Markers of chronic cocaine exposure on neural mechanisms in animals and humans is of great interest. The probabilistic reversal-learning task may be an effective way to examine dysfunction associated with cocaine addiction. However the exact nature of the performance deficits observed in cocaine users has yet to be disambiguated.
Data from a probabilistic reversal-learning task performed by 45 cocaine users and 41 controls was compared and fit to a Bayesian hidden Markov model (HMM).
Cocaine users demonstrated the predicted performance deficit in achieving the reversal criterion relative to controls. The deficit appeared to be due to excessive switching behavior as evidenced by responsivity to false feedback and spontaneous switching. This decision-making behavior could be captured by a single parameter in an HMM and did not require an additional parameter to represent perseverative errors.
Cocaine users are characterized by excessive switching behavior on the reversal-learning task. While there may be a compulsive component to behavior on this task, impulsive decision-making may be more relevant to observed impairment. This is important in building diagnostic tools to quantify the degree to which each type of dysfunction is present in individuals, and may play a role in developing treatments for those dysfunctions.
reinforcement learning; Bayesian hidden Markov model; reversal learning; decision making; reward; state switching; cocaine; impulsivity; compulsivity
The Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS), and the Positive and Negative Syndrome Scale for Schizophrenia (PANSS) are the most widely used schizophrenia symptom rating scales, but despite their co-existence for 25 years no easily usable between-scale conversion mechanism exists. The aim of this study was to provide equations for between-scale symptom rating conversions. Two- hundred-and-five schizophrenia patients [mean age±SD=39.5±11.6), 156 males] were assessed with the SANS, SAPS, and PANSS. Pearson’s correlations between symptom scores from each of the scales were computed. Linear regression analyses, on data from 176 randomly selected patients, were performed to derive equations for converting ratings between the scales. Intraclass correlations, on data from the remaining 29 patients, not part of the regression analyses, were performed to determine rating conversion accuracy. Between-scale positive and negative symptom ratings were highly correlated. Intraclass correlations between the original positive and negative symptom ratings and those obtained via conversion of alternative ratings using the conversion equations were moderate to high (ICCs = 0.65 to 0.91). Regression-based equations may be useful for conversion between schizophrenia symptom severity as measured by the SANS/SAPS and PANSS, though additional validation is warranted. This study’s conversion equations, implemented at http::/converteasy.org, may aid in the comparison of medication efficacy studies, in meta- and mega-analyses examining symptoms as moderator variables, and in retrospective combination of symptom data in multi-center data sharing projects that need to pool symptom rating data when such data are obtained using different scales.
schizophrenia; symptoms; Marder; conversion; meta; multi-center
Healthy participants (n = 79), ages 9–23, completed a delay discounting task assessing the extent to which the value of a monetary reward declines as the delay to its receipt increases. Diffusion tensor imaging (DTI) was used to evaluate how individual differences in delay discounting relate to variation in fractional anisotropy (FA) and mean diffusivity (MD) within whole-brain white matter using voxel-based regressions. Given that rapid prefrontal lobe development is occurring during this age range and that functional imaging studies have implicated the prefrontal cortex in discounting behavior, we hypothesized that differences in FA and MD would be associated with alterations in the discounting rate. The analyses revealed a number of clusters where less impulsive performance on the delay discounting task was associated with higher FA and lower MD. The clusters were located primarily in bilateral frontal and temporal lobes and were localized within white matter tracts, including portions of the inferior and superior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus, inferior fronto-occipital fasciculus, corticospinal tract, and splenium of the corpus callosum. FA increased and MD decreased with age in the majority of these regions. Some, but not all, of the discounting/ DTI associations remained significant after controlling for age. Findings are discussed in terms of both developmental and age-independent effects of white matter organization on discounting behavior.
Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.
The human brain is a fascinating organ full of exquisite anatomical and functional detail. A striking feature of this detail lies in the presence of small modules nested within one another across hierarchical levels of organization. Here we develop and apply computational analysis tools to probe these features of brain architecture by examining network representations in which brain areas are treated as network nodes and links between areas are treated as network edges. The class of methods that we describe are referred to as “multi-resolution techniques” and enable us to identify and isolate neural structures associated with different edge properties. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.
