White matter aberrations and age-related trajectories in patients with schizophrenia and bipolar disorder revealed by diffusion tensor imaging

Morphological abnormalities in youth with bipolar disorder and their relationship to clinical characteristics

OBJECTIVES

To characterize the neuroanatomy of BD in youth and its correlation to clinical characteristics.

METHODS

The current study includes a sample of 105 unmedicated youth with first-episode BD, aged between 10.1 and 17.9 years, and 61 healthy comparison adolescents, aged between 10.1 and 17.7 years, who were matched for age, race, sex, socioeconomic status, intelligence quotient (IQ), and education level. T1-weighted magnetic resonance imaging (MRI) images were obtained using a 4 T MRI scanner. Freesurfer (V6.0) was used to preprocess and parcellate the structural data, and 68 cortical and 12 subcortical regions were considered for statistical comparisons. The relationship between morphological deficits and clinical and demographic characteristics were evaluated using linear models.

RESULTS

Compared with healthy youth, youth with BD had decreased cortical thickness in frontal, parietal, and anterior cingulate regions. These youth also showed decreased gray matter volumes in 6 of the 12 subcortical regions examined including thalamus, putamen, amygdala and caudate. In further subgroup analyses, we found that youth with BD with comorbid attention-deficit hyperactivity disorder (ADHD) or with psychotic symptoms had more significant deficits in subcortical gray matter volume.

LIMITATIONS

We cannot provide information about the course of structural changes and impact of treatment and illness progression.

CONCLUSIONS

Our findings indicate that youth with BD have significant neurostructural deficits in both cortical and subcortical regions mainly located in the regions related to emotion processing and regulation. Variability in clinical characteristics and comorbidities may contribute to the severity of anatomic alterations in this disorder.

Using Fatty Acid-Binding Proteins as Potential Biomarkers to Discriminate between Parkinson's Disease and Dementia with Lewy Bodies: Exploration of a Novel Technique

An increase in the global aging population is leading to an increase in age-related conditions such as dementia and movement disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), and dementia with Lewy bodies (DLB). The accurate prediction of risk factors associated with these disorders is crucial for early diagnosis and prevention. Biomarkers play a significant role in diagnosing and monitoring diseases. In neurodegenerative disorders like α-synucleinopathies, specific biomarkers can indicate the presence and progression of disease. We previously demonstrated the pathogenic impact of fatty acid-binding proteins (FABPs) in α-synucleinopathies. Therefore, this study investigated FABPs as potential biomarkers for Lewy body diseases. Plasma FABP levels were measured in patients with AD, PD, DLB, and mild cognitive impairment (MCI) and healthy controls. Plasma FABP3 was increased in all groups, while the levels of FABP5 and FABP7 tended to decrease in the AD group. Additionally, FABP2 levels were elevated in PD. A correlation analysis showed that higher FABP3 levels were associated with decreased cognitive function. The plasma concentrations of Tau, GFAP, NF-L, and UCHL1 correlated with cognitive decline. A scoring method was applied to discriminate between diseases, demonstrating high accuracy in distinguishing MCI vs. CN, AD vs. DLB, PD vs. DLB, and AD vs. PD. The study suggests that FABPs could serve as potential biomarkers for Lewy body diseases and aid in early disease detection and differentiation.

Mapping the impact of nonlinear gradient fields with noise on diffusion MRI

In diffusion MRI, gradient nonlinearities cause spatial variations in the magnitude and direction of diffusion gradients. Studies have shown artifacts from these distortions can results in biased diffusion tensor information and tractography. Here, we investigate the impact of gradient nonlinearity correction in the presence of noise. We introduced empirically derived gradient nonlinear fields at different signal-to-noise ratio (SNR) levels in two experiments: tensor field simulation and simulation of the brain. For each experiment, this work compares two techniques empirically: voxel-wise gradient table correction and approximate correction by scaling the signal directly. The impact was assessed through diffusion metrics including mean diffusivity (MD), fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and principal eigen vector (V1). The study shows (1) the correction of gradient nonlinearities will not lead to substantively incorrect estimation of diffusion metrics in a linear system, (2) gradient nonlinearity correction does not interact adversely with noise, (3) nonlinearity correction suppresses the impact of nonlinearities in typical SNR data, (4) for SNR below 30, the performance of both the gradient nonlinearity correction techniques were similar, and (5) larger impacts are seen in regions where the gradient nonlinearities are distinct. Thus, this study suggests that there were greater beneficial effects than adverse effects due to the correction of nonlinearities. Additionally, correction of nonlinearities is recommended when region of interests are in areas with pronounced nonlinearities.

Exploring the Hypothesis of a Schizophrenia and Bipolar Disorder Continuum: Biological, Genetic and Pharmacologic Data

Present time nosology has its roots in Kraepelin's demarcation of schizophrenia and bipolar disorder. However, accumulating evidence has shed light on several commonalities between the two disorders, and some authors have advocated for the consideration of a disease continuum. Here, we review previous genetic, biological and pharmacological findings that provide the basis for this conceptualization. There is a cross-disease heritability, and they share single-nucleotide polymorphisms in some common genes. EEG and imaging patterns have a number of similarities, namely reduced white matter integrity and abnormal connectivity. Dopamine, serotonin, GABA and glutamate systems have dysfunctional features, some of which are identical among the disorders. Finally, cellular calcium regulation and mitochondrial function are, also, impaired in the two.

Deviations from normative brain white and gray matter structure are associated with psychopathology in youth

Combining imaging modalities and metrics that are sensitive to various aspects of brain structure and maturation may help identify individuals that show deviations in relation to same-aged peers, and thus benefit early-risk-assessment for mental disorders. We used one timepoint multimodal brain imaging, cognitive, and questionnaire data from 1280 eight- to twenty-one-year-olds from the Philadelphia Neurodevelopmental Cohort. We estimated age-related gray and white matter properties and estimated individual deviation scores using normative modeling. Next, we tested for associations between the estimated deviation scores, and with psychopathology domain scores and cognition. More negative deviations in DTI-based fractional anisotropy (FA) and the first principal eigenvalue of the diffusion tensor (L1) were associated with higher scores on psychosis positive and prodromal symptoms and general psychopathology. A more negative deviation in cortical thickness (CT) was associated with a higher general psychopathology score. Negative deviations in global FA, surface area, L1 and CT were also associated with poorer cognitive performance. No robust associations were found between the deviation scores based on CT and DTI. The low correlations between the different multimodal magnetic resonance imaging-based deviation scores suggest that psychopathological burden in adolescence can be mapped onto partly distinct neurobiological features.

