 |
|
Frontotemporal Alterations in Pediatric Bipolar Disorder
Results of a Voxel-Based Morphometry Study
Daniel P. Dickstein, MD;
Michael P. Milham, MD, PhD;
Allison C. Nugent, PhD;
Wayne C. Drevets, MD;
Dennis S. Charney, MD;
Daniel S. Pine, MD;
Ellen Leibenluft, MD
Arch Gen Psychiatry. 2005;62:734-741.
ABSTRACT
| |
Context While numerous magnetic resonance imaging (MRI) studies have evaluated adults with bipolar disorder (BPD), few have examined MRI changes in children with BPD.
Objective To determine volume alterations in children with BPD using voxel-based morphometry, an automated MRI analysis method with reduced susceptibility to various biases. A priori regions of interest included amygdala, accumbens, hippocampus, dorsolateral prefrontal cortex (DLPFC), and orbitofrontal cortex.
Design Ongoing study of the pathophysiology of pediatric BPD.
Setting Intramural National Institute of Mental Health; approved by the institutional review board.
Patients Pediatric subjects with BPD (n = 20) with at least 1 manic or hypomanic episode meeting strict DSM-IV criteria for duration and elevated, expansive mood. Controls (n = 20) and their first-degree relatives lacked psychiatric disorders. Groups were matched for age and sex and did not differ in IQ.
Main Outcome Measures With a 1.5-T MRI machine, we collected 1.2-mm axial sections (124 per subject) with an axial 3-dimensional spoiled gradient recalled echo in the steady state sequence. Image analysis was by optimized voxel-based morphometry.
Results Subjects with BPD had reduced gray matter volume in the left DLPFC. With a less conservative statistical threshold, additional gray matter reductions were found in the left accumbens and left amygdala. No difference was found in the hippocampus or orbitofrontal cortex.
Conclusions Our results are consistent with data implicating the prefrontal cortex in emotion regulation, a process that is perturbed in BPD. Reductions in amygdala and accumbens volumes are consistent with neuropsychological data on pediatric BPD. Further study is required to determine the relationship between these findings in children and adults with BPD.
INTRODUCTION
Pediatric bipolar disorder (BPD) is currently one of the most active and controversial areas of clinical and research interest in child psychiatry. Investigators have systematically described the clinical presentation of pediatric BPD and are now exploring neural mechanisms that might mediate the symptoms of the illness.1-2 One approach to such pathophysiologic research is to use neuropsychological tests to implicate specific brain regions whose function might be impaired in children with BPD, and then to follow up on these behavioral results with neuroimaging studies.
Emerging behavioral data in "narrow-phenotype" BPD—ie, children with distinct manic episodes meeting full DSM-IV criteria including abnormally elevated, expansive mood lasting 4 days or more—show that children with BPD may have dysfunction in a circuit involving the amygdala, accumbens area, and prefrontal cortex (PFC).1-2 Specifically, behavioral data show that children with narrow-phenotype BPD are impaired in (1) attentional set shifting and reversal learning3-4; (2) recognition of facial emotion5; and (3) reward-related processing.6 These psychological processes are subserved by circuits involving the amygdala, PFC, and ventral striatum (including the accumbens area). However, a dearth of neuroimaging data in pediatric BPD prevents linking these deficits to alterations in specific brain regions, as has been done to some extent in adult BPD research.7-9
Magnetic resonance (MR) imaging studies in adults with BPD have documented a range of morphometric differences in cortical and subcortical regions involved in emotion regulation, a process whereby initial responses to motivationally salient stimuli are altered in the face of changing goal demands. Specifically, studies in adult BPD have found abnormalities in regions of interest (ROIs) central to both the initial processing of emotional stimuli and response generation. These regions include the amygdala, ventral striatum, temporal lobe, and orbitofrontal cortex. Moreover, studies in adults with BPD have found abnormalities in structures thought to regulate initial emotional responses, including the dorsolateral prefrontal cortex (DLPFC).10-13
Despite an emerging emphasis on the neural circuitry of emotion regulation in adult BPD, there are inconsistencies in the literature. For example, in adults with BPD compared with controls, 3 studies found increased amygdala volume,14-16 while 1 study found reduced amygdala volume.17 Studies of the hippocampus and temporal lobe are also inconsistent, although many studies have found some form of abnormality in BPD.7, 14-16,18-20 Magnetic resonance imaging studies of adults with BPD have found decreased PFC volume, both of the PFC as a whole7 and of the subgenual PFC in particular,21 and a second, more recent study found decreased PFC density.22 Variability of MR imaging findings in adult BPD extends to investigations of white matter, with some studies,23-24 but not others,25-27 showing increased white matter hyperintensities in adults with BPD. This inconsistency in results of MR imaging studies in adult BPD may be due in part to methodologic variability of image analysis and patient selection.
Traditional MR imaging analytic methods—ie, manual tracing of multiple ROIs—may account for some of the inconsistency in the adult BPD neuroimaging literature. Hand tracing is susceptible to both type I and II errors, given its dependence on human raters’ ability to reliably define neuroanatomic regions. A novel, emerging method for MR imaging analysis is voxel-based morphometry (VBM). Voxel-based morphometry provides an objective means of examining the brain voxel by voxel in an automated fashion, determining differences in tissue volume, and avoiding the potential for bias in manual tracing. Moreover, in contrast to traditional manual tracing, VBM facilitates the simultaneous evaluation of multiple regions across the entire brain while generating appropriate voxel-wise statistical values. Such an approach appears particularly valuable for conditions such as BPD, where abnormalities in distributed neural circuitry might be anticipated. Studies have used VBM to evaluate neuropsychiatric disorders, such as Alzheimer disease, obsessive-compulsive disorder, panic disorder, and posttraumatic stress disorder, as well as developmental processes, such as age-related alterations in gray matter.28-32 Furthermore, a study by Testa et al33 suggested that VBM detects hippocampal changes in Alzheimer disease with greater sensitivity than traditional morphometry. Thus, VBM may reduce the variability inherent in traditional morphometric MR imaging analyses.
