Connections of the cortical–thalamic–cerebellar–cortical regions provide a framework for studying the neural substrates of schizophrenia. A novel diffusion tensor tractography method was used to evaluate the differences in white matter connectivity between 12 patients with schizophrenia and 10 controls. For the tract tracing, we focused on the connection between the cerebellum and the thalamus. Fractional anisotropy (FA) measures along the fiber tracks were compared between patients and the control sample. Fiber tracts located between the cerebellar white matter and the thalamus exhibit a reduced FA in patients with schizophrenia in comparison with controls. The FA values along the defined fiber tracts were not overall reduced but exhibited a reduction in the anisotropy in the region in the superior cerebellar peduncles projecting towards the red nucleus.
Diffusion tensor; Schizophrenia; Tractography
A number of studies are now collecting diffusion tensor imaging (DTI) data across sites. While the reliability of anatomical images has been established by a number of groups, the reliability of DTI data has not been studied as extensively. In this study, five healthy controls were recruited and imaged at eight imaging centers. Repeated measures were obtained across two imaging protocols allowing intra-subject and inter-site variability to be assessed. Regional measures within white matter were obtained for standard rotationally invariant measures: fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity. Intra-subject coefficient of variation (CV) was typically <1% for all scalars and regions. Inter-site CV increased to ∼1%–3%. Inter-vendor variation was similar to inter-site variability. This variability includes differences in the actual implementation of the sequence.
diffusion tensor; fractional anisotropy; magnetic resonance; mean diffusivity; reliability; white matter
Adolescence is a period of radical normative changes and increased risk for substance use, mood disorders, and physical injury. Researchers have proposed that increases in reward sensitivity, i.e., sensitivity of the behavioral approach system (BAS), and/or increases in reactivity to all emotional stimuli (i.e., reward and threat sensitivities) lead to these phenomena. The present study is the first longitudinal investigation of changes in reward (i.e., BAS) sensitivity in 9 to 23-year-olds across a two-year follow-up. We found support for increased reward sensitivity from early to late adolescence and evidence for decline in the early twenties. This decline is combined with a decrease in left nucleus accumbens (Nacc) volume, a key structure for reward processing, from the late teens into the early twenties. Furthermore, we found longitudinal increases in sensitivity to reward to be predicted by individual differences in the Nacc and medial OFC volumes at baseline in this developmental sample. Similarly, increases in sensitivity to threat (i.e., BIS sensitivity) were qualified by sex, with only females experiencing this increase, and predicted by individual differences in lateral OFC volumes at baseline.
Adolescence; behavioral approach system (BAS); reward sensitivity
Neuropsychiatric disorders such as schizophrenia, bipolar disorder and Alzheimer's disease are major public health problems. However, despite decades of research, we currently have no validated prognostic or diagnostic tests that can be applied at an individual patient level. Many neuropsychiatric diseases are due to a combination of alterations that occur in a human brain rather than the result of localized lesions. While there is hope that newer imaging technologies such as functional and anatomic connectivity MRI or molecular imaging may offer breakthroughs, the single biomarkers that are discovered using these datasets are limited by their inability to capture the heterogeneity and complexity of most multifactorial brain disorders. Recently, complex biomarkers have been explored to address this limitation using neuroimaging data. In this manuscript we consider the nature of complex biomarkers being investigated in the recent literature and present techniques to find such biomarkers that have been developed in related areas of data mining, statistics, machine learning and bioinformatics.
•We review data mining approaches for discovering four types of complex biomarkers.•Linear biomarkers capture linear combinations that are related to the phenotype.•Combinatorial biomarkers capture biomarkers for heterogeneous samples in a study.•Pathway biomarkers study the role of known subsystems for a given disorder.•Network biomarkers capture the role of brain network structure in a phenotype.