Inefficient white matter activity in Schizophrenia evoked during intra and inter-hemispheric communication

Intensive cognitive tasks induce inefficient regional and network responses in schizophrenia (SCZ). fMRI-based studies have naturally focused on gray matter, but appropriately titrated visuo-motor integration tasks reliably activate inter- and intra-hemispheric white matter pathways. Such tasks can assess network inefficiency without demanding intensive cognitive effort. Here, we provide the first application of this framework to the study of white matter functional responses in SCZ. Event-related fMRI data were acquired from 28 patients (nine females, mean age 43.3, ±11.7) and 28 age- and gender-comparable controls (nine females, mean age 42.1 ± 10.1), using the Poffenberger paradigm, a rapid visual detection task used to induce intra- (ipsi-lateral visual and motor cortex) or inter-hemispheric (contra-lateral visual and motor cortex) transfer. fMRI data were pre- and post-processed to reliably isolate activations in white matter, using probabilistic tractography-based white matter tracts. For intra- and inter-hemispheric transfer conditions, SCZ evinced hyper-activations in longitudinal and transverse white matter tracts, with hyper-activation in sub-regions of the corpus callosum primarily observed during inter-hemispheric transfer. Evidence for the functional inefficiency of white matter was observed in conjunction with small (~50 ms) but significant increases in response times. Functional inefficiencies in SCZ are (1) observable in white matter, with the degree of inefficiency contextually related to task-conditions, and (2) are evoked by simple detection tasks without intense cognitive processing. These cumulative results while expanding our understanding of this dys-connection syndrome, also extend the search of biomarkers beyond the traditional realm of fMRI studies of gray matter.

Neuroimaging Studies of Brain Structure in Older Adults with Bipolar Disorder: A Review

Bipolar disorder (BD) is a common mood disorder that can have severe consequences during later life, including suffering and impairment due to mood and cognitive symptoms, elevated risk for dementia and an especially high risk for suicide. Greater understanding of the brain circuitry differences involved in older adults with BD (OABD) in later life and their relationship to aging processes is required to improve outcomes of OABD. The current literature on gray and white matter findings, from high resolution structural and diffusion-weighted magnetic resonance imaging (MRI) studies, has shown that BD in younger age groups is associated with gray matter reductions within cortical and subcortical brain regions that subserve emotion processing and regulation, as well as reduced structural integrity of white matter tracts connecting these brain regions. While fewer neuroimaging studies have focused on OABD, it does appear that many of the structural brain differences found in younger samples are present in OABD. There is also initial suggestion that there are additional brain differences, for at least a subset of OABD, that may result from more pronounced gray and white matter declines with age that may contribute to adverse outcomes. Preclinical and clinical data supporting neuro-plastic and -protective effects of mood-stabilizing medications, suggest that treatments may reverse and/or prevent the progression of brain changes thereby reducing symptoms. Future neuroimaging research implementing longitudinal designs, and large-scale, multi-site initiatives with detailed clinical and treatment data, holds promise for reducing suffering, cognitive dysfunction and suicide in OABD.

White matter characteristics in the early and late stages of bipolar disorder: A diffusion tensor imaging study

BACKGROUND

Bipolar disorder (BD) is characterized by recurrent mood episodes that may progress over time. Staging models may be used to follow the long-term course of BD. BD is associated with microstructural changes in white matter (WM). This study aims to compare the WM integrity within patients groups who are in different stages of BD and healthy controls and investigate whether WM integrity changes may be a biomarker that can be used in the clinical staging of BD.

METHODS

The study sample included euthymic 54 patients diagnosed with BD according to Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) and 27 healthy volunteers. Early-stage patients (n = 26) were determined as patients who have not had any mood episodes after the first manic episode, and late-stage patients (n = 28) determined as patients with recurrent mood episodes. MRI was performed using a 1.5 Tesla MR system and DTI sequences were acquired.

RESULTS

Region of interest (ROI) analyses showed that late-stage patients had significantly reduced fractional anisotropy (FA) in the right sagittal stratum and genu of the corpus callosum compared with healthy controls and early-stage patients. Regression models show that corpus callosum genu and right sagittal stratum FA values are predictive for the late-stage patient group.

LIMITATIONS

There are some limitations of the ROI method. The cross-sectional design is another limitation of this study.

CONCLUSIONS

WM integrity of corpus callosum genu and right sagittal stratum may be a biomarker for clinical staging of BD. Identifying stage-specific biomarkers may help us predict the neuroprogressive course of BD. Longitudinal studies would be required to detect stage-specific biomarkers.

White matter microstructure and the clinical risk for psychosis: A diffusion tensor imaging study of individuals with basic symptoms and at ultra-high risk

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This DTI cross-sectional study compared UHR, basic symptom & control groups (n = 112).

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The splenium of UHR individuals exhibited differences in fractional anisotropy (FA).

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Basic symptoms alone were not associated with white matter microstructure changes.

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Large differences in FA & radial diffusivity were found in converters to psychosis.

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Regional FA was inversely correlated with the general psychopathology domain.

Background

Widespread white matter abnormalities are a frequent finding in chronic schizophrenia patients. More inconsistent results have been provided by the sparser literature on at-risk states for psychosis, i.e., emerging subclinical symptoms. However, considering risk as a homogenous construct, an approach of earlier studies, may impede our understanding of neuro-progression into psychosis.

Methods

An analysis was conducted of 3-Tesla MRI diffusion and symptom data from 112 individuals (mean age, 21.97 ± 4.19) within two at-risk paradigm subtypes, only basic symptoms (n = 43) and ultra-high risk (n = 37), and controls (n = 32). Between-group comparisons (involving three study groups and further split based on the subsequent transition to schizophrenia) of four diffusion-tensor-imaging-derived scalars were performed using voxelwise tract-based spatial statistics, followed by correlational analyses with Structured Interview for Prodromal Syndromes responses.