Few MR imaging morphometry studies exist in pediatric BPD. Currently, only 4 published studies have examined volumetric changes in cortical or subcortical structures in adolescents with BPD. Two have found decreased amygdalar volume in adolescents with BPD compared with controls, with one of these also finding a reduction in hippocampal volume.34-35 A third study found that adolescents with BPD had decreased left superior temporal gyrus volume.36 Recently, a fourth study used VBM to evaluate 12 ROIs in 10 adolescents with BPD and found that, compared with controls, the patients had increased gray matter volume bilaterally in the basal ganglia and thalamus, as well as larger left temporal lobes.37 In addition, investigators have found evidence of increased white matter hyperintensities in children with BPD, but this finding may lack specificity since similar increases have been reported in children with other psychiatric disorders.38-41 Clearly, more neuroimaging studies are needed in children with BPD to enhance our understanding of the developmental psychobiology of the illness.
We examined volumetric MR imaging changes in children with narrow-phenotype BPD by means of optimized VBM. We hypothesized that pediatric subjects with BPD would have volume reductions in key areas—including the amygdala, accumbens area, hippocampus, DLPFC, and orbitofrontal cortex—suggested by our behavioral data and by other MR imaging studies.
METHODS
SUBJECTS
Twenty children with BPD, aged 7 to 17 years, were recruited for an ongoing longitudinal neurocognitive and neuroimaging study conducted at the National Institute of Mental Health, Bethesda, Md, and approved by the institutional review board. After the study was explained and before participation, parents and children gave written informed consent and assent, respectively. Subjects were recruited nationwide via material placed on support groups’ Web sites, distributed at professional conferences, and sent to child psychiatrists.
Inclusion criteria for children with BPD were as follows: (1) meeting DSM-IV criteria for BPD, including a history of at least 1 episode meeting full duration criteria for hypomania ( 4 days) or mania (7 days) during which the child exhibited abnormally elevated or expansive mood and a total of at least 3 other DSM-IV criterion "B" mania symptoms1, 42; (2) involvement with ongoing mental health treatment; and (3) presence of a primary caretaker to grant consent and to participate in the research process. Children with irritability only, without elevated or expansive mood, were excluded. Thus, these patients represented the narrow phenotype of pediatric BPD.1
Exclusion criteria for pediatric BPD were as follows: IQ less than 70; autistic disorder or severe pervasive developmental disorder; psychosis interfering with the child’s capacity to understand and comply with study procedures; unstable medical illness (eg, severe asthma); medical illness that could cause the symptoms of bipolar illness (eg, multiple sclerosis, thyroid disease); pregnancy; or substance abuse within past 2 months.
After a telephone screening interview to ascertain a lifetime history of hypomanic, manic, and depressive episodes, patients thought likely to meet inclusion criteria were invited to the National Institute of Mental Health. The more detailed on-site screening included the Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version, a semistructured diagnostic clinical interview instrument, completed with parent and child individually by trained graduate-level clinicians, with established interrater reliability.43All diagnoses were based on best-estimate procedures,44 generated in a consensus conference of research staff led by 1 child and adolescent psychiatrist and 1 general psychiatrist, both with extensive experience studying children with BPD and related illnesses. We collected the following mood and function ratings on all subjects with BPD: Young Mania Rating Scale,45 Children’s Depression Rating Scale,46 Multidimensional Anxiety Scale for Children,47 and Children’s Global Assessment of Severity.48
Controls (n = 20) were matched individually with patients for age and sex. As with subjects with BPD, controls completed a telephone screen, and then graduate-level clinicians completed the Child Schedule for Affective Disorders, Present and Lifetime Version, with the child control and his or her parent separately. Inclusion criteria were negative psychiatric history in the control subject and his or her first-degree relatives; normal results of physical and neurologic examinations; lack of current, regular medication use; and an identified primary care physician. Exclusion criteria for controls were IQ less than 70; ongoing medical illness; neurologic disorder (including seizures); pregnancy; past or present substance abuse; and history of sexual abuse.
MR IMAGING METHODS
MR Imaging Protocol
Images were acquired on a 1.5-T scanner (Signa; GE Healthcare, Milwaukee, Wis). After a sagittal scout sequence, morphometric images were collected by means of an axial 3-dimensional spoiled gradient recalled echo in the steady state with echo time of 5 milliseconds, repetition time of 24 milliseconds, flip angle of 20°, acquisition matrix of 224 x 224, 1 excitation, and field of view of 22 cm. We also used a 300-millisecond inversion recovery preparation pulse used for T1 weighting with bandwidth of 15.63 Hz. Contiguous 1.2-mm axial section (124 total per subject) were collected with a voxel size of 0.98 x 0.98 x 1.2 mm. Head placement was standardized by aligning the nasion.
VBM Overview
As described elsewhere in more detail,28-29,49 optimized VBM analysis involves the following preprocessing of each subject's brain image (explained in detail in the following sections): (1) brain extraction (removal of nonbrain tissue, such as skull and dura); (2) segmentation (ie, separation of brain tissue into white matter, gray matter, and cerebrospinal fluid); (3) spatial transformation (transformation of tissue maps to common stereotaxic space); and (4) modulation (volume preservation that corrects for unintended changes in total tissue volume produced by spatial transformation).
For the extraction step, all MR images were examined by a neuroradiologist and found to be free of clinically significant abnormalities. We removed nonbrain tissue (ie, dura and skull) from the MR images by means of an automated method (Brain Extraction Tool; Oxford Centre for Functional Magnetic Resonance Imaging of the Brain [FMRIB], Oxford, England). Then, using MEDx (version 3.4.2; Medical Numerics Inc, Sterling, Va), we manually removed high-signal areas of the orbits and prechiasmatic optic nerve to increase segmentation accuracy.
