ratio in the anterior cingulate cortex and in the parieto-occipital cortex in acutely manic BD patients, relative to both acutely psychotic SCZ patients and matched controls. These results did not covary with medication status, although it is not possible to rule out such effects. The authors suggested that this result could be indicative of glutamatergic overactivity as well as abnormal neuronal-glial interactions, and that both mechanisms could be operating in combination. Further evidence for amino acid concentration abnormalities in frontal WM comes from a recent p-MRS study by Port and colleagues (2008), in which decreased glutamine/glutamate concentrations were found in the WM of the dorsolateral PFC. This pattern of increased orbital and decreased dorsal concentrations of amino acids in prefrontal WM needs to be replicated and may indicate a system of abnormal glumatergic functioning in prefrontal WM pathways. Further MRS investigation of WM is required to fully examine neuronal-glial interactions in BD. Few MRS studies have examined WM in BD, though information regarding the molecular profile of this tissue is critically important in furthering our understanding of this disorder.

3.4 Magnetization Transfer Imaging Studies

Magnetization transfer (MT) imaging is another specialized form of MRI that permits the detection of myelin and axonal abnormalities, even in the absence of volume loss (Bruno et al., 2006, van Buchem and Tofts, 2000). This technique is therefore sensitive to changes in the myelin sheath that are not detectable by traditional MRI. MT imaging quantifies tissue abnormalities through the magnetization transfer ratio (MTR), an index of macrostructural integrity. In white matter, the degree to which MTR is reduced has been found to correlate with neuronal integrity (Pendlebury et al., 1999), as well as with the degree of myelin and/or axonal loss in the WM (van Buchem and Tofts, 2000). To date, only two studies have applied MT imaging to the study of bipolar disorder, both by the same group. Bruno et al. (2004) conducted the first study to assess WM integrity using MT imaging in BD. This study provided evidence that the MTR is significantly reduced in the right subgenual portion of the anterior cingulate and in the subgyral WM surrounding this area in patients with bipolar disorder relative to controls (Bruno et al., 2004). Given that the anterior cingulate is believed to be involved in a wide range of executive and emotional functions, and damage to this area has been shown to result in dysregulated emotional responses (Damasio, 1997), the finding that the WM subserving this region is abnormal lends support to a model of bipolar disorder featuring WM disconnectivity in regions involved in emotion generation and regulation. As noted above, this study also found a reduction in WM density in prefrontal areas bilaterally. On the right side, this area of reduced WM density overlapped with, but was not identical to, the area of reduced MTR observed through the analyses of the MT images. The authors speculated that, while the areas of abnormality identified through the two different procedures (MTI and VBM) and analyses were not identical, the fact that both areas overlapped and are part of a larger frontostriatal connectivity pathway that is involved in emotional functioning may be noteworthy.

In terms of the functional correlates, Bruno et al. (2006) correlated MTR reduction with an index of decreased cognitive functioning. The authors administered a battery of cognitive tests designed to assess premorbid and current IQ to a subsample of patients from their original MT imaging study (Bruno et al., 2004) as a means of examining the relationship between MTR and IQ decline. Several brain areas were found in which MTR reduction was significantly correlated with IQ decline, but these areas were only significant for patients with BD II; this is perhaps related to the finding that IQ decline was greater among this subset of patients than it was among patients with BD I. The areas in which IQ decline correlated with MTR reduction in BD II patients included those areas found to have significant MTR reduction relative to controls in the previous study (Bruno et al., 2004): the right subgenual anterior cingulate cortex and the adjacent white matter. However, additional locations of correlation between IQ reduction and MTR reduction were observed in these patients: the right superior and middle temporal gyri and the adjacent subgyral white matter, the right cingulate gyrus and the adjacent white matter, and regions within the frontal and parietal WM (Bruno et al., 2006). Thus, the regions that showed a significant correlation between myelin and axonal abnormalities and IQ reduction were all areas that have previously been implicated in cognitive functioning. Ideally, longitudinal studies would best address the issue of cognitive decline and its neuropathological correlates in bipolar disorder.

3.5 Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) provides a measure of WM integrity and microstructure that is potentially more sensitive than traditional T1-weighted imaging. DTI measures the movement of water molecules within the brain as a means of assessing the coherence of brain tissue. DTI also allows for the potential to investigate WM macrostructure through the visualization of fiber tracts. Three indices of WM integrity are commonly reported in DTI studies: the apparent diffusion coefficient (ADC), mean diffusivity (MD) and fractional anisotropy (FA). ADC is an index of the degree to which water freely diffuses within a brain region. Within the neuronal white matter, a greater degree of axonal myelination and/or axonal density is thought to be associated with lower ADC; that is, an increase in myelinated axonal fibers results in restricted water diffusion. Likewise, local brain regions with known axonal demyelination and/or axonal loss have been shown to have higher ADC (Beaulieu, 2002). MD is related to ADC and is simply the mean diffusion occurring within a given voxel or brain region. FA is an index of the preferential diffusion of water parallel to the main fiber orientation relative to other directions. That is, the micro- and macrostructure of the axons and axonal bundles of the WM influence water diffusion; FA quantifies the preferential diffusion of water in one direction (i.e. parallel to the main fiber orientation) relative to the restricted diffusion in all other directions. Thus, FA values can range from 1 (indicating completely anisotropic diffusion) to 0 (indicating completely isotropic diffusion).

To date, several DTI studies have been used to investigate the pathophysiology of BD (see Table 3). During the relatively short time that DTI has been used in research studies, several methodological innovations have already been implemented (for reviews, see Assaf & Pasternak, 2008; Mori et al., 2009). The analysis of the diffusion tensor allows for the visualization of fractional anisotropy color maps, in which the directionality of each tract is color-coded (e.g., anterior-posterior tracts are colored green, inferior-posterior tracts are blue, left-right tracts are red, etc). Visualization of the color map allows for more precise localization of clusters of significant voxels, as well as the ability to isolate specific tracts for post-hoc analyses. Voxelwise analysis of DTI data allows for brain-wide exploration of diffusion without constraining the analysis to pre-determined ROIs. An additional development in DTI has been the ability to estimate tractography using either probabilistic or deterministic algorithms. Tractography is used in several general ways: one is for the estimation of tracts passing through a specified ROI or significant cluster of voxels, which allows for the visualization and quantification of estimated tracts along which an abnormality is suspected or identified; another application of tractography is to specify two or more seed regions within the brain and to allow a tractography algorithm to propogate between the two regions. This allows for an estimation of fiber pathways that may exist between these regions and the ability to analyze the microstructural properties (i.e., FA, ADC) of these estimated pathways. A third major innovation in DTI which has been applied to the investigation of BD is tract-based spatial statistics (TBSS; Smith et al., 2006). TBSS overcomes some of the problems in registration and spatial smoothing of DTI data associated with voxelwise analyses of such data and enables local cross-subject comparisons (Smith et al., 2006). We now review the findings that have been reported in studies of BD using each of these approaches (Table 3). We then discuss some of the limitations of and future directions in DTI studies in BD.

Table 3
Diffusion Tensor Imaging Studies in Bipolar Disorder

3.5.1. Region of interest-based approaches

The first report of diffusion abnormalities in BD using DTI found lower FA in regions of prefrontal WM in BD compared to healthy controls (Adler et al., 2004), providing evidence that WM tracts connecting the prefrontal cortex with subcortical areas and other cortical structures are abnormal in patients with BD. More recently, the same group examined ADC and FA in similarly placed regions of interest among a sample of medication-naïve adolescents with BD experiencing their first episode of mania and found similar results (Adler et al., 2006a). This evidence suggests that prefrontal-subcortical WM abnormality is not a result of medication, and that it is present early in the course of the disorder. A sample of pediatric BD patients was found to have lower FA in the anterior corona radiata as well as greater ADC in the splenium of the corpus callosum (Pavuluri et al., 2009), supporting the existence of WM abnormalties in early-onset BD.

Several other groups employing ROI-based methodology reported diffusion abnormalities in prefrontal-subcortical WM (Beyer et al., 2005; Haznedar et al., 2005; Pavuluri et al., 2009; Wang et al., 2008a; Wang et al., 2008b; Yurgelun-Todd et al., 2007). Altered FA has been reported in distributed regions of prefrontal-thalamic-subcorticial WM (Haznedar et al., 2005) in a sample of BD spectrum (subtypes I, II, and cyclothymia) patients. Lower FA has been found in the orbitofrontal cortex (Beyer et al., 2005), anterior cingulum (Wang et al., 2008a), and the genu (Yurgelun-Todd et al., 2007; Wang et al., 2008b), rostral body, and anterior midbody of the CC (Wang et al., 2008b) in adult BD samples. These latter results are consistent with previous reports of volumetric deficits and lower signal intensity in the CC in BD (Arnone et al., 2008; Atmaca et al., 2007; Brambilla et al., 2003; Brambilla et al., 2004; Caetano et al., 2008; Coffman et al., 1990). Decreased FA in the anterior, but not posterior cingulum in BD (Wang et al., 2008a) is consistent with findings that suggest the anterior, but not necessarily the posterior, cingulate is directly involved in emotional functioning and perception (Phillips et al., 2003a, 2003b, 2008).

3.5.2. Voxelwise approaches

Whole-brain voxelwise analyses allow for the assessment of DTI data across the entire brain without necessarily restricting analyses to hypothesis-driven regions of interest. Despite the removal of regional constraints in whole-brain voxel-wise analyses, each study that has used this approach to investigate diffusion in BD has found evidence for diffusivity abnormalities in prefrontal-subcortical WM in children (Fraizer et al., 2007), adolescents (Barnea-Goraly et al., 2009; Kafantaris et al., 2009) and adults with BD (Bruno et al., 2008; Chaddock et el., 2009; Mahon et al., 2009; Sussman et al., 2009; Versace et al., 2008; Wessa et al., 2009; Zanetti et al., 2009). With the use of colormaps and/or tractography, diffusion abnormalities identified through whole-brain studies have been localized to specific white matter tracts (Table 3 and Figure 1). The majority of tracts along which diffusion abnormalities have been reported are those that connect regions within the anterior limbic network, suggesting that WM connections between these regions are an important component of the pathophysiology of BD.

Recent evidence suggests that mood state may have an effect on WM microstructural abnormalities in BD (Zanetti et al., 2009). A sample of currently-depressed BD I patients was found to have extensive diffusion abnormalities compared to currently-remitted BD I patients, particularly in ventromedial PFC WM and distributed association and projection tracts within the right hemisphere. This result suggests that mood episodes are marked by subtle yet detectable anatomical changes. The authors speculate that these changes may be related to an aberrant inflammatory process occurring in acute mood states in BD, a mechanism that has been proposed by several other groups (see Brietzke and Kapczinski, 2008 for a review).

Consistent with evidence suggesting that WM volume is both abnormal and highly heritable in BD, evidence that genetic liability to BD is associated with abnormal FA has been reported (Chaddock et al., 2009; Frazier et al., 2007). In a sample of adults with BD, their unaffected relatives, and healthy controls, genetic liability to develop BD was associated with decreased FA within extensive regions of the brain including bilateral uncinate fasciculus, deep prefrontal WM, cerebellum, superior longitudinal fascisulus, and corpus callosum (Chaddock et al., 2009). Frazier et al. (2007) reported that children at-risk for developing BD had lower FA in bilateral superior longitudinal fasciculus compared to a sample of control children. Abnormal WM microcircuitry, in addition to WMH, appears to be a potentially valid endophenotypic marker for at least a subset of BD cases. Further evaluation of WM diffusion as an endophenotype is likely to yield useful information regarding the pathophysiology of BD. Tract-based spatial statistics

One of the major limitations of voxelwise analysis of DTI data is that of potential misregistration leading to partial volume effects and/or misinterpretation of crossing fibers. In the context of traditional voxelwise analysis, it is not possible to know if a result of lower FA is due to a genuinely greater level of isotropic diffusion along a uniformly directed tract, the result of misregistration or an area of crossing fibers thus lowering the anisotropic diffusion of water more generally. In the first case, an interpretion of diffusion abnormality is supported whereas in the latter two, abnormality cannot be assumed. Tract-based spatial statistics (TBSS; Smith et al., 2006) partially overcomes these problems by registering each image to the same mean FA tract skeleton comprised of the center of each tract. Analyses are then conducted within the tract skeleton so that the likelihood of partial volume effects is much lower than in traditional voxelwise analysis.

