Mapping human brain charts cross-sectionally and longitudinally.

Brain scans acquired across large, age-diverse cohorts have facilitated recent progress in establishing normative brain aging charts. Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We show that age-related brain changes inferred from cross-sectionally mapped brain charts can substantially underestimate actual changes measured longitudinally. We further find that brain aging trajectories vary markedly between individuals and are difficult to predict with population-level age trends estimated cross-sectionally. Prediction errors relate modestly to neuroimaging confounds and lifestyle factors. Our findings provide explicit evidence for the importance of longitudinal measurements in ascertaining brain development and aging trajectories.

Characterization of the extracellular free water signal in schizophrenia using multi-site diffusion MRI harmonization.

Studies applying Free Water Imaging have consistently reported significant global increases in extracellular free water (FW) in populations of individuals with early psychosis. However, these published studies focused on homogenous clinical participant groups (e.g., only first episode or chronic), thereby limiting our understanding of the time course of free water elevations across illness stages. Moreover, the relationship between FW and duration of illness has yet to be directly tested. Leveraging our multi-site diffusion magnetic resonance imaging(dMRI) harmonization approach, we analyzed dMRI scans collected by 12 international sites from 441 healthy controls and 434 individuals diagnosed with schizophrenia-spectrum disorders at different illness stages and ages (15-58 years). We characterized the pattern of age-related FW changes by assessing whole brain white matter in individuals with schizophrenia and healthy controls. In individuals with schizophrenia, average whole brain FW was higher than in controls across all ages, with the greatest FW values observed from 15 to 23 years (effect size range = [0.70-0.87]). Following this peak, FW exhibited a monotonic decrease until reaching a minima at the age of 39 years. After 39 years, an attenuated monotonic increase in FW was observed, but with markedly smaller effect sizes when compared to younger patients (effect size range = [0.32-0.43]). Importantly, FW was found to be negatively associated with duration of illness in schizophrenia (p = 0.006), independent of the effects of other clinical and demographic data. In summary, our study finds in a large, age-diverse sample that participants with schizophrenia with a shorter duration of illness showed higher FW values compared to participants with more prolonged illness. Our findings provide further evidence that elevations in the FW are present in individuals with schizophrenia, with the greatest differences in the FW being observed in those at the early stages of the disorder, which might suggest acute extracellular processes.

Network analysis of neuropsychiatric, cognitive, and functional complications of stroke: implications for novel treatment targets.

AIM: Recovery from stroke is adversely affected by neuropsychiatric complications, cognitive impairment, and functional disability. Better knowledge of their mutual relationships is required to inform effective interventions. Network theory enables the conceptualization of symptoms and impairments as dynamic and mutually interacting systems. We aimed to identify interactions of poststroke complications using network analysis in diverse stroke samples. METHODS: Data from 2185 patients were sourced from member studies of STROKOG (Stroke and Cognition Consortium), an international collaboration of stroke studies. Networks were generated for each cohort, whereby nodes represented neuropsychiatric symptoms, cognitive deficits, and disabilities on activities of daily living. Edges characterized associations between them. Centrality measures were used to identify hub items. RESULTS: Across cohorts, a single network of interrelated poststroke complications emerged. Networks exhibited dissociable depression, apathy, fatigue, cognitive impairment, and functional disability modules. Worry was the most central symptom across cohorts, irrespective of the depression scale used. Items relating to activities of daily living were also highly central nodes. Follow-up analysis in two studies revealed that individuals who worried had more densely connected networks than those free of worry (CASPER [Cognition and Affect after Stroke: Prospective Evaluation of Risks] study: S = 9.72, P = 0.038; SSS [Sydney Stroke Study]: S = 13.56, P = 0.069). CONCLUSION: Neuropsychiatric symptoms are highly interconnected with cognitive deficits and functional disabilities resulting from stroke. Given their central position and high level of connectedness, worry and activities of daily living have the potential to drive multimorbidity and mutual reinforcement between domains of poststroke complications. Targeting these factors early after stroke may have benefits that extend to other complications, leading to better stroke outcomes.

Parameter estimation for connectome generative models: Accuracy, reliability, and a fast parameter fitting method.