For segmentation, each subject’s brain tissue was classified as gray matter, white matter, or cerebrospinal fluid on a voxel-wise basis by means of a highly accurate segmentation algorithm (FMRIB’s Automated Segmentation Tool). Specifically, on the basis of voxel intensity values and spatial contiguities derived from hidden Markov random fields, this segmentation algorithm generates a 3-dimensional map for each tissue type, representing the tissue-belonging probabilities for each voxel. On the basis of on these tissue probabilities, the segmentation algorithm generates partial volume estimates that are used in the volumetric analyses.
During the spatial normalization step, brain images were transformed from their native space to a common stereotaxic space (ie, the Montreal Neurological Institute’s 152-image adult space [MNI]) in which images can be compared across subjects and groups. We attempted to address several concerns that have been raised in the past regarding spatial normalization in VBM.50-51 Some authors have suggested that pediatric MR imaging studies should use pediatric brain templates, rather than adult brain templates such as those in the MNI database, to avoid image registration errors due to age-related changes in brain structures.52 However, another strategy that has been used to address concerns about differences between a study population and the MNI template is to create a study-specific or "local" template.28, 53 We created a local template by spatially normalizing each child's image to MNI space by means of a 12-parameter affine implemented in a registration tool (FMRIB’s Linear Image Registration Tool),54 spatially filtering the normalized images with a gaussian kernel (full-width half-maximum, 8 mm) and then averaging all of the images, ie, for both children with BPD and control children. Using this template, we then recalculated the spatial transformation for each participant by means of 12-parameter affine and nonlinear normalization (4 x 5 x 4-basis function, medium regularization) as implemented in Statistical Parametric Mapping 99 (SPM99; Wellcome Department of Imaging Neuroscience, London, England).
A second concern regarding spatial normalization is whether spatial normalization procedures alter the total volume of gray or white matter in a brain image, potentially biasing measures of volume. Optimized VBM protocols include a volume preservation ("modulation") step that restores prenormalization tissue volume by adjusting voxel-wise intensity (volume) values. During this step, a voxel’s intensity value is increased or decreased according to whether the surrounding region was compressed or expanded during normalization. For example, in the case of a brain region that is stretched during normalization, the intensity values for voxels within that region will be decreased, thereby preserving overall tissue volume. The converse is true for tissue that is compressed during normalization. Specifically, this involves calculating the determinant of the Jacobian matrix for the spatial transformation, thereby providing a compression map for the image—ie, a scaling factor for each voxel—as suggested by Ashburner and Friston.49 Total tissue volume is preserved by multiplying the partial volume estimate map by the corresponding compression map.
STATISTICAL ANALYSIS
Given the lack of neuromorphometry in childhood-onset BPD, we analyzed our results so as to balance both type I and type II error. We selected 5 a priori ROIs based on previous behavioral and neuroimaging research in children with BPD: amygdala, accumbens area, hippocampus, DLPFC, and orbitofrontal cortex.3, 34-37 For each a priori ROI, we used individual masks generated by identifying the regions on the single subject template (in MNI space) provided by SPM99. Anatomic criteria for these ROIs are given in previous publications.55-60 For each partial volume estimate, statistical analyses for the comparison of patients with BPD vs healthy controls were carried out by means of the general linear model implemented in SPM99. As noted in the previous paragraph, the determinant of the Jacobian matrix for the spatial transformation was included to model the possible contributions of spatial normalization to group differences. All coordinates presented have been converted from MNI space to that of Talairach and Tournoux.61
We determined voxel-wise volume differences between patients with BPD and controls in the a priori ROIs. Given the paucity of previous studies, our analyses were conducted at 2 levels. To correct for multiple comparisons, in our primary analysis, we assembled a global mask encompassing all of the ROIs. We report results only for those voxels that remained significant after the application of SPM99’s small-volume correction over this entire global mask.62 In a secondary, more liberal set of analyses, we used a small-volume correction for each individual ROI with no additional correction for the examination of multiple ROIs. This analysis, however, does correct for multiple voxel-based comparisons within each prespecified individual ROI. Both primary and secondary analyses covaried for global gray matter differences (analysis of covariance).
RESULTS
As indicated in the Table, the pediatric BPD and control samples were matched for age and sex and did not differ in IQ. In the BPD sample, the mean ± SD age was 13.4 ± 2.5 years (range, 8.6-17.5 years). For the control sample, the mean age was 13.3 ± 2.3 years (range, 9.8-17.0 years). Both BPD and control samples were 35% male. There was no significant between-group difference in full-scale IQ (BPD group, 109 ± 13.6; control group, 114 ± 13.3; t38 = 1.24; P = .22). Onset of BPD symptoms occurred at a mean age of 10.1 ± 3.2 years. At the time of MR imaging, the pediatric BPD sample was on average euthymic (Young Mania Rating Scale–Parent, 7.6 ± 6.3; Children’s Depression Rating Scale–Parent, 26.9 ± 10.2; Multidimensional Anxiety Scale for Children, 34.9 ± 13.2). Children with BPD were moderately functionally impaired (mean Children’s Global Assessment of Severity, 56.0 ± 10.6). All but one were taking psychiatric medications at the time of the scan (mean number of psychotropic medications, 3.4 ± 1.5).
|
|
|
|
Table. Demographic Information in Patients With BPD and Normal Control Sample
|
|
|
In our primary analysis, the voxel-wise analysis using the general linear model (with analysis of covariance for global gray matter) identified a focus of volume reduction in the left DLPFC (x = –32, y = 42, z = 32; t = 4.52, Z = 4.01; Pcorrected = .04) that survived small-volume correction for all a priori ROIs merged (Figure). No significant between-group differences in volume were found in the voxel-wise analysis using this method in other regions, including the accumbens area, amygdala, hippocampus, or orbitofrontal cortex bilaterally.
|
|
|
|
Figure. Areas of volume reduction in pediatric subjects with bipolar disorder (n = 20) compared with age- and sex-matched controls (n = 20). Color scale represents T scores, increasing from red to white. Dorsolateral prefrontal cortex is significant in primary analysis, controlling for all gray matter within a priori regions of interest merged. Accumbens area and amygdala are significant in secondary analyses, controlling for all gray matter within each individual a priori region of interest.
|
|
|
In our secondary analyses, while covarying for global gray matter, we identified significant volume reductions in 2 individual ROIs: the left amygdala (x = –24, y = 5, z = –15; t = 3.64, Z = 3.35; Pcorrected = .01) (Figure) and left accumbens area (x = –6, y = 9, z = –7; t = 3.96, Z = 3.59; Pcorrected = .004) (Figure). On a whole-brain map thresholded at the P<.05 uncorrected level, these 2 results are part of a larger, contiguous region of volume reduction in the infralimbic cortex. No other significant volume alterations were identified by small-volume correction for each a priori ROI individually.