To date, three studies have used TBSS to examine WM in BD. Lower FA in prefrontal-thalamic tracts was reported in a sample of adolescents with familial BD I using TBSS (Barnea-Goraly et al., 2009). Additional areas of lower FA in patients included distributed regions of the corpus callosum as well as in the fornix, the corona radiata, and a left mid-posterior portion of the cingulate. Two separate studies reported higher FA in left frontal tracts in patients compared to controls (Versace et al., 2008; Wessa et al., 2009). In a sample of euthymic patients, Wessa and colleagues reported higher FA in left frontal WM, as well as in bilateral occipital and parietal WM. These findings were replicated using traditional voxel-based methods as well. Versace et al. (2008) reported higher FA in regions in the orbito-medial PFC along the left uncinate fasciculus and decreased FA along the right uncinate fasciculus in patients compared to controls. Furthermore, increased FA along the left uncinate fasciculus was driven by an increase in longitudinal diffusivity (i.e., increased diffusivity along the main fiber direction), along with reductions in radial diffusivity (i.e., decreased diffusivity in directions other than along the main fiber direction). The authors noted that this finding is consistent with an increase in longitudinally aligned fibers of the uncinate fasciculus, along with a decrease in obliquely oriented fibers of this tract. Decreased FA in the right UF was driven by an increase in radial diffusivity in the absence of any significant change in axial diffusivity. The authors suggested that such increased radial diffusivity may indicate an increase in the number of obliquely oriented fibers, although they noted the possibility that local inflammation could also account for decreased FA driven by increased radial diffusivity. The same study reported higher FA in the left optic radiation and the right anterior thalamic radiation. Subgroup analyses revealed lower FA in the left uncinate fasciculus among BD subjects with a history of lifetime alcohol and/or substance abuse compared to BD subjects without such a history, as well as lower FA in the left optic radiation and right anterior thalamic radiation in BD patients receiving mood stabilizers versus those who were not. Acute mood state also contributed to diffusion abnormalities in that depressed BD patients had lower FA in the left optic radiation relative to remitted BD patients. These data thus highlight the importance of investigating the effects of clinical state and medications on diffusion measures.

3.5.3 Tractography

Given the theoretical importance and empirical evidence of abnormalities along WM tracts that connect prefrontal and subcortical regions, several groups have used tractography to estimate the number and microstructural properties of such tracts. Using fiber tractography, Houenou et al. (2007) investigated the uncinate fasciculus, the WM tract connecting the subgenual cingulate and the amgydala-hippocampal complex, in a sample of BD patients and matched controls. The tractography algorithm produced significantly more estimated fibers along the left uncinate fasciculus in patients relative to controls; there were no differences in the number of estimated fibers on the right side, nor were there any differences between the groups in the FA or ADC along the reconstructed fibers on either side. It may be that the usual right greater than left asymmetry of the uncinate fasciculus found in healthy individuals (Highley et al., 2002) is altered or reversed in BD. This result is notable not only for the implications it may have for abnormal frontal-limbic connectivity in BD, but also for providing evidence that WM tract alterations may still be present even in the absence of significant findings in traditional diffusion indices such as FA and ADC. McIntosh et al. (2008) used probabilistic tractography to investigate diffusivity along the uncinate fasciculus and portions of the anterior thalamic radiation in a sample of patients with familial SCZ or BD, as well as matched controls. In contrast to Houenou et al. (2007), FA was found to be significantly lower along both the uncinate fasciculus and the anterior thalamic radiations bilaterally and in both patient groups relative to controls. Despite the differences in the particular findings in these two studies, the consistency of altered uncinate fasciculus diffusivity in BD relative to controls reported in both indicates that this region should be a focus of future investigation in BD. The lack of specificity to BD in the latter study suggests that uncinate fasciculus abnormalities may be a common feature of both BD and SCZ with larger neurobiological implications.

3.5.4 Limitations of DTI and Future Directions

A limitation of many studies reported to date is the potentially insufficient number of directions that are sampled in the acquisition. Jones (2004) has provided evidence that at least 20 orientations are required to achieve robust estimations of anisotropy and that at least 30 orientations are required to estimate MD as well as the directionality of the tensor. Eight of the 21 DTI studies in BD conducted to date have acquired 6 orientations to estimate FA, and only 7 studies have acquired 30 or more orientations (Table 3). Future studies that wish to estimate FA or tractography should include an adequate number of directions to permit proper assessments. Another important consideration in DTI analyses is that of using age as a covariate, especially when examining patient populations (e.g., Jones et al., 2006).

It is important to acknowledge that DTI results provide evidence for abnormalities without concomitant information about what may be driving such an effect. For example, lower FA and higher ADC values have been identified in patients with demyelinating diseases such as multiple sclerosis relative to healthy controls (Ge et al., 2005). Axonal demyelination, however, is just one of several possible causes that can result in decreased FA (Beaulieu, 2002); damage to and/or disruption of the axonal tract, neuronal loss, or a less rigidly oriented or less coherent alignment of axonal organization within the fiber bundles of the WM may also yield decreased FA (Moeller et al., 2007; Song et al., 2003). Thus, findings of abnormal FA in either direction that are not followed up by definitive post-mortem investigations should be interpreted with caution.

An additional limitation of DTI is that one cannot infer whether a particular WM fiber bundle functions as a feedforward or feedback pathway. Multimodal studies that employ fMRI and DTI may assist in this regard. Recently, de Almeida and colleagues (2009) reported altered effective connectivity between the orbital-medial PFC (OMPFC) and the amygdala in BD patients relative to controls. Using dynamic casual modeling (Friston et al., 2003) of fMRI data, this group showed that left-sided top-down effective connectivity between OMPFC and amygdala was reduced in BD and UD patients compared to controls and that right-sided bottom-up effective connectivity was abnormal in BD subjects compared to UD and control subjects when performing an emotion-labeling task. It may be that WM abnormalities between these regions (e.g., via the uncinate fasciculus) may mediate altered patterns of connectivity.

An empirical study linking functional and diffusion data in BD by Wang and colleagues (2009) measured event-related BOLD in response to emotional stimuli and FA in the same sample of BD and control subjects. These authors reported decreased functional connectivity between the perigenual anterior cingulate cortex and the amygdala in the BD group that was significantly correlated with decreased FA along tracts that connect these two regions (i.e., the uncinate fasciculus and surrounding WM). Emotional stimuli are likely to elicit greater and more theory-driven functional abnormalities in BD samples and should thus be used in multi-modal structure-function paradigms. Future studies that assess both structural and functional connectivity are likely to provide the most compelling evidence for circuit dysfunction in BD, and will help to elucidate the nature of both the circuitry and the abnormalities within it.

Findings from DTI studies in BD conducted to date appear to converge on diffusion abnormalities along the uncinate fasciculus and other WM tracts subserving the OFC, particularly on the left side, as well as on the WM adjacent to the anterior cingulate. The OFC is directly connected with the limbic cortex and structures, and as proposed by Phillips et al. (2008) it may serve as a moderator between subcortical limbic structures and the more lateral and dorsal regions of the PFC. Results of DTI studies conducted thus far, using a variety of different methodologies and patient samples (children, adolescents, adults, and unmedicated patients), suggest that the WM fibers connecting the OFC and the limbic cortex are abnormal in BD. In addition, there is evidence for diffusion abnormalities in large projection and association tracts such as the thalamic radiation fibers and the superior longitudinal fasciculus, respectively. Although the implications for these more diffuse findings are not currently clear, such abnormalities may become incorporated into existing models and help to clarify the neurobiology of BD.

4. Neuropathological Evidence

Relatively few neuropathological studies have been conducted in BD, yet the results indicate that cytoarchitectural and neurochemical abnormalities are present in this disorder (Connor et al., 2009; Harrison, 2002; Rajkowska, 2002). As is the case for neuroimaging studies, neuropathological studies have tended to focus on GM and have not investigated the WM to the same extent. Of particular relevance for WM investigation is the study of oligodendrocytes and myelin, although few studies have directly assessed these in BD. Oligodendrocytes are found in the GM as well as the WM, although it is generally the WM oligodendrocytes that produce the myelin sheath that surrounds axon fibers. The majority of studies that have assessed oligodendrocytes in BD have focused on the perineuronal oligodendrocytes that exist in the GM. Although alterations in GM neuronal and glial organization are related to WM changes, the impact of these alterations and the directionality of the relationship between the two remain unclear.

Guided by evidence from neuroimaging studies and by models of BD pathophysiology, researchers have repeatedly targeted the ACC and the DLPFC as regions of investigation. The evidence accumulated thus far appears to suggest fewer glial cells in the GM of the subgenual ACC (Öngür et al., 1998) and a lower neuronal density in the sub-and pre-genual ACC (Benes et al., 2001; Bouras et al., 2001). A reduction in neuronal cell bodies in subregions of the ACC could potentially result in a reduction in efferent axonal fibers, although this possibility has not been examined. Further studies are needed to investigate the ODC populations in the afferent and efferent projections of the ACC that are strongly implicated in BD pathophysiology (eg Phillips et al., 2008). Recently, Connor et al., (2009) reported a significantly increased population of neurons in the WM beneath the ACC in BD. Analysis of post-mortem samples from patients with SCZ, patients with BD, and controls indicated that approximately 25% of each patient group demonstrated an increased density of neuron-specific nuclear protein (NeuN) positive cells in the WM subserving BA 33. The authors concurrently demonstrated that in normal development, the density of NeuN+ neurons in this region decreases within the first year of life but then remains stable throughout the lifespan. Taken together, the evidence suggests that at least a subset of cases of SCZ or BD may be characterized by abnormal WM neurodevelopment.

Thomas et al. (2004) examined the level of intracellular adhesion molecule-1 (ICAM-1), a marker of cerebral inflammation, in the supragenual portion of the ACC as well as in the DLPFC and the surrounding WM in samples from patients with BD, UD, and SCZ, as well as from controls. ICAM-1 was found to be increased in the ACC GM and WM in BD samples and to a lesser extent in UD samples relative to both SCZ and control samples; there were no differences between the groups in the DLPFC. This is consistent with reported evidence that abnormal inflammatory processes are an important pathophysiological mechanism in BD (Brietzke and Kapczinski, 2008; Kim et al., 2007; O’Brien et al., 2006), The authors noted that this result may be consistent with reduced GM glial populations reported in the ACC (Öngür et al., 1998; Todtenkopf et al., 2005), in that fewer glial cells in this region in BD could lead to ischemia-induced inflammation in this area (Cotter et al., 2001). One of the many functions of glial cells is to regulate the amount of blood flow to neurons; thus, a loss of such cells might lead to a decrease in perfusion. It is therefore conceivable that WMH may reflect ischemia induced by glial reduction.

Several studies have investigated the cytoarchitecture of the DLPFC (BA 9 and BA 46) in BD and have found evidence for abnormalities in cellular organization in this region as well. In particular, neuronal and glial density (Rajkowska et al., 2001; Vostrikov et al., 2007), smaller glial size (Cotter et al., 2002), and signs of apoptosis (Uranova et al., 2001) have been reported. Uranova et al. (2004) examined oligodendrocytes in the GM as well as in the surrounding WM of BA 9 and found that the numerical density of GM oligodendrocytes was decreased in layer VI in BD, UD, and SCZ samples relative to control samples. Investigation of the myelin-producing oligodendrocytes located in the superficial WM adjacent to BA 9 suggested that numerical density of these cells is unchanged in SCZ, BD and UD samples. Regenold et al. (2007) reported evidence for myelin pallor in the deep but not superficial WM underlying BA 9 and BA 46 in samples from BD, UD, and SCZ samples relative to control samples, providing neuropathological evidence that WM is abnormal in these illnesses in the deep WM, but may be uncompromised in the superficial WM. Beasley et al., (2002) examined interstitial neurons in the superficial WM underlying the DLPFC (BA 9 and BA 46) and found no differences in the density or distribution of such neurons in SCZ, UD, BD, and control samples. Abnormalities in the distribution and organization of interstitial neurons are believed to be the result of abnormal neuronal migration during development. Molnar et al. (2003) examined the distribution of WM interstitial cells in the DLPFC (BA 9) of the left hemisphere in 7 control samples and 7 samples from a combined depressed group made up of UD and BD samples. Although this study investigated a deeper level of WM than that examined by Beasley et al. (2002), the results suggested that there were no differences in interstitial cell distribution in any of the layers studied. The available evidence thus indicates that neuronal migration may not be disrupted in BD, although further examination is required to fully evaluate this possibility.