Generative models of the human connectome enable in silico generation of brain networks based on probabilistic wiring rules. These wiring rules are governed by a small number of parameters that are typically fitted to individual connectomes and quantify the extent to which geometry and topology shape the generative process. A significant shortcoming of generative modeling in large cohort studies is that parameter estimation is computationally burdensome, and the accuracy and reliability of current estimation methods remain untested. Here, we propose a fast, reliable, and accurate parameter estimation method for connectome generative models that is scalable to large sample sizes. Our method achieves improved estimation accuracy and reliability and reduces computational cost by orders of magnitude, compared to established methods. We demonstrate an inherent tradeoff between accuracy, reliability, and computational expense in parameter estimation and provide recommendations for leveraging this tradeoff. To enable power analyses in future studies, we empirically approximate the minimum sample size required to detect between-group differences in generative model parameters. While we focus on the classic two-parameter generative model based on connection length and the topological matching index, our method can be generalized to other growth-based generative models. Our work provides a statistical and practical guide to parameter estimation for connectome generative models.

Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource.

We mapped functional and structural brain networks for more than 40,000 UK Biobank participants. Structural connectivity was estimated with tractography and diffusion MRI. Resting-state functional MRI was used to infer regional functional connectivity. We provide high-quality structural and functional connectomes for multiple parcellation granularities, several alternative measures of interregional connectivity, and a variety of common data pre-processing techniques, yielding more than one million connectomes in total and requiring more than 200,000 h of compute time. For a single subject, we provide 28 out-of-the-box versions of structural and functional brain networks, allowing users to select, e.g., the parcellation and connectivity measure that best suit their research goals. Furthermore, we provide code and intermediate data for the time-efficient reconstruction of more than 1000 different versions of a subject's connectome based on an array of methodological choices. All connectomes are available via the UK Biobank data-sharing platform and our connectome mapping pipelines are openly available. In this report, we describe our connectome resource in detail for users, outline key considerations in developing an efficient pipeline to map an unprecedented number of connectomes, and report on the quality control procedures that were completed to ensure connectome reliability and accuracy. We demonstrate that our structural and functional connectivity matrices meet a number of quality control checks and replicate previously established findings in network neuroscience. We envisage that our resource will enable new studies of the human connectome in health, disease, and aging at an unprecedented scale.

Cell type-specific manifestations of cortical thickness heterogeneity in schizophrenia.

Brain morphology differs markedly between individuals with schizophrenia, but the cellular and genetic basis of this heterogeneity is poorly understood. Here, we sought to determine whether cortical thickness (CTh) heterogeneity in schizophrenia relates to interregional variation in distinct neural cell types, as inferred from established gene expression data and person-specific genomic variation. This study comprised 1849 participants in total, including a discovery (140 cases and 1267 controls) and a validation cohort (335 cases and 185 controls). To characterize CTh heterogeneity, normative ranges were established for 34 cortical regions and the extent of deviation from these ranges was measured for each individual with schizophrenia. CTh deviations were explained by interregional gene expression levels of five out of seven neural cell types examined: (1) astrocytes; (2) endothelial cells; (3) oligodendrocyte progenitor cells (OPCs); (4) excitatory neurons; and (5) inhibitory neurons. Regional alignment between CTh alterations with cell type transcriptional maps distinguished broad patient subtypes, which were validated against genomic data drawn from the same individuals. In a predominantly neuronal/endothelial subtype (22% of patients), CTh deviations covaried with polygenic risk for schizophrenia (sczPRS) calculated specifically from genes marking neuronal and endothelial cells (r = -0.40, p = 0.010). Whereas, in a predominantly glia/OPC subtype (43% of patients), CTh deviations covaried with sczPRS calculated from glia and OPC-linked genes (r = -0.30, p = 0.028). This multi-scale analysis of genomic, transcriptomic, and brain phenotypic data may indicate that CTh heterogeneity in schizophrenia relates to inter-individual variation in cell-type specific functions. Decomposing heterogeneity in relation to cortical cell types enables prioritization of schizophrenia subsets for future disease modeling efforts.

Development of morning-eveningness in adolescence: implications for brain development and psychopathology.

