Kanchana Jagannathan

Measuring brain connectivity: Diffusion tensor imaging validates resting state temporal correlations

Diffusion tensor imaging (DTI) and resting state temporal correlations (RSTC) are two leading techniques for investigating the connectivity of the human brain. They have been widely used to investigate the strength of anatomical and functional connections between distant brain regions in healthy subjects, and in clinical populations. Though they are both based on magnetic resonance imaging (MRI) they have not yet been compared directly. In this work both techniques were employed to create global connectivity matrices covering the whole brain gray matter. This allowed for direct comparisons between functional connectivity measured by RSTC with anatomical connectivity quantified using DTI tractography. We found that connectivity matrices obtained using both techniques showed significant agreement. Connectivity maps created for a priori defined anatomical regions showed significant correlation, and furthermore agreement was especially high in regions showing strong overall connectivity, such as those belonging to the default mode network. Direct comparison between functional RSTC and anatomical DTI connectivity, presented here for the first time, links two powerful approaches for investigating brain connectivity and shows their strong agreement. It provides a crucial multi-modal validation for resting state correlations as representing neuronal connectivity. The combination of both techniques presented here allows for further combining them to provide richer representation of brain connectivity both in the healthy brain and in clinical conditions.

Brain Connectivity Is Not Only Lower but Different in Schizophrenia: A Combined Anatomical and Functional Approach

BACKGROUND Schizophrenia is hypothesized to involve disordered connectivity between brain regions. Currently, there are no direct measures of brain connectivity; functional and structural connectivity used separately provide only limited insight. Simultaneous measure of anatomical and functional connectivity and its interactions allow for better understanding of schizophrenia-related alternations in brain connectivity. METHODS Twenty-seven schizophrenia patients and 27 healthy control subjects underwent magnetic resonance imaging with resting state functional magnetic resonance imaging and diffusion tensor imaging. Separate functional and anatomical connectivity maps were calculated and combined for each subject. Global, regional, and voxel measures and K-means network analysis were employed to identify group differences and correlation with clinical symptoms. RESULTS A global connectivity analysis indicated that patients had lower anatomical connectivity and lower coherence between the two imaging modalities. In schizophrenia these group differences correlated with clinical symptom severity. Although anatomical connectivity nearly uniformly decreased, functional connectivity in schizophrenia was lower for some connections (e.g., middle temporal gyrus) and higher for others (e.g., cingulate and thalamus). Within the default mode network (DMN) two separate subsystems can be identified. Schizophrenia patients showed decoupling between structural and functional connectivity that can be localized to networks originating in posterior cingulate cortex as well as in the task-positive network and one of the DMN components. CONCLUSIONS Combining two measures of brain connectivity provides more comprehensive descriptions of altered brain connectivity underlying schizophrenia. Patients show deficits in white matter anatomy, but functional connectivity alterations are more complex. Fusion of both methods allows identification of subsystems showing both increased and decreased functional connectivity.

A Large Scale (N=400) Investigation of Gray Matter Differences in Schizophrenia Using Optimized Voxel-based Morphometry

BACKGROUND Many studies have employed voxel-based morphometry (VBM) of MRI images as an automated method of investigating cortical gray matter differences in schizophrenia. However, results from these studies vary widely, likely due to different methodological or statistical approaches. OBJECTIVE To use VBM to investigate gray matter differences in schizophrenia in a sample significantly larger than any published to date, and to increase statistical power sufficiently to reveal differences missed in smaller analyses. METHODS Magnetic resonance whole brain images were acquired from four geographic sites, all using the same model 1.5T scanner and software version, and combined to form a sample of 200 patients with both first episode and chronic schizophrenia and 200 healthy controls, matched for age, gender and scanner location. Gray matter concentration was assessed and compared using optimized VBM. RESULTS Compared to healthy controls, schizophrenia patients showed significantly less gray matter concentration in multiple cortical and subcortical regions, some previously unreported. Overall, we found lower concentrations of gray matter in regions identified in prior studies, most of which reported only subsets of the affected areas. CONCLUSIONS Gray matter differences in schizophrenia are most comprehensively elucidated using a large, diverse and representative sample.

Anomalous neural circuit function in schizophrenia during a virtual Morris water task

