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The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method. •First paper to evaluate the state-of-the-art in cerebellum parcellation.•Presenting results on both Adult and Pediatric Cohorts.•Adult Cohort contains healthy controls, and patients with either symptoms of cerebellar dysfunction or SCA 6.•Pediatric Cohort contains healthy controls, and patients with ADHD or Autism.

Background Studies to date examining cortical thickness and surface area in young individuals At Risk Mental State (ARMS) of developing psychosis have revealed inconsistent findings, either reporting increased, decreased or no differences compared to mentally healthy individuals. The inconsistencies may be attributed to small sample sizes, varying age ranges, different ARMS identification criteria, lack of control for recreational substance use and antipsychotic pharmacotherapy, as well as different methods for deriving morphological brain measures. Methods A surfaced-based approach was employed to calculate fronto-temporal cortical grey matter thickness and surface area derived from magnetic resonance imaging (MRI) data collected from 44 young antipsychotic-naïve ARMS individuals, 19 young people with recent onset schizophrenia, and 36 age-matched healthy volunteers. We conducted group comparisons of the morphological measures and explored their association with symptom severity, global and socio-occupational function levels, and the degree of alcohol and cannabis use in the ARMS group. Results Grey matter thickness and surface areas in ARMS individuals did not significantly differ from their age-matched healthy counterparts. However, reduced left-frontal grey matter thickness was correlated with greater symptom severity and lower function levels; the latter being also correlated with smaller left-frontal surface areas. ARMS individuals with more severe symptoms showed greater similarities to the recent onset schizophrenia group. The morphological measures in ARMS did not correlate with the lifetime level of alcohol or cannabis use. Conclusions Our findings suggest that a decline in function levels and worsening mental state are associated with morphological changes in the left frontal cortex in ARMS but to a lesser extent than those seen in recent onset schizophrenia. Alcohol and cannabis use did not confound these findings. However, the cross-sectional nature of our study limits our ability to draw conclusions about the potential progressive nature of these morphological changes in ARMS.

Mismatch negativity (MMN) is a component of the event-related potential elicited by deviant auditory stimuli. It is presumed to index pre-attentive monitoring of changes in the auditory environment. MMN amplitude is smaller in groups of individuals with schizophrenia compared to healthy controls. We compared duration-deviant MMN in 16 recent-onset and 19 chronic schizophrenia patients versus age- and sex-matched controls. Reduced frontal MMN was found in both patient groups, involved reduced hemispheric asymmetry, and was correlated with Global Assessment of Functioning (GAF) and negative symptom ratings. A cortically-constrained LORETA analysis, incorporating anatomical data from each individual's MRI, was performed to generate a current source density model of the MMN response over time. This model suggested MMN generation within a temporal, parietal and frontal network, which was right hemisphere dominant only in controls. An exploratory analysis revealed reduced CSD in patients in superior and middle temporal cortex, inferior and superior parietal cortex, precuneus, anterior cingulate, and superior and middle frontal cortex. A region of interest (ROI) analysis was performed. For the early phase of the MMN, patients had reduced bilateral temporal and parietal response and no lateralisation in frontal ROIs. For late MMN, patients had reduced bilateral parietal response and no lateralisation in temporal ROIs. In patients, correlations revealed a link between GAF and the MMN response in parietal cortex. In controls, the frontal response onset was 17 ms later than the temporal and parietal response. In patients, onset latency of the MMN response was delayed in secondary, but not primary, auditory cortex. However amplitude reductions were observed in both primary and secondary auditory cortex. These latency delays may indicate relatively intact information processing upstream of the primary auditory cortex, but impaired primary auditory cortex or cortico-cortical or thalamo-cortical communication with higher auditory cortices as a core deficit in schizophrenia.

