Sexual dimorphism of the cerebellar vermis in schizophrenia

CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation

Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegenerative and acquired diseases. Especially for the most common spinocerebellar ataxias (SCA), for which the first antisense oligonculeotide-base gene silencing trial has recently started, there is an urgent need for quantitative, sensitive imaging markers at pre-symptomatic stages for stratification and treatment assessment. This work introduces CerebNet, a fully automated, extensively validated, deep learning method for the lobular segmentation of the cerebellum, including the separation of gray and white matter. For training, validation, and testing, T1-weighted images from 30 participants were manually annotated into cerebellar lobules and vermal sub-segments, as well as cerebellar white matter. CerebNet combines FastSurferCNN, a UNet-based 2.5D segmentation network, with extensive data augmentation, e.g. realistic non-linear deformations to increase the anatomical variety, eliminating additional preprocessing steps, such as spatial normalization or bias field correction. CerebNet demonstrates a high accuracy (on average 0.87 Dice and 1.742mm Robust Hausdorff Distance across all structures) outperforming state-of-the-art approaches. Furthermore, it shows high test-retest reliability (average ICC >0.97 on OASIS and Kirby) as well as high sensitivity to disease effects, including the pre-ataxic stage of spinocerebellar ataxia type 3 (SCA3). CerebNet is compatible with FreeSurfer and FastSurfer and can analyze a 3D volume within seconds on a consumer GPU in an end-to-end fashion, thus providing an efficient and validated solution for assessing cerebellum sub-structure volumes. We make CerebNet available as source-code (https://github.com/Deep-MI/FastSurfer).

Sex Differences in Cognition in Schizophrenia: What We Know and What We Do Not Know

Cognitive impairment is a core feature of schizophrenia. This selective review examines whether schizophrenia patients show preserved sexual dimorphism in cognition. Existing studies using performance tasks largely show comparable sex effects between schizophrenia patients and healthy populations. This pattern appears to be similar across multiple cognitive domains and across phase of illness. Our selective review also identifies several unresolved questions about sex differences in cognition in schizophrenia. A better understanding of sex differences in cognition in schizophrenia may provide important clues to probing the relationship between cognitive impairment and pathophysiological processes of the disorder.

Sex Differences of Cerebellum and Cerebrum: Evidence from Graph Convolutional Network

This work aims to exploit a novel graph neural network to predict the sex of the brain topological network, and to find the sex differences in the cerebrum and cerebellum. A two-branch multi-scale graph convolutional network (TMGCN) is designed to analyze the sex differences of the brain. Two complementary templates are used to construct cerebrum and cerebellum networks, respectively, followed by a two-branch sub-network with multi-scale filters and a trainable weighted fusion strategy for the final prediction. Finally, a trainable graph topk-pooling layer is utilized in our model to visualize key brain regions relevant to the prediction. The proposed TMGCN achieves a prediction accuracy of 84.48%. In the cerebellum, the bilateral Crus I-II, lobule VI and VIIb, and the posterior vermis (VI-X) are discriminative for this task. As for the cerebrum, the discriminative brain regions consist of the bilateral inferior temporal gyrus, the bilateral fusiform gyrus, the bilateral parahippocampal gyrus, the bilateral cingulate gyrus, the bilateral medial ventral occipital cortex, the bilateral lateral occipital cortex, the bilateral amygdala, and the bilateral hippocampus. This study tackles the sex prediction problem from a more comprehensive view, and may provide the resting-state fMRI evidence for further study of sex differences in the cerebellum and cerebrum.

Altered Coupling of Cerebral Blood Flow and Functional Connectivity Strength in First-Episode Schizophrenia Patients With Auditory Verbal Hallucinations

Objective

Auditory verbal hallucinations (AVHs) are a major symptom of schizophrenia and are connected with impairments in auditory and speech-related networks. In schizophrenia with AVHs, alterations in resting-state cerebral blood flow (CBF) and functional connectivity have been described. However, the neurovascular coupling alterations specific to first-episode drug-naïve schizophrenia (FES) patients with AVHs remain unknown.