Neuroimaging research indicates that human intellectual ability is related to brain structure including the thickness of the cerebral cortex. Most studies indicate that general intelligence is positively associated with cortical thickness in areas of association cortex distributed throughout both brain hemispheres. In this study, we performed a cortical thickness mapping analysis on data from 182 healthy typically developing males and females ages 9 to 24 years to identify correlates of general intelligence (g) scores. To determine if these correlates also mediate associations of specific cognitive abilities with cortical thickness, we regressed specific cognitive test scores on g scores and analyzed the residuals with respect to cortical thickness. The effect of age on the association between cortical thickness and intelligence was examined. We found a widely distributed pattern of positive associations between cortical thickness and g scores, as derived from the first unrotated principal factor of a factor analysis of Wechsler Abbreviated Scale of Intelligence (WASI) subtest scores. After WASI specific cognitive subtest scores were regressed on g factor scores, the residual score variances did not correlate significantly with cortical thickness in the full sample with age covaried. When participants were grouped at the age median, significant positive associations of cortical thickness were obtained in the older group for g-residualized scores on Block Design (a measure of visual-motor integrative processing) while significant negative associations of cortical thickness were observed in the younger group for g-residualized Vocabulary scores. These results regarding correlates of general intelligence are concordant with the existing literature, while the findings from younger versus older subgroups have implications for future research on brain structural correlates of specific cognitive abilities, as well as the cognitive domain specificity of behavioral performance correlates of normative gray matter thinning during adolescence.
neuroimaging; development; cortical thickness; general intelligence; specific cognitive abilities
Cocaine dependence is a particularly severe problem in the United States, resulting in broad economic and personal costs. Significant evidence of generalized cognitive deficits associated with cocaine dependence has been reported. Two studies evaluated whether context processing, the processes involved in representing and maintaining information regarding the context of one’s environment, might be seen as a process-specific deficit that may explain some aspects of the broader cognitive deficits associated with cocaine dependence. Study 1 used the expectancy variant of the AX task to assess this ability; Study 2 employed the Dot Pattern Expectancy (DPX) task. Significant between-group differences were found in each study for d′-context, a comparison of AX hits and BX misses; these results indicated significant between-group differences in context processing ability. In Study 1, significant between-group a priori contrasts of AY vs. BX trials indicated the likelihood of a specific deficit in context processing in the cocaine group; however, this contrast was not significant in Study 2. Overall, the results of these studies support the theory of impaired context processing ability associated with cocaine misuse. However, these results do not allow for the interpretation of a process-specific deficit in context processing ability. Future research targeted at investigating aspects of this context processing impairment associated with cocaine misuse can shed light on the specificity of this deficit.
cocaine; drug dependence; cognitive control; executive functioning
Apathy is common in late-life depression and is associated with disability and poor antidepressant response. This study examined whether resting functional connectivity (FC) of the nucleus accumbens (NAcc) and the dorsal anterior cingulate (dACC) with other structures can distinguish apathetic depressed older patients from nonapathetic depressed patients and normal subjects.
functional connectivity; apathy; late life depression
Expertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and sex and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). The Mental Illness and Neuroscience Discovery Institute, now the Mind Research Network (MRN, www.mrn.org), comprised of investigators at the University of New Mexico, the University of Minnesota, Massachusetts General Hospital, and the University of Iowa, conducted a cross-sectional study to identify quantitative neuroimaging biomarkers of schizophrenia. Data acquisition across multiple sites permitted the integration and cross-validation of clinical, cognitive, morphometric, and functional neuroimaging results gathered from unique samples of schizophrenia patients and controls using a common protocol across sites. Particular effort was made to recruit patients early in the course of their illness, at the onset of their symptoms. There is a relatively even sampling of illness duration in chronic patients. This data repository will be useful to 1) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops. Sharing provides the opportunity for independent replication of already published results from this data set and novel exploration. This manuscript describes the inclusion/exclusion criteria, imaging parameters and other information that will assist those wishing to use this data repository.
Medical Image Data repository; Schizophrenia; fMRI; DWI; mMRI; healthy controls
Alcohol use in excessive quantities has deleterious effects on brain structure and behavior in adults and during periods of rapid neurodevelopment, such as prenatally. Whether similar outcomes characterize other developmental periods, such as adolescence, and in the context of less extensive use is unknown. Recent cross-sectional studies suggest that binge drinking as well as alcohol use disorders in adolescence are associated with disruptions in white matter microstructure and gray matter volumes.