This report provides practical recommendations for the design and execution of Multi-Center functional Magnetic Resonance Imaging (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The paper was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multi-site aspects include: (1) establishing and verifying scan parameters including scanner types and magnetic fields, (2) establishing and monitoring of a scanner quality program, (3) developing task paradigms and scan session documentation, (4) establishing clinical and scanner training to ensure consistency over time, (5) developing means for uploading, storing, and monitoring of imaging and other data, (6) the use of a traveling fMRI expert and (7) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery.
Functional magnetic resonance imaging; fMRI; multi-center; multi-site; FIRST Biomedica Informatics Research Network; FBIRN
The objective of our study is to introduce a fully automated, computational linguistic technique to quantify semantic relations between words generated on a standard semantic verbal fluency test and to determine its cognitive and clinical correlates. Cognitive differences between patients with Alzheimer’s disease and mild cognitive impairment are evident in their performance on the semantic verbal fluency test. In addition to the semantic verbal fluency test score, several other performance characteristics sensitive to disease status and predictive of future cognitive decline have been defined in terms of words generated from semantically related categories (clustering) and shifting between categories (switching). However, the traditional assessment of clustering and switching has been performed manually in a qualitative fashion resulting in subjective scoring with limited reproducibility and scalability. Our approach uses word definitions and hierarchical relations between the words in WordNet®, a large electronic lexical database, to quantify the degree of semantic similarity and relatedness between words. We investigated the novel semantic fluency indices of mean cumulative similarity and relatedness between all pairs of words regardless of their order, and mean sequential similarity and relatedness between pairs of adjacent words in a sample of patients with clinically diagnosed probable (n=55) or possible (n=27) Alzheimer’s disease or mild cognitive impairment (n=31). The semantic fluency indices differed significantly between the diagnostic groups, and were strongly associated with neuropsychological tests of executive function, as well as the rate of global cognitive decline. Our results suggest that word meanings and relations between words shared across individuals and computationally modeled via WordNet and large text corpora provide the necessary context to account for the variability in language-based behavior and relate it to cognitive dysfunction observed in mild cognitive impairment and Alzheimer’s disease.
semantic verbal fluency; Alzheimer’s disease; mild cognitive impairment; semantic similarity; semantic relatedness; computational semantics
In the present report, estimates of test–retest and between-site reliability of fMRI assessments were produced in the context of a multicenter fMRI reliability study (FBIRN Phase 1, www.nbirn.net). Five subjects were scanned on 10 MRI scanners on two occasions. The fMRI task was a simple block design sensorimotor task. The impulse response functions to the stimulation block were derived using an FIR-deconvolution analysis with FMRISTAT. Six functionally-derived ROIs covering the visual, auditory and motor cortices, created from a prior analysis, were used. Two dependent variables were compared: percent signal change and contrast-to-noise-ratio. Reliability was assessed with intraclass correlation coefficients derived from a variance components analysis. Test–retest reliability was high, but initially, between-site reliability was low, indicating a strong contribution from site and site-by-subject variance. However, a number of factors that can markedly improve between-site reliability were uncovered, including increasing the size of the ROIs, adjusting for smoothness differences, and inclusion of additional runs. By employing multiple steps, between-site reliability for 3T scanners was increased by 123%. Dropping one site at a time and assessing reliability can be a useful method of assessing the sensitivity of the results to particular sites. These findings should provide guidance to others on the best practices for future multicenter studies.
test–retest; reproducibility; intraclass correlation coefficient; multicenter; FMRI
Abnormalities have been identified in the Cognitive Control Network (CCN) and the default mode network (DMN) during episodes of late-life depression. This study examined whether functional connectivity at rest (FC) within these networks characterize late-life depression and predict antidepressant response.
26 non-demented, non-MCI older adults were studied. Of these, 16 had major depression and 10 had no psychopathology. Depressed patients were treated with escitalopram (target dose 20 mg) for 12 weeks after a 2-week placebo phase. Resting state timeseries was determined prior to treatment. FC within the CCN was determined by placing seeds in the dACC and the DLPFC bilaterally. FC within the DMN was assessed from a seed placed in the posterior cingulate.