Although relatively few studies have examined the neuropathology of BD, and even fewer have directly investigated WM oligodendrocytes and myelin, it appears that there are important cytoarchitectural differences in brain regions involved in emotion regulation in BD. Glial reduction in the subgenual ACC (Öngür et al 1998; Todtenkopf et al., 2005) accompanied by increased inflammation in this region and the surrounding WM (Thomas et al., 2004) may imply a loss in perfusion. Given the consistent evidence for subgenual ACC involvement in emotion regulation (eg Mayberg et al., 2005; Phillips et al., 2008) abnormalities in this region are intriguing and require further investigation. Neuronal (Cotter et al., 2002; Rajkowska et al., 2001), glial (Rajkowska et al., 2001), and GM oligodendrocyte (Uranova et al., 2001; Uranova et al 2004; Vostrikov et al., 2007) abnormalities in DLPFC indicate that the cytoarchitecture of this region, also critically involved in emotion regulation, is disturbed. Rajkowska (2002) has demonstrated that these abnormalities, taken together, suggest that a fundamental alteration in cell resiliency and plasticity in regions involved in emotion generation and regulation may underlie BD. This suggestion is supported by neuroimaging findings that demonstrate altered connectivity rather than gross volumetric differences in WM and is consistent with circuit-based models of BD (Adler et al., 2006b; Green et al., 2007; Lyoo et al., 2006; Phillips et al., 2003b; Phillips et al., 2008; Soares and Mann, 1997; Strakowski et al., 2005).

5. Genetic Evidence

There is no doubt that the genetic underpinnings of BD are likely to be immensely complex. Twin studies have estimated the concordance rate for monozygotic twin pairs to be approximately 43%, whereas the rate for dizygotic twins appears to be approximately 6% (Kiessepä et al., 2003). Van der Schot et al. (2009) found that WM deficits in BD appear to be genetically mediated, whereas this was not found to be the case for GM deficits. Data from microarray and genetic linkage studies suggest that genes and proteins involved in connectivity, synaptic plasticity, and myelination are abnormal in BD. Evidence from various groups indicates that genes related to oligodendrocytes and myelin appear to be abnormally expressed in SCZ (Hakak et al 2001; Pongrac et al 2002; Tkachev et al 2003; Aston et al 2004; Dracheva et al 2006; Carter et al 2007a), and the evidence is accumulating to suggest that this is also the case in BD (Tkachev et al 2003; Carter et al 2007a). A potential limitation, however, is that the influence of antipsychotics on gene expression is not well understood, and that findings may be related to medication rather than to pathophysiology.

Tkachev and colleagues (2003) analyzed the expression of a wide range of myelin-and oligodendrocyte-related proteins in BD, SCZ, and control post-mortem tissue samples. mRNA expression of proteolipid protein 1, the most abundant myelin-related protein in the brain, was reduced in BA 9 in both SCZ and BD samples relative to control samples, with a greater reduction reported in BD (Tkachev et al., 2003). Proteolipid protein 1 is believed to play a role in neuronal-glial interactions, so this finding may be consistent with early indications of abnormal neuronal-glial interactions in mania (Öngür et al., 2008). In fact, recent evidence suggests that transgenic mice with extra copies of the proteolipid protein 1 gene have abnormal neuronal-glial interactions, as well as reduced prepulse inhibition, abnormal anxiety-related behaviors, and deficits in working memory (Tanaka et al., 2009). Other myelin- and oligodendrocyte-related proteins that were found to be altered in BD and SCZ include oligodendrocyte-specific protein, myelin-associated glycoprotein, and myelin oligodendrocyte glycoprotein (Tkachev et al., 2003).

Transferrin, a gene associated with the initiation of myelination, was downregulated in both patient groups in the same study (Tkachev et al., 2003), as was SOX10, a transcription factor that is believed to regulate the expression of several myelin-related genes (Stolt et al., 2002). The authors noted that downregulation of key myelin- and oligodendrocyte-related genes could certainly have implications for micro- and macrostructural impairment of WM, and are consistent with findings suggesting such impairments from neuroimaging and neuropathological studies.

Another important finding from the study by Tkachev et al. (2003) is that of downregulation of ERB3, a receptor for neuregulin1 that is known to be involved in ODC growth and differentiation. This downregulation was apparent in both patient groups, although the effect was more pronounced in BD. An intriguing study on ERB signaling pathways and their effect on oligodendrocytes in mice found that when ERB signaling in oligodendrocytes is blocked, the mice exhibited subtle but functionally significant changes (Roy et al., 2007). Although the number of myelinated axons was unchanged, the thickness of the myelin sheath was lower in the transgenic mice. Furthermore, the population of smaller oligodendrocytes was greater in these mice; this morphometric change may contribute to the overall decrease in myelin thickness that was observed along with the preservation of the number of myelinated axons. A decrease in the myelin sheath may have led to the reduction in conduction velocity that was observed in the experimental mice. Unexpectedly, mice in which ERB signaling was blocked also exhibited an increase in dopamine receptors and transporters in regions known to be involved in emotion regulation (cortex, striatum, and nucleus accumbens) and that have been implicated in BD and SCZ. Behavioral abnormalities observed in the experimental animals, such as reduced social activity and locomotion, emphasize the link between seemingly subtle neurochemical alterations and gross behavioral effects. Given these results in mice, it is noteworthy that ERB signaling appears to be abnormal in BD and SCZ.

ERB3 and ERB4 are receptors for neuregulin1, a growth factor that is crucial in myelination and which has also been linked to both SCZ and BD (Georgieva et al., 2008; Green et al., 2005; Thomson et al., 2007; Walss-Bass et al 2006). McIntosh et al. (2007) demonstrated that healthy volunteers with the risk-associated genotype at the single-nucleotide polymorphism SNP8NRG243177 demonstrated reduced WM density and integrity in the anterior limb of the internal capsule as assessed by both T1-weighted and DTI. These findings converge with those of neuroimaging studies that have demonstrated similar alterations in the brains of BD patients (Strakowski et al., 2005). Neuregulin1 was not found to have altered expression in the study by Tkachev et al. (2003), although more recent studies have confirmed that the neuregulin1 SNP appears to be a susceptibility locus for BD and SCZ (Georgieva et al., 2008; Green et al., 2005; Thomson et al., 2007; Walss-Bass et al., 2006). Genetic expression work in BD is in the very early stages, but as is the case for neuropathological studies of BD, the evidence accumulated thus far suggests the existence of alterations in oligodendrocytes and myelination that may have particular relevance for connectivity in BD.

6. Summary and Integration with Existing Models

Evidence for altered WM metabolism and compromised WM coherence and organization, in addition to a wealth of evidence suggesting functional disconnection in BD, indicates that WM connectivity is likely to be an important component in the pathophysiology of this disorder. In general, models of BD and SCZ have moved beyond discrete lesion-based proposals to models based on circuit-wide dysfunction, and WM investigation is an essential facet of this more recent focus. The lack of consistent gross WM volumetric abnormalities, coupled with the evidence for an increased prevalence of WMH in BD, suggests that the WM pathology present in BD may be characterized by subtle but potentially crucial disruptions in the WM connections of the brain.

Theoretical and empirical research suggests a model of BD in which structures involved in emotion perception, generation and regulation are abnormal. Evidence from fMRI investigations using emotional stimuli suggests a complicated pattern of abnormal activity in VLPFC (Altshuler et al., 2005; Elliott et al., 2004; Lawrence et al., 2004; Malhi et al., 2005; Robinson et al., 2008), DLPFC (Chang et al., 2004), MdPFC (Elliott et al., 2004; Malhi et al., 2007), OFC (Wessa et al., 2007), anterior cingulate cortex (Lennox et al., 2004; Malhi et al., 2007), and subcortical structures (Caligiuri et al., 2003; Chang et al., 2004; Lagopoulos and Malhi, 2007; Lawrence et al., 2004; Malhi et al., 2004a; Malhi et al., 2004b; Wessa et al., 2007), especially the amygdala (Altshuler et al., 2005; Foland et al., 2008; Lennox et al., 2004; Malhi et al., 2004b; Yurgelun-Todd et al., 2000). Findings across studies appear to be moderated by mood state and medication status, although differences in samples and study designs preclude direct comparison. Taken together with evidence from genetic and neuropathological studies of BD, as well as studies of healthy emotional regulation, several groups have proposed models of BD that may account for this complicated pattern of findings. A common feature of such models is that of hypothesized alterations in circuits comprised of subcortical limbic structures and prefrontal regions involved in executive functioning and cognitive appraisal, and in particular, deficient prefrontal modulation of subcortical regions involved in emotion perception and generation (Phillips et al 2003b, 2008; Strakowski et al 2005; Green et al 2007). Despite the circuit-based nature of such models, the WM that forms the structural connections between GM structures has been relatively under-emphasized.

Evidence for alterations along several of the tracts that connect prefrontal and subcortical structures implicated in emotional regulation has been reported (Table 3 and Figure 1). Given that emotional regulation is hypothesized to consist of both top-down and bottom-up processing of emotional stimuli via reciprocal connections between sensory cortex, subcortical limbic structures, and PFC subregions, alterations along these tracts is likely to play a role in the deficient emotional regulation that characterizes BD. Deficits in prefrontal modulation of subcortical hyper- or hypoactivation could be mediated through abnormal WM connectivity, in particular along the uncinate fasiculus and the anterior cingulum. Persistence of abnormal subcortical emotional activation as a result of deficient inhibitory inputs from prefrontal regions may play a role in exaggerated mood states. Foland et al. (2008) have recently reported evidence for deficient prefrontal modulation of amygdala activity in manic BD subjects relative to controls in an emotional labeling task. The effective connectivity between OMPFC and amygdala in BD patients performing an emotional labeling task has recently been investigated (de Almeida et al., 2009). Effective connectivity, when analyzed using dynamic causal modeling (Friston et al., 2003), allows for inferences to be made regarding causal relationships between activation in two or more brain regions. In this regard, de Almeida and colleagues (2009) reported that WM alterations may mediate an altered functional relationship between OMPFC and amygdala.

Phillips et al. (2003a, 2003b, 2008) suggest a distinction between automatic emotional processes, such as involuntary attention to emotional stimuli, inhibition of the stress response, and implicit cognitive appraisal and reappraisal, and voluntary emotional processes, such as selective attention, attentional inhibition, and behavioral suppression. Evidence suggests that automatic emotional processes are associated most consistently with the OFC, ventral PFC including subgenual ACC, and subcortical limbic structures such as the amygdala; voluntary processes, in contrast, are associated most consistently with DLPFC and VLPFC (see Phillips et al., 2008). A further distinction has been made between more ventral and medial emotionally-generative regions and more dorsal and lateral emotionally-appraising regions. Numerous studies suggest that the OFC serves as a kind of way station between dorsal and lateral regions of the PFC and limbic regions, in that these PFC regions are indirectly connected to limbic structures through direct connections with the OFC (Beauregard, 2007; Cavada et al., 2000) via tracts such as the uncinate fasciculus, anterior cingulum, the anterior fronto-occipital fasciculus, and others. Notably, these tracts are among those that appear to be abnormal in BD.