COMMENT
Our current study used VBM, which avoids bias due to manual tracing, to examine neuroanatomic differences between children with narrow-phenotype BPD and controls. Our primary analysis, using correction for multiple comparisons, demonstrated that pediatric patients with BPD had significantly decreased gray matter volume in the left DLPFC. Our secondary analyses, using small-volume correction for each a priori ROI individually, disclosed volume reduction of the left amygdala and left accumbens area. Thus, our work provides evidence of prefrontal abnormalities in pediatric BPD, while suggesting that amygdala and accumbens abnormalities may also be present.
Volume reduction in Brodmann area 9, surviving correction for all the gray matter in the combined ROIs, is our primary finding. Previous research demonstrated that the DLPFC regulates emotion by directing attention away from the emotional context of stimuli.12, 63-64 Moreover, Davidson10, 65-66 suggested that circuitry encompassing the DLPFC and amygdala is involved in emotion regulation. Specifically, data suggest that the DLPFC exerts an inhibitory influence on regions, such as the amygdala, that are involved in the generation of negative emotional states.
Regarding the DLPFC’s role in the pathophysiology of BPD, other structural MR imaging studies document decreases in PFC gray matter volume in adults with BPD, and functional MR imaging studies in adults with BPD show reduced DLPFC activation, compared with controls, while attending to emotional faces.21, 67-68 Postmortem studies of adults with BPD have found decreased PFC neuronal density, including in Brodmann area 9, in comparison with controls.69 Thus, our finding of reduced DLPFC volume in children with BPD is consistent with studies in adults with BPD showing that this may be a key region in the pathophysiology of the disorder. However, our morphometric finding is somewhat at odds with our behavioral findings in pediatric BPD, since the latter have tended to implicate ventral, rather than dorsal, prefrontal abnormalities.3 This apparent inconsistency highlights both the limited ability of behavioral tasks to localize brain abnormalities and our imprecise understanding of structure-function relationships in developmental psychopathologies. Obviously, further research is needed to delineate the precise manner in which prefrontal dysfunction contributes to the pathophysiology of BPD in both children and adults.
The accumbens area, a region integral to reward behavior, showed some evidence of volume reduction in subjects with BPD in our secondary analyses. This finding may be relevant to behavioral data suggesting that children with BPD and controls respond differently on a decision-making task involving reward and punishment.6 Previous animal research has shown that midbrain dopamine projections into areas including the accumbens are key to the appetitive and desire aspects of reward behavior.70-73 Few neuroimaging studies have evaluated functional or morphometric changes in the accumbens area in subjects with mood disorders, despite the fact that altered reward and pleasure seeking are central to both mania and major depressive disorder. The lack of such morphometric studies may be due to the difficulty of tracing such a small region reliably, and to some debate concern the boundaries of the region in humans. Voxel-based morphometry, with its reliance on standard-space coordinates, may provide advantages in this regard. Of note, postmortem studies by Baumann et al74 demonstrate volume reduction of the left accumbens area in adults with BPD. Given the centrality of dysregulated reward behavior in BPD, additional research regarding accumbens structure and function in patients with the illness is warranted.
Many neuroimaging studies using a variety of techniques, including morphometric and functional MR imaging as well as positron emission tomography, have evaluated amygdala changes in BPD. However, the direction of these changes (ie, increased or decreased size or activation) is inconsistent in adults with BPD.14-17,19, 34, 75-78 Moreover, a recent study found no alteration in amygdala volume in medicated adults with BPD.79 In older adolescents with BPD, 2 studies using traditional hand-traced morphometry have shown decreased amygdala volume in comparison with control subjects.34-35 Now, using optimized VBM in children and adolescents with BPD, we have obtained evidence suggesting volume reduction of the left amygdala. Taken as a whole, these studies provide evidence of volume reduction in pediatric BPD. Additional work is necessary to determine whether these morphometric changes are associated with functional amygdala abnormalities in pediatric BPD.
Of note, the left amygdala and accumbens peaks of volume reduction are contiguous within the infralimbic cortex if whole-brain results are examined at the P<.05 level. This contiguity highlights some of the strengths and limitations of VBM, compared with hand-traced morphometry. Hand-traced morphometry may be more definitive than VBM in ascertaining between-group differences in the volume of specific, well-defined structures, such as the hippocampus or amygdala. Conversely, VBM may enable detection of more localized structural abnormalities within these regions, and may demonstrate volume alterations in areas that are difficult to hand trace, such as the accumbens.80 Comparative studies of hand tracing and VBM are needed, including the effect of sample size on results from both methods, as only one such published study exists.33
Interestingly, all of the significant abnormalities that we observed in children with BPD were left sided. Considerable data examine the relationship between lateralized brain dysfunction and psychopathology. This includes neuropsychological, electrophysiologic, and neuroimaging studies of patients with brain lesions or psychiatric illness. Studies of brain-injured patients, for example, suggest that left-sided damage may predispose to depression.81-85 However, other findings implicate right-hemisphere dysfunction in mania.82, 86 In any case, virtually all of this research examined adults. Since lateralization occurs relatively late in development, these results obtained in studies of adults may not be generalizable to children.87 Additional research is needed to examine directly the role of lateralized brain dysfunction in pediatric BPD.