Results

Relative to controls, fractional anisotropy was lower in the splenium of the corpus callosum of ultra-high-risk individuals, but only before stringent multiple-testing correction, and negatively correlated with General Symptom severity among at-risk individuals. At-risk participants who transitioned to schizophrenia within 3 years, compared to those that did not transition, had more severe WM differences in fractional anisotropy and radial diffusivity (particularly in the corpus callosum, anterior corona radiata, and motor/sensory tracts), which were even more extensive compared to healthy controls.

Conclusions

These findings align with the subclinical symptom presentation and more extensive disruptions in converters, suggestive of severity-related demyelination or axonal pathology. Fine-grained but detectable differences among ultra-high-risk subjects (i.e., with brief limited intermittent and/or attenuated psychotic symptoms) point to the splenium as a discrete site of emerging psychopathology, while basic symptoms alone were not associated with altered fractional anisotropy.

Evolution of the Human Brain Can Help Determine Pathophysiology of Neurodevelopmental Disorders

The evolution of humans brought about a co-occurring evolution of the human brain, which is far larger and more complex than that of many other organisms. The brain has evolved characteristically in humans in many respects, including macro-and micro-anatomical changes in the brain structure, changes in gene expression, and cell populations and ratios. These characteristics are essential for the execution of higher functions, such as sociality, language, and cognition, which express humanity, and are thought to have been acquired over evolutionary time. However, with the acquisition of higher functions also comes the risk of the disease in which they fail. This review focuses on human brain evolution and neurodevelopmental disorders (NDDs) and discusses brain development, molecular evolution, and human brain evolution. Discussing the potential for the development and pathophysiology of NDDs acquired by human brain evolution will provide insights into the acquisition and breakdown of higher functions from a new perspective.

Automated Multiclass Artifact Detection in Diffusion MRI Volumes via 3D Residual Squeeze-and-Excitation Convolutional Neural Networks

Diffusion MRI (dMRI) is widely used to investigate neuronal and structural development of brain. dMRI data is often contaminated with various types of artifacts. Hence, artifact type identification in dMRI volumes is an essential pre-processing step prior to carrying out any further analysis. Manual artifact identification amongst a large pool of dMRI data is a highly labor-intensive task. Previous attempts at automating this process are often limited to a binary classification ("poor" vs. "good" quality) of the dMRI volumes or focus on detecting a single type of artifact (e.g., motion, Eddy currents, etc.). In this work, we propose a deep learning-based automated multiclass artifact classifier for dMRI volumes. Our proposed framework operates in 2 steps. In the first step, the model predicts labels associated with 3D mutually exclusive collectively exhaustive (MECE) sub-volumes or "slabs" extracted from whole dMRI volumes. In the second step, through a voting process, the model outputs the artifact class present in the whole volume under investigation. We used two different datasets for training and evaluating our model. Specifically, we utilized 2,494 poor-quality dMRI volumes from the Adolescent Brain Cognitive Development (ABCD) and 4,226 from the Healthy Brain Network (HBN) dataset. Our results demonstrate accurate multiclass volume-level main artifact type prediction with 96.61 and 97.52% average accuracies on the ABCD and HBN test sets, respectively. Finally, in order to demonstrate the effectiveness of the proposed framework in dMRI pre-processing pipelines, we conducted a proof-of-concept dMRI analysis exploring the relationship between whole-brain fractional anisotropy (FA) and participant age, to test whether the use of our model improves the brain-age association.

Transdiagnostic role of glutamate and white matter damage in neuropsychiatric disorders: A Systematic Review

Neuropsychiatric disorders including generalized anxiety disorder (GAD), obsessive-compulsive disorder (OCD), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ) have been considered distinct categories of diseases despite their overlapping characteristics and symptomatology. We aimed to provide an in-depth review elucidating the role of glutamate/Glx and white matter (WM) abnormalities in these disorders from a transdiagnostic perspective. The PubMed online database was searched for studies published between 2010 and 2021. After careful screening, 401 studies were included. The findings point to decreased levels of glutamate in the Anterior Cingulate Cortex in both SZ and BD, whereas Glx is elevated in the Hippocampus in SZ and MDD. With regard to WM abnormalities, the Corpus Callosum and superior Longitudinal Fascicle were the most consistently identified brain regions showing decreased fractional anisotropy (FA) across all the reviewed disorders, except GAD. Additionally, the Uncinate Fasciculus displayed decreased FA in all disorders, except OCD. Decreased FA was also found in the inferior Longitudinal Fasciculus, inferior Fronto-Occipital Fasciculus, Thalamic Radiation, and Corona Radiata in SZ, BD, and MDD. Decreased FA in the Fornix and Corticospinal Tract were found in BD and SZ patients. The Cingulum and Anterior Limb of Internal Capsule exhibited decreased FA in MDD and SZ patients. The results suggest a gradual increase in severity from GAD to SZ defined by the number of brain regions with WM abnormality which may be partially caused by abnormal glutamate levels. WM damage could thus be considered a potential marker of some of the main neuropsychiatric disorders.

Single episode brief psychotic disorder versus bipolar disorder: A diffusion tensor imaging and executive functions study

BACKGROUND

Despite fast progress in neuroscientific approaches, the neurobiological continuum links psychotic spectrum, and affective disorder is obscure. White matter WM abnormalities found utilizing Diffusion Tensor Imaging (DTI) showing impaired communication in both disorders have been consistently demonstrated; however, direct comparisons of findings between them are scarce. This study aims to study WM abnormalities in single episode bipolar I disorder, and single episode brief psychotic disorder related to healthy control with the association of executive function.

METHODS

A cross-sectional case-control study was used to assess 60 subjects divided into 20 patients with single episode bipolar I disorder, 20 individuals with single episode brief psychotic disorder (both groups of patients were in remission), and 20 healthy controls. The present study examined the superior longitudinal fasciculus (SLF), and cingulum bundle fractional anisotropy (FA) determined from DTI images symmetrically and connected these results with cognitive functions as assessed by the trail making test (TMT) and Wisconsin card sorting test (WCST).

RESULTS

DTI data indicated that the psychotic group had a significant decrease in FA of the right SLF (p-value less than 0.001), left SLF (p-value less than 0.001), and left cingulum (p-value less than 0.001) than the bipolar I group. In terms of executive functioning, the psychotic group performed significantly worse than the bipolar I group on the TMT part B (p-value less than 0.001), the WCST (number of classifications fulfilled) (p-value less than 0.001), and perseverative errors (p-value less than 0.001).