BACKGROUND: Morning-evening preference is defined as an individual's preference for a morning- or evening-oriented rhythm. Across adolescence, a preference for eveningness becomes more predominant. Although eveningness is cross-sectionally associated with internalizing and externalizing psychopathology, few studies have examined developmental changes in eveningness and its potential biological substrates. Here, we investigated the longitudinal relationships among the trajectory of eveningness preference, internalizing and externalizing psychopathology and white matter development, across adolescence. METHODS: Two-hundred and nine adolescents (49% male) were assessed longitudinally at four separate time points between 12 and 19 years of age. Morning-evening preference and internalizing and externalizing symptoms were assessed at each time point. Diffusion-weighted images were acquired on a subset of participants at the final two time points to estimate changes in global mean fractional anisotropy (FA). Linear mixed models were performed to estimate the change in eveningness over time. A series of linear regression models assessed the influence of change in eveningness on psychopathology and white matter development at age 19. RESULTS: Across the sample, a preference for eveningness became more predominant by 19 years of age. Greater individual-level change towards eveningness significantly predicted greater severity in externalizing, but not internalizing, symptoms at 19 years of age. In contrast, change in psychopathology from 12 to 19 years of age was not associated with morning-eveningness at age 19. A change towards eveningness predicted an attenuated increase in FA between 17 and 19 years of age. CONCLUSIONS: This study suggests that developmental changes in morning-evening preference may predict both neurodevelopmental and psychological outcomes in adolescents.

Midline brain structures in adult Niemann-Pick type C disease: a cross-sectional study.

OBJECTIVE: A range of neuropathological changes occur in the brains of individuals with adult Niemann-Pick type C disease (NPC), a recessive disorder of cholesterol trafficking that results in accumulation of cholesterol and gangliosides in lysosomes, particularly in neurons. One of the most significant regions of grey matter loss occurs in the thalami, which abut the midline. What is not known is whether these are neurodevelopmental in origin well prior to symptomatic onset. We aimed to examine other markers of midline developmental anomalies in adults with NPC. METHOD: We examined the size of adhesio interthalamica (AI) and cavum septum pellucidum (CSP) (if present) in nine individuals diagnosed with NPC and nine healthy comparison subjects, matched for age and gender, using a 3T magnetic resonance volumetric sequence and measured the length of the AI and CSP in mm. RESULTS: We found that 5/9 NPC patients and 0/9 controls had a missing AI. AI length was significantly shorter in the patient group. No subject in other group had a large CSP, and CSP length did not differ. Duration of illness showed a trend to a negative correlation with AI length in patients. CONCLUSIONS: Our findings suggest that adult NPC patients show some markers of early neurodevelopmental disturbance, matching findings seen in psychotic disorders. The differences in AI, but not CSP, suggest neurodevelopmental change may occur early in gestation rather than post-partum. The relationship with duration of illness suggests that there may be atrophy over time in these structures, consistent with prior analyses of grey matter regions in NPC.

Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort.

The heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. For each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n = 195). Individuals with schizophrenia (n = 322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. Compared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region. Furthermore, 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59 ± 2%, p < 0.001). Thus, while infra-normal deviations were common among patients, their anatomical loci were highly inconsistent between individuals. Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r = -0.17, p = 0.006). We conclude that anatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.

White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis.

Subtle alterations in white matter microstructure are observed in youth at clinical high risk (CHR) for psychosis. However, the timing of these changes and their relationships to the emergence of psychosis remain unclear. Here, we track the evolution of white matter abnormalities in a large, longitudinal cohort of CHR individuals comprising the North American Prodrome Longitudinal Study (NAPLS-3). Multi-shell diffusion magnetic resonance imaging data were collected across multiple timepoints (1-5 over 1 year) in 286 subjects (aged 12-32 years): 25 CHR individuals who transitioned to psychosis (CHR-P; 61 scans), 205 CHR subjects with unknown transition outcome after the 1-year follow-up period (CHR-U; 596 scans), and 56 healthy controls (195 scans). Linear mixed effects models were fitted to infer the impact of age and illness-onset on variation in the fractional anisotropy of cellular tissue (FAT) and the volume fraction of extracellular free water (FW). Baseline measures of white matter microstructure did not differentiate between HC, CHR-U and CHR-P individuals. However, age trajectories differed between the three groups in line with a developmental effect: CHR-P and CHR-U groups displayed higher FAT in adolescence, and 4% lower FAT by 30 years of age compared to controls. Furthermore, older CHR-P subjects (20+ years) displayed 4% higher FW in the forceps major (p < 0.05). Prospective analysis in CHR-P did not reveal a significant impact of illness onset on regional FAT or FW, suggesting that transition to psychosis is not marked by dramatic change in white matter microstructure. Instead, clinical high risk for psychosis-regardless of transition outcome-is characterized by subtle age-related white matter changes that occur in tandem with development.

Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness.

Episodic memory ability relies on hippocampal-prefrontal connectivity. However, few studies have examined relationships between memory performance and white matter (WM) microstructure in hippocampal-prefrontal pathways in schizophrenia-spectrum disorder (SSDs). Here, we investigated these relationships in individuals with first-episode psychosis (FEP) and chronic schizophrenia-spectrum disorders (SSDs) using tractography analysis designed to interrogate the microstructure of WM tracts in the hippocampal-prefrontal pathway. Measures of WM microstructure (fractional anisotropy [FA], radial diffusivity [RD], and axial diffusivity [AD]) were obtained for 47 individuals with chronic SSDs, 28 FEP individuals, 52 older healthy controls, and 27 younger healthy controls. Tractography analysis was performed between the hippocampus and three targets involved in hippocampal-prefrontal connectivity (thalamus, amygdala, nucleus accumbens). Measures of WM microstructure were then examined in relation to episodic memory performance separately across each group. Both those with FEP and chronic SSDs demonstrated impaired episodic memory performance. However, abnormal WM microstructure was only observed in individuals with chronic SSDs. Abnormal WM microstructure in the hippocampal-thalamic pathway in the right hemisphere was associated with poorer memory performance in individuals with chronic SSDs. These findings suggest that disruptions in WM microstructure in the hippocampal-prefrontal pathway may contribute to memory impairments in individuals with chronic SSDs but not FEP.

Mortality in dementia is predicted by older age of onset and cognitive presentation.

OBJECTIVES: Survival information in dementia is important for future planning and service provision. There have been limited Australian data investigating survival duration and risk factors associated with mortality in younger-onset dementia. METHODS: This was a cross-sectional retrospective study investigating survival in inpatients with a diagnosis of dementia admitted to a tertiary neuropsychiatry service from 1991 to 2014. The Australian Institute of Health and Welfare National Death Index was used to obtain mortality information. RESULTS: A total of 468 inpatients were identified, of which 75% had symptom onset at ⩽65 years of age (defined as younger-onset dementia). Dementia was categorised into four subtypes, Alzheimer's dementia, frontotemporal dementia, vascular dementia and other dementias; 72% of the patients had died. Overall median survival duration was 10.6 years with no significant differences in duration within the dementia subtypes (p = 0.174). Survival in older-onset dementia (symptom onset at >65 years of age) was about half of that in younger-onset dementia (median survival 6.3 years compared to 12.7 years, respectively). Independent predictors of mortality were having older-onset dementia (hazard ratio: 3.2) and having initial presenting symptoms being cognitive in nature (hazard ratio: 1.5). Females with an older-onset dementia had longer survival compared to males with an older-onset dementia, and this was reversed for younger-onset dementia. Older-onset dementia and younger-onset dementia conferred 3 and 6 times, respectively, increased risk of death compared to the general population. CONCLUSION: This is the largest Australian study to date investigating survival and risk factors to mortality in dementia. We report important clinical information to patients with dementia and their families about prognosis which will assist with future planning. Our findings suggest that for both older-onset dementia and younger-onset dementia, 'new onset' psychiatric symptoms precede the cognitive symptoms of a neurodegenerative process. This, and sex differences in survival depending on the age of onset of the dementia warrant further investigation.

Exposure to Repetitive Head Impacts Is Associated With Corpus Callosum Microstructure and Plasma Total Tau in Former Professional American Football Players.