Prior studies reported that the hippocampal volume is smaller in Alzheimer's disease patients carrying the Apolipoprotein E ε4 allele (APOE4) versus patients who are non-carriers of this allele. This effect however has not been detected consistently, possibly because of the regionally-specific involvement of the hippocampal formation in Alzheimer's disease. The aim of this study was to analyze the local effect of APOE4 on hippocampal atrophy in Alzheimer's disease patients. Using high-resolution T1-weighted images we investigated 14 patients heterozygous for the ε4 allele (age 72±8SD years; MMSE 20±4SD) and 14 patients not carrying the ε4 allele (age 71±10; MMSE 20±5SD), and 28 age-, sex-, and education-matched controls (age 71±8; MMSE 29±1SD). The hippocampal formation was outlined with manual tracing and 3D parametric surface models were created for each subject. Radial atrophy was assessed on the whole hippocampal surface using the UCLA mapping technique. E4 carriers and non-carriers did not differ in their level of impairment in global cognition (p=0.91, Mann–Whitney test) or memory (p>0.29). Hippocampal surface analysis showed the typical pattern of CA1 and subicular tissue atrophy in both ε4-carriers and non-carriers compared with controls (e4 carriers: p<0.0002; ε4 non-carriers: p<0.01, permutation test). The left hippocampal volume was significantly smaller in ε4-carriers than non-carriers (p=0.044, Mann–Whitney test), the effect of APOE4 mapping to the subicular/CA1 region (p=0.041, permutation test). Differences were not statistically significant in the right hippocampus (p>0.20, permutation test). These findings show that hippocampal atrophy is greater in APOE4 carriers in regions typically affected by pathology. APOE4 may affect the structural expression of Alzheimer's disease. ► The ε4 allele of APOE gene (APOE4) is the major risk factor for AD. ► It is currently unclear whether this allele affects atrophy in AD. ► In this study we investigated APOE4 effect on the hippocampal surface in AD. ► APOE4 was associated with greater hippocampal atrophy in disease-specific subfields.

Progressive brain atrophy is believed to be the Alzheimer’s disease (AD) marker with the greatest evidence for validity. Mapping the topography of cortical atrophy throughout the stages of severity may allow the neural networks affected to be identified. Twenty healthy elderly persons (OH, MMSE 29.1 ± 1.0), 11 patients with incipient AD (iAD, 26.5 ± 2.0), 15 with mild AD (miAD, 23.5 ± 2.2), and 15 with moderate AD (moAD, 16.5 ± 2.0) underwent 3D magnetic resonance. Cortical pattern matching analysis was performed and maps of percent differences in gray matter distribution were computed between the following groups: iAD versus OH, miAD versus iAD, and moAD versus miAD. Compared to OH, iAD patients exhibited a mean cortical gray matter loss of 9–20% in areas encompassing the polysynaptic hippocampal pathway (posterior cingulate/retrosplenial and medial temporal cortex) and subgenual/orbitofrontal cortices, and a less widespread loss of 5–11% in other neocortical areas. Compared to iAD, miAD featured widespread mean gray matter loss of 14–19% in areas encompassing the direct hippocampal pathway (temporal pole, temporoparietal association cortex, and dorsal prefrontal cortex), sensorimotor, and visual cortex, with a less marked loss (7–9%) in the polysynaptic pathway areas. Compared to miAD, only atrophy in the primary sensorimotor cortex was still relatively marked in moAD, with a mean gray matter loss of 10–11%; the loss in other regions was generally below 10%. These findings suggest that the polysynaptic hippocampal pathway is affected in iAD, the direct pathway and sensorimotor and visual networks are affected in moAD, and the sensorimotor network is affected in moAD.