CONCLUSION

Even after clinical remission, individuals with single episode brief psychotic disorder had more pronounced white matter impairments and executive function deficiencies than individuals with single episode bipolar I disorder.

Cardiometabolic risk factors associated with brain age and accelerate brain ageing

The structure and integrity of the ageing brain is interchangeably linked to physical health, and cardiometabolic risk factors (CMRs) are associated with dementia and other brain disorders. In this mixed cross-sectional and longitudinal study (interval mean = 19.7 months), including 790 healthy individuals (mean age = 46.7 years, 53% women), we investigated CMRs and health indicators including anthropometric measures, lifestyle factors, and blood biomarkers in relation to brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). We performed tissue specific brain age prediction using machine learning and performed Bayesian multilevel modeling to assess changes in each CMR over time, their respective association with brain age gap (BAG), and their interaction effects with time and age on the tissue-specific BAGs. The results showed credible associations between DTI-based BAG and blood levels of phosphate and mean cell volume (MCV), and between T1-based BAG and systolic blood pressure, smoking, pulse, and C-reactive protein (CRP), indicating older-appearing brains in people with higher cardiometabolic risk (smoking, higher blood pressure and pulse, low-grade inflammation). Longitudinal evidence supported interactions between both BAGs and waist-to-hip ratio (WHR), and between DTI-based BAG and systolic blood pressure and smoking, indicating accelerated ageing in people with higher cardiometabolic risk (smoking, higher blood pressure, and WHR). The results demonstrate that cardiometabolic risk factors are associated with brain ageing. While randomized controlled trials are needed to establish causality, our results indicate that public health initiatives and treatment strategies targeting modifiable cardiometabolic risk factors may also improve risk trajectories and delay brain ageing.

Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults

There is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. Although research has demonstrated deleterious effects of obesity on brain structure and function, the majority of studies have used conventional measures such as waist-to-hip ratio, waist circumference, and body mass index. While sensitive to gross features of body composition, such global anthropometric features fail to describe regional differences in body fat distribution and composition. The sample consisted of baseline brain magnetic resonance imaging (MRI) acquired from 790 healthy participants aged 18-94 years (mean ± standard deviation (SD) at baseline: 46.8 ± 16.3), and follow-up brain MRI collected from 272 of those individuals (two time-points with 19.7 months interval, on average (min = 9.8, max = 35.6). Of the 790 included participants, cross-sectional body MRI data was available from a subgroup of 286 participants, with age range 19-86 (mean = 57.6, SD = 15.6). Adopting a mixed cross-sectional and longitudinal design, we investigated cross-sectional body magnetic resonance imaging measures of adipose tissue distribution in relation to longitudinal brain structure using MRI-based morphometry (T1) and diffusion tensor imaging (DTI). We estimated tissue-specific brain age at two time points and performed Bayesian multilevel modelling to investigate the associations between adipose measures at follow-up and brain age gap (BAG) - the difference between actual age and the prediction of the brain's biological age - at baseline and follow-up. We also tested for interactions between BAG and both time and age on each adipose measure. The results showed credible associations between T1-based BAG and liver fat, muscle fat infiltration (MFI), and weight-to-muscle ratio (WMR), indicating older-appearing brains in people with higher measures of adipose tissue. Longitudinal evidence supported interaction effects between time and MFI and WMR on T1-based BAG, indicating accelerated ageing over the course of the study period in people with higher measures of adipose tissue. The results show that specific measures of fat distribution are associated with brain ageing and that different compartments of adipose tissue may be differentially linked with increased brain ageing, with potential to identify key processes involved in age-related transdiagnostic disease processes.

The uncinate fasciculus in individuals with and at risk for bipolar disorder: A meta-analysis

BACKGROUND

Bipolar disorder (BD) is a severe mental disorder, characterized by prominent mood swings and emotion regulation (ER) deficits. The uncinate fasciculus (UF), a white matter tract connecting the amygdala and the ventral prefrontal cortex, has been implicated in ER. Aberrancies in UF microstructure may be an endophenotype associated with increased risk for BD. However, studies in individuals with BD and their first-degree relatives (REL) have yielded inconsistent findings. This meta-analysis takes a region-of-interest approach to consolidate the available evidence and elucidate the role of the UF in the risk-architecture of BD.

METHODS

Using web-based search engines, we identified diffusion tensor imaging (DTI) studies focusing on the left and right UF and conducted meta-analyses comparing fractional anisotropy (FA) and radial diffusivity (RD) between BD or REL and healthy control participants (HC).

RESULTS

We included 32 studies (n_BD=1186, n_REL=289, n_HC=2315). Compared to HC, individuals with BD showed lower FA in the right (WMD=-0.31, p<0.0001) and left UF (WMD=-0.21, p = 0.010), and higher RD in the right UF (WMD=0.32, p = 0.009). We found no significant differences between REL and HC. In the right but not left UF, REL showed higher FA than BD (p = 0.043).

CONCLUSION

Our findings support aberrant UF microstructure, potentially related to alterations in myelination, as a mechanism, but not as an endophenotype of BD. However, given the limited power in the REL subsample, the latter finding must be considered preliminary. Studies examining the role of the UF in individuals at familial risk for BD are warranted.

Mapping the Impact of Non-Linear Gradient Fields on Diffusion MRI Tensor Estimation

Non-linear gradients impact diffusion weighted (DW) MRI by corrupting the experimental setup and lead to problems during image encoding including the effects in-plane distortion, in-plane shifts, intensity modulations and phase errors. Recent studies have been shown this may present significant complication in the interpretation of results and conclusion while studying tractography and tissue microstructure in data. To interpret the degree in consequences of gradient non-linearities between the desired and achieved gradients, we introduced empirically derived gradient nonlinear fields at different orientations and different tensor properties. The impact is assessed through diffusion tensor properties including mean diffusivity (MD), fractional anisotropy (FA) and principal eigen vector (PEV). The study shows lower FA are more susceptible to LR fields and LR fields with determinant <1 or >1 corrupt tensor more. The corruption can result in significantly different FA based on true-FA and LR field. Apparent MD decreases for negative determinant, on the other hand positive determinant shows the opposite effect. LR field have a larger impact on PEV when FA value is small. The results are dependent on the underlying orientation, non-linear field corruption can cause both increase and decrease of estimated FA, MD and PEV value. This work provides insight into characterizing the non-linear gradient error and aid in selecting correction techniques to address the inaccuracies in b-values.