The current study followed typically developing adolescents from a baseline assessment, where no experience with alcohol was present, through two years, after which some individuals transitioned into regular use.
Participants (n = 55) completed MRI scans and behavioral assessments.
Alcohol initiators (n = 30; mean baseline age 16.7 ± 1.3 years), compared to non-users (n = 25; mean baseline age 17.1 ± 1.2 years), showed altered patterns of neurodevelopment. They showed greater-than-expected decreases in cortical thickness in the right middle frontal gyrus from baseline to follow-up as well as blunted development of white matter in the right hemisphere precentral gyrus, lingual gyrus, middle temporal gyrus and anterior cingulate. Diffusion tensor imaging revealed a relative decrease over time in fractional anisotropy in the left caudate/thalamic region as well as in the right inferior frontal occipital fasciculus. Alcohol initiators did not differ from non-users at the baseline assessment; the groups were largely similar in other premorbid characteristics.
Subclinical alcohol use during mid-to-late adolescence is associated with deviations in neurodevelopment across several brain tissue classes. Implications for continued development and behavior are discussed.
Adolescence; brain development; MRI
Previous studies, including those employing Diffusion Tensor Imaging (DTI), have revealed significant disturbances in the white matter of individuals with Fetal Alcohol Spectrum Disorders (FASD). Both macrostructural and microstructural abnormalities have been observed across levels of FASD severity. Emerging evidence suggests that these white matter abnormalities are associated with functional deficits. This study used resting-state fMRI to evaluate the status of network functional connectivity in children with FASD compared to control subjects.
Participants included 24 children with FASD, ages 10–17, and 31 matched controls. Neurocognitive tests were administered including Wechsler Intelligence Scales, California Verbal Learning Test, and Behavior Rating Inventory of Executive Functioning. High resolution anatomical MRI data and six-minute resting-state fMRI data were collected. The resting-state fMRI data were subjected to a graph theory analysis and four global measures of cortical network connectivity were computed: characteristic path length, mean clustering coefficient, local efficiency, and global efficiency.
Results revealed significantly altered network connectivity in those with FASD. The characteristic path length was 3.1% higher (p=.04, Cohen’s d=.47) and global efficiency was 1.9% lower (p=.04, d=.63) in children with FASD compared to controls, suggesting decreased network capacity that may have implications for integrative cognitive functioning. Global efficiency was significantly positively correlated with cortical thickness in frontal (r=.38, p=.005), temporal (r=.28, p=.043), and parietal (r=.36, p=.008) regions. No relationship between facial dysmorphology and functional connectivity was observed. Exploratory correlations suggested that global efficiency and characteristic path length are associated with capacity for immediate verbal memory on the CVLT (r=.41, p=.05 and r=.41, p=.01 respectively) among those with FASD.
Resting-state functional connectivity measures provide new insight into the integrity of brain networks in clinical populations such as FASD. Results demonstrate that children with FASD have alterations in core components of network function and that these aspects of brain integrity are related to measures of structure and cognitive functioning.
Fetal alcohol (FAS, FASD); Brain; functional MRI (fMRI); resting-state; connectivity; neuropsychological
Diffusion Tensor Imaging was used to evaluate cerebral white matter in 16 patients (ages 9–18) with myotonic dystrophy type 1 compared to 15 matched controls. Patients with myotonic dystrophy showed abnormalities in mean diffusivity compared to controls in frontal, temporal, parietal, and occipital white matter and in all individual tracts examined. Whole cerebrum mean diffusivity was 8.6% higher overall in patients with myotonic dystrophy compared to controls. Whole cerebrum fractional anisotropy was also abnormal (10.8% low overall) in all regions and tracts except corticospinal tracts. Follow-up analysis of parallel and perpendicular diffusivity suggests possible relative preservation of myelin in corticospinal tracts. Correlations between Wechsler working memory performance and mean diffusivity were strong for all regions. Frontal and temporal fractional anisotropy were correlated with working memory as well. Results are consistent with earlier studies demonstrating that significant white matter disturbances are characteristic in young patients with myotonic dystrophy and that these abnormalities are associated with the degree of working memory impairment seen in this disease.