Previous studies have reported learning and navigation impairments in schizophrenia patients during virtual reality allocentric learning tasks. The neural bases of these deficits have not been explored using functional MRI despite well-explored anatomic characterization of these paradigms in non-human animals. Our objective was to characterize the differential distributed neural circuits involved in virtual Morris water task performance using independent component analysis (ICA) in schizophrenia patients and controls. Additionally, we present behavioral data in order to derive relationships between brain function and performance, and we have included a general linear model-based analysis in order to exemplify the incremental and differential results afforded by ICA. Thirty-four individuals with schizophrenia and twenty-eight healthy controls underwent fMRI scanning during a block design virtual Morris water task using hidden and visible platform conditions. Independent components analysis was used to deconstruct neural contributions to hidden and visible platform conditions for patients and controls. We also examined performance variables, voxel-based morphometry and hippocampal subparcellation, and regional BOLD signal variation. Independent component analysis identified five neural circuits. Mesial temporal lobe regions, including the hippocampus, were consistently task-related across conditions and groups. Frontal, striatal, and parietal circuits were recruited preferentially during the visible condition for patients, while frontal and temporal lobe regions were more saliently recruited by controls during the hidden platform condition. Gray matter concentrations and BOLD signal in hippocampal subregions were associated with task performance in controls but not patients. Patients exhibited impaired performance on the hidden and visible conditions of the task, related to negative symptom severity. While controls showed coupling between neural circuits, regional neuroanatomy, and behavior, patients activated different task-related neural circuits, not associated with appropriate regional neuroanatomy. GLM analysis elucidated several comparable regions, with the exception of the hippocampus. Inefficient allocentric learning and memory in patients may be related to an inability to recruit appropriate task-dependent neural circuits.

Genetic Associations of Brain Structural Networks in Schizophrenia: A Preliminary Study

BACKGROUND Schizophrenia is a complex genetic disorder, with multiple putative risk genes and many reports of reduced cortical gray matter. Identifying the genetic loci contributing to these structural alterations in schizophrenia (and likely also to normal structural gray matter patterns) could aid understanding of schizophrenias pathophysiology. We used structural parameters as potential intermediate illness markers to investigate genomic factors derived from single nucleotide polymorphism (SNP) arrays. METHOD We used research quality structural magnetic resonance imaging (sMRI) scans from European American subjects including 33 healthy control subjects and 18 schizophrenia patients. All subjects were genotyped for 367 SNPs. Linked sMRI and genetic (SNP) components were extracted to reveal relationships between brain structure and SNPs, using parallel independent component analysis, a novel multivariate approach that operates effectively in small sample sizes. RESULTS We identified an sMRI component that significantly correlated with a genetic component (r = -.536, p < .00005); components also distinguished groups. In the sMRI component, schizophrenia gray matter deficits were in brain regions consistently implicated in previous reports, including frontal and temporal lobes and thalamus (p < .01). These deficits were related to SNPs from 16 genes, several previously associated with schizophrenia risk and/or involved in normal central nervous system development, including AKT, PI3K, SLC6A4, DRD2, CHRM2, and ADORA2A. CONCLUSIONS Despite the small sample size, this novel analysis method identified an sMRI component including brain areas previously reported to be abnormal in schizophrenia and an associated genetic component containing several putative schizophrenia risk genes. Thus, we identified multiple genes potentially underlying specific structural brain abnormalities in schizophrenia.

Physiogenomic Analysis of Localized fMRI Brain Activity in Schizophrenia

The search for genetic factors associated with disease is complicated by the complexity of the biological pathways linking genotype and phenotype. This analytical complexity is particularly concerning in diseases historically lacking reliable diagnostic biological markers, such as schizophrenia and other mental disorders. We investigate the use of functional magnetic resonance imaging (fMRI) as an intermediate phenotype (endophenotype) to identify physiogenomic associations to schizophrenia. We screened 99 subjects, 30 subjects diagnosed with schizophrenia, 13 unaffected relatives of schizophrenia patients, and 56 unrelated controls, for gene polymorphisms associated with fMRI activation patterns at two locations in temporal and frontal lobes previously implied in schizophrenia. A total of 22 single nucleotide polymorphisms (SNPs) in 15 genes from the dopamine and serotonin neurotransmission pathways were genotyped in all subjects. We identified three SNPs in genes that are significantly associated with fMRI activity. SNPs of the dopamine beta-hydroxylase (DBH) gene and of the dopamine receptor D4 (DRD4) were associated with activity in the temporal and frontal lobes, respectively. One SNP of serotonin-3A receptor (HTR3A) was associated with temporal lobe activity. The results of this study support the physiogenomic analysis of neuroimaging data to discover associations between genotype and disease-related phenotypes.

Impairment in semantic retrieval is associated with symptoms in schizophrenia but not bipolar disorder.

BACKGROUND The Semantic Object Retrieval Task (SORT) requires participants to indicate whether word pairs recall a third object. Schizophrenia individuals (SZ) tend to report associations between nonassociated word pairs; this overretrieval is related to formal thought disorder (FTD). Since semantic memory impairments and psychosis are also found in bipolar disorder (BP), we examined whether SORT impairments and their relationship to symptoms are also present in BP. METHODS Participants (n = 239; healthy control subjects [HC] = 133; BP = 32; SZ = 74) completed SORT while undergoing functional magnetic resonance imaging (fMRI) scanning. RESULTS Retrieval accuracy negatively correlated with negative symptoms and no-retrieval accuracy negatively correlated with FTD severity in SZ but not BP. Retrieval versus no-retrieval trials activated a distributed fronto-parieto-temporal network; bilateral inferior parietal lobule (IPL) activity was larger in HC versus SZ and HC versus BP, with no difference in SZ versus BP. Right IPL activity positively correlated with positive and general psychosis symptoms in SZ but not BP. CONCLUSIONS SZ reported more associations between unrelated word pairs than HC; this overretrieval increased with FTD severity. Schizophrenia individuals were also more likely to fail to find associations between related word pairs; this underretrieval increased with negative symptom severity. fMRI symptom correlations in IPL in SZ are consistent with arguments that IPL abnormality relates to loosening of associations in SZ. By comparison, BP showed intermediate impairments on SORT, uncorrelated with symptoms, suggesting that the relationship between SORT performance, fMRI activity, and psychotic symptoms is schizophrenia-specific.