White matter impairments in patients with schizophrenia: A multisite diffusion MRI study

There is a lack of convincing and replicative findings regarding white matter abnormalities in schizophrenia. Several multisite diffusion magnetic resonance imaging (dMRI) studies have been conducted to increase statistical power and reveal subtle white matter changes. Data pooling methods are crucial in joint analysis to compensate for the use of different scanners and image acquisition parameters. A harmonization method using raw dMRI data was developed to overcome the limited generalizability of previous data pooling methods. We obtained dMRI data of 242 healthy controls and 190 patients with schizophrenia from four different study sites. After applying the harmonization method to the raw dMRI data, a two-tensor whole-brain tractography was performed, and diffusion measures were compared between the two groups. The correlation of fractional anisotropy (FA) with the positive and negative symptoms was evaluated, and the interaction effect of diagnosis-by-age, age-squared, and sex was examined. The following white matter tracts showed significant group differences in the FA: the right superior longitudinal fascicle (SLF), the left-to-right lateral orbitofrontal commissural tract, pars orbitalis (pOr-pOr) commissural tract, and pars triangularis (pTr-pTr) commissural tract. The FA of the right SLF and pTr-pTr commissural tract were significantly associated with the Positive and Negative Syndrome Scale (PANSS) positive and negative scores. No significant interaction effect was observed. These findings add to the evidence on structural brain abnormalities in schizophrenia and can aid in obtaining a better understanding of the biological foundations of schizophrenia.

Automatic Volumetric Quality Assessment of Diffusion MR Images via Convolutional Neural Network Classifiers

Diffusion Tensor Imaging (DTI) is widely used to find brain biomarkers for various stages of brain structural and neuronal development. Processing DTI data requires a detailed Quality Assessment (QA) to detect artifactual volumes amongst a large pool of data. Since large cohorts of brain DTI data are often used in different studies, manual QA of such images is very labor-intensive. In this paper, a deep learning-based tool is developed for quick automatic QA of 3D raw diffusion MR images. We propose a 2-step framework to automate the process of binary (i.e., 'good' vs 'poor') quality classification of diffusion MR images. In the first step, using two separately trained 3D convolutional neural networks with different input sizes, quality labels for individual Regions of Interest (ROIs) sampled from whole DTI volumes are predicted. In the second step, two distinct novel voting systems are designed and fine-tuned to predict the quality label of whole brain DTI volumes using the individual ROI labels predicted in the previous step. Our results demonstrate the validity and practicality of our tool. Specifically, using a balanced dataset of 6,940 manually-labeled 3D DTI volumes from 85 unique subjects for training, validation, and testing, our model achieves 100% accuracy via one voting system, and 98% accuracy via another voting system on the same test set.

White matter tracts in Bipolar Disorder patients: A comparative study based on diffusion kurtosis and tensor imaging

BACKGROUND

Diffusion kurtosis imaging (DKI), an extension of diffusion tensor imaging (DTI), is a powerful tool for studying human brain.The purpose is to investigate differences between DKI and DTI by comparing parameters in same analysis methods with bipolar disorder (BD) patients.

METHODS

In this study, we attained in 47 BD patients and 49 age-, sex-, and education-matched healthy controls, complimented DTI and DKI scanning and got Fractional Anisotropy (FA), Mean Diffusion (MD) and Mean Kurtosis (MK). Voxel-wise statistical analysis was performed by the tract-based spatial statistics (TBSS) analysis and atlas-based regional data analysis.

RESULTS

TBSS analysis showed more widespread regions and higher fidelity in DKI parameters than DTI parameters with the same p-value threshold, and DKI parameters showed significant alterations after Family-Wise Error correction. The DKI-FA value in the corpus callosum, bilateral cingulum (cingulate gyrus), bilateral superior corona radiata, left anterior corona radiata and left posterior corona radiata of BD patients was negatively correlated with the duration of illness. In the atlas-based regional data analysis, the effect size of DTI-FA, DTI-MD, DKI-FA and DKI-MD were quantified using Cohen's d value. DKI-FA and DKI-MD demonstrated more between-group different regions and the higher (p < 0.001) absolute Cohen's d value than DTI-FA.

LIMITATIONS

This study did not consider the difference between sub-types of BD.

CONCLUSIONS

Compared to DTI parameters, DKI parameters were more sensitive and stable to probe the local microstructure, and particularly powerful to exploit cerebral alterations in BD patients.

Shared and distinct white matter abnormalities in schizophrenia and bipolar disorder

While white matter impairments play an integral part in the pathophysiology of schizophrenia and bipolar disorder, the literature on white matter abnormality differences between the two disorders is insufficient. The University of California Los Angeles Consortium for Neuropsychiatric Phenomic LA5c public dataset, including 47 patients with schizophrenia, 47 with bipolar disorder, and 115 healthy controls, was obtained via OpenNeuro. Whole-brain tractography was performed using Unscented Kalman filter-based two-tensor tractography and White Matter Query Language. Diffusion indices, including fractional anisotropy (FA), axial diffusivity, radial diffusivity (RD), and trace (TR), were used to compare subject groups. Spearman's partial correlation with a covariate of age was used for correlation with clinical variables. Both patient groups exhibited significantly higher RD in the left external capsule and TR in the right extreme capsule. Significantly lower FA in the left external capsule, right thalamo-occipital and thalamo-parietal tracts were found in the schizophrenia group in comparison with bipolar disorder and healthy control groups. Compared with healthy controls, patients with schizophrenia had significantly lower FA in the left-to-right lateral orbitofrontal commissural tract. There were possible associations of the FA and RD of the left external capsule with the anxiety-depression score of the Brief Psychiatric Rating Scale in patients with schizophrenia. The white matter alterations identified in schizophrenia and bipolar disorder may be a neurobiological basis contributing to characterization of the two disorders.