Cerebellar dysfunction has been proposed to lead to “cognitive dysmetria” in schizophrenia via the cortico-cerebellar-thalamic-cortical circuit, contributing to a range of cognitive and clinical symptoms of the disorder. Here we investigated total cerebellar grey and white matter volumes and cerebellar regional grey matter abnormalities in 13 remitted first-episode schizophrenia patients with less than 2 years’ duration of illness. Patient data were compared to 13 pair-wise age, gender, and handedness-matched healthy volunteers using cortical pattern averaging on high-resolution magnetic resonance images. Total cerebellar volume and total grey matter volumes in first-episode schizophrenia patients did not differ from healthy control subjects, but total cerebellar white matter was increased and total grey to white matter ratios were reduced in patients. Four clusters of cerebellar grey matter reduction were identified: (i) in superior vermis; (ii) in the left lobuli VI; (iii) in right-inferior lobule IX, extending into left lobule IX; and (iv) bilaterally in the areas of lobuli III, peduncle and left flocculus. Grey matter deficits were particularly prominent in right lobuli III and IX, left flocculus and bilateral pedunculi. These cerebellar areas have been implicated in attention control, emotional regulation, social functioning, initiation of smooth pursuit eye movements, eye-blink conditioning, language processing, verbal memory, executive function and the processing of spatial and emotional information. Consistent with common clinical, cognitive, and pathophysiological signs of established illness, our findings demonstrate cerebellar pathology as early as in first-episode schizophrenia.

Epidemiological data link adolescent cannabis use to psychosis and schizophrenia, but its contribution to schizophrenia neuropathology remains controversial. First-episode schizophrenia (FES) patients show regional cerebral grey- and white-matter changes as well as a distinct pattern of regional grey-matter loss in the vermis of the cerebellum. The cerebellum possesses a high density of cannabinoid type 1 receptors involved in the neuronal diversification of the developing brain. Cannabis abuse may interfere with this process during adolescent brain maturation leading to ‘schizophrenia-like’ cerebellar pathology. Magnetic resonance imaging and cortical pattern matching techniques were used to investigate cerebellar grey and white matter in FES patients with and without a history of cannabis use and non-psychiatric cannabis users. In the latter group we found lifetime dose-dependent regional reduction of grey matter in the right cerebellar lobules and a tendency for more profound grey-matter reduction in lobule III with younger age at onset of cannabis use. The overall regional grey-matter differences in cannabis users were within the normal variability of grey-matter distribution. By contrast, FES subjects had lower total cerebellar grey-matter:total cerebellar volume ratio and marked grey-matter loss in the vermis, pedunculi, flocculi and lobules compared to pair-wise matched healthy control subjects. This pattern and degree of grey-matter loss did not differ from age-matched FES subjects with comorbid cannabis use. Our findings indicate small dose-dependent effects of juvenile cannabis use on cerebellar neuropathology but no evidence of an additional effect of cannabis use on FES cerebellar grey-matter pathology.

Due to its three-dimensional folding pattern, the human neocortex poses a challenge for accurate co-registration of grouped functional brain imaging data. The present study addressed this problem by employing three-dimensional continuum-mechanical image-warping techniques to derive average anatomical representations for co-registration of functional magnetic resonance brain imaging data obtained from 10 male first-episode schizophrenia patients and 10 age-matched male healthy volunteers while they performed a version of the Tower of London task. This novel technique produced an equivalent representation of blood oxygenation level dependent (BOLD) response across hemispheres, cortical regions, and groups, respectively, when compared to intensity average co-registration, using a deformable Brodmann area atlas as anatomical reference. Somewhat closer association of Brodmann area boundaries with primary visual and auditory areas was evident using the gyral pattern average model. Statistically-thresholded BOLD cluster data confirmed predominantly bilateral prefrontal and parietal, right frontal and dorsolateral prefrontal, and left occipital activation in healthy subjects, while patients' hemispheric dominance pattern was diminished or reversed, particularly decreasing cortical BOLD response with increasing task difficulty in the right superior temporal gyrus. Reduced regional gray matter thickness correlated with reduced left-hemispheric prefrontal/frontal and bilateral parietal BOLD activation in patients. This is the first study demonstrating that reduction of regional gray matter in first-episode schizophrenia patients is associated with impaired brain function when performing the Tower of London task, and supports previous findings of impaired executive attention and working memory in schizophrenia.

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I 2  = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d  = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project ( n  = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia’s alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.