Low resting state FC within the CCN and high FC within the DMN distinguished depressed from normal elderly subjects. Beyond this “double dissociation”, low resting state FC within the CCN predicted low remission rate and persistence of depressive symptoms and signs, apathy, and dysexecutive behavior after treatment with escitalopram. In contrast, resting state FC within the DMN was correlated with pessimism but did not predict treatment response.
If confirmed, these findings may serve as a signature of the brain’s functional topography characterizing late-life depression and sustaining its symptoms. By identifying the network abnormalities underlying biologically meaningful characteristics (apathy, dysexecutive behavior, pessimism) and sustaining late-life depression, these findings can provide a novel target on which new somatic and psychosocial treatments can be tested.
Pathophysiological mechanisms underlying the clinically devastating CNS features of myotonic dystrophy (DM) remain more enigmatic and controversial than do the muscle abnormalities of this common form of muscular dystrophy. To better define CNS and cranial muscle changes in DM, we used quantitative volumetric and diffusion tensor MRI methods to measure cerebral and masticatory muscle differences between controls (n=5) and adults with either congenital (n=5) or adult onset (n=5) myotonic dystrophy type 1, myotonic dystrophy type 2 (n=5). Muscle volumes were diminished in DM1 and strongly correlated with reduced white matter integrity and gray matter volume. Moreover, correlation of reduced fractional anisotropy (white matter integrity) and gray matter volume in both DM1 and DM2 suggests that these abnormalities may share a common underlying pathophysiological mechanism. Further quantitative temporal and spatial characterization of these features will help delineate developmental and progressive neurological components of DM, and help determine the causative molecular and cellular mechanisms.
Myotonic dystrophy; DM; DM1; DM2; diffusion tensor imaging; magnetic resonance imaging; MRI; cerebral white matter; cerebral gray matter; craniofacial muscle; pterygoid; temporalis; masseter
To date, there has been little work describing the neurochemical profile of young, heavy marijuana users. In this study, we examined 27 young-adult marijuana users and 26 healthy controls using single-voxel magnetic resonance spectroscopy on a 3 T scanner. The voxel was placed in the dorsal striatum, and estimated concentrations of glutamate + glutamine, myo-inositol, taurine + glucose, total choline and total N-acetylaspartate were examined between groups. There were no overall group effects, but two metabolites showed group by sex interactions. Lower levels of glutamate + glutamine (scaled to total creatine) were observed in female, but not male, marijuana users compared to controls. Higher levels of myo-inositol were observed in female users compared to female non-users and to males in both groups. Findings are discussed in relation to patterns of corticostriatal connectivity and function, in the context of marijuana abuse.
•The neurochemical profile of the basal ganglia was examined in young marijuana users.•Glutamate/glutamine levels were lower in female users versus male users and controls.•Higher myo-inositol levels were observed in female users as compared to other groups.•Neurochemical impacts of marijuana may be particularly pronounced in females.
Cannabis; Glutamate; Basal ganglia; Adolescence
The complexity of the human brain’s activity and connectivity varies over temporal scales and is altered in disease states such as schizophrenia. Using a multi-level analysis of spontaneous low-frequency fMRI data stretching from the activity of individual brain regions to the coordinated connectivity pattern of the whole brain, we investigate the role of brain signal complexity in schizophrenia. Specifically, we quantitatively characterize the univariate wavelet entropy of regional activity, the bivariate pairwise functional connectivity between regions, and the multivariate network organization of connectivity patterns. Our results indicate that univariate measures of complexity are less sensitive to disease state than higher level bivariate and multivariate measures. While wavelet entropy is unaffected by disease state, the magnitude of pairwise functional connectivity is significantly decreased in schizophrenia and the variance is increased. Furthermore, by considering the network structure as a function of correlation strength, we find that network organization specifically of weak connections is strongly correlated with attention, memory, and negative symptom scores and displays potential as a clinical biomarker, providing up to 75% classification accuracy and 85% sensitivity. We also develop a general statistical framework for the testing of group differences in network properties, which is broadly applicable to studies where changes in network organization are crucial to the understanding of brain function.