White matter microstructure in schizophrenia patients with a history of violence

Schizophrenia (SCZ) is associated with increased risk of violence compared to the general population. Neuroimaging research suggests SCZ to be a disorder of disrupted connectivity, with diffusion tensor imaging (DTI) indicating white matter (WM) abnormalities. It has been hypothesized that SCZ patients with a history of violence (SCZ-V) have brain abnormalities distinguishing them from SCZ patients with no history of violence (SCZ-NV). Yet, a thorough investigation of the neurobiological underpinnings of state and trait measures of violence and aggression in SCZ derived from DTI indices is lacking. Using tract-based spatial statistics, we compared DTI-derived microstructural indices: fractional anisotropy (FA), mean, axial (AD) and radial diffusivity across the brain; (1) between SCZ-V (history of murder, attempted murder, or severe assault towards other people, n = 24), SCZ-NV (n = 52) and healthy controls (HC, n = 94), and (2) associations with current aggression scores among both SCZ groups. Then, hypothesis-driven region of interest analyses of the uncinate fasciculus and clinical characteristics including medication use were performed. SCZ-V and SCZ-NV showed decreased FA and AD in widespread regions compared to HC. There were no significant differences on any DTI-based measures between SCZ-V and SCZ-NV, and no significant associations between state or trait measures of aggression and any of the DTI metrics in the ROI analyses. The DTI-derived WM differences between SCZ and HC are in line with previous findings, but the results do not support the hypothesis of specific brain WM microstructural correlates of violence or aggression in SCZ.

Fast qualitY conTrol meThod foR derIved diffUsion Metrics (YTTRIUM) in big data analysis: U.K. Biobank 18,608 example

Deriving reliable information about the structural and functional architecture of the brain in vivo is critical for the clinical and basic neurosciences. In the new era of large population‐based datasets, when multiple brain imaging modalities and contrasts are combined in order to reveal latent brain structural patterns and associations with genetic, demographic and clinical information, automated and stringent quality control (QC) procedures are important. Diffusion magnetic resonance imaging (dMRI) is a fertile imaging technique for probing and visualising brain tissue microstructure in vivo, and has been included in most standard imaging protocols in large‐scale studies. Due to its sensitivity to subject motion and technical artefacts, automated QC procedures prior to scalar diffusion metrics estimation are required in order to minimise the influence of noise and artefacts. However, the QC procedures performed on raw diffusion data cannot guarantee an absence of distorted maps among the derived diffusion metrics. Thus, robust and efficient QC methods for diffusion scalar metrics are needed. Here, we introduce Fast qualitY conTrol meThod foR derIved diffUsion Metrics (YTTRIUM), a computationally efficient QC method utilising structural similarity to evaluate diffusion map quality and mean diffusion metrics. As an example, we applied YTTRIUM in the context of tract‐based spatial statistics to assess associations between age and kurtosis imaging and white matter tract integrity maps in U.K. Biobank data (n = 18,608). To assess the influence of outliers on results obtained using machine learning (ML) approaches, we tested the effects of applying YTTRIUM on brain age prediction. We demonstrated that the proposed QC pipeline represents an efficient approach for identifying poor quality datasets and artefacts and increases the accuracy of ML based brain age prediction.

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 in Individuals With and At Risk for Bipolar Disorder: Evidence for an Endophenotype From a Voxel-Based Meta-analysis

BACKGROUND

Aberrant white matter (WM) microstructure has been proposed as a mechanism underlying bipolar disorder (BD). Given the strong genetic underpinnings of both WM microstructure and BD, such WM aberrations may be not only a disease marker, but also an endophenotype of BD. If so, they should be observable in individuals at risk for BD (AR) (i.e., first-degree relatives). This meta-analysis integrates evidence on perturbed WM microstructure in individuals with or at risk for BD.

METHODS

A comprehensive search of literature published through April 2020 identified diffusion tensor imaging studies that used a voxel-based approach to compare fractional anisotropy (FA) and radial diffusivity between individuals with BD and/or AR individuals and healthy volunteers. Effect size comparison and conjunction analysis allowed identification of endophenotypes and disease markers of BD. Effects of age, sex, mood state, and psychotropic medication were explored using meta-regressions.

RESULTS

We included 57 studies in individuals with BD (N = 4631) and 10 in AR individuals (N = 753). Both individuals with and at risk for BD were associated with lower FA in the body and splenium of the corpus callosum. In the BD group, decreased FA and increased radial diffusivity comprised the entire corpus callosum, anterior thalamic radiation, fronto-orbito-polar tracts, and superior longitudinal fasciculus, and were influenced by age, sex, and mood state. Studies with higher proportions of individuals taking lithium or antipsychotics reported smaller FA reductions in BD.

CONCLUSIONS

Findings suggest that abnormalities in the body and splenium of the corpus callosum may be an endophenotype for BD, and they associate BD with WM tracts relevant for working memory performance, attention, and reward processing.

Neuroanatomic and Functional Neuroimaging Findings

The search for brain morphology findings that could explain behavioral disorders has gone through a long path in the history of psychiatry. With the advance of brain imaging technology, studies have been able to identify brain morphology and neural circuits associated with the pathophysiology of mental illnesses, such as bipolar disorders (BD). Promising results have also shown the potential of neuroimaging findings in the identification of outcome predictors and response to treatment among patients with BD. In this chapter, we present brain imaging structural and functional findings associated with BD, as well as their hypothesized relationship with the pathophysiological aspects of that condition and their potential clinical applications.

White matter microstructure across the adult lifespan: A mixed longitudinal and cross-sectional study using advanced diffusion models and brain-age prediction

The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. In this mixed cross-sectional and longitudinal study (mean interval: 15.2 months) including 702 multi-shell dMRI datasets, we combined complementary dMRI models to investigate age trajectories in healthy individuals aged 18 to 94 years (57.12% women). Using linear mixed effect models and machine learning based brain age prediction, we assessed the age-dependence of diffusion metrics, and compared the age prediction accuracy of six different diffusion models, including diffusion tensor (DTI) and kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), restriction spectrum imaging (RSI), spherical mean technique multi-compartment (SMT-mc), and white matter tract integrity (WMTI). The results showed that the age slopes for conventional DTI metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilk's theorem analysis showed that the 'FA fine' metric of the RSI model and 'orientation dispersion' (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.

Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder: A Multisample Diffusion Tensor Imaging Study

BACKGROUND

Schizophrenia (SZ) and bipolar disorder (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, patients with BD, and healthy control (HC) subjects across 10 cohorts.

METHODS

We trained 6 cross-validated models using different combinations of DTI data from 927 HC subjects (18-94 years of age) and applied the models to the test sets including 648 patients with SZ (18-66 years of age), 185 patients with BD (18-64 years of age), and 990 HC subjects (17-68 years of age), estimating the brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results.