Our study differs from previous MR imaging investigations in pediatric BPD in a number of respects. First, our study is unique with respect to BPD diagnosis and subjects’ mood state. Specifically, all of our subjects met diagnostic criteria more stringent than those of DSM-IV-TR, in that they all met the "A" criterion of mania requiring elevated, expansive mood, rather than irritable mood. This is important given the nonspecificity of irritability in child psychiatric disorders.88 In contrast, 3 of the 4 other studies in pediatric BPD included patients with a history of only irritable mania, and 1 of the 4 studies included subjects with BPD "not otherwise specified."36 Moreover, our subjects were scanned while euthymic on average; patients in the other studies were in manic-mixed,35, 37 euthymic,36 or heterogeneous34 mood states. Second, since all 4 previous morphometry studies evaluated older adolescents (up to age 21 years) and 1 study specifically excluded prepubertal subjects, our study is the first, to our knowledge, to examine prepubertal and young adolescent subjects with BPD.34-37 Third, the only previous study of VBM in adolescents with BPD included only 10 subjects.36 Our current findings highlight the need for developmentally oriented imaging work to evaluate both state- and trait-related morphometric differences in prepubertal children with BPD.
Our study was limited, in part, by the fact that 19 of 20 children with BPD were taking psychotropic medications at the time of MR imaging. This is not uncommon given the ethical issues inherent in discontinuing medication in children with severe psychiatric illnesses. Further work is necessary to dissociate neuronal alterations secondary to BPD and those resulting from pharmacologic treatment.
CONCLUSIONS
In summary, our study is novel in its use of VBM to systematically examine MR images for structural brain alterations in children with narrow-phenotype BPD. In patients, we found volume reduction in the left DLPFC (Brodmann area 9), and evidence suggesting reductions in the amygdala and accumbens area. Further work might elucidate the association between these findings and the unique developmental aspects of pediatric BPD, such as high comorbidity with attention-deficit/hyperactivity disorder and frequent cycling. Additional study is also required to determine state-trait plasticity of these neural structures.
AUTHOR INFORMATION
Correspondence: Daniel P. Dickstein, MD, Pediatrics and Developmental Neuropsychiatry Branch, National Institute of Mental Health, 10 Center Dr, MSC 1255, Bldg 10, Room 4N208, Bethesda, MD 20892 (Dicksted{at}mail.nih.gov).
Submitted for Publication: April 12, 2004; final revision received January 6, 2005; accepted January 13, 2005.
Acknowledgment: We gratefully acknowledge the participation of the children and families of both the BPD and control groups, without whom this research would not be possible. We also acknowledge all of the invaluable work of the MR technicians.
Author Affiliations: Mood and Anxiety Disorders Program, National Institute of Mental Health, Bethesda, Md (Drs Dickstein, Nugent, Drevets, Pine, and Leibenluft); Department of Psychiatry, New York University School of Medicine (Dr Milham), and Department of Psychiatry, Mount Sinai School of Medicine (Dr Charney), New York.
REFERENCES
| |
1. Leibenluft E, Charney DS, Towbin KE, Bhangoo RK, Pine DS. Defining clinical phenotypes of juvenile mania. Am J Psychiatry. 2003;160:430-437.
FREE FULL TEXT
2. Leibenluft E, Charney DS, Pine DS. Researching the pathophysiology of pediatric bipolar disorder. Biol Psychiatry. 2003;53:1009-1020.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
3. Dickstein DP, Treland JE, Snow J, McClure EB, Mehta MS, Towbin KE, Pine DS, Leibenluft E. Neuropsychological performance in pediatric bipolar disorder. Biol Psychiatry. 2004;55:32-39.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
4. Gorrindo T, Blair RJR, Budhani S, Dickstein DP, Pine DS, Leibenluft E. Probabilistic response reversal deficits in pediatric bipolar disorder. Am J Psychiatry. In press.
5. McClure EB, Pope K, Hoberman AJ, Pine DS, Leibenluft E. Facial expression recognition in adolescents with mood and anxiety disorders. Am J Psychiatry. 2003;160:1172-1174.
FREE FULL TEXT
6. Ernst M, Dickstein DP, Munson SEN, Pradella AG, Jazbec S, Pine DS, Leibenluft E. Reward-related processes in pediatric bipolar disorder: a pilot study. J Affect Disord. 2004;82(suppl 1):S89-S101.
7. Sax KW, Strakowski SM, Zimmerman ME, DelBello MP, Keck PE Jr, Hawkins JM. Frontosubcortical neuroanatomy and the continuous performance test in mania. Am J Psychiatry. 1999;156:139-141.
FREE FULL TEXT
8. Ali SO, Denicoff KD, Altshuler LL, Hauser P, Li X, Conrad AJ, Mirsky AF, Smith-Jackson EE, Post RM. A preliminary study of the relation of neuropsychological performance to neuroanatomic structures in bipolar disorder. Neuropsychiatry Neuropsychol Behav Neurol. 2000;13:20-28.
WEB OF SCIENCE
| PUBMED
9. Ali SO, Denicoff KD, Altshuler LL, Hauser P, Li X, Conrad AJ, Smith-Jackson EE, Leverich GS, Post RM. Relationship between prior course of illness and neuroanatomic structures in bipolar disorder: a preliminary study. Neuropsychiatry Neuropsychol Behav Neurol. 2001;14:227-232.
WEB OF SCIENCE
| PUBMED
10. Davidson RJ. Anxiety and affective style: role of prefrontal cortex and amygdala. Biol Psychiatry. 2002;51:68-80.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
11. LeDoux J. The emotional brain, fear, and the amygdala. Cell Mol Neurobiol. 2003;23:727-738.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
12. Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion perception, I: the neural basis of normal emotion perception. Biol Psychiatry. 2003;54:504-514.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
13. Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion perception, II: implications for major psychiatric disorders. Biol Psychiatry. 2003;54:515-528.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
14. Altshuler LL, Bartzokis G, Grieder T, Curran J, Mintz J. Amygdala enlargement in bipolar disorder and hippocampal reduction in schizophrenia: an MRI study demonstrating neuroanatomic specificity. Arch Gen Psychiatry. 1998;55:663-664.