schizophrenia; functional connectivity; network analysis; graph theory; resting state
Diffusion tensor imaging (DTI) is sensitive to the directionally- constrained flow of water, which diffuses preferentially along axons. Tractography programs may be used to infer matrices of connectivity (anatomical networks) between pairs of brain regions. Little is known about how these computed connectivity measures depend on the scans’ spatial and angular resolutions. To determine this, we scanned 8 young adults with DTI at 2.5 and 3 mm resolutions, and an additional subject at 4 resolutions between 2–4 mm. We computed 70×70 connectivity matrices, using whole-brain tractography to measure fiber density between all pairs of 70 cortical and subcortical regions. Spatial and angular resolution affected the computed connectivity for narrower tracts (internal capsule and cerebellum), but also for the corticospinal tract. Data resolution affected the apparent role of some key structures in cortical anatomic networks. Care is needed when comparing network data across studies, and interpreting apparent disagreements among findings.
Connectivity; diffusion imaging; tractography; networks; MRI; brain
Alzheimer’s disease (AD), cerebral vascular brain injury (VBI), and isocortical Lewy body (LB) disease (LBD) are the major contributors to dementia in community- or population-based studies: Adult Changes in Thought (ACT) study, Honolulu-Asia Aging Study (HAAS), Nun Study (NS), and Oregon Brain Aging Study (OBAS). However, the prevalence of clinically silent forms of these diseases in cognitively normal (CN) adults is less clear.
DESIGN and SETTING
We evaluated 1672 brain autopsies from ACT, HAAS, NS, and OBAS of which 424 met criteria for CN.
MAIN OUTCOME MEASURES
Of these, 336 cases had a comprehensive neuropathologic examination of neuritic plaque (NP) density, Braak stage for neurofibrillary tangles (NFTs), Lewy body (LB) distribution, and number of cerebral microinfarcts (CMIs).
47% of CN cases had moderate or frequent NP density; of these 6% also had Braak stage V or VI for NFTs. 15% of CN cases had medullary LBD; 8% also had nigral and 4% isocortical LBD. The presence of any CMIs was identified in 33% and high level CMIs in 10% of CN individuals. Overall burden of lesions in each individual and their co-morbidity varied widely within each study but were similar among studies.
These data show an individually varying complex convergence of subclinical diseases in the brain of older CN adults. Appreciating this ecology should help guide future biomarker or neuroimaging studies as well as clinical trials that focus on community- or population-based cohorts.
Alzheimer’s disease; vascular brain injury; Lewy body disease; cognitive aging
Functional neuroimaging studies suggest that chronic cocaine use is associated with frontal lobe abnormalities. Functional connectivity (FC) alterations of cocaine dependent individuals (CD), however, are not yet clear. This is the first study to our knowledge that examines resting FC of anterior cingulate cortex (ACC) in CD. Because ACC is known to integrate inputs from different brain regions to regulate behavior, we hypothesize that CD will have connectivity abnormalities in ACC networks. In addition, we hypothesized that abnormalities would be associated with poor performance in delayed discounting and reversal learning tasks.
Resting functional magnetic resonance imaging data were collected to look for FC differences between twenty-seven cocaine dependent individuals (CD) (5 females, age: M=39.73, SD=6.14) and twenty-four controls (5 females, age: M=39.76, SD = 7.09). Participants were assessed with delayed discounting and reversal learning tasks. Using seed-based FC measures, we examined FC in CD and controls within five ACC connectivity networks with seeds in subgenual, caudal, dorsal, rostral, and perigenual ACC.