BACKGROUND: Exposure to repetitive head impacts (RHI) is associated with an increased risk of later-life neurobehavioral dysregulation and neurodegenerative disease. The underlying pathomechanisms are largely unknown. PURPOSE: To investigate whether RHI exposure is associated with later-life corpus callosum (CC) microstructure and whether CC microstructure is associated with plasma total tau and neuropsychological/neuropsychiatric functioning. STUDY TYPE: Retrospective cohort study. POPULATION: Seventy-five former professional American football players (age 55.2 ± 8.0 years) with cognitive, behavioral, and mood symptoms. FIELD STRENGTH/SEQUENCE: Diffusion-weighted echo-planar MRI at 3 T. ASSESSMENT: Subjects underwent diffusion MRI, venous puncture, neuropsychological testing, and completed self-report measures of neurobehavioral dysregulation. RHI exposure was assessed using the Cumulative Head Impact Index (CHII). Diffusion MRI measures of CC microstructure (i.e., free-water corrected fractional anisotropy (FA), trace, radial diffusivity (RD), and axial diffusivity (AD)) were extracted from seven segments of the CC (CC1-7), using a tractography clustering algorithm. Neuropsychological tests were selected: Trail Making Test Part A (TMT-A) and Part B (TMT-B), Controlled Oral Word Association Test (COWAT), Stroop Interference Test, and the Behavioral Regulation Index (BRI) from the Behavior Rating Inventory of Executive Function, Adult version (BRIEF-A). STATISTICAL TESTS: Diffusion MRI metrics were tested for associations with RHI exposure, plasma total tau, neuropsychological performance, and neurobehavioral dysregulation using generalized linear models for repeated measures. RESULTS: RHI exposure was associated with increased AD of CC1 (correlation coefficient (r) = 0.32, P < 0.05) and with increased plasma total tau (r = 0.34, P < 0.05). AD of the anterior CC1 was associated with increased plasma total tau (CC1: r = 0.30, P < 0.05; CC2: r = 0.29, P < 0.05). Higher trace, AD, and RD of CC1 were associated with better performance (P < 0.05) in TMT-A (trace, r = 0.33; AD, r = 0.31; and RD, r = 0.28) and TMT-B (trace, r = 0.31; RD, r = 0.34). Higher FA and AD of CC2 were associated with better performance (P < 0.05) in TMT-A (FA, r = 0.36; AD, r = 0.28), TMT-B (FA, r = 0.36; AD, r = 0.27), COWAT (FA, r = 0.36; AD, r = 0.32), and BRI (AD, r = 0.29). DATA CONCLUSION: These results suggest an association among RHI exposure, CC microstructure, plasma total tau, and clinical functioning in former professional American football players. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 1.

White matter abnormalities across the lifespan of schizophrenia: a harmonized multi-site diffusion MRI study.

Several prominent theories of schizophrenia suggest that structural white matter pathologies may follow a developmental, maturational, and/or degenerative process. However, a lack of lifespan studies has precluded verification of these theories. Here, we analyze the largest sample of carefully harmonized diffusion MRI data to comprehensively characterize age-related white matter trajectories, as measured by fractional anisotropy (FA), across the course of schizophrenia. Our analysis comprises diffusion scans of 600 schizophrenia patients and 492 healthy controls at different illness stages and ages (14-65 years), which were gathered from 13 sites. We determined the pattern of age-related FA changes by cross-sectionally assessing the timing of the structural neuropathology associated with schizophrenia. Quadratic curves were used to model between-group FA differences across whole-brain white matter and fiber tracts at each age; fiber tracts were then clustered according to both the effect-sizes and pattern of lifespan white matter FA differences. In whole-brain white matter, FA was significantly lower across the lifespan (up to 7%; p < 0.0033) and reached peak maturation younger in patients (27 years) compared to controls (33 years). Additionally, three distinct patterns of neuropathology emerged when investigating white matter fiber tracts in patients: (1) developmental abnormalities in limbic fibers, (2) accelerated aging and abnormal maturation in long-range association fibers, (3) severe developmental abnormalities and accelerated aging in callosal fibers. Our findings strongly suggest that white matter in schizophrenia is affected across entire stages of the disease. Perhaps most strikingly, we show that white matter changes in schizophrenia involve dynamic interactions between neuropathological processes in a tract-specific manner.

White matter microstructure and connectivity in patients with obsessive-compulsive disorder and their unaffected siblings.

OBJECTIVE: We aimed to examine white matter microstructure and connectivity in individuals with obsessive-compulsive disorder (OCD) and their unaffected siblings, relative to healthy controls. METHODS: Diffusion-weighted magnetic resonance imaging (dMRI) scans were acquired in 30 patients with OCD, 21 unaffected siblings, and 31 controls. We examined white matter microstructure using measures of fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD). Structural networks were examined using network-based statistic (NBS). RESULTS: Compared to controls, OCD patients showed significantly reduced FA and increased RD in clusters traversing the left forceps minor, inferior fronto-occipital fasciculus, anterior thalamic radiation, and cingulum. Furthermore, the OCD group displayed significantly weaker connectivity (quantified by the streamline count) compared to controls in the right hemisphere, most notably in edges connecting subcortical structures to temporo-occipital cortical regions. The sibling group showed intermediate streamline counts, FA and RD values between OCD and healthy control groups in connections found to be abnormal in patients with OCD. However, these reductions did not significantly differ compared to controls. CONCLUSION: Therefore, siblings of OCD patients display intermediate levels in dMRI measures of microstructure and connectivity, suggesting white matter abnormalities might be related to the familial predisposition for OCD.