The complicated pattern of altered activation reported in fMRI studies across mood states suggests that the occurrence of mood episodes may be a result of subtle pathway disruption rather than fixed GM structural or functional abnormalities. A lack of normal anatomical connectivity among regions involved in emotional functioning suggests that errors occurring in any region along a circuit may be perpetuated, maintained, and even compounded by a lack of regulatory feedback. Thus, the same pathophysiologic process could allow different stimuli (e.g. lack of sleep, social rejection) to trigger an abnormal feedback loop that generates and maintains a manic or depressed episode. For example, the lateral nucleus of the amygdala is known to receive sensory information from the cortex that is then “tagged” with an emotional valence that is transmitted to other subcortical and cortical brain regions, including the PFC (eg Cardinal et al., 2002; Davis and Whalen, 2001; Gallagher and Chiba, 1996; LeDoux, 2003; LeDoux et al., 1990; Quirk et al., 1995). Given the evidence for significant (over 40%) neuronal deficits in the lateral nucleus in BD (Berretta et al., 2007), as well as the evidence for altered amygdalar activation in BD mania and depression (Altshuler et al., 2005; Blumberg et al., 2005; Lawrence et al., 2004; Yurgelun-Todd et al 2000), it is possible that altered processing of emotional valence by the amygdala is a factor in BD. The dense reciprocal connections between the amygdala and the OFC, and the anterior cingulate in particular, have been found to be altered in BD (see Figure 1). Given that the OFC is hypothesized to play a role as a moderator between subcortical and more dorsal and lateral prefrontal regions, it is notable that findings in BD appear to converge on tracts that subserve this region. It may be that an abnormal relationship between the OFC and subcortical limbic structures results in a larger disconnection between lateral PFC and the limbic system. Potential errors in emotionally valenced coding in the amygdala could then be perpetuated in higher order brain regions such as the lateral PFC through deficiencies in normal feedback circuits. Much research is required to begin to identify disruptions along these circuits; the investigation of both the structural and functional relationships between GM and WM is a promising step in this direction (Wang et al., 2009). As imaging, neuropathological, and genetic methodology improves, it will likely be possible to assess more specific subdivisions of larger tracts, as well as examine smaller, but theoretically important tracts such as the stria terminalis.

Models featuring circuit disruption are inherently more complex than discrete lesion models, and allow for the integration of critical interactions between genes, environment, affect, and behavior. It may be that the subtle WM pathology observed in BD is the result of abnormal signaling between groups of neurons that are genetically vulnerable to environmental stresses. Carter (2007b) reviewed the genes demonstrated to be associated with BD and outlined the interactions between the environment and such genes and the implications for signaling pathways and ultimately ODC vulnerability that appears to be a critical mechanism of BD pathophysiology. Similarly, Hains and Arnsten (2008) have recently elaborated upon the molecular signaling pathways that are commonly found to be disrupted in BD and SCZ, and have related these disruptions to molecular mechanisms of stress. Evidence for molecular dysfunction also appears to be supported by recent evidence suggesting abnormal glucose metabolism in SCZ and BD and may be crucial to understanding at least some subtypes of these disorders (Kato & Kato, 2000; Quiroz et al., 2008; Shao et al., 2008; Stork & Renshaw, 2005). Abnormal glucose metabolism is likely related to WM abnormalities documented in both disorders, and to WMH in BD in particular (Regenold et al., 2008).

7. Conclusions and Future Directions

Long neglected due to the limited feasibility of examining such tissue in vivo, researchers are increasingly turning to WM examination as a means of more fully understanding the neurological underpinnings of bipolar disorder. Imaging, genetic, and neuropathological evidence suggest that abnormalities in WM tissue play an important role in BD pathophysiology and phenomenology. In particular, theoretical and empirical research suggests a model of BD in which the connections within and between structures involved in emotion generation and regulation are altered. Broadly, this model proposes alterations along WM tracts interconnecting the amygdala, hypothalamus, striatum, and the subdivisions of the frontal cortex.

Evidence for alterations along several of these implicated tracts has been reported (Table 3). Evidence from genetics and post-mortem research appears to support the imaging findings of WM pathology. In particular, altered expression of oligodendrocyte and myelin genes (Tkachev et al., 2003) and a lower density of oligodendroglial (Uranova et al., 2004) and glial (Rajkowska et al., 2001) cells have been reported in the prefrontal cortex of patients compared to healthy volunteers. The large discrepancies among results in all areas of research in BD are likely influenced by heterogeneity of patient samples and methodological differences. Patient heterogeneity in BD research is a notorious problem, and comprises many attributes among which patients regularly differ. In addition to the traditional problem of medication effects, varying mood states, multiple subtypes (bipolar I and II), and subgroups of patients that experience psychosis as part of their illness add significantly to the complexity of the phenotype. As BD I is viewed as a more severe form of the illness, patients with this form of BD could be a primary focus of research at the descriptive level. Within BD I patients, there is enormous variation, however, in characteristics such as age, substance abuse and/or dependence, length and severity of illness, medication history and status, pre-morbid and current cognitive functioning, and family history of illness. Although the vast majority of studies in BD seek to control for these variables, it is rare that samples are large enough to allow for their systematic investigation. Additional variables that may be important to consider are the absolute and relative lengths of time that an individual remains in manic, euthymic, and depressed states. Although there is a decrement to generalizability when focusing on such a specific subset of individuals, it is possible that heterogeneous patient groups obscure the subtle alterations that underlie BD. Until these alterations are understood, more homogeneous patient groups may be needed to speed the pace of discovery.

Studies that combine imaging and other assessment techniques in a multi-modal fashion are likely to increase our ability to place findings in a meaningful context and to empirically connect structure and function. For example, resting and/or task-related brain activation as assessed through fMRI may inform results from concurrent microcircuitry analyses and ultimately, the functional consequences of abnormal circuitry may become apparent. The first study to attempt such an investigation in BD yielded compelling evidence that functional disconnectivity between the pregenual anterior cingulate cortex and the amygdala is associated with structural abnormalities within the anatomical WM connections between these regions (Wang et al., 2009). WM investigations in bipolar disorder are largely conducted at the level of preliminary description, and replication and refinement are very much needed. As knowledge of WM structure advances, studies that link WM pathology with clinical, genetic, metabolic, and functional correlates, as well as with GM pathology, may further elucidate the ways in which these neural abnormalities contribute to BD and advance progress toward a unifying theory of underlying pathophysiological mechanisms in BD.


This work was supported in part by grants from the Stanley Foundation and the NSLIJ Research Institute General Clinical Research Center (M01 RR018535).