FREE FULL TEXT
15. Altshuler LL, Bartzokis G, Grieder T, Curran J, Jimenez T, Leight K, Wilkins J, Gerner R, Mintz J. An MRI study of temporal lobe structures in men with bipolar disorder or schizophrenia. Biol Psychiatry. 2000;48:147-162.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
16. Brambilla P, Harenski K, Nicoletti M, Sassi RB, Mallinger AG, Frank E, Kupfer DJ, Keshavan MS, Soares JC. MRI investigation of temporal lobe structures in bipolar patients. J Psychiatr Res. 2003;37:287-295.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
17. Pearlson GD, Barta PE, Powers RE, Menon RR, Richards SS, Aylward EH, Federman EB, Chase GA, Petty RG, Tien AY. Ziskind-Somerfeld Research Award 1996: medial and superior temporal gyral volumes and cerebral asymmetry in schizophrenia versus bipolar disorder. Biol Psychiatry. 1997;41:1-14.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
18. Altshuler LL, Conrad A, Hauser P, Li XM, Guze BH, Denikoff K, Tourtellotte W, Post R. Reduction of temporal lobe volume in bipolar disorder: a preliminary report of magnetic resonance imaging. Arch Gen Psychiatry. 1991;48:482-483.
FREE FULL TEXT
19. Strakowski SM, DelBello MP, Sax KW, Zimmerman ME, Shear PK, Hawkins JM, Larson ER. Brain magnetic resonance imaging of structural abnormalities in bipolar disorder. Arch Gen Psychiatry. 1999;56:254-260.
FREE FULL TEXT
20. Hauser P, Matochik J, Altshuler LL, Denicoff KD, Conrad A, Li X, Post RM. MRI-based measurements of temporal lobe and ventricular structures in patients with bipolar I and bipolar II disorders. J Affect Disord. 2000;60:25-32.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
21. Drevets WC, Price JL, Simpson JR Jr, Todd RD, Reich T, Vannier M, Raichle ME. Subgenual prefrontal cortex abnormalities in mood disorders. Nature. 1997;386:824-827.
FULL TEXT
| PUBMED
22. 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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
23. Aylward EH, Roberts-Twillie JV, Barta PE, Kumar AJ, Harris GJ, Geer M, Peyser CE, Pearlson GD. Basal ganglia volumes and white matter hyperintensities in patients with bipolar disorder. Am J Psychiatry. 1994;151:687-693.
FREE FULL TEXT
24. 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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
25. Strakowski SM, Woods BT, Tohen M, Wilson DR, Douglass AW, Stoll AL. MRI subcortical signal hyperintensities in mania at first hospitalization. Biol Psychiatry. 1993;33:204-206.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
26. 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.
FREE FULL TEXT
27. 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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
28. Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ, Frackowiak RS. A voxel-based morphometric study of ageing in 465 normal adult human brains. Neuroimage. 2001;14:21-36.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
29. Karas GB, Burton EJ, Rombouts SA, van Schijndel RA, O'Brien JT, Scheltens P, McKeith IG, Williams D, Ballard C, Barkhof F. A comprehensive study of gray matter loss in patients with Alzheimer's disease using optimized voxel-based morphometry. Neuroimage. 2003;18:895-907.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
30. Massana G, Serra-Grabulosa JM, Salgado-Pineda P, Gasto C, Junque C, Massana J, Mercader JM, Gomez B, Tobena A, Salamero M. Amygdalar atrophy in panic disorder patients detected by volumetric magnetic resonance imaging. Neuroimage. 2003;19:80-90.
WEB OF SCIENCE
| PUBMED
31. Yamasue H, Kasai K, Iwanami A, Ohtani T, Yamada H, Abe O, Kuroki N, Fukuda R, Tochigi M, Furukawa S, Sadamatsu M, Sasaki T, Aoki S, Ohtomo K, Asukai N, Kato N. Voxel-based analysis of MRI reveals anterior cingulate gray-matter volume reduction in posttraumatic stress disorder due to terrorism. Proc Natl Acad Sci U S A. 2003;100:9039-9043.
FREE FULL TEXT
32. Pujol J, Soriano-Mas C, Alonso P, Cardoner N, Menchon JM, Deus J, Vallejo J. Mapping structural brain alterations in obsessive-compulsive disorder. Arch Gen Psychiatry. 2004;61:720-730.
FREE FULL TEXT
33. Testa C, Laakso MP, Sabattoli F, Rossi R, Beltramello A, Soininen H, Frisoni GB. A comparison between the accuracy of voxel-based morphometry and hippocampal volumetry in Alzheimer's disease. J Magn Reson Imaging. 2004;19:274-282.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
34. Blumberg HP, Kaufman J, Martin A, Whiteman R, Zhang JH, Gore JC, Charney DS, Krystal JH, Peterson BS. Amygdala and hippocampal volumes in adolescents and adults with bipolar disorder. Arch Gen Psychiatry. 2003;60:1201-1208.
FREE FULL TEXT
35. DelBello MP, Zimmerman ME, Mills NP, Getz GE, Strakowski SM. Magnetic resonance imaging analysis of amygdala and other subcortical brain regions in adolescents with bipolar disorder. Bipolar Disord. 2004;6:43-52.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
36. Chen HH, Nicoletti MA, Hatch JP, Sassi RB, Axelson D, Brambilla P, Monkul ES, Keshavan MS, Ryan ND, Birmaher B, Soares JC. Abnormal left superior temporal gyrus volumes in children and adolescents with bipolar disorder: a magnetic resonance imaging study. Neurosci Lett. 2004;363:65-68.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
37. Wilke M, Kowatch RA, DelBello MP, Mills NP, Holland SK. Voxel-based morphometry in adolescents with bipolar disorder: first results. Psychiatry Res. 2004;131:57-69.