Methods

Resting-state functional MRI and arterial spin labeling (ASL) was performed on 46 first-episode drug-naïve schizophrenia (FES) patients with AVHs (AVH), 39 FES drug-naïve schizophrenia patients without AVHs (NAVH), and 48 healthy controls (HC). Then we compared the correlation between the CBF and functional connection strength (FCS) of the entire gray matter between the three groups, as well as the CBF/FCS ratio of each voxel. Correlation analyses were performed on significant results between schizophrenia patients and clinical measures scale.

Results

The CBF/FCS ratio was reduced in the cognitive and emotional brain regions in both the AVH and NAVH groups, primarily in the crus I/II, vermis VI/VII, and cerebellum VI. In the AVH group compared with the HC group, the CBF/FCS ratio was higher in auditory perception and language-processing areas, primarily the left superior and middle temporal gyrus (STG/MTG). The CBF/FCS ratio in the left STG and left MTG positively correlates with the score of the Auditory Hallucination Rating Scale in AVH patients.

Conclusion

These findings point to the difference in neurovascular coupling failure between AVH and NAVH patients. The dysfunction of the forward model based on the predictive and computing role of the cerebellum may increase the excitability in the auditory cortex, which may help to understand the neuropathological mechanism of AVHs.

Sex is a defining feature of neuroimaging phenotypes in major brain disorders

Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.

Sex-differential associations between cognitive impairments and white matter abnormalities in first episode and drug-naïve schizophrenia

AIM

Previous evidence has suggested that schizophrenia patients may display sex differences in cognitive impairments and cognitive impairments are related to disrupted white matter (WM) microstructure. The current research aims to address the intriguing possibility for the sex-specific association between cognitive deficits and WM abnormalities in first-episode and drug-naïve schizophrenia.

METHODS

Cognitive performance on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) was measured in 39 FEND patients (females:males = 23:16) and 30 healthy controls (females:males = 17:13), together with whole-brain WM fractional anisotropy (FA) values determined using voxel-based diffusion tensor imaging. Correlations between cognitive performance and FA values were assessed.

RESULTS

Patients performed significantly worse than healthy controls in the total score and most of the subscores of MCCB. Female patients displayed better cognitive performance than male patients on the Trail Making A Test, the Hopkins Verbal Learning Test and the Spatial Span Test in the Wechsler Memory Scale. More importantly, sex-differential association between cognitive performance and FA values was found in patients, but not in healthy controls. In particular, FA values in the cerebellum were negatively correlated with the continuous performance and digital sequence scores in male patients but positively correlated with the performance on the Spatial Span Test in the Wechsler Memory Scale in female patients.

CONCLUSIONS

These findings suggest sex-specific neurobiological substrates involved in cognitive deficits in early-onset schizophrenia and have important implications for differentially targeted interventions between males and females.

Entire duration of active psychosis and neurocognitive performance in first-episode non-affective psychosis

AIM

To explore if the entire duration of active psychosis (DAP) is related to neurocognitive performance at baseline and at 3-year follow-up in patients with first episode psychosis (FEP).

METHODS

DAP was estimated for 481 FEP patients. A neuropsychological battery was administered to measure neurocognitive specific domains, and a global indicator of neurocognitive impairment (global deficits score, GDS) was calculated. According to the DAP quartiles, four subgroups were formed, and these were compared. In addition, a logistic regression analysis was carried out to predict neurocognitive impairment at 3-year follow-up.

RESULTS

FEP patients with the longest DAP (more than 18.36 months) presented a more severe global neurocognitive impairment evidenced in their GDS, both at baseline (F = 5.53; p˂ .01) and at 3-year follow-up (F = 4.16; p˂ .01). Moreover, a subgroup of participants with DAP between 7.40 and 18.36 months showed a specific attentional decline over the 3-year follow-up (F = 3.089; p˂ .05).The logistic regression model showed that sex (Wald = 7.29, p < .010), premorbid adjustment (Wald = 7.24, p < .010), attention (Wald = 12.10, p < .001), verbal memory (Wald = 16.29, p < .001) and visual memory (Wald = 9.41, p < .010) were significant predictors of neurocognitive impairment 3 years after the FEP. The variables composing the DAP were not significant predictors in this model.