  • Adler CM, Adams J, DelBello MP, Holland SK, Schmithorst V, Levine A, Jarvis K, Strakowski SM. Evidence of white matter pathology in bipolar disorder adolescents experiencing their first episode of mania: a diffusion tensor imaging study. Am. J. Psychiatry. 2006a;163:322–324. [PubMed]
  • Adler CM, DelBello MP, Strakowski SM. Brain network dysfunction in bipolar disorder. CNS Spectr. 2006b;11:312–320. [PubMed]
  • Adler CM, Holland SK, Schmithorst V, Wilke M, Weiss KL, Pan H, Strakowski SM. Abnormal frontal white matter tracts in bipolar disorder: a diffusion tensor imaging study. Bipolar Disord. 2004;6:197–203. [PubMed]
  • Ahn KH, Lyoo IK, Lee HK, Song IC, Oh JS, Hwang J, Kwon J, Kim MJ, Kim M, Renshaw PF. White matter hyperintensities in subjects with bipolar disorder. Psychiatry Clin. Neurosci. 2004;58:516–521. [PubMed]
  • Alexopoulos GS, Meyers BS, Young RC, Campbell S, Silbersweig D, Charlson M. ‘Vascular depression’ hypothesis. Arch. Gen. Psychiatry. 1997;54:915–922. [PubMed]
  • Altshuler L, Bookheimer S, Proenza MA, Townsend J, Firestine A, Bartzokis G, et al. Increased amygdala activation during mania: a functional magnetic resonance imaging study. A.m. J. Psychiatry. 2005;162:1211–1213. [PubMed]
  • Altshuler LL, Curran JG, Hauser P, Mintz J, Denicoff K, Post R. T2 hyperintensities in bipolar disorder: magnetic resonance imaging comparison and literature meta-analysis. Am. J. Psychiatry. 1995;152:1139–1144. [PubMed]
  • Angst J. The emerging epidemiology of hypomania and bipolar II disorder. J. Affect. Disord. 1998;50:143–151. [PubMed]
  • Arnone D, McIntosh AM, Chandra P, Ebmeier KP. Meta-analysis of magnetic resonance imaging studies of the corpus callosum in bipolar disorder. Acta Psychiatr. Scand. 2008;118:357–362. [PubMed]
  • Ashburner J, Friston KJ. Voxel-based morphometry- the methods. Neuroimage. 2000;11:805–821. [PubMed]
  • Assaf Y, Pasternak O. Diffusion tensor tmaging (DTI)-based white matter mapping in brain research: a review. J. Mol. Neurosci. 2008;34:51–61. [PubMed]
  • Aston C, Jiang L, Sokolov BP. Microarray analysis of postmortem temporal cortex from patients with schizophrenia. J. Neurosci. Res. 2004;77:858–866. [PubMed]
  • Atmaca M, Ozdemir H, Yildirim H. Corpus callosum areas in first-episode patients with bipolar disorder. Psychological Med. 2007:699–704. [PubMed]
  • Aylward EH, Roberts-Twillie JV, Barta PE, Kumar AJ, Harris GJ, Geer M, et al. Basal ganglia volumes and white matter hyperintensities in patients with bipolar disorder. Am. J. Psychiatry. 1994;151:687–693. [PubMed]
  • Barnea-Goraly N, Chang KD, Karchemskiy A, Howe ME, Reiss AL. Limbic and corpus calloum aberrations in adolescents with bipolar disorder: a tract-based spatial statistics analysis. Biol. Psychiatry. 2009;66:238–244. [PubMed]
  • Bearden CE, Hoffman KM, Cannon TD. The neuropsychology and neuroanatomy of bipolar affective disorder: a critical review. Bipolar Disord. 2001;3:106–150. [PubMed]
  • Beasley CL, Cotter DR, Everall IP. Density and distribution of white matter neurons in schizophrenia, bipolar disorder and major depressive disorder: no evidence for abnormalities of neuronal migration. Mol. Psychiatry. 2002;7:564–570. [PubMed]
  • Beaulieu C. The basis of anisotropic water diffusion in the nervous system - a technical review. N.M.R. Biomed. 2002;15:435–455. [PubMed]
  • Beauregard M. Mind does really matter: evidence from neuroimaging studies of emotional self-regulation, psychotherapy, and placebo effect. Prog. Neurobiol. 2007;81:218–236. [PubMed]
  • Benes FM, Vincent SL, Todtenkopf M. The density of pyramidal and nonpyramidal neurons in anterior cingulate cortex of schizophrenic and bipolar subjects. Biol. Psychiatry. 2001;50:395–406. [PubMed]
  • Berretta S, Pantazopoulos H, Lange N. Neuron numbers and volume of the amygdala in subjects diagnosed with bipolar disorder or schizophrenia. Biol. Psychiatry. 2007;62:884–893. [PubMed]
  • Beyer JL, Kuchibhatla M, Payne ME, MacFall J, Cassidy F, Krishnan KRK. Gray and white matter brain volumes in older adults with bipolar disorder. Int. J. Geriatr. Psychiatry. 2009 doi: 10.1002/gps2285. [PMC free article] [PubMed]
  • Beyer JL, Taylor WD, MacFall JR, Kuchibhatla M, Payne ME, Provenzale JM, Cassidy F, Krishnan KR. Cortical white matter microstructural abnormalities in bipolar disorder. Neuropsychopharmacology. 2005;30:2225–2229. [PubMed]
  • Blasi G, Bertolino A, Brudaglio F, Sciota D, Altamura M, Antonucci N, Scarabino T, Weinberger DR, Nardini M. Hippocampal neurochemical pathology in patients at first episode of affective psychosis: a proton magnetic resonance spectroscopic imaging study. Psychiatry Res. 2004;131:95–105. [PubMed]
  • Blumberg HP, Donegan NH, Sanislow CA, Collins S, Lacadie C, Skudlarski P, et al. Preliminary evidence for medication effects on functional abnormalities in the amygdala and anterior cingulate in bipolar disorder. Psychopharmacology. 2005;183:308–313. [PubMed]
  • Botteron KN, Vannier MW, Geller B, Todd RD, Lee BC. Preliminary study of magnetic resonance imaging characteristics in 8- to 16-year-olds with mania. J. Am. Acad. Child Adolesc. Psychiatry. 1995;34:742–749. [PubMed]
  • Bouras C, Kövari E, Hof PR, Riederer BM, Giannakopoulos P. Anterior cingulate cortex pathology in schizophrenia and bipolar disorder. Acta Neuropathol. 2001;102:373–379. [PubMed]
  • Brambilla P, Harenski K, Nicoletti M, Mallinger AG, Frank E, Kupfer DJ, Keshavan MS, Soares JC. Differential effects of age on brain gray matter in bipolar patients and healthy individuals. Neuropsychobiology. 2001;43:242–247. [PubMed]
  • Brambilla P, Nicoletti M, Sassi RB, Mallinger AG, Frank E, Keshavan MS, Soares JC. Corpus callosum signal intensity in patients with bipolar and unipolar disorder. J. Neurol. Neurosurg. Psychiatry. 2004;75:221–225. [PMC free article] [PubMed]
  • Brambilla P, Nicoletti MA, Sassi RB, Mallinger AG, Frank E, Kupfer DJ, et al. Magnetic resonance imaging study of corpus callosum abnormalities in patients with bipolar disorder. Biol. Psychiatry. 2003;54:1294–1297. [PubMed]
  • Breeze JL, Hesdorffer DC, Hong X, Frazier JA, Renshaw PF. Clinical significance of brain white matter hyperintensities in young adults with psychiatric illness. Harv. Rev. Psychiatry. 2003;11:269–283. [PubMed]
  • Brietzke E, Kapczinski F. TNF-α as a molecular target in bipolar disorder. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2008;32:1355–1361. [PubMed]
  • Brown FW, Lewine RJ, Hudgins PA, Risch SC. White matter hyperintensity signals in psychiatric and nonpsychiatric subjects. Am. J. Psychiatry. 1992;149:620–625. [PubMed]
  • Bruno S, Cercignani M, Ron MA. White matter abnormalities in bipolar disorder: a voxel-based diffusion tensor imaging study. Bipolar Disord. 2008;10:460–468. [PubMed]
  • Bruno SD, Barker GJ, Cercignani M, Symms M, Ron MA. A study of bipolar disorder using magnetization transfer imaging and voxel-based morphometry. Brain. 2004;127:2433–2440. [PubMed]
  • Bruno SD, Papadopoulou K, Cercignani M, Cipolotti L, Ron MA. Structural brain correlates of IQ changes in bipolar disorder. Psychol. Med. 2006;36:609–618. [PubMed]
  • Caetano SC, Magalhães Silveria C, Kaur S, Nicoletti M, Hatch JP, Brambilla P, et al. Abnormal corpus callosum myelination in pediatric bipolar patients. J. Affect. Disord. 2008;108:297–301. [PMC free article] [PubMed]
  • Caligiuri MP, Brown GG, Meloy MJ, Eberson SC, Kindermann SS, Frank LR, Zorrilla LE, Lohr JB. An fMRI study of affective state and medication on cortical and subcortical brain regions during motor performance in bipolar disorder. Psychiatry Res. 2003;123:171–182. [PubMed]
  • Cardinal RN, Parkinson JA, Hall J, Everitt BJ. Emotion and motivation: the role of the amygdala, ventral striatum, and prefrontal cortex. Neurosci. Biobehav. Rev. 2002;26:321–352. [PubMed]
  • Carter CJ. eIF2B and oligodendrocyte survival: where nature and nurture meet in bipolar disorder and schizophrenia? Schizophr. Bull. 2007a;33:1343–1353. [PMC free article] [PubMed]
  • Carter CJ. Mulitple genes and factors associated with bipolar disorder converge on growth factor and stress activated kinase pathways controlling translation initiation: implications for oligodendrocyte viability. Neurochemistry International. 2007b;50:461–490. [PubMed]
  • Cavada C, Compañy T, Tejedor J, Cruz-Rizzolo RJ, Reinoso-Suñrez F. The anatomical connections of the macaque monkey orbitofrontal cortex. A review. Cereb. Cortex. 2000;10:220–242. [PubMed]
  • Cecil KM, DelBello MP, Morey R, Strakowski SM. Frontal lobe differences in bipolar disorder as determined by proton MR spectroscopy. Bipolar Disord. 2002;4:357–365. [PubMed]
  • Cecil KM, DelBello MP, Sellars MC, Strakowski SM. Proton magnetic resonance spectroscopy of the frontal lobe and cerebellar vermis in children with a mood disorder and a familial risk for bipolar disorders. J. Child Adolesc. Psychopharmacol. 2003;13:545–555. [PubMed]
  • Chabriat H, Vahedi K, Iba-Zizen MT, Joutel A, Nibbio A, Nagv TG, et al. Clinical spectrum of CADASIL: a study of 7 families. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. Lancet. 1995;346:934–939. [PubMed]
  • Chaddock CA, Barker GJ, Marshall N, Schulze K, Hall MH, Fern A, Walshe M, et al. White matter microstructural impairments and genetic liability to familial bipolar I disorder. Br. J. Psychiatry. 2009;194:527–534. [PubMed]
  • Chang K, Adleman NE, Dienes K, Simeonova DI, Menon V, Reiss A. Anomalous prefrontal-subcortical activation in familial pediatric bipolar disorder: a functional magnetic resonance imaging investigation. Arch. Gen. Psychiatry. 2004;61:781–792. [PubMed]
  • Chang K, Barnea-Goraly N, Karchemskiy A, Iorgova Simeonova D, Barnes P, Ketter T, et al. Cortical magnetic resonance imaging findings in familial pediatric bipolar disorder. Biol. Psychiatry. 2005;58:197–203. [PubMed]
  • Chen HH, Nicoletti MA, Hatch JP, Sassi RB, Axelson D, Brambilla P, Monkul ES, Keshavan MS, Ryan ND, et al. Abnormal left superior temporal gyrus volumes in children and adolescents with bipolar disorder: a magnetic resonance imaging study. Neurosci. Lett. 2004;363:65–68. [PubMed]
  • Coffman JA, Bornstein RA, Olson SC, Schwarzkopf SB, Nasrallah HA. Cognitive impairment and cerebral structure by MRI in bipolar disorder. Biol. Psychiatry. 1990;27:1188–1196. [PubMed]
  • Connor CM, Guo Y, Akbarian S. Cingulate white matter neurons in schizophrenia and bipolar disorder. Biol. Psychiatry. 2009;66:486–493. [PMC free article] [PubMed]
  • Cotter D, Mackay D, Chana G, Beasley C, Landau S, Everall IP. Reduced neuronal size and glial cell density in area 9 of the dorsolateral prefrontal cortex in subjects with major depressive disorder. Cereb. Cortex. 2002;12:386–394. [PubMed]
  • Cotter DR, Pariante CM, Everall IP. Glial cell abnormalities in major psychiatric disorders: the evidence and implications. Brain Res. Bull. 2001;55:585–595. [PubMed]
  • Dager SR, Friedman SD, Parow A, Demopulos C, Stoll AL, Lyoo IK, Dunner DL, Renshaw PF. Brain metabolic alterations in medication-free patients with bipolar disorder. Arch. Gen. Psychiatry. 2004;61:450–458. [PubMed]
  • Damasio AR. Neuropsychology. Towards a neuropathology of emotion and mood. Nature. 1997;386:769–770. [PubMed]
  • Davis KA, Kwon A, Cardenas VA, Deicken RF. Decreased cortical gray and cerebral white matter in male patients with familial bipolar I disorder. J. Affect Disord. 2004;82:475–485. [PubMed]
  • Davis M, Whalen PJ. The amygdala: vigilance and emotion. Mol. Psychiatry. 2001;6:13–34. [PubMed]