RESULTS

Tenfold cross-validation revealed high accuracy for all models. Compared with HC subjects, the model including all feature sets significantly overestimated the age of patients with SZ (Cohen's d = -0.29) and patients with BD (Cohen's d = 0.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy-based models showed larger group differences than the models based on other DTI-derived metrics.

CONCLUSIONS

Brain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.

Distribution and localization of phosphatidylinositol 5-phosphate, 4-kinase alpha and beta in the brain

Phosphatidylinositol-4,5-bisphosphate (PI-4,5-P₂ ) is critical for synaptic vesicle docking and fusion and generation of the second messengers, diacylglycerol and inositol-1,4,5-trisphosphate. PI-4,5-P₂ can be generated by two families of kinases: type 1 phosphatidylinositol-4-phosphate 5-kinases, encoded by PIP5K1A, PIP5K1B and PIP5K1C, and type 2 phosphatidylinositol-5-phosphate 4-kinases, encoded by PIP4K2A, PIP4K2B, and PIP4K2C. While the roles of the type 1 enzymes in brain function have been extensively studied, the roles of the type 2 enzymes are poorly understood. Using selective antibodies validated by genetic deletion of pip4k2a or pip4k2b in mouse brain, we characterized the location of the enzymes, PI5P4Kα and PI5P4Kβ, encoded by these genes. In mice, we demonstrate that PI5P4Kα is expressed in adulthood, whereas PI5P4Kβ is expressed early in development. PI5P4Kα localizes to white matter tracts, especially the corpus callosum, and at a low level in neurons, while PI5P4Kβ is expressed in neuronal populations, especially hippocampus and cortex. Dual labeling studies demonstrate that PI5P4Kα co-localizes with the oligodendrocyte marker, Olig2, whereas PI5P4Kβ co-localizes with the neuronal marker, NeuN. Ultrastructural analysis demonstrates that both kinases are contained in axon terminals and dendritic spines adjacent to the synaptic membrane, which support a potential role in synaptic transmission. Immunoperoxidase analysis of macaque and human brain tissue demonstrate a conserved pattern for PI5P4Kα and PI5P4Kβ. These results highlight the diverse cell-autonomous expression of PI5P4Kα and PI5P4Kβ and support further exploration into their role in synaptic function in the brain.

Phase-Amplitude Markers of Synchrony and Noise: A Resting-State and TMS-EEG Study of Schizophrenia

The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here, we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity, we used 3 weekly sessions and analyzed both resting-state and TMS-EEG data. For the TMS responses, our analysis verifies known results. For the resting state, we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha, and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha- and beta-resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally, and temporally correlated activity is reduced in schizophrenia, a conclusion, that is, in accord with previous experiments on TMS-EEG and on resting-state EEG.

White Matter Microstructure across the Psychosis Spectrum

Diffusion-weighted imaging (DWI) is a neuroimaging technique that has allowed us an unprecedented look at the role that white matter microstructure may play in mental illnesses, such as psychosis. Psychosis-related illnesses, including schizophrenia, are increasingly viewed as existing along a spectrum; spectrums may be defined based on factors such as stage of illness, symptom severity, or genetic liability. This review first focuses on an overview of some of the recent findings from DWI studies. Then, it examines the ways in which DWI analyses have been extended across the broader psychosis spectrum, or spectrums, and what we have learned from such approaches.

Reverse engineering human brain evolution using organoid models

Primate brains vary dramatically in size and organization, but the genetic and developmental basis for these differences has been difficult to study due to lack of experimental models. Pluripotent stem cells and brain organoids provide a potential opportunity for comparative and functional studies of evolutionary differences, particularly during the early stages of neurogenesis. However, many challenges remain, including isolating stem cell lines from additional great ape individuals and species to capture the breadth of ape genetic diversity, improving the reproducibility of organoid models to study evolved differences in cell composition and combining multiple brain regions to capture connectivity relationships. Here, we describe strategies for identifying evolved developmental differences between humans and non-human primates and for isolating the underlying cellular and genetic mechanisms using comparative analyses, chimeric organoid culture, and genome engineering. In particular, we focus on how organoid models could ultimately be applied beyond studies of progenitor cell evolution to decode the origin of recent changes in cellular organization, connectivity patterns, myelination, synaptic development, and physiology that have been implicated in human cognition.

Microstructural White Matter and Links With Subcortical Structures in Chronic Schizophrenia: A Free-Water Imaging Approach

Schizophrenia is a severe mental disorder with often a chronic course. Neuroimaging studies report brain abnormalities in both white and gray matter structures. However, the relationship between microstructural white matter differences and volumetric subcortical structures is not known. We investigated 30 long-term treated patients with schizophrenia and schizoaffective disorder (mean age 51.1 ± 7.9 years, mean illness duration 27.6 ± 8.0 years) and 42 healthy controls (mean age 54.1 ± 9.1 years) using 3 T diffusion and structural magnetic resonance imaging. The free-water imaging method was used to model the diffusion signal, and subcortical volumes were obtained from FreeSurfer. We applied multiple linear regression to investigate associations between (i) patient status and regional white matter microstructure, (ii) medication dose or clinical symptoms on white matter microstructure in patients, and (iii) for interactions between subcortical volumes and diagnosis on microstructural white matter regions showing significant patient-control differences. The patients had significantly decreased free-water corrected fractional anisotropy (FA_t), explained by decreased axial diffusivity and increased radial diffusivity (RD_t) bilaterally in the anterior corona radiata (ACR) and the left anterior limb of the internal capsule (ALIC) compared to controls. In the fornix, the patients had significantly increased RD_t. In patients, positive symptoms were associated with localized increased free-water and negative symptoms with localized decreased FA_t and increased RD_t. There were significant interactions between patient status and several subcortical structures on white matter microstructure and the free-water compartment for left ACR and fornix, and limited to the free-water compartment for right ACR and left ALIC. The Cohen's d effect sizes were medium to large (0.61 to 1.20, absolute values). The results suggest a specific pattern of frontal white matter axonal degeneration and demyelination and fornix demyelination that is attenuated in the presence of larger structures of the limbic system in patients with chronic schizophrenia and schizoaffective disorder. Findings warrant replication in larger samples.