Quantifying Genetic and Environmental Influence on Gray Matter Microstructure Using Diffusion MRI.

Early neuroimaging work in twin studies focused on studying genetic and environmental influence on gray matter macrostructure. However, it is also important to understand how gray matter microstructure is influenced by genes and environment to facilitate future investigations of their influence in mental disorders. Advanced diffusion MRI (dMRI) measures allow more accurate assessment of gray matter microstructure compared with conventional diffusion tensor measures. To understand genetic and environmental influence on gray matter, we used diffusion and structural MRI data from a large twin and sibling study (N = 840) and computed advanced dMRI measures including return to origin probability (RTOP), which is heavily weighted toward intracellular and intra-axonal restricted spaces, and mean squared displacement (MSD), more heavily weighted to diffusion in extracellular space and large cell bodies in gray matter. We show that while macrostructural features like brain volume are mainly genetically influenced, RTOP and MSD can together tap into both genetic and environmental influence on microstructure.

Differential involvement of hippocampal subfields in Niemann-Pick type C disease: a case-control study.

Hippocampal brain regions are strongly implicated in Niemann Pick type C disease (NPC), but little is known regarding distinct subregions of the hippocampal complex and whether these are equally or differentially affected. To address this gap, we compared volumes of five hippocampal subfields between NPC and healthy individuals using MRI. To this end, 9 adult-onset NPC cases and 9 age- and gender-matched controls underwent a 3 T T1-weighted MRI scan. Gray matter volumes of the cornu ammonis (CA1, CA2 and CA3), dentate gyrus (DG), subiculum, entorhinal cortex and hippocampal-amygdalar transition area were calculated by integrating MRI-based image intensities with microscopically defined cytoarchitectonic probabilities. Compared to healthy controls, NPC patients showed smaller volumes of the CA1-3 and DG regions bilaterally, with the greatest difference localized to the left DG (Cohen's d = 1.993, p = 0.008). No significant associations were shown between hippocampal subfield volumes and key clinical features of NPC, including disease duration, symptom severity and psychosis. The pattern of hippocampal subregional atrophy in NPC differs from those seen in other dementias, which may indicate unique cytoarchitectural vulnerabilities in this earlier-onset disorder. Future MRI studies of hippocampal subfields may clarify its potential as a biomarker of neurodegeneration in NPC.

Neuroimaging auditory verbal hallucinations in schizophrenia patient and healthy populations.

BACKGROUND: Auditory verbal hallucinations (AVH) are a cardinal feature of schizophrenia, but they can also appear in otherwise healthy individuals. Imaging studies implicate language networks in the generation of AVH; however, it remains unclear if alterations reflect biologic substrates of AVH, irrespective of diagnostic status, age, or illness-related factors. We applied multimodal imaging to identify AVH-specific pathology, evidenced by overlapping gray or white matter deficits between schizophrenia patients and healthy voice-hearers. METHODS: Diffusion-weighted and T1-weighted magnetic resonance images were acquired in 35 schizophrenia patients with AVH (SCZ-AVH), 32 healthy voice-hearers (H-AVH), and 40 age- and sex-matched controls without AVH. White matter fractional anisotropy (FA) and gray matter thickness (GMT) were computed for each region comprising ICBM-DTI and Desikan-Killiany atlases, respectively. Regions were tested for significant alterations affecting both SCZ-AVH and H-AVH groups, relative to controls. RESULTS: Compared with controls, the SCZ-AVH showed widespread FA and GMT reductions; but no significant differences emerged between H-AVH and control groups. While no overlapping pathology appeared in the overall study groups, younger (<40 years) H-AVH and SCZ-AVH subjects displayed overlapping FA deficits across four regions (p < 0.05): the genu and splenium of the corpus callosum, as well as the anterior limbs of the internal capsule. Analyzing these regions with free-water imaging ascribed overlapping FA abnormalities to tissue-specific anisotropy changes. CONCLUSIONS: We identified white matter pathology associated with the presence of AVH, independent of diagnostic status. However, commonalities were constrained to younger and more homogenous groups, after reducing pathologic variance associated with advancing age and chronicity effects.