  • de Almeida JRC, Versace A, Mechelli A, Hassel S, Quevedo K, Kupfer DJ, et al. Abnormal amygdala-prefrontal effective connectivity to happy faces differentiates bipolar from major depression. Biol. Psychiatry. 2009;66:451–459. [PMC free article] [PubMed]
  • de Asis JM, Greenwald BS, Alexopoulos GS, Kiosses DN, Ashtari M, Heo M, Young RC. Frontal signal hyperintensities in mania in old age. Am. J. Geriatr. Psychiatry. 2006;14:598–604. [PubMed]
  • Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition. Washington, DC: American Psychiatric Association; 1994.
  • Dixon JF, Hokin LE. The antibipolar drug valproate mimics lithium in stimulating glutamate release and inositol 1,4,5-trisphosphate accumulation in brain cortex slices but not accumulation of inositol monophosphates and bisphosphates. Proc. Natl. Acad. Sci. U.S.A. 1997;94:4757–4760. [PubMed]
  • Dixon JF, Hokin LE. Lithium acutely inhibits and chronically up-regulates and stabilizes glutamate uptake by presynaptic nerve endings in mouse cerebral cortex. Proc. Natl. Acad. Sci. U.S.A. 1998;95:8363–8368. [PubMed]
  • Dolan RJ, Poynton AM, Bridges PK, Trimble MR. Altered magnetic resonance white-matter T1 values in patients with affective disorder. Br. J. Psychiatry. 1990;157:107–110. [PubMed]
  • Dos Santos A, Alves da Silva J, Almeida J, Barahona Correa B, Gago J, Xavier M. Bipolar disorder, homocysteine and white matter hyperintensities. Bipolar Disord. 2008;10:748–751. [PubMed]
  • Dracheva S, Davis KL, Chin B, Woo DA, Schmeidler J, Haroutunian V. Myelin-associated mRNA and protein expression deficits in the anterior cingulate cortex and hippocampus in elderly schizophrenia patients. Neurobiol. Dis. 2006;21:531–540. [PubMed]
  • Drevets WC, Price JL, Simpson JR, Todd RD, Reich T, Vannier M, Raichle ME. Subgenual prefrontal cortex abnormalities in mood disorders. Nature. 1997;386:824–827. [PubMed]
  • Dupont RM, Butters N, Schafer K, Wilson T, Hesselink J, Gillin JC. Diagnostic specificity of focal white matter abnormalities in bipolar and unipolar mood disorder. Biol. Psychiatry. 1995;38:482–486. [PubMed]
  • Dupont RM, Jernigan TL, Butters N, Delis D, Hesselink JR, Heindel W, et al. Subcortical abnormalities detected in bipolar affective disorder using magnetic resonance imaging. Clinial and neuropsychological significance. Arch. Gen. Psychiatry. 1990;47:55–59. [PubMed]
  • Elliott R, Ogilvie A, Rubinsztein JS, Calderon G, Dolan RJ, Sahakian BJ. Abnormal ventral frontal response during performance of an affective go/no go task in patients with mania. Biol. Psychiatry. 2004;55:1163–1170. [PubMed]
  • Farrow TF, Whitford TJ, Williams LM, Gomes L, Harris AW. Diagnosis-related regional gray matter loss over two years in first episode schizophrenia and bipolar disorder. Biol. Psychiatry. 2005;58:713–723. [PubMed]
  • Figiel GS, Krishnan KR, Rao VP, Doraiswamy M, Ellinwood EH, Nemeroff CB, Evans D, Boyko O. Subcortical hyperintensities on brain magnetic resonance imaging: a comparison of normal and bipolar subjects. J. Neuropsychiatry Clin. Neurosci. 1991;3:18–22. [PubMed]
  • Foland LC, Altshuler LL, Bookheimer SY, Eisenberger N, Townsend J, Thompson PM. Evidence for deficient modulation of amygdala response by prefrontal cortex in bipolar mania. Psychiatry Res. 2008;162:27–37. [PMC free article] [PubMed]
  • Frazier JA, Breeze JL, Papadimitriou G, Kennedy DN, Hodge SM, Moore CM, Howard JD, Rohan MP, Caviness VS, Makris N. White matter abnormalities in children with and at risk for bipolar disorder. Bipolar Disord. 2007;9:799–809. [PubMed]
  • Friedman SD, Dager SR, Parow A, Hirashima F, Demopulos C, Stoll AL, Lyoo IK, Dunner DL, Renshaw PF. Lithium and valproic acid treatment effects on brain chemistry in bipolar disorder. Biol. Psychiatry. 2004;56:340–348. [PubMed]
  • Friston KL, Harrison L, Penny W. Dynamic causal modeling. Neuroimage. 2003;19:1273–1302. [PubMed]
  • Frye MA, Thomas MA, Yue K, Binesh N, Davanzo P, Ventura J, O'Neill J, Guze B, Curran JG, Mintz J. Reduced concentrations of N-acetylaspartate NAA and the NAA-creatine ratio in the basal ganglia in bipolar disorder: a study using 3-Tesla proton magnetic resonance spectroscopy. Psychiatry Res. 2007;154:259–265. [PubMed]
  • Gallagher M, Chiba AA. The amygdala and emotion. Curr. Opin. Neurobiol. 1996;6:221–227. [PubMed]
  • Ge Y, Law M, Grossman RI. Applications of diffusion tensor MR imaging in multiple sclerosis. Ann. N.Y. Acad. Sci. 2005;1064:202–219. [PubMed]
  • Georgieva L, Dimitrova A, Ivanov D, Nikolov I, Williams NM, Grozeva D, Zaharieva I, Toncheva D, Owen MJ, et al. Support for neuregulin 1 as a susceptibility gene for bipolar disorder and schizophrenia. Biol. Psychiatry. 2008;64:419–427. [PubMed]
  • Goodwin FK, Jamison KR, Ghaemi SN. Manic-depressive illness: bipolar disorders and recurrent depression. New York: Oxford University Press; 2007.
  • Green EK, Raybould R, Macgregor S, Gordon-Smith K, Heron J, Hyde S, Grozeva D, Hamshere M, Williams N, et al. Operation of the schizophrenia susceptibility gene, neuregulin 1, across traditional diagnostic boundaries to increase risk for bipolar disorder. Arch. Gen. Psychiatry. 2005;62:642–648. [PubMed]
  • Green MJ, Cahill CM, Malhi GS. The cognitive and neurophysiological basis of emotion dysregulation in bipolar disorder. J. Affect. Disord. 2007;103:29–42. [PubMed]
  • Gulseren S, Gurcan M, Gulseren L, Gelal F, Erol A. T2 hyperintensities in bipolar patients and their healthy siblings. Arch. Med. Res. 2006;37:79–85. [PubMed]
  • Gunning-Dixon FM, Raz N. The cognitive correlates of white matter abnormalities in normal aging: a quantitative review. Neuropsychology. 2000;14:224–232. [PubMed]
  • Hains AB, Arnsten AF. Molecular mechanisms of stress-induced prefrontal cortical impairment: implications for mental illness. Learn. Mem. 2008;15:551–564. [PubMed]
  • Hajek T, Carrey N, Alda M. Neuroanatomical abnormalities as risk factors for bipolar disorder. Bipolar Disord. 2005;7:393–403. [PubMed]
  • Hakak Y, Walker JR, Li C, Wong WH, Davis KL, Buxbaum JD, Haroutunian V, Fienberg AA. Genome-wide expression analysis reveals dysregulation of myelination-related genes in chronic schizophrenia. Proc. Natl. Acad. Sci. U.S.A. 2001;98:4746–4751. [PubMed]
  • Haldane M, Frangou S. New insights help define the pathophysiology of bipolar affective disorder: neuroimaging and neuropathology findings. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2004;28:943–960. [PubMed]
  • Hamilton M. A rating scale for depression. J. Neurol. Neurosurg. Psychiatry. 1960;23:56–62. [PMC free article] [PubMed]
  • Harrison PJ. The neuropathology of primary mood disorder. Brain. 2002;125:1428–1449. [PubMed]
  • Hauser P, Dauphinais ID, Berrettini W, DeLisi LE, Gelernter J, Post RM. Corpus callosum dimensions measured by magnetic resonance imaging in bipolar affective disorder and schizophrenia. Biol. Psychiatry. 1989;26:659–668. [PubMed]
  • Haznedar MM, Roversi F, Pallanti S, Baldini-Rossi N, Schnur DB, Licalzi EM, Tang C, Hof PR, Hollander E, Buchsbaum MS. Fronto-thalamo-striatal gray and white matter volumes and anisotropy of their connections in bipolar spectrum illnesses. Biol. Psychiatry. 2005;57:733–742. [PubMed]
  • Highley JR, Walker MA, Esiri MM, Crow TJ, Harrison PJ. Asymmetry of the uncinate fasciculus: a post-mortem study of normal subjects and patients with schizophrenia. Cereb. Cortex. 2002;12:1218–1224. [PubMed]
  • Houenou J, Wessa M, Douaud G, Leboyer M, Chanraud S, Perrin M, Poupon C, Martinot JL, Paillere-Martinot ML. Increased white matter connectivity in euthymic bipolar patients: diffusion tensor tractography between the subgenual cingulate and the amygdalo-hippocampal complex. Mol. Psychiatry. 2007;12:1001–1010. [PubMed]
  • Jones DK. The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn. Res. Med. 2004;51:807–815. [PubMed]
  • Jones DK, Catani M, Pierpaoli C, Reeves SJC, Shergill SS, O'Sullivan M, et al. Age effects on diffusion tensor magnetic resonance imaging tractography measures of frontal cortex connections in schizophrenia. Hum. Brain Mapp. 2006;27:230–238. [PubMed]
  • Joutel A, Corpechot C, Ducros A, Vahedi K, Chabriat H, Mouton P, et al. Notch3 mutations in CADASIL, a hereditary adult-onset condition causing stroke and dementia. Nature. 1996;383:707–710. [PubMed]
  • Kafantaris V, Kingsley P, Ardekani B, Saito E, Lencz T, Lim K, Szeszko P. Lower orbital frontal white matter integrity in adolescents with bipolar I disorder. J. Am. Acad. Child. Adolesc. Psychiatry. 2009;48:79–86. [PMC free article] [PubMed]
  • Kato T, Kato N. Mitochondrial dysfunction in bipolar disorder. Bipolar Disord. 2000;2:180–190. [PubMed]
  • Kato T, Murashita J, Kamiya A, Shioiri T, Kato N, Inubushi T. Decreased brain intracellular pH measured by 31P-MRS in bipolar disorder: a confirmation in drug-free patients and correlation with white matter hyperintensity. Eur. Arch. Psychiatry Clin. Neurosci. 1998;248:301–306. [PubMed]
  • Kempton MJ, Geddes JR, Ettinger U, Williams SCR, Grasby PM. Meta-analysis, database, and meta-regression of 98 structural imaging studies in bipolar disorder. Arch. Gen. Psychiatry. 2008;65:1017–1032. [PubMed]
  • Kieseppä T, van Erp TG, Haukka J, Partonen T, Cannon TD, Poutanen VP, Kaprio J, Lönnqvist J. Reduced left hemispheric white matter volume in twins with bipolar I disorder. Biol. Psychiatry. 2003;54:896–905. [PubMed]
  • Kim Y-K, Jung H-G, Myint A-M, Kim H, Park S-H. Imbalance between pro-inflammatory and anti-inflammatory cytokines in bipolar disorder. J. Affect. Disord. 2007;104:91–95. [PubMed]
  • Kirkpatrick JB, Hayman LA. White-matter lesions in MR imaging of clinically healthy brains of elderly subjects: possible pathologic basis. Radiology. 1987;162:509–511. [PubMed]
  • Krabbendam L, Honig A, Wiersma J, Vuurman EF, Hofman PA, Derix MM, Nolen WA, Jolles J. Cognitive dysfunctions and white matter lesions in patients with bipolar disorder in remission. Acta Psychiatr. Scand. 2000;101:274–280. [PubMed]
  • Lagopoulos J, Malhi GS. A functional magnetic resonance imaging study of emotional Stroop in euthymic bipolar disorder. Neuroreport. 2007;18:1583–1587. [PubMed]
  • Lawrence NS, Williams AM, Surguladze S, Giampietro V, Brammer MJ, Andrew C, et al. Subcortical and ventral prefrontal cortical neural responses to facial expressions distinguish patients with bipolar disorder and major depression. Biol. Psychiatry. 2004;55:578–587. [PubMed]
  • LeDoux J. The emotional brain, fear, and the amygdala. Cell. Mol. Neurobiol. 2003;23:727–738. [PubMed]
  • LeDoux JE, Cicchetti P, Xagoraris A, Romanski LM. The lateral amygdaloid nucleus: sensory interface of the amygdala in fear conditioning. J. Neurosci. 1990;10:1062–1069. [PubMed]
  • Lennox BR, Jacob R, Calder AJ, Lupson V, Bullmore ET. Behavioural and neurocognitive responses to sad facial affect are attenuated in patients with mania. Psychol. Med. 2004;34:795–802. [PubMed]
  • Leuchter AF, Dunkin JJ, Lufkin RB, Anzai Y, Cook IA, Newton TF. Effect of white matter disease on functional connections in the aging brain. J. Neurol. Neurosurg. Psychiatry. 1994;57:1347–1354. [PMC free article] [PubMed]
  • Lewine RRJ, Hudgins P, Brown F, Caudle J, Risch SC. Differences in qualitative brain morphology findings in schizophrenia, major depression, bipolar disorder and normal volunteers. Schizophrenia Res. 1995;15:253–259. [PubMed]
  • Lim KO, Rosenbloom MJ, Faustman WO, Sullivan EV, Pfefferbaum A. Cortical gray matter deficit in patients with bipolar disorder. Schizophr. Res. 1999;40:219–227. [PubMed]