CD showed increased FC within the perigenual ACC network in left middle frontal gyrus, ACC and middle temporal gyrus when compared to controls. FC abnormalities were significantly positively correlated with task performance in delayed discounting and reversal learning tasks in CD.
The present study shows that participants with chronic cocaine-dependency have hyperconnectivity within an ACC network known to be involved in social processing and mentalizing. In addition, FC abnormalities found in CD were associated with difficulties with delay rewards and slower adaptive learning.
cocaine; functional connectivity; anterior cingulate; delayed discount; reversal learning; frontal
Background: Schizophrenia is characterized by a lack of integration between thought, emotion, and behavior. A disruption in the connectivity between brain processes may underlie this schism. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were used to evaluate functional and anatomical brain connectivity in schizophrenia. Methods: In all, 29 chronic schizophrenia patients (11 females, age: mean = 41.3, SD = 9.28) and 29 controls (11 females, age: mean = 41.1, SD = 10.6) were recruited. Schizophrenia patients were assessed for severity of negative and positive symptoms and general cognitive abilities of attention/concentration and memory. Participants underwent a resting-fMRI scan and a DTI scan. For fMRI data, a hybrid independent components analysis was used to extract the group default mode network (DMN) and accompanying time-courses. Voxel-wise whole-brain multiple regressions with corresponding DMN time-courses was conducted for each subject. A t-test was conducted on resulting DMN correlation maps to look between-group differences. For DTI data, voxel-wise statistical analysis of the fractional anisotropy data was carried out to look for between-group differences. Voxel-wise correlations were conducted to investigate the relationship between brain connectivity and behavioral measures. Results: Results revealed altered functional and anatomical connectivity in medial frontal and anterior cingulate gyri of schizophrenia patients. In addition, frontal connectivity in schizophrenia patients was positively associated with symptoms as well as with general cognitive ability measures. Discussion: The present study shows convergent fMRI and DTI findings that are consistent with the disconnection hypothesis in schizophrenia, particularly in medial frontal regions, while adding some insight of the relationship between brain disconnectivity and behavior.
fMRI; DTI; default mode network; medial frontal; behavioral correlates
MRI studies, including recent diffusion tensor imaging (DTI) studies, have shown corpus callosum abnormalities in children prenatally exposed to alcohol, especially in the posterior regions. These abnormalities appear across the range of Fetal Alcohol Spectrum Disorders (FASD). Several studies have demonstrated cognitive correlates of callosal abnormalities in FASD including deficits in visual-motor skill, verbal learning, and executive functioning. The goal of this study was to determine if inter-hemispheric structural connectivity abnormalities in FASD are associated with disrupted inter-hemispheric functional connectivity and disrupted cognition.
Twenty-one children with FASD and 23 matched controls underwent a six minute resting-state functional MRI scan as well as anatomical imaging and DTI. Using a semiautomated method, we parsed the corpus callosum and delineated seven inter-hemispheric white matter tracts with DTI tractography. Cortical regions of interest (ROIs) at the distal ends of these tracts were identified. Right-left correlations in resting fMRI signal were computed for these sets of ROIs and group comparisons were done. Correlations with facial dysmorphology, cognition, and DTI measures were computed.
A significant group difference in inter-hemispheric functional connectivity was seen in a posterior set of ROIs, the para-central region. Children with FASD had functional connectivity that was 12% lower than controls in this region. Sub-group analyses were not possible due to small sample size, but the data suggest that there were effects across the FASD spectrum. No significant association with facial dysmorphology was found. Para-central functional connectivity was significantly correlated with DTI mean diffusivity, a measure of microstructural integrity, in posterior callosal tracts in controls but not in FASD. Significant correlations were seen between these structural and functional measures and Wechsler perceptual reasoning ability.