CONCLUSIONS

DAP seems to be related to global neurocognitive impairment in FEP patients. These findings contribute in several ways to our understanding of the effects of active psychosis on the brain, and provide the basis for future research.

Volumetric differences in gray and white matter of cerebellar Crus I/II across the different clinical stages of schizophrenia

AIM

Schizophrenia is considered to be a disorder of progressive structural brain abnormalities. Previous studies have indicated that the cerebellar Crus I/II plays a critical role in schizophrenia. We aimed to investigate how specific morphological features in the Crus I/II at different critical stages of the schizophrenia spectrum contribute to the disease.

METHODS

The study involved 73 participants on the schizophrenia spectrum (28 with ultra-high risk for psychosis [UHR], 17 with first-episode schizophrenia [FES], and 28 with chronic schizophrenia) and 79 healthy controls. We undertook a detailed investigation into differences in Crus I/II volume using a semiautomated segmentation method optimized for the cerebellum. We analyzed the effects of group and sex, as well as their interaction, on Crus I/II volume in gray matter (GM) and white matter (WM).

RESULTS

Significant group × sex interactions were found in WM volumes of the bilateral Crus I/II; the males with UHR demonstrated significantly larger WM volumes compared with the other male groups, whereas no significant group differences were found in the female groups. Additionally, WM and GM volumes of the Crus I/II had positive associations with symptom severity in the UHR group, whereas, in contrast, GM volumes in the FES group were negatively associated with symptom severity.

CONCLUSIONS

The present findings provide evidence that the morphology of Crus I/II is involved in schizophrenia in a sex- and disease stage-dependent manner. Additionally, alterations of WM volumes of Crus I/II may have potential as a biological marker of early detection and treatment for individuals with UHR.

SS-Detect: Development and Validation of a New Strategy for Source-Based Morphometry in Multiscanner Studies

BACKGROUND AND PURPOSE

Source-based morphometry(SBM) has been used in multicenter studies pooling magnetic resonance imaging data across different scanners to advance the reproducibility of neuroscience research. In the present study, we developed an analysis strategy for Scanner-Specific Detection (SS-Detect) of SBPs in multiscanner studies, and evaluated its performance relative to a conventional strategy.

METHODS

In the first experiment, the SimTB toolbox was used to generate simulated datasets mimicking 20 different scanners with common and scanner-specific SBPs. In the second experiment, we generated one simulated SBP from empirical gray matter volume (GMV) datasets from two different scanners. Moreover, we applied two strategies to compare SBPs between schizophrenia patients' and healthy controls' GMV from two scanners.

RESULTS

The outputs of the conventional strategy were limited to whole-sample-level results across all scanners; the outputs of SS-Detect included whole-sample-level and scanner-specific results. In the first simulation experiment, SS-Detect successfully estimated all simulated SBPs, including the common and scanner-specific SBPs, whereas the conventional strategy detected only some of the whole-sample SBPs. The second simulation experiment showed that both strategies could detect the simulated SBP. Quantitative evaluations of both experiments demonstrated greater accuracy of the SS-Detect in estimating spatial SBPs and subject-specific loading parameters. In the third experiment, SS-Detect detected more significant between-group SBPs, and these SBPs corresponded with the results from voxel-based morphometry analysis, suggesting that SS-Detect has higher sensitivity in detecting between-group differences.

CONCLUSIONS

SS-Detect outperformed the conventional strategy and can be considered advantageous when SBM is applied to a multiscanner study.

Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains

The dimorphism among male, female and freemartin intersex bovines, focusing on the vermal lobules VIII and IX, was analyzed using a novel data analytics approach to quantify morphometric differences in the cytoarchitecture of digitalized sections of the cerebellum. This methodology consists of multivariate and multi-aspect testing for cytoarchitecture-ranking, based on neuronal cell complexity among populations defined by factors, such as sex, age or pathology. In this context, we computed a set of shape descriptors of the neural cell morphology, categorized them into three domains named size, regularity and density, respectively. The output and results of our methodology are multivariate in nature, allowing an in-depth analysis of the cytoarchitectonic organization and morphology of cells. Interestingly, the Purkinje neurons and the underlying granule cells revealed the same morphological pattern: female possessed larger, denser and more irregular neurons than males. In the Freemartin, Purkinje neurons showed an intermediate setting between males and females, while the granule cells were the largest, most regular and dense. This methodology could be a powerful instrument to carry out morphometric analysis providing robust bases for objective tissue screening, especially in the field of neurodegenerative pathologies.

Deep learning identifies morphological determinants of sex differences in the pre-adolescent brain

The application of data-driven deep learning to identify sex differences in developing brain structures of pre-adolescents has heretofore not been accomplished. Here, the approach identifies sex differences by analyzing the minimally processed MRIs of the first 8144 participants (age 9 and 10 years) recruited by the Adolescent Brain Cognitive Development (ABCD) study. The identified pattern accounted for confounding factors (i.e., head size, age, puberty development, socioeconomic status) and comprised cerebellar (corpus medullare, lobules III, IV/V, and VI) and subcortical (pallidum, amygdala, hippocampus, parahippocampus, insula, putamen) structures. While these have been individually linked to expressing sex differences, a novel discovery was that their grouping accurately predicted the sex in individual pre-adolescents. Another novelty was relating differences specific to the cerebellum to pubertal development. Finally, we found that reducing the pattern to a single score not only accurately predicted sex but also correlated with cognitive behavior linked to working memory. The predictive power of this score and the constellation of identified brain structures provide evidence for sex differences in pre-adolescent neurodevelopment and may augment understanding of sex-specific vulnerability or resilience to psychiatric disorders and presage sex-linked learning disabilities.

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

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.

A Key Characteristic of Sex Differences in the Developing Brain: Greater Variability in Brain Structure of Boys than Girls

In many domains, including cognition and personality, greater variability is observed in males than in females in humans. However, little is known about how variability differences between sexes are represented in the brain. The present study tested whether there is a sex difference in variance in brain structure using a cohort of 643 males and 591 females aged between 3 and 21 years. The broad age-range of the sample allowed us to test if variance differences in the brain differ across age. We observed significantly greater male than female variance for several key brain structures, including cerebral white matter and cortex, hippocampus, pallidum, putamen, and cerebellar cortex volumes. The differences were observed at both upper and lower extremities of the distributions and appeared stable across development. These findings move beyond mean levels by showing that sex differences were pronounced for variability, thereby providing a novel perspective on sex differences in the developing brain.

Cerebellar volume and cerebellocerebral structural covariance in schizophrenia: a multisite mega-analysis of 983 patients and 1349 healthy controls

Although cerebellar involvement across a wide range of cognitive and neuropsychiatric phenotypes is increasingly being recognized, previous large-scale studies in schizophrenia (SZ) have primarily focused on supratentorial structures. Hence, the across-sample reproducibility, regional distribution, associations with cerebrocortical morphology and effect sizes of cerebellar relative to cerebral morphological differences in SZ are unknown. We addressed these questions in 983 patients with SZ spectrum disorders and 1349 healthy controls (HCs) from 14 international samples, using state-of-the-art image analysis pipelines optimized for both the cerebellum and the cerebrum. Results showed that total cerebellar grey matter volume was robustly reduced in SZ relative to HCs (Cohens's d=-0.35), with the strongest effects in cerebellar regions showing functional connectivity with frontoparietal cortices (d=-0.40). Effect sizes for cerebellar volumes were similar to the most consistently reported cerebral structural changes in SZ (e.g., hippocampus volume and frontotemporal cortical thickness), and were highly consistent across samples. Within groups, we further observed positive correlations between cerebellar volume and cerebral cortical thickness in frontotemporal regions (i.e., overlapping with areas that also showed reductions in SZ). This cerebellocerebral structural covariance was strongest in SZ, suggesting common underlying disease processes jointly affecting the cerebellum and the cerebrum. Finally, cerebellar volume reduction in SZ was highly consistent across the included age span (16-66 years) and present already in the youngest patients, a finding that is more consistent with neurodevelopmental than neurodegenerative etiology. Taken together, these novel findings establish the cerebellum as a key node in the distributed brain networks underlying SZ.