  • Lloyd AJ, Moore PB, Cousins DA, Thompson JM, McAllister VL, Hughes JH, et al. White matter lesions in euthymic patients with bipolar disorder. Acta Psychiatrica Scandinavia. 2009 doi: 10.1111/j.1600-0447.2009.0146.x. [PubMed]
  • López-Larson MP, DelBello MP, Zimmerman ME, Schwiers ML, Strakowski SM. Regional prefrontal gray and white matter abnormalities in bipolar disorder. Biol. Psychiatry. 2002;52:93–100. [PubMed]
  • Lyoo IK, Hwang J, Sim M, Dunn BJ, Renshaw PF. Advances in magnetic resonance imaging methods for the evaluation of bipolar disorder. CNS Spectr. 2006;11:269–280. [PubMed]
  • Lyoo IK, Kim MJ, Stoll AL, Demopulos CM, Parow AM, Dager SR, Friedman SD, Dunner DL, Renshaw PF. Frontal lobe gray matter density decreases in bipolar I disorder. Biol. Psychiatry. 2004;55:648–651. [PubMed]
  • Lyoo IK, Lee HK, Jung JH, Noam GG, Renshaw PF. White matter hyperintensities on magnetic resonance imaging of the brain in children with psychiatric disorders. Compr. Psychiatry. 2002;43:361–368. [PubMed]
  • MacLean PD. The Triune Brain in Evolution: Role in Paleocerebral Functions. New York: Plenum Press; 1990. [PubMed]
  • Mahon K, Wu J, Malhotra AK, Burdick KE, DeRosse P, Ardekani BA, Szeszko PR. A voxel-based diffusion tensor imaging study in bipolar disorder. Neuropsychopharmacology. 2009;34:1590–1600. [PMC free article] [PubMed]
  • Malhi GS, Lagopoulos J, Owen AM, Ivanovski B, Shnier R, Sachdev P. Reduced activation to implicit affect induction in euthymic bipolar patients: an fMRI study. J. Affect. Disord. 2007;97:109–122. [PubMed]
  • Malhi GS, Lagopoulos J, Sachdev P, Mitchell PB, Ivanovski B, Parker GB. Cognitive generation of affect in hypomania: an fMRI study. Bipolar Disord. 2004a;6:271–285. [PubMed]
  • Malhi GS, Lagopoulos J, Sachdev PS, Ivanovski B, Shnier R. An emotional Stroop functional MRI study of euthymic bipolar disorder. Bipolar Disord. 2005;7 Suppl. 5:58–69. [PubMed]
  • Malhi GS, Lagopoulos J, Ward PB, Kumari V, Mitchell PB, Parker GB, Ivanovski B, Sachdev P. Cognitive generation of affect in bipolar depression: an fMRI study. Eur. J. Neurosci. 2004b;19:741–754. [PubMed]
  • Mayberg HS. Limbic-cortical dysregulation: a proposed model of depression. J. Neuropsychiatry Clin. Neurosci. 1997;9:471–481. [PubMed]
  • Mayberg HS, Liotti M, Brannan SK, McGinnis S, Mahurin RK, Jerabek PA, Silva JA, Tekell JL, Martin CC, et al. Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am. J. Psychiatry. 1999;156:675–682. [PubMed]
  • Mayberg HS, Lozano AM, Voon V, McNeely HE, Seminowicz D, Hamani C, Schwalb JM, Kennedy SH. Deep brain stimulation for treatment-resistant depression. Neuron. 2005;45:651–660. [PubMed]
  • McDonald C, Bullmore E, Sham P, Chitnis X, Suckling J, MacCabe J, et al. Regional volume deviations of brain structure in schizophrenia and psychotic bipolar disorder: a computational morphometry study. Br. J. Psychiatry. 2005;186:369–377. [PubMed]
  • McDonald C, Bullmore ET, Sham PC, Chitnis X, Wickham H, Bramon E. Association of genetic risks for schizophrenia and bipolar disorder with specific and generic brain structural endophenotypes. Arch. Gen. Psychiatry. 2004;61:974–984. [PubMed]
  • McDonald WM, Krishnan KR, Doraiswamy PM, Blazer DG. Occurrence of subcortical hyperintensities in elderly subjects with mania. Psychiatry Res. 1991;40:211–220. [PubMed]
  • McDonald WM, Tupler LA, Marsteller FA, Figiel GS, DiSouza S, Nemeroff CB, Krishnan KR. Hyperintense lesions on magnetic resonance images in bipolar disorder. Biol. Psychiatry. 1999;45:965–971. [PubMed]
  • McIntosh AM, Job DE, Moorhead WJ, Harrison LK, Whalley HC, Johnstone EC, et al. Genetic liability to schizophrenia or bipolar disorder and its relationship to brain structure. Am. J. Med. Genet. B. 2006;141:76–83. [PubMed]
  • McIntosh AM, Job DE, Moorhead TW, Harrison LK, Lawrie SM, Johnstone EC. White matter density in patients with schizophrenia, bipolar disorder and their unaffected relatives. Biol. Psychiatry. 2005;58:254–257. [PubMed]
  • McIntosh AM, Maniega SM, Lymer GK, McKirdy J, Hall J, Sussmann JE, Bastin ME, Clayden JD, Johnstone EC, Lawrie SM. White Matter Tractography in Bipolar Disorder and Schizophrenia. Biol. Psychiatry. 2008;64:1088–1092. [PubMed]
  • McIntosh AM, Moorhead TW, Job D, Lymer GK, Muñoz Maniega S, McKirdy J, Sussmann JE, Baig BJ, Bastin ME, et al. The effects of a neuregulin 1 variant on white matter density and integrity. Mol Psychiatry. 2007;13:1054–1059. [PubMed]
  • Mesulam MM, Geula C. Nucleus basalis (Ch4) and cortical cholinergic innervation in the human brain: observations based on the distribution of acetylcholinesterase and choline acetyltransferase. J Comp Neurol. 1988;275:216–240. [PubMed]
  • Moeller FG, Hasan KM, Steinberg JL, Kramer LA, Valdes I, Lai LY, Swann AC, Narayana PA. Diffusion tensor imaging eigenvalues: preliminary evidence for altered myelin in cocaine dependence. Psychiatry Res. 2007;154:253–258. [PubMed]
  • Molnar M, Potkin SG, Bunney WE, Jones EG. MRNA expression patterns and distribution of white matter neurons in dorsolateral prefrontal cortex of depressed patients differ from those in schizophrenia patients. Biol. Psychiatry. 2003;53:39–47. [PubMed]
  • Moore PB, El-Badri SM, Cousins D, Shepherd DJ, Young AH, McAllister VL, Ferrier IN. White matter lesions and season of birth of patients with bipolar affective disorder. Am. J. Psychiatry. 2001a;158:1521–1524. [PubMed]
  • Moore PB, Shepherd DJ, Eccleston D, Macmillan IC, Goswami U, McAllister VL, Ferrier IN. Cerebral white matter lesions in bipolar affective disorder: relationship to outcome. Br. J. Psychiatry. 2001b;178:172–176. [PubMed]
  • Mori S, Oishi K, Faria AV. White matter atlases based on diffusion tensor imaging. Curr. Opin. Neurol. 2009;22:362–369. [PMC free article] [PubMed]
  • Murray CJ, Lopez AD. Evidence-based health policy--lessons from the Global Burden of Disease Study. Science. 1996;274:740–743. [PubMed]
  • Narrow WE, Rae DS, Robins LN, Regier DA. Revised prevalence estimates of mental disorders in the United States: using a clinical significance criterion to reconcile 2 surveys' estimates. Arch. Gen. Psychiatry. 2002;59:115–123. [PubMed]
  • O'Brien JT, Firbank MJ, Krishnan MS, van Straaten EC, van der Flier WM, Petrovic K, Pantoni L, Simoni M, Erkinjuntti T, et al. White matter hyperintensities rather than lacunar infarcts are associated with depressive symptoms in older people: the LADIS study. Am. J. Geriatr. Psychiatry. 2006;14:834–841. [PubMed]
  • Öngür D, Price JL. The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans. Cereb. Cortex. 2000;10:206–219. [PubMed]
  • Öngür D, Drevets WC, Price JL. Glial reduction in the subgenual prefrontal cortex in mood disorders. Proc. Natl. Acad. Sci. U.S.A. 1998;95:13290–13295. [PubMed]
  • Öngür D, Jensen JE, Prescot AP, Stork C, Lundy M, Cohen BM, Renshaw PF. Abnormal glutamatergic neurotransmission and neuronal-glial interactions in acute mania. Biol. Psychiatry. 2008;64:718–726. [PMC free article] [PubMed]
  • Osher Y, Sela B-A, Levine J, Belmaker RH. Elevated homocysteine levels in euthymic bipolar disorder patients showing functional deterioration. Bipolar Disord. 2004;6:82–86. [PubMed]
  • Pavuluri MN, O’Connor MM, Harral E, Sweeney JA. Affective neural circuitry during facial emotion processing in pediatric bipolar disorder. Biol. Psychiatry. 2007;62:158–167. [PubMed]
  • Pavuluri MN, Yang S, Kamineni K, Passarotti AM, Srinivasan G, Harral EM, Sweeney JA, Zhou XJ. Diffusion tensor imaging study of white matter fiber tracts in pediatric bipolar disorder and attention-deficit/hyperactivity disorder. Biol. Psychiatry. 2009;65:586–593. [PMC free article] [PubMed]
  • Pendlebury ST, Blamire AM, Lee MA, Styles P, Matthews PM. Axonal injury in the internal capsule correlates with motor impairment after stroke. Stroke. 1999;30:956–962. [PubMed]
  • Persuad R, Russow H, Harvey I, Lewis SW, Ron M, Murray RM. Focal signal hyperintensities in schizophrenia. Schizophrenia Res. 1997;27:55–64. [PubMed]
  • Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion perception I: The neural basis of normal emotion perception. Biol. Psychiatry. 2003a;54:504–514. [PubMed]
  • Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion perception II: Implications for major psychiatric disorders. Biol. Psychiatry. 2003b;54:515–528. [PubMed]
  • Phillips ML, Ladouceur CD, Drevets WC. A neural model of voluntary and automatic emotion regulation: implications for understanding the pathophysiology and neurodevelopment of bipolar disorder. Mol. Psychiatry. 2008;13(829):833–857. [PMC free article] [PubMed]
  • Pillai JJ, Friedman L, Stuve TA, Trinidad S, Jesberger JA, Lewin JS, Findling RL, Swales TP, Schulz SC. Increased presence of white matter hyperintensities in adolescent patients with bipolar disorder. Psychiatry Res. 2002;114:51–56. [PubMed]
  • Pompili M, Innamorati M, Mann JJ, Oquendo MA, Lester D, Del Casale A, et al. Periventricular white matter hyperintensities as predictors of suicide attempts in bipolar disorders and unipolar depression. Progress Neuro-Psychopharm. Biol. Psychiatry. 2008;32:1501–1507. [PubMed]
  • Pongrac J, Middleton FA, Lewis DA, Levitt P, Mirnics K. Gene expression profiling with DNA microarrays: advancing our understanding of psychiatric disorders. Neurochem. Res. 2002;27:1049–1063. [PubMed]
  • Port JD, Unal SS, Mrazek DA, Marcus SM. Metabolic alterations in medication-free patients with bipolar disorder: A 3T CSF-corrected magnetic resonance spectroscopic imaging study. Psychiatr. Res. 2008;162:113–121. [PubMed]
  • Quirk GJ, Repa C, LeDoux JE. Fear conditioning enhances short-latency auditory responses of lateral amygdala neurons: parallel recordings in the freely behaving rat. Neuron. 1995;15:1029–1039. [PubMed]
  • Quiroz JA, Gray NA, Kato T, Manji HK. Mitochondrially mediated plasticity in the pathophysiology and treatment of bipolar disorder. Neuropsychopharmacology. 2008;33:2551–2565. [PubMed]
  • Rajkowska G. Cell pathology in bipolar disorder. Bipolar Disord. 2002;4:105–116. [PubMed]
  • Rajkowska G, Halaris A, Selemon LD. Reductions in neuronal and glial density characterize the dorsolateral prefrontal cortex in bipolar disorder. Biol. Psychiatry. 2001;49:741–752. [PubMed]
  • Regenold WT, D'Agostino CA, Ramesh N, Hasnain M, Roys S, Gullapalli RP. Diffusion-weighted magnetic resonance imaging of white matter in bipolar disorder: a pilot study. Bipolar Disord. 2006;8:188–195. [PubMed]
  • Regenold WT, Hisley KC, Phatak P, Marano CM, Obuchowski A, Lefkowitz DM, Sassan A, Ohri S, Phillips TL, et al. Relationship of cerebrospinal fluid glucose metabolites to MRI deep white matter hyperintensities and treatment resistance in bipolar disorder patients. Bipolar Disord. 2008;10:753–764. [PMC free article] [PubMed]
  • Regenold WT, Phatak P, Marano CM, Gearhart L, Viens CH, Hisley KC. Myelin staining of deep white matter in the dorsolateral prefrontal cortex in schizophrenia, bipolar disorder, and unipolar major depression. Psychiatry Res. 2007;151:179–188. [PubMed]
  • Regenold WT, Phatak P, Marano CM, Sassan A, Conley RR, Kling MA. Elevated cerebrospinal fluid lactate concentrations in patients with bipolar disorder and schizophrenia: implications for the mitochondrial dysfunction hypothesis. Biol. Psychiatry. 2009;65:489–494. [PMC free article] [PubMed]
  • Robinson JL, Monkul ES, Tordesillas-Gutiérrez D, Franklin C, Bearden CE, Fox PT, Glahn DC. Fronto-limbic circuitry in euthymic bipolar disorder: evidence for prefrontal hyperactivation. Psychiatry Res. 2008;164:106–113. [PubMed]