Inter-hemispheric functional connectivity disturbances were observed in children with FASD relative to controls. The disruption was measured in medial parietal regions (para-central) that are connected by posterior callosal fiber projections. We have previously shown microstructural abnormalities in these same posterior callosal regions and the current study suggests a possible relationship between the two. These measures have clinical relevance as they are associated with cognitive functioning.
Fetal alcohol (FAS, FASD); Brain; functional MRI (fMRI); resting-state, connectivity; neuropsychological
Neuroimaging studies of normative human brain development indicate that the brain matures at differing rates across time and brain regions, with some areas maturing into young adulthood. In particular, changes in cortical thickness may index maturational progressions from an overabundance of neuropil toward efficiently pruned neural networks. Developmental changes in structural MRI measures have rarely been examined in relation to discrete neuropsychological functions. In this study, healthy right-handed adolescents completed MRI scanning and the Controlled Oral Word Association Test (COWAT). Associations of task performance and cortical thickness were assessed with cortical-surface-based analyses. Significant correlations between increasing COWAT performances and decreasing cortical thickness were found in left hemisphere language regions, including perisylvian regions surrounding Wernicke’s and Broca’s areas. Task performance was also correlated with regions associated with effortful verbal processing, working memory, and performance monitoring. Structure–function associations were not significantly different between older and younger subjects. Decreases in cortical thicknesses in regions that comprise the language network likely reflect maturation toward adult-like cortical organization and processing efficiency. The changes in cortical thicknesses that support verbal fluency are apparent by middle childhood, but with regionally separate developmental trajectories for males and females, consistent with other studies of adolescent development.
The majority of patients with schizophrenia smoke cigarettes. Both nicotine use and schizophrenia have been associated with alterations in brain white matter microstructure as measured by diffusion tensor imaging (DTI). The purpose of this study was to examine fractional anisotropy (FA) in smoking and non-smoking patients with schizophrenia and in healthy volunteers. A total of 43 patients (28 smoking and 15 non-smoking) with schizophrenia and 40 healthy, non-smoking participants underwent DTI. Mean FA was calculated in four global regions of interest (ROIs) (whole brain, cerebellum, brainstem, and total cortical) as well as in four regional ROIs (frontal, temporal, parietal and occipital lobes). The non-smoking patient group had a significantly higher IQ compared to the patients who smoked and our results depended on whether IQ was included as a covariate. Without IQ correction, significant between-group effects for FA were found in four ROIs: total brain, total cortical, frontal lobe and the occipital lobe. In all cases the FA was lower among the smoking patient group, and highest in the control group. Smoking patients differed significantly from non-smoking patients in the frontal lobe ROI. However, these differences were no longer significant after IQ correction. FA differences between non-smoking patients and controls were not significant. Among smoking and non-smoking patients with schizophrenia but not healthy controls, FA was correlated with IQ. In conclusion, group effects of smoking on FA in schizophrenia might be mediated by IQ. Further, low FA in specific brain areas may be a neural marker for complex pathophysiology and risk for diverse problems such as schizophrenia, low IQ, and nicotine addiction.
Diffusion Tensor Imaging; Nicotine; Fractional Anisotropy
Artifacts in fMRI data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI preprocessing. Independent component analysis’ demonstrated capacity to separate sources of neural signal, structured noise, and random noise into separate components might be utilized in improved procedures to remove artifacts from fMRI data. Such procedures require a method for labeling independent components (ICs) as representing artifacts to be removed or neural signals of interest to be spared. Visual inspection is often considered an accurate method for such labeling as well as a standard to which automated labeling methods are compared. However, detailed descriptions of methods for visual inspection of ICs are lacking in the literature. Here we describe the details of, and the rationale for, an operationalized fMRI data denoising procedure that involves visual inspection of ICs (96% inter-rater agreement). We estimate that dozens of subjects/sessions can be processed within a few hours using the described method of visual inspection. Our hope is that continued scientific discussion of and testing of visual inspection methods will lead to the development of improved, cost-effective fMRI denoising procedures.
fMRI; independent component analysis (ICA); denoising; visual inspection; artifacts; structured noise; independent component (IC) labeling
As part of a sham controlled treatment trial using daily left rTMS, brain changes associated with four to six weeks of treatment were examined using diffusion tensor imaging (DTI) in order to non-invasively evaluate prefrontal white matter microstructure. A decrease in fractional anisotropy (FA) values of the left prefrontal white matter could indicate damage to the region.