WEB OF SCIENCE
| PUBMED
38. Botteron KN, Figiel GS, Wetzel MW, Hudziak J, VanEerdewegh M. MRI abnormalities in adolescent bipolar affective disorder. J Am Acad Child Adolesc Psychiatry. 1992;31:258-261.
WEB OF SCIENCE
| PUBMED
39. 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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
40. 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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
41. 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.
WEB OF SCIENCE
| PUBMED
42. Geller B, Zimerman B, Williams M, DelBello MP, Bolhofner K, Craney JL, Frazier J, Beringer L, Nickelsburg MJ. DSM-IV mania symptoms in a prepubertal and early adolescent bipolar disorder phenotype compared to attention-deficit hyperactive and normal controls. J Child Adolesc Psychopharmacol. 2002;12:11-25.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
43. Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, Williamson D, Ryan N. Schedule for Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime Version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. 1997;36:980-988.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
44. Leckman JF, Sholomskas D, Thompson WD, Belanger A, Weissman MM. Best estimate of lifetime psychiatric diagnosis: a methodological study. Arch Gen Psychiatry. 1982;39:879-883.
FREE FULL TEXT
45. Young RC, Biggs JT, Ziegler VE, Meyer DA. A rating scale for mania: reliability, validity and sensitivity. Br J Psychiatry. 1978;133:429-435.
FREE FULL TEXT
46. Emslie GJ, Weinberg WA, Rush AJ, Adams RM, Rintelmann JW. Depressive symptoms by self-report in adolescence: phase I of the development of a questionnaire for depression by self-report. J Child Neurol. 1990;5:114-121.
FREE FULL TEXT
47. March JS, Parker JD, Sullivan K, Stallings P, Conners CK. The Multidimensional Anxiety Scale for Children (MASC): factor structure, reliability, and validity. J Am Acad Child Adolesc Psychiatry. 1997;36:554-565.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
48. Shaffer D, Gould MS, Brasic J, Ambrosini P, Fisher P, Bird H, Aluwahlia S. A children’s global assessment scale (CGAS). Arch Gen Psychiatry. 1983;40:1228-1231.
FREE FULL TEXT
49. Ashburner J, Friston KJ. Voxel-based morphometry: the methods. Neuroimage. 2000;11:805-821.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
50. Ashburner J, Friston KJ. Why voxel-based morphometry should be used. Neuroimage. 2001;14:1238-1243.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
51. Bookstein FL. "Voxel-based morphometry" should not be used with imperfectly registered images. Neuroimage. 2001;14:1454-1462.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
52. Wilke M, Schmithorst VJ, Holland SK. Assessment of spatial normalization of whole-brain magnetic resonance images in children. Hum Brain Mapp. 2002;17:48-60.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
53. Rusch N, van Elst LT, Ludaescher P, Wilke M, Huppertz HJ, Thiel T, Schmahl C, Bohus M, Lieb K, Hesslinger B, Hennig J, Ebert D. A voxel-based morphometric MRI study in female patients with borderline personality disorder. Neuroimage. 2003;20:385-392.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
54. Jenkinson M, Smith S. A global optimisation method for robust affine registration of brain images. Med Image Anal. 2001;5:143-156.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
55. Szeszko PR, Bilder RM, Lencz T, Pollack S, Alvir JM, Ashtari M, Wu H, Lieberman JA. Investigation of frontal lobe subregions in first-episode schizophrenia. Psychiatry Res. 1999;90:1-15.
WEB OF SCIENCE
| PUBMED
56. Szeszko PR, Robinson D, Alvir JM, Bilder RM, Lencz T, Ashtari M, Wu H, Bogerts B. Orbital frontal and amygdala volume reductions in obsessive-compulsive disorder. Arch Gen Psychiatry. 1999;56:913-919.
FREE FULL TEXT
57. Drevets WC, Bogers W, Raichle ME. Functional anatomical correlates of antidepressant drug treatment assessed using PET measures of regional glucose metabolism. Eur Neuropsychopharmacol. 2002;12:527-544.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
58. Nelson EE, McClure EB, Monk CS, Zarahn E, Leibenluft E, Pine DS, Ernst M. Developmental differences in neuronal engagement during implicit encoding of emotional faces: an event-related fMRI study. J Child Psychol Psychiatry. 2003;44:1015-1024.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
59. Monk CS, McClure EB, Nelson EE, Zarahn E, Bilder RM, Leibenluft E, Charney DS, Ernst M, Pine DS. Adolescent immaturity in attention-related brain engagement to emotional facial expressions. Neuroimage. 2003;20:420-428.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
60. McClure EB, Monk CS, Nelson EE, Zarahn E, Leibenluft E, Bilder RM, Charney DS, Ernst M, Pine DS. A developmental examination of gender differences in brain engagement during evaluation of threat. Biol Psychiatry. 2004;55:1047-1055.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
61. Talairach J, Tournoux P. Co-Planar Stereotaxic Atlas of the Human Brain. New York, NY: Thieme Medical Publishers Inc; 1988.
62. Friston KJ, Holmes A, Poline JB, Price CJ, Frith CD. Detecting activations in PET and fMRI: levels of inference and power. Neuroimage. 1996;4:223-235.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
63. Tucker DM, Luu P, Pribram KH. Social and emotional self-regulation. Ann N Y Acad Sci. 1995;769:213-239.
WEB OF SCIENCE
| PUBMED
64. Compton RJ, Banich MT, Mohanty A, Milham MP, Herrington J, Miller GA, Scalf PE, Webb A, Heller W. Paying attention to emotion: an fMRI investigation of cognitive and emotional Stroop tasks. Cogn Affect Behav Neurosci. 2003;3:81-96.