Increased extracellular free-water in adult male rats following in utero exposure to maternal immune activation.

BACKGROUND: In previous work, we applied novel in vivo imaging methods to reveal that white matter pathology in patients with first-episode psychosis (FEP) is mainly characterized by excessive extracellular free-water, and to a lesser extent by cellular processes, such as demyelination. Here, we apply a back-translational approach to evaluate whether or not a rodent model of maternal immune activation (MIA) induces patterns of white matter pathology that we observed in patients with FEP. To this end, we examined free-water and tissue-specific white matter alterations in rats born to mothers exposed to the viral mimic polyriboinosinic-polyribocytidylic acid (Poly-I:C) in pregnancy, which is widely used to produce alterations relevant to schizophrenia and is characterized by a robust neuroinflammatory response. METHOD: Pregnant dams were injected on gestational day 15 with the viral mimic Poly-I:C (4 mg/kg) or saline. Diffusion-weighted magnetic resonance images were acquired from 17 male offspring (9 Poly-I:C and 8 saline) on postnatal day 90, after the emergence of brain structural and behavioral abnormalities. The free-water fraction (FW) and tissue-specific fractional anisotropy (FAT), as well as conventional fractional anisotropy (FA) were computed across voxels traversing a white matter skeleton. Voxel-wise and whole-brain averaged white matter were tested for significant microstructural alterations in immune-challenged, relative to saline-exposed offspring. RESULTS: Compared to saline-exposed offspring, those exposed to maternal Poly-I:C displayed increased extracellular FW averaged across voxels comprising a white matter skeleton (t(15) = 2.74; p = 0.01). Voxel-wise analysis ascribed these changes to white matter within the corpus callosum, external capsule and the striatum. In contrast, no significant between-group differences emerged for FAT or for conventional FA, measured across average and voxel-wise white matter. CONCLUSION: We identified excess FW across frontal white matter fibers of rats exposed to prenatal immune activation, analogous to our "bedside" observation in FEP patients. Findings from this initial experiment promote use of the MIA model to examine pathological pathways underlying FW alterations observed in patients with schizophrenia. Establishing these mechanisms has important implications for clinical studies, as free-water imaging reflects a feasible biomarker that has so far yielded consistent findings in the early stages of schizophrenia.

Structural connectivity and weight loss in children with obesity: a study of the "connectobese".

BACKGROUND: Previous studies suggest that obesity (OB) is associated with disrupted brain network organization; however, it remains unclear whether these differences already exist during childhood. Moreover, it should be investigated whether deviant network organization may be susceptible to treatment. METHODS: Here, we compared the structural connectomes of children with OB with age-matched healthy weight (HW) controls (aged 7-11 years). In addition, we examined the effect of a multidisciplinary treatment program, consisting of diet restriction, cognitive behavioral therapy, and physical activity for children with OB on brain network organization. After stringent quality assessment criteria, 40 (18 OB, 22 HW) data sets of the total sample of 51 participants (25 OB, 26 HW) were included in further analyses. For all participants, anthropometric measurements were administered twice, with a 5-month interval between pre- and post tests. Pre- and post T1- and diffusion-weighted imaging scans were also acquired and analyzed using a graph-theoretical approach and network-based statistics. RESULTS: Global network analyses revealed a significantly increased normalized clustering coefficient and small-worldness in children with OB compared with HW controls. In addition, regional analyses revealed increased betweenness centrality, reduced clustering coefficient, and increased structural network strength in children with OB, mainly in the motor cortex and reward network. Importantly, children with OB lost a considerable amount of their body mass after the treatment; however, no changes were observed in the organization of their brain networks. CONCLUSION: This is the first study showing disrupted structural connectomes of children with OB, especially in the motor and reward network. These results provide new insights into the pathophysiology underlying childhood obesity. The treatment did result in a significant weight loss, which was however not associated with alterations in the brain networks. These findings call for larger samples to examine the impact of short-term and long-term weight loss (treatment) on children's brain network organization.