DTI was performed prior to and after 4–6 weeks of daily rTMS treatments. Mean FA levels associated with active rTMS and sham rTMS for the right and left prefrontal white matter (LPF-WM) were assessed.
Adequate images were acquired for eight participants (active n=4, sham n=4) before and after rTMS. A mean increase was found for the LPF-WM. The mixed model revealed a trend toward a significant Treatment Group × Region interaction effect (p=0.11). Further, simple Region effects (left prefrontal WM vs. right prefrontal WM) were at a trend toward significance for difference after treatment within the active rTMS group (p=.07), but not within the sham rTMS group (p=.88).
RTMS resulted in no evidence of damage to WM on the side of stimulation. DTI may offer a unique modality to increase our understanding of mechanisms of action for rTMS.
Diffusion Tensor Imaging (DTI); Transcranial Magnetic Stimulation; rTMS; depression; mixed linear model analysis of repeated measures
Diffusion Tensor Imaging was used to evaluate cerebral white matter in eight patients (ages 10–17) with myotonic dystrophy type 1 (3 congenital-onset, 5 juvenile-onset) compared to eight controls matched for age and sex. Four regions of interest were examined: inferior frontal, superior frontal, supracallosal, and occipital. The myotonic dystrophy group showed white matter abnormalities compared to controls in all regions. All indices of white matter integrity were abnormal: fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. With no evidence of regional variation, correlations between whole cerebrum white matter fractional anisotropy and neurocognitive functioning were examined in the patients. Strong correlations were observed between whole cerebrum fractional anisotropy and full-scale intelligence and a measure of executive functioning. Results indicate that significant white matter abnormality is characteristic of young patients with myotonic dystrophy type 1 and that the white matter abnormality seen with neuroimaging has implications for cognitive functioning.
Borderline personality disorder (BPD) is a complex psychiatric disorder that involves the core feature of affect dysregulation. Prior neuroimaging studies have indicated that BPD patients have (1) excessive amygdala activation to negative emotion and (2) diminished frontal regulation. This study examined amygdala functional connectivity in 12 women with BPD and 12 matched healthy comparison volunteers. We explored how connectivity patterns would change in the context of processing neutral, overt fear, or masked fear face expressions. Each participant underwent three 5-min fMRI scans in which they primarily viewed: (1) neutral, (2) overt fear, and (3) masked fear faces. In comparison to their healthy counterparts, young women with BPD showed (1) lower connectivity between bilateral amygdala and mid-cingulate cortex during the neutral scan; (2) higher connectivity between bilateral amygdala and rostral anterior cingulate cortex during the overt fear scan; and (3) higher right amygdala connectivity with bilateral thalamus and right caudate during the masked fear scan. Exploratory analyses revealed interesting correlations between amygdala connectivity in these conditions with multiple clinical measures. Results from the neutral scan add to the few prior connectivity studies in BPD that have been suggestive of lower fronto-limbic connectivity in BPD. However, the connectivity findings during fear processing are novel, and map onto basic research models for amygdala connectivity, that is, connections to frontal areas for overt fear processing versus connections to thalamus for automatic fear processing. Further, results suggest that BPD subjects tap into both pathways more strongly than healthy comparisons.