Diffusion Tensor Imaging; DTI; Myotonic Dystrophy; Child; MRI
The field of neuromodulation encompasses a wide spectrum of interventional technologies that modify pathological activity within the nervous system to achieve a therapeutic effect. Therapies including deep brain stimulation (DBS), intracranial cortical stimulation (ICS), transcranial direct current stimulation (tDCS), and transcranial magnetic stimulation (TMS) have all shown promising results across a range of neurological and neuropsychiatric disorders. While the mechanisms of therapeutic action are invariably different amongst these approaches, there are several fundamental neuroengineering challenges that are commonly applicable to improving neuromodulation efficacy. This article reviews the state-of-the-art of neuromodulation for brain disorders and discusses the challenges and opportunities available for clinicians and researchers interested in advancing neuromodulation therapies.
neuromodulation; neuroengineering; deep brain stimulation; intracranial cortical stimulation; transcranial magnetic stimulation; transcranial direct current stimulation
The quest to map brain connectivity is being pursued worldwide using diffusion imaging, among other techniques. Even so, we know little about how brain connectivity measures depend on the magnetic field strength of the scanner. To investigate this, we scanned 10 healthy subjects at 7 and 3 tesla—using 128-gradient high-angular resolution diffusion imaging. For each subject and scan, whole-brain tractography was used to estimate connectivity between 113 cortical and subcortical regions. We examined how scanner field strength affects (i) the signal-to-noise ratio (SNR) of the non-diffusion-sensitized reference images (b0); (ii) diffusion tensor imaging (DTI)-derived fractional anisotropy (FA), mean, radial, and axial diffusivity (MD/RD/AD), in atlas-defined regions; (iii) whole-brain tractography; (iv) the 113×113 brain connectivity maps; and (v) five commonly used network topology measures. We also assessed effects of the multi-channel reconstruction methods (sum-of-squares, SOS, at 7T; adaptive recombine, AC, at 3T). At 7T with SOS, the b0 images had 18.3% higher SNR than with 3T-AC. FA was similar for most regions of interest (ROIs) derived from an online DTI atlas (ICBM81), but higher at 7T in the cerebral peduncle and internal capsule. MD, AD, and RD were lower at 7T for most ROIs. The apparent fiber density between some subcortical regions was greater at 7T-SOS than 3T-AC, with a consistent connection pattern overall. Suggesting the need for caution, the recovered brain network was apparently more efficient at 7T, which cannot be biologically true as the same subjects were assessed. Care is needed when comparing network measures across studies, and when interpreting apparently discrepant findings.
brain network analysis; DTI; fractional anisotropy; graph theory; high-field MRI; high angular resolution diffusion imaging (HARDI); signal-to-noise ratio; tractography
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. Therewere 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.
Cannabis; Glutamate; Basal ganglia; Adolescence
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
Age at onset of diagnostic motor manifestations in Huntington disease (HD) is strongly correlated with an expanded CAG trinucleotide repeat. The length of the normal CAG repeat allele has been reported also to influence age at onset, in interaction with the expanded allele. Due to profound implications for disease mechanism and modification, we tested whether the normal allele, interaction between the expanded and normal alleles, or presence of a second expanded allele affects age at onset of HD motor signs.
We modeled natural log-transformed age at onset as a function of CAG repeat lengths of expanded and normal alleles and their interaction by linear regression.
An apparently significant effect of interaction on age at motor onset among 4,068 subjects was dependent on a single outlier data point. A rigorous statistical analysis with a well-behaved dataset that conformed to the fundamental assumptions of linear regression (e.g., constant variance and normally distributed error) revealed significance only for the expanded CAG repeat, with no effect of the normal CAG repeat. Ten subjects with 2 expanded alleles showed an age at motor onset consistent with the length of the larger expanded allele.
Normal allele CAG length, interaction between expanded and normal alleles, and presence of a second expanded allele do not influence age at onset of motor manifestations, indicating that the rate of HD pathogenesis leading to motor diagnosis is determined by a completely dominant action of the longest expanded allele and as yet unidentified genetic or environmental factors. Neurology® 2012;78:690–695