PUBMED
65. Davidson RJ. Anterior cerebral asymmetry and the nature of emotion. Brain Cogn. 1992;20:125-151.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
66. Davidson RJ. What does the prefrontal cortex "do" in affect: perspectives on frontal EEG asymmetry research. Biol Psychol. 2004;67:219-234.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
67. 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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
68. Lopez-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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
69. 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.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
70. Koob GF. Hedonic valence, dopamine and motivation. Mol Psychiatry. 1996;1:186-189.
WEB OF SCIENCE
| PUBMED
71. Mirenowicz J, Schultz W. Preferential activation of midbrain dopamine neurons by appetitive rather than aversive stimuli. Nature. 1996;379:449-451.
FULL TEXT
| PUBMED
72. Wyvell CL, Berridge KC. Intra-accumbens amphetamine increases the conditioned incentive salience of sucrose reward: enhancement of reward "wanting" without enhanced "liking" or response reinforcement. J Neurosci. 2000;20:8122-8130.
FREE FULL TEXT
73. Salamone JD, Correa M, Mingote S, Weber SM. Nucleus accumbens dopamine and the regulation of effort in food-seeking behavior: implications for studies of natural motivation, psychiatry, and drug abuse. J Pharmacol Exp Ther. 2003;305:1-8.
FREE FULL TEXT
74. Baumann B, Danos P, Krell D, Diekmann S, Leschinger A, Stauch R, Wurthmann C, Bernstein HG, Bogerts B. Reduced volume of limbic system–affiliated basal ganglia in mood disorders: preliminary data from a postmortem study. J Neuropsychiatry Clin Neurosci. 1999;11:71-78.
FREE FULL TEXT
75. Drevets WC, Videen TO, Price JL, Preskorn SH, Carmichael ST, Raichle ME. A functional anatomical study of unipolar depression. J Neurosci. 1992;12:3628-3641.
ABSTRACT
76. Drevets WC, Price JL, Bardgett ME, Reich T, Todd RD, Raichle ME. Glucose metabolism in the amygdala in depression: relationship to diagnostic subtype and plasma cortisol levels. Pharmacol Biochem Behav. 2002;71:431-447.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
77. Strakowski SM, Adler CM, DelBello MP. Volumetric MRI studies of mood disorders: do they distinguish unipolar and bipolar disorder? Bipolar Disord. 2002;4:80-88.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
78. Blumberg HP, Leung HC, Skudlarski P, Lacadie CM, Fredericks CA, Harris BC, Charney DS, Gore JC, Krystal JH, Peterson BS. A functional magnetic resonance imaging study of bipolar disorder: state- and trait-related dysfunction in ventral prefrontal cortices. Arch Gen Psychiatry. 2003;60:601-609.
FREE FULL TEXT
79. Nugent AC, Sills R, Bain EE, Cannon D, Mah L, Zarate C, Drevets WC. Neuromorphometric measurements of the amygdala in medicated and unmedicated bipolar disorder. Abstract presented at: Human Brain Mapping Meeting; June 15, 2004; Budapest, Hungary.
80. Friston KJ, Ashburner J. Generative and recognition models for neuroanatomy. Neuroimage. 2004;23:21-24.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
81. Gainotti G. Emotional behavior and hemispheric side of the lesion. Cortex. 1972;8:41-55.
PUBMED
82. Sackeim HA, Greenberg MS, Weiman AL, Gur RC, Hungerbuhler JP, Geschwind N. Hemispheric asymmetry in the expression of positive and negative emotions: neurologic evidence. Arch Neurol. 1982;39:210-218.
FREE FULL TEXT
83. Sackeim HA, Decina P, Malitz S. Functional brain asymmetry and affective disorders. Adolesc Psychiatry. 1982;10:320-335.
PUBMED
84. Gadian DG, Isaacs EB, Cross JH, Connelly A, Jackson GD, King MD, Neville BG, Vargha-Khadem F. Lateralization of brain function in childhood revealed by magnetic resonance spectroscopy. Neurology. 1996;46:974-977.
FREE FULL TEXT
85. Jorge RE, Robinson RG, Moser D, Tateno A, Crespo-Facorro B, Arndt S. Major depression following traumatic brain injury. Arch Gen Psychiatry. 2004;61:42-50.
FREE FULL TEXT
86. Starkstein SE, Robinson RG, Honig MA, Parikh RM, Joselyn J, Price TR. Mood changes after right-hemisphere lesions. Br J Psychiatry. 1989;155:79-85.
FREE FULL TEXT
87. Pine DS, Grun J, Maguire EA, Burgess N, Zarahn E, Koda V, Fyer A, Szeszko PR, Bilder RM. Neurodevelopmental aspects of spatial navigation: a virtual reality fMRI study. Neuroimage. 2002;15:396-406.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
88. Leibenluft E, Blair RJ, Charney DS, Pine DS. Irritability in pediatric mania and other childhood psychopathology. Ann N Y Acad Sci. 2003;1008:201-218.
FULL TEXT
|
WEB OF SCIENCE
| PUBMED
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati  Twitter
What's this?
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
Influence of Genes and Environment on Brain Volumes in Twin Pairs Concordant and Discordant for Bipolar Disorder
van der Schot et al.
Arch Gen Psychiatry 2009;66:142-151.
ABSTRACT
| FULL TEXT
Pediatric Bipolar Disorder
Leibenluft and Rich
Focus 2008;6:331-347.
ABSTRACT
| FULL TEXT
Diagnostic and Sex Effects on Limbic Volumes in Early-Onset Bipolar Disorder and Schizophrenia
Frazier et al.
Schizophr Bull 2008;34:37-46.
ABSTRACT
| FULL TEXT
Identifying Functional Neuroimaging Biomarkers of Bipolar Disorder: Toward DSM-V
Phillips and Vieta
Schizophr Bull 2007;33:893-904.
ABSTRACT
| FULL TEXT
Limbic hyperactivation during processing of neutral facial expressions in children with bipolar disorder
Rich et al.
Proc. Natl. Acad. Sci. USA 2006;103:8900-8905.
ABSTRACT
| FULL TEXT
|