amygdala; borderline personality disorder; functional connectivity; functional neuroimaging; masked fear; overt fear
Background: Emerging evidence implicates white matter (WM) abnormalities in the pathophysiology of schizophrenia. However, there is considerable heterogeneity in the presentation of WM abnormalities in the existing studies. The object of this study was to evaluate WM integrity in a large sample of patients with first-episode (FE) and chronic schizophrenia in comparison to matched control groups. Our goal was to assess whether WM findings occurred early in the illness or whether these abnormalities developed with the illness over time. Methods: Participants included 114 patients with schizophrenia (31 FE and 83 chronic patients) and 138 matched controls. High-resolution structural and diffusion tensor images were obtained on all participants. Measures of fractional anisotropy (FA) were calculated for the 4 cortical lobes and the cerebellum and brain stem. Results: FA was significant lower in patients vs controls in the whole brain and individually in the frontal, parietal, occipital, and temporal lobes. FA was not significantly different in the brain stem or cerebellum. FA differences were significant only in patients with chronic schizophrenia and not in the FE group. Conclusions: We found global differences in the WM microstructure in patients with chronic but not FE schizophrenia. These findings suggest progressive alterations in WM microstructure.
first-episode schizophrenia; fractional anisotropy; neuroimaging; DTI; microstructure
Previous studies have observed disruptions in brain white and gray matter structure in individuals with type 1 diabetes, and these structural differences have been associated with neurocognitive testing deficiencies. This study investigated the relationship between cerebral cortical thickness reductions and white matter microstructural integrity loss in a group of patients with type 1 diabetes and in healthy control subjects using diffusion tensor imaging (DTI).
RESEARCH DESIGN AND METHODS
Twenty-five subjects with type 1 diabetes for at least 15 years and 25 age- and sex-matched control subjects underwent structural T1 and proton-density and DTI on a 3.0 Tesla scanner. Fractional anisotropy measurements were made on major cerebral white matter tracts, and DTI tractography was performed to identify cortical regions with high connectivity to these tracts.
Posterior white matter tracts with reduced fractional anisotropy (optic radiations, posterior corona radiata, and the splenium region of the corpus callosum) were found to have high connectivity with a number of posterior cortical regions, including the cuneus, precuneus, fusiform, and posterior parietal cortical regions. A significant reduction in cortical thickness in the diabetic group was observed in the regions with high connectivity to the optic radiations and posterior corona radiata tracts (P < 0.05).
The direct relationship between white and gray matter structural pathology has not been previously demonstrated in subjects with long-standing type 1 diabetes. The relationship between posterior white matter microstructural integrity disruption and lower cortical thickness demonstrated using a novel DTI connectivity technique suggests a common or interrelated pathophysiological mechanism in type 1 diabetes.
Structural abnormalities in the hippocampus have been implicated in the pathophysiology of major depressive disorder (MDD). The brain derived neurotrophic factor (BDNF) val66met polymorphism may contribute to these abnormalities and therefore confer vulnerability to MDD. This study examined whether there is a relationship among BDNF genotype, hippocampal volumes, and MDD in older adults.
Thirty-three older adults with MDD and 23 psychiatrically normal comparison subjects were studied. Structural MRI analysis was used to quantify hippocampal volumes. A repeated measures ANCOVA examined the relationships among BDNF val66met (val/val, met carrier), diagnosis (depressed, non-depressed), and hippocampal volumes (right, left). Age, gender, education, and whole brain volume were included as covariates.
Elderly MDD BDNF val/val homozygotes had significantly higher right hippocampal volumes compared with non-depressed val/val subjects. However, there was no difference between the depressed and healthy non-depressed met carriers. Additionally, depressed met carriers had an earlier age of onset of depressive illness than val/val homozygotes but age of onset did not moderate the relationship between hippocampal volumes and MDD diagnosis.
These results provide preliminary evidence of a neuroprotective role of the val/val genotype, suggesting neurotrophic factor production protects against pathophysiological processes triggered by depression in older adults with later age of onset of MDD. The BDNF val66met polymorphism may play a salient role in structural alterations of the hippocampus in older adults with MDD.
Geriatric depression; BDNF val66met; hippocampus; older adults