  • Rosso IM, Killgore WD, Cintron CM, Gruber SA, Tohen M, Yurgelun-Todd DA. Reduced amygdala volumes in first-episode bipolar disorder and correlation with cerebral white matter. Biol. Psychiatry. 2007;61:743–749. [PubMed]
  • Roy K, Murtie JC, El-Khodor BF, Edgar N, Sardi SP, Hooks BM, Benoit-Marand M, Chen C, Moore H, et al. Loss of erbB signaling in oligodendrocytes alters myelin and dopaminergic function, a potential mechanism for neuropsychiatric disorders. Proc. Natl. Acad. Sci. U.S.A. 2007;104:8131–8136. [PubMed]
  • Sarnicola A, Kempton M, Germana C, Haldane M, Hadjulis M, Christodoulou T, et al. No differential effect of age on brain matter volume and cognition in bipolar patients and healthy individuals. Bipolar Disord. 2009;11:316–322. [PubMed]
  • Sassi RB, Brambilla P, Nicoletti M, Mallinger AG, Frank E, Kupfer DJ, Keshavan MS, Soares JC. White matter hyperintensities in bipolar and unipolar patients with relatively mild-to-moderate illness severity. J. Affect. Disord. 2003;77:237–245. [PubMed]
  • Sassi RB, Nicoletti M, Brambilla P, Mallinger AG, Frank E, Kupfer DJ, Keshavan MS, Soares JC. Increased gray matter volume in lithium-treated bipolar disorder patients. Neurosci. Lett. 2002;329:243–245. [PubMed]
  • Savitz J, Drevets WC. Bipolar and major depressive disorder: neuroimaging the developmental-degenerative divide. Neuroscience and Biobehavioral Reviews. 2009;33:699–771. [PMC free article] [PubMed]
  • Shao L, Martin MV, Watson SJ, Schatzberg A, Akil H, Myers RM, Jones EG, Bunney WE, Vawter MP. Mitochondrial involvement in psychiatric disorders. Ann. Med. 2008;40:281–295. [PMC free article] [PubMed]
  • Silverstone T, McPherson H, Li Q, Doyle T. Deep white matter hyperintensities in patients with bipolar depression, unipolar depression and age-matched control subjects. Bipolar Disord. 2003;5:53–57. [PubMed]
  • Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, Watkins KE, Ciccarelli O, Cader MZ, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. 2006;31:1487–1505. [PubMed]
  • Soares JC, Mann JJ. The anatomy of mood disorders--review of structural neuroimaging studies. Biol. Psychiatry. 1997;41:86–106. [PubMed]
  • Song SK, Sun SW, Ju WK, Lin SJ, Cross AH, Neufeld AH. Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage. 2003;20:1714–1722. [PubMed]
  • Stanfield AC, Moorhead TWJ, Job DE, McKirdy J, Sussman JED, Hall J, et al. Structural abnormalities of ventrolateral and orbitofrontal cortex in patients with familial bipolar disorder. Bipolar Disord. 2009;11:135–144. [PubMed]
  • Stoll AL, Renshaw PF, Yurgelun-Todd DA, Cohen BM. Neuroimaging in bipolar disorder: what have we learned? Biol. Psychiatry. 2000;48:505–517. [PubMed]
  • Stolt CC, Rehberg S, Ader M, Lommes P, Riethmacher D, Schachner M, Bartsch U, Wegner M. Terminal differentiation of myelin-forming oligodendrocytes depends on the transcription factor Sox10. Genes Dev. 2002;16:165–170. [PubMed]
  • Stork C, Renshaw PF. Mitochondrial dysfunction in bipolar disorder: evidence from magnetic resonance spectroscopy research. Mol. Psychiatry. 2005;10:900–919. [PubMed]
  • Strakowski SM, Delbello MP, Adler CM. The functional neuroanatomy of bipolar disorder: a review of neuroimaging findings. Mol. Psychiatry. 2005;10:105–116. [PubMed]
  • Strakowski SM, Wilson DR, Tohen M, Woods BT, Douglass AW, Stoll AL. Structural brain abnormalities in first-episode mania. Biol. Psychiatry. 1993a;33:602–609. [PubMed]
  • Strakowski SM, Woods BT, Tohen M, Wilson DR, Douglass AW, Stoll AL. MRI subcortical signal hyperintensities in mania at first hospitalization. Biol. Psychiatry. 1993b;33:204–206. [PubMed]
  • Sussmann JE, Lymer GK, McKirdy J, Moorhead TW, Maniega SM, Job D, Hall J, Bastin ME, Johnstone EC. White matter abnormalities in bipolar disorder and schizophrenia detected using diffusion tensor magnetic resonance imaging. Bipolar Disord. 2009;11:11–18. [PubMed]
  • Swayze VW, Andreasen NC, Alliger RJ, Ehrhardt JC, Yuh WT. Structural brain abnormalities in bipolar affective disorder. Ventricular enlargement and focal signal hyperintensities. Arch. Gen. Psychiatry. 1990;47:1054–1059. [PubMed]
  • Takahashi K, Oshima A, Ida I, Kumano H, Yuuki N, Fukuda M, et al. Relationship between age at onset and magnetic resonance image-defined hyperintensities in mood disorders. J. Psychiatric. Res. 2008;42:443–450. [PubMed]
  • Tamashiro JH, Zung S, Zanetti MV, de Castro CC, Vallada H, Busatto GF, de Toledo Ferraz Alves TC. Increased rates of white matter hyperintensities in late-onset bipolar disorder. Bipolar Disord. 2008;10:765–775. [PubMed]
  • Tanaka H, Ma J, Tanaka KF, Takao K, Komada M, Tanda K, et al. Mice with altered myelin proteolipid protein gene expression display cognitive deficits accompanied by abnormal neuron-glia interactions and decreased conduction velocities. J. Neurosci. 2009;29:8363–8371. [PubMed]
  • Taylor WD, Payne ME, Krishnan KR, Wagner HR, Provenzale JM, Steffens DC, MacFall JR. Evidence of white matter tract disruption in MRI hyperintensities. Biol. Psychiatry. 2001;50:179–183. [PubMed]
  • Thomas AJ, Davis S, Ferrier IN, Kalaria RN, O'Brien JT. Elevation of cell adhesion molecule immunoreactivity in the anterior cingulate cortex in bipolar disorder. Biol. Psychiatry. 2004;55:652–655. [PubMed]
  • Thomas AJ, O'Brien JT, Davis S, Ballard C, Barber R, Kalaria RN, Perry RH. Ischemic basis for deep white matter hyperintensities in major depression: a neuropathological study. Arch. Gen. Psychiatry. 2002a;59:785–792. [PubMed]
  • Thomas AJ, Perry R, Barber R, Kalaria RN, O'Brien JT. Pathologies and pathological mechanisms for white matter hyperintensities in depression. Ann. N.Y. Acad. Sci. 2002b;977:333–339. [PubMed]
  • Thomson PA, Christoforou A, Morris SW, Adie E, Pickard BS, Porteous DJ, Muir WJ, Blackwood DH, Evans KL. Association of Neuregulin 1 with schizophrenia and bipolar disorder in a second cohort from the Scottish population. Mol. Psychiatry. 2007;12:94–104. [PubMed]
  • Tkachev D, Mimmack ML, Ryan MM, Wayland M, Freeman T, Jones PB, Starkey M, Webster MJ, Yolken RH, Bahn S. Oligodendrocyte dysfunction in schizophrenia and bipolar disorder. Lancet. 2003;362:798–805. [PubMed]
  • Todtenkopf MS, Vincent SL, Benes FM. A cross-study meta-analysis and three-dimensional comparison of cell counting in the anterior cingulate cortex of schizophrenic and bipolar brain. Schizophr. Res. 2005;73:79–89. [PubMed]
  • Uranova N, Orlovskaya D, Vikhreva O, Zimina I, Kolomeets N, Vostrikov V, Rachmanova V. Electron microscopy of oligodendroglia in severe mental illness. Brain Res. Bull. 2001;55:597–610. [PubMed]
  • Uranova NA, Vostrikov VM, Orlovskaya DD, Rachmanova VI. Oligodendroglial density in the prefrontal cortex in schizophrenia and mood disorders: a study from the Stanley Neuropathology Consortium. Schizophr. Res. 2004;67:269–275. [PubMed]
  • van Buchem MA, Tofts PS. Magnetization transfer imaging. Neuroimaging Clin. N. Am. 2000;10:771–788. [PubMed]
  • van der Schot AC, Vonk R, Brans RG, van Haren NE, Koolschijn PC, Nuboer V, Schnack HG, van Baal GC, Boomsma DI, et al. Influence of genes and environment on brain volumes in twin pairs concordant and discordant for bipolar disorder. Arch. Gen. Psychiatry. 2009;66:142–151. [PubMed]
  • Vawter MP, Freed WJ, Kleinman JE. Neuropathology of bipolar disorder. Biol. Psychiatry. 2000;48:486–504. [PubMed]
  • Versace A, Almeida JR, Hassel S, Walsh ND, Novelli M, Klein CR, Kupfer DJ, Phillips ML. Elevated left and reduced right orbitomedial prefrontal fractional anisotropy in adults with bipolar disorder revealed by tract-based spatial statistics. Arch. Gen. Psychiatry. 2008;65:1041–1052. [PMC free article] [PubMed]
  • Vostrikov VM, Uranova NA, Orlovskaya DD. Deficit of perineuronal oligodendrocytes in the prefrontal cortex in schizophrenia and mood disorders. Schizophr. Res. 2007;94:273–280. [PubMed]
  • Walss-Bass C, Liu W, Lew DF, Villegas R, Montero P, Dassori A, Leach RJ, Almasy L, Escamilla M, Raventos H. A novel missense mutation in thetransmembrane domain of neuregulin 1 is associated with schizophrenia. Biol. Psychiatry. 2006;60:548–553. [PubMed]
  • Walterfang M, Wood AG, Barton S, Velakoulis D, Chen J, Reutens DC, et al. Corpus callosum size and shape alterations in individuals with bipolar disorder and their first-degree relatives. Prog. Neuro-psychopharm. Biol. Psychiatry. 2009a;33:1050–1057. [PubMed]
  • Walterfang M, Wood AG, Reutens DC, Wood SJ, Chen J, Velakoulis D, et al. Corpus callosum size and shape in first-episode affective and schizophrenia-spectrum psychosis. Psychiatr. Res. 2009b;173:77–82. [PubMed]
  • Wang F, Jackowski M, Kalmar JH, Chepenik LG, Tie K, Qiu M, Gong G, Pittman BP, Jones MM, et al. Abnormal anterior cingulum integrity in bipolar disorder determined through diffusion tensor imaging. Br. J. Psychiatry. 2008a;193:126–129. [PMC free article] [PubMed]
  • Wang F, Kalmar JH, Edmiston E, Chepenik LG, Bhagwagar Z, Spencer L, et al. Abnormal corpus callosum integrity in bipolar disorder: a diffusion tensor imaging study. Biol. Psychiatry. 2008b;64:730–733. [PMC free article] [PubMed]
  • Wang F, Kalmar J, He Y, Jackowski M, Chepenik LG, Edmiston EE, et al. Functional and structural connectivity between the perigenual anterior cingulate and amygdala in bipolar disorder. Biol. Psychiatry. 2009;66:516–521. [PMC free article] [PubMed]
  • Wessa M, Houenou J, Leboyer M, Chanraud S, Poupon C, Martinot J-L, et al. Microstructural white matter changes in euthymic bipolar patients: a whole-brain diffusion tensor imaging study. Bipolar Disord. 2009;11:504–514. [PubMed]
  • Wessa M, Houenou J, Paillère-Martinot ML, Berthoz S, Artiges E, Leboyer M, Martinot JL. Fronto-striatal overactivation in euthymic bipolar patients during an emotional go/nogo task. Am. J. Psychiatry. 2007;164:638–646. [PubMed]
  • Woods BT, Yurgelun-Todd D, Mikulis D, Pillay SS. Age-related MRI abnormalities in bipolar illness: a clinical study. Biol. Psychiatry. 1995;38:846–847. [PubMed]
  • Yasar AS, Monkul ES, Sassi RB, Axelson D, Brambilla P, Nicoletti MA, et al. MRI study of corpus callosum in children and adolescents with bipolar disorder. Psychiatr. Res. 2006;146:83–85. [PubMed]
  • Yuan P, Salvadore G, Li X, Zhang L, Du J, Chen G, et al. Valproate activates the Notch3 / c-FLIP signaling cascade: a strategy to attenuate white matter hyperintensities in bipolar disorder in late life? Bipolar Disord. 2009;11:256–269. [PMC free article] [PubMed]
  • Yurgelun-Todd DA, Gruber SA, Kanayama G, Killgore WD, Baird AA, Young AD. fMRI during affect discrimination in bipolar affective disorder. Bipolar Disord. 2000;2:237–248. [PubMed]
  • Yurgelun-Todd DA, Silveri MM, Gruber SA, Rohan ML, Pimentel PJ. White matter abnormalities observed in bipolar disorder: a diffusion tensor imaging study. Bipolar Disord. 2007;9:504–512. [PubMed]
  • Zanetti MV, Cordeiro Q, Busatto GF. Late onset bipolar disorder associated with white matter hyperintensities: A pathophysiological hypothesis. Prog. Neuropsychopharm. Biol. Psychiatry. 2007;31:551–556. [PubMed]
  • Zanetti M, Jackowski MP, Versace A, Almeida JRC, Hassel S, Duran FLS. State-dependent microstructural white matter changes in bipolar I depression. Eur. Arch. Clin. Neurosci. 2009;259:316–328. [PMC free article] [PubMed]
  • Zanetti MV, Schaufelberger MS, de Castro CC, Menezes PR, Scazufca M, McGuire PK, et al. White-matter hyperintensities in first-episode psychosis. Br. J. Psychiatry. 2008;193:25–30. [PMC free article] [PubMed]
  • Zipursky RB, Seeman MV, Bury A, Langevin R, Wortzman G, Katz R. Deficits in gray matter volume are present in schizophrenia but not bipolar disorder. Schizophr. Res. 1997;26:85–92. [PubMed]