Gray matter morphological anomalies in the cerebellar vermis in first-episode schizophrenia patients with cognitive deficits

BACKGROUND

Cognitive deficits are a core feature of early schizophrenia. However, the pathological foundations underlying cognitive deficits are still unknown. The present study examined the association between gray matter density and cognitive deficits in first-episode schizophrenia.

METHOD

Structural magnetic resonance imaging of the brain was performed in 34 first-episode schizophrenia patients and 21 healthy controls. Patients were divided into two subgroups according to working memory task performance. The three groups were well matched for age, gender, and education, and the two patient groups were also further matched for diagnosis, duration of illness, and antipsychotic treatment. Voxel-based morphometric analysis was performed to estimate changes in gray matter density in first-episode schizophrenia patients with cognitive deficits. The relationships between gray matter density and clinical outcomes were explored.

RESULTS

Patients with cognitive deficits were found to have reduced gray matter density in the vermis and tonsil of cerebellum compared with patients without cognitive deficits and healthy controls, decreased gray matter density in left supplementary motor area, bilateral precentral gyrus compared with patients without cognitive deficits. Classifier results showed GMD in cerebellar vermis tonsil cluster could differentiate SZ-CD from controls, left supplementary motor area cluster could differentiate SZ-CD from SZ-NCD. Gray matter density values of the cerebellar vermis cluster in patients groups were positively correlated with cognitive severity.

CONCLUSIONS

Decreased gray matter density in the vermis and tonsil of cerebellum may underlie early psychosis and serve as a candidate biomarker for schizophrenia with cognitive deficits.

Voxel-Based Morphometry in Individuals at Genetic High Risk for Schizophrenia and Patients with Schizophrenia during Their First Episode of Psychosis

BACKGROUND

Understanding morphologic changes in vulnerable and early disease state of schizophrenia (SZ) may provide further insight into the development of psychosis.

METHOD

Whole brain voxel-based morphometry was performed to identify gray matter (GM) regional differences in 60 individuals with SZ during their first psychotic episode (FE-SZ), 31 individuals at genetic high risk for SZ (GHR-SZ) individuals, and 71 healthy controls.

RESULTS

Significant differences were found in several regions including the prefrontal cortex, parietal lobe, temporal lobe, hippocampus, occipital lobe, and cerebellum among the three groups (p<0.05, corrected). Compared to the HC group, the FE-SZ group had significantly decreased GM volumes in several regions including the cerebellum, hippocampus, fusiform gyrus, lingual gyrus, supramarginal gyrus, and superior, middle, and inferior temporal gyri and significantly increased GM volumes in the middle frontal gyrus and inferior operculum frontal gyrus (p<0.05). The GHR-SZ group had significant decreases in GM volumes in the supramaginal gyrus, precentral gyrus, and rolandic operculum and significant increases in GM volumes in the cerebellum, fusiform gyrus, middle frontal gyrus, inferior operculum frontal gyrus, and superior, middle, and inferior temporal gyri when compared to the HC group (p<0.05). Compared to the GHR-SZ group, the FE-SZ group had significant decreases in GM volumes in several regions including the cerebellum, fusiform gyrus, supramarginal gyrus, and superior, middle, and inferior temporal gyri (p<0.05).

CONCLUSIONS

The findings herein implicate the involvement of multisensory integration in SZ development and pathophysiology. Additionally, the patterns of observed differences suggest possible indicators of disease, vulnerability, and resiliency in SZ.