Effect of exercise training on hippocampal volume in humans: a pilot study.

The hippocampus is the primary site of memory and learning in the brain. Both normal aging and various disease pathologies (e.g., alcoholism, schizophrenia, and major depressive disorder) are associated with lower hippocampal volumes in humans ( Agartz, Momenan, Rawlings, Kerich, & Hommer, 1999; Barta, Dhingra, Royall, & Schwartz, 1997; Jernigan et al., 2001; McKinnon, Yucel, Nazarov, & MacQueen, 2009; Meisenzahl et al., 2009), and hippocampal atrophy predicts progression of Alzheimers disease (Henneman et al., 2009). In animals, there is convincing evidence that exercise training increases hippocampal volume (Van der Borght, Havekes, Bos, Eggen, & Van der Zee, 2007; van Praag, Shubert, Zhao, & Gage, 2005;). A recent cross-sectional study in older humans demonstrated a positive relation between aerobic fitness and hippocampal volume (Erickson et al., 2009). Moreover, a recent study found that a year of aerobic exercise training increases hippocampal volume by 2% in older adults (Erickson et al., 2011). Accordingly, in the current preliminary study we sought to confirm the direct effect of supervised exercise training on magnetic resonance imaging (MRI) estimates of hippocampal volume in healthy humans. Method

Figural memory performance and functional magnetic resonance imaging activity across the adult lifespan.

We examined performance and functional magnetic resonance imaging activity in participants (n = 235) aged 17-81 years on a nonverbal recognition memory task, figural memory. Reaction time, error rate, and response bias measures indicated that the youngest and oldest participants were faster, made fewer errors, and showed a more conservative response bias than participants in the median age ranges. Encoding and Recognition phases activated a distributed bilateral network encompassing prefrontal, subcortical, lateral, and medial temporal and occipital regions. Activation during Encoding phase did not correlate with age. During Recognition, task-related activation for correctly identified targets (Hit-Targets) correlated linearly positively with age; nontask related activity correlated negative quadratically with age. During correctly identified distractors (Hit-Distractors) activity in task-related regions correlated positive linearly with age, nontask activity showed positive and negative quadratic relationships with age. Missed-Targets activity did not correlate with age. We concluded that figural memory performance and functional magnetic resonance imaging activity during Recognition but not Encoding was affected both by continued maturation of the brain in the early 20s and compensatory recruitment of additional brain regions during recognition memory in old age.

Estudio a gran escala (n = 400) de las diferencias de la sustancia gris en la esquizofrenia mediante morfometría optimizada basada en vóxels

Fundamento En muchos estudios se ha utilizado morfometria basada en voxels (MBV) de imagenes de resonancia magnetica (RM) como un metodo automatizado para estudiar las diferencias en la sustancia gris cortical en la esquizofrenia. No obstante, los resultados de estos estudios varian ampliamente, lo que probablemente se deba a las diferencias metodologicas o del analisis estadistico. Objetivo Usar la MBV para estudiar las diferencias en la sustancia gris en la esquizofrenia en una muestra significativamente mas amplia que cualquiera de las publicadas hasta la fecha y aumentar la potencia estadistica lo suficiente para revelar las diferencias omitidas en los analisis a menor escala. Metodos A partir de cuatro lugares geograficos, se adquirieron imagenes de resonancia magnetica del cerebro en conjunto usando el mismo modelo de equipo de 1,5 T y la misma version del programa informatico, y se combinaron para formar una muestra de 200 pacientes tanto con un primer episodio como con esquizofrenia cronica y 200 individuos de control sanos apareados por edad, sexo y localizacion del escaner. Se evaluo la concentracion de sustancia gris y se la comparo utilizando MBV optimizada. Resultados Comparados con los individuos de control, en pacientes con esquizofrenia se detecto una concentracion significativamente menor de sustancia gris en multiples regiones corticales y subcorticales, algunas no descritas previamente. En conjunto, encontramos concentraciones menores de sustancia gris en regiones identificadas en estudios previos, que en su mayoria solo documentaron subgrupos de las areas afectadas. Conclusiones En la esquizofrenia las diferencias en la sustancia gris se dilucidan mas exhaustivamente usando una muestra a gran escala, diversa y representativa.