Accelerated evolution of oligodendrocytes in the human brain

Recent discussions of human brain evolution have largely focused on increased neuron numbers and changes in their connectivity and expression. However, it is increasingly appreciated that oligodendrocytes play important roles in cognitive function and disease. Whether both cell types follow similar or distinctive evolutionary trajectories is not known. We examined the transcriptomes of neurons and oligodendrocytes in the frontal cortex of humans, chimpanzees, and rhesus macaques. We identified human-specific trajectories of gene expression in neurons and oligodendrocytes and show that both cell types exhibit human-specific up-regulation. Moreover, oligodendrocytes have undergone more pronounced accelerated gene expression evolution in the human lineage compared to neurons. We highlighted human-specific coexpression networks with specific functions. Our data suggest that oligodendrocyte human-specific networks are enriched for alternative splicing and transcriptional regulation. Oligodendrocyte networks are also enriched for variants associated with schizophrenia and other neuropsychiatric disorders. Such enrichments were not found in neuronal networks. These results offer a glimpse into the molecular mechanisms of oligodendrocytes during evolution and how such mechanisms are associated with neuropsychiatric disorders.

Towards an optimised processing pipeline for diffusion magnetic resonance imaging data: Effects of artefact corrections on diffusion metrics and their age associations in UK Biobank

Increasing interest in the structural and functional organisation of the human brain encourages the acquisition of big data sets comprising multiple neuroimaging modalities, often accompanied by additional information obtained from health records, cognitive tests, biomarkers and genotypes. Diffusion weighted magnetic resonance imaging data enables a range of promising imaging phenotypes probing structural connections as well as macroanatomical and microstructural properties of the brain. The reliability and biological sensitivity and specificity of diffusion data depend on processing pipeline. A state-of-the-art framework for data processing facilitates cross-study harmonisation and reduces pipeline-related variability. Using diffusion magnetic resonance imaging (MRI) data from 218 individuals in the UK Biobank, we evaluate the effects of different processing steps that have been suggested to reduce imaging artefacts and improve reliability of diffusion metrics. In lack of a ground truth, we compared diffusion metric sensitivity to age between pipelines. By comparing distributions and age sensitivity of the resulting diffusion metrics based on different approaches (diffusion tensor imaging, diffusion kurtosis imaging and white matter tract integrity), we evaluate a general pipeline comprising seven postprocessing blocks: noise correction; Gibbs ringing correction; evaluation of field distortions; susceptibility, eddy-current and motion-induced distortion corrections; bias field correction; spatial smoothing and final diffusion metric estimations. Based on this evaluation, we suggest an optimised processing pipeline for diffusion weighted MRI data.

Transdiagnostic neuroimaging in psychiatry: A review

Transdiagnostic approach has a long history in neuroimaging, predating its recent ascendance as a paradigm for new psychiatric nosology. Various psychiatric disorders have been compared for commonalities and differences in neuroanatomical features and activation patterns, with different aims and rationales. This review covers both structural and functional neuroimaging publications with direct comparison of different psychiatric disorders, including schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, conduct disorder, anorexia nervosa, and bulimia nervosa. Major findings are systematically presented along with specific rationales for each comparison.

Subtle white matter alterations in schizophrenia identified with a new measure of fiber density

Altered cerebral connectivity is one of the core pathophysiological mechanism underlying the development and progression of information-processing deficits in schizophrenia. To date, most diffusion tensor imaging (DTI) studies used fractional anisotropy (FA) to investigate disrupted white matter connections. However, a quantitative interpretation of FA changes is often impeded by the inherent limitations of the underlying tensor model. A more fine-grained measure of white matter alterations could be achieved by measuring fiber density (FD) - a novel non-tensor-derived diffusion marker. This study investigates, for the first time, FD alterations in schizophrenia patients. FD and FA maps were derived from diffusion data of 25 healthy controls (HC) and 21 patients with schizophrenia (SZ). Using tract-based spatial statistics (TBSS), group differences in FD and FA were investigated across the entire white matter. Furthermore, we performed a region of interest (ROI) analysis of frontal fasciculi to detect potential correlations between FD and positive symptoms. As a result, whole brain TBSS analysis revealed reduced FD in SZ patients compared to HC in several white matter tracts including the left and right thalamic radiation (TR), superior longitudinal fasciculus (SLF), corpus callosum (CC), and corticospinal tract (CST). In contrast, there were no significant FA differences between groups. Further, FD values in the TR were negatively correlated with the severity of positive symptoms and medication dose in SZ patients. In summary, a novel diffusion-weighted data analysis approach enabled us to identify widespread FD changes in SZ patients with most prominent white matter alterations in the frontal and subcortical regions. Our findings suggest that the new FD measure may be more sensitive to subtle changes in the white matter microstructure compared to FA, particularly in the given population. Therefore, investigating FD may be a promising approach to detect subtle changes in the white matter microstructure of altered connectivity in schizophrenia.

Age-Related Alterations of White Matter Integrity in Adolescents and Young Adults With Bipolar Disorder

BACKGROUND

Alterations of white matter integrity during adolescence/young adulthood may contribute to the neurodevelopmental pathophysiology of bipolar disorder (BD), but it remains unknown how white matter integrity changes in BD patients during this critical period of brain development. In the present study, we aimed to identify possible age-associated alterations of white matter integrity in adolescents and young adults with BD across the age range of 13-30 years.

METHODS

We divided the participants into two groups by age as follows: adolescent group involving individuals of 13-21 years old (39 patients with BD and 39 healthy controls) and young adult group involving individuals of 22-30 years old (47 patients with BD and 47 healthy controls). Diffusion tensor imaging (DTI) was performed in all participants to assess white matter integrity.

RESULTS

In the adolescent group, compared to those of healthy controls, fractional anisotropy (FA) values were significantly lower in BD patients in the left inferior longitudinal fasciculus, splenium of the corpus callosum and posterior thalamic radiation. In the young adult group, BD patients showed significantly decreased FA values in the bilateral uncinate fasciculus, genu of the corpus callosum, right anterior limb of internal capsule and fornix compared to healthy controls. White matter impairments changed from the posterior brain to the anterior brain representing a back-to-front spatiotemporal directionality in an age-related pattern.

CONCLUSIONS

Our findings provide neuroimaging evidence supporting a back-to-front spatiotemporal directionality of the altered development of white matter integrity associated with age in BD patients during adolescence/young adulthood.