Neuroanatomical and cognitive correlates of visual hallucinations in Parkinson's disease and dementia with Lewy bodies: Voxel-based morphometry and neuropsychological meta-analysis

Gray matter alterations in Huntington's disease: A meta-analysis of VBM neuroimaging studies

Increasing neuroimaging studies have attempted to identify biomarkers of Huntington's disease (HD) progression. Here, we conducted voxel-based meta-analyses of voxel-based morphometry (VBM) studies on HD to investigate the evolution of gray matter volume (GMV) alterations and explore the effects of genetic and clinical features on GMV changes. A systematic review was performed to identify the relevant studies. Meta-analyses of whole-brain VBM studies were performed to assess the regional GMV changes in all HD mutation carriers, in presymptomatic HD (pre-HD), and in symptomatic HD (sym-HD). A quantitative comparison was performed between pre-HD and sym-HD. Meta-regression analyses were used to explore the effects of genetic and clinical features on GMV changes. Twenty-eight studies were included, comparing a total of 1811 HD mutation carriers [including 1150 pre-HD and 560 sym-HD] and 969 healthy controls (HCs). Pre-HD showed decreased GMV in the bilateral caudate nuclei, putamen, insula, anterior cingulate/paracingulate gyri, middle temporal gyri, and left dorsolateral superior frontal gyrus compared with HCs. Compared with pre-HD, GMV decrease in sym-HD extended to the bilateral median cingulate/paracingulate gyri, Rolandic operculum and middle occipital gyri, left amygdala, and superior temporal gyrus. Meta-regression analyses found that age, mean lengths of CAG repeats, and disease burden were negatively associated with GMV atrophy of the bilateral caudate and right insula in all HD mutation carriers. This meta-analysis revealed the pattern of GMV changes from pre-HD to sym-HD, prompting the understanding of HD progression. The pattern of GMV changes may be biomarkers for disease progression in HD.

Distinct grey and white matter changes are associated with the phenomenology of visual hallucinations in Lewy Body Disease

Visual hallucinations in Lewy body disease (LBD) can be differentiated based on phenomenology into minor phenomena (MVH) and complex hallucinations (CVH). MVH include a variety of phenomena, such as illusions, presence and passage hallucinations occurring at early stages of LBD. The neural mechanisms of visual hallucinations are largely unknown. The hodotopic model posits that the hallucination state is due to abnormal activity in specialized visual areas, that occurs in the context of wider network connectivity alterations and that phenomenology of VH, including content and temporal characteristics, may help identify brain regions underpinning these phenomena. Here we investigated both the topological and hodological neural basis of visual hallucinations integrating grey and white matter imaging analyses. We studied LBD patients with VH and age matched healthy controls (HC). VH were assessed using a North-East-Visual-Hallucinations-Interview that captures phenomenological detail. Then we applied voxel-based morphometry and tract based spatial statistics approaches to identify grey and white matter changes. First, we compared LBD patients and HC. We found a reduced grey matter volume and a widespread damage of white tracts in LBD compared to HC. Then we tested the association between CVH and MVH and grey and white matter indices. We found that CVH duration was associated with decreased grey matter volume in the fusiform gyrus suggesting that LBD neurodegeneration-related abnormal activity in this area is responsible for CVH. An unexpected finding was that MVH severity was associated with a greater integrity of white matter tracts, specifically those connecting dorsal, ventral attention networks and visual areas. Our results suggest that networks underlying MVH need to be partly intact and functional for MVH experiences to occur, while CVH occur when cortical areas are damaged. The findings support the hodotopic view and the hypothesis that MVH and CVH relate to different neural mechanisms, with wider implications for the treatment of these symptoms in a clinical context.

Decreased grey matter volume in dorsolateral prefrontal cortex and thalamus accompanied by compensatory increases in middle cingulate gyrus of premature ejaculation patients

INTRODUCTION

The prefrontal-cingulate-thalamic areas are associated with ejaculation control. Functional abnormalities of these areas and decreased grey matter volume (GMV) in the subcortical areas have been confirmed in premature ejaculation (PE) patients. However, no study has explored the corresponding GMV changes in the prefrontal-cingulate-thalamic areas, which are considered as the important basis for functional abnormalities. This study aimed to investigated whether PE patients exhibited impaired GMV in the brain, especially the prefrontal-cingulate-thalamic areas, and whether these structural deficits were associated with declined ejaculatory control.

METHODS

T1-weighted structural magnetic resonance imaging (MRI) data were acquired from 50 lifelong PE patients and 50 age-, and education-matched healthy controls (HCs). The PE diagnostic tool (PEDT) was applied to assess the subjective symptoms of PE. Based on the method of voxel-based morphometry (VBM), GMV were measured and compared between groups. In addition, the correlations between GMV of brain regions showed differences between groups and PEDT scores were evaluated in the patient group.

RESULTS

PE patients showed decreased GMV in the right dorsolateral superior frontal gyrus (clusters = 13, peak T-values = -4.30) and left thalamus (clusters = 47, T = -4.33), and increased GMV in the left middle cingulate gyrus (clusters = 12, T = 4.02) when compared with HCs. In the patient group, GMV of the left thalamus were negatively associated with PEDT scores (r = -0.35; P = 0.01). Receiver operating characteristic (ROC) analysis showed that GMV of the right dorsolateral superior frontal gyrus (AUC = 0.71, P < 0.01, sensitivity = 60%, specificity = 78%), left thalamus (AUC = 0.72, P < 0.01, sensitivity = 92%, specificity = 46%) and middle cingulate gyrus (AUC = 0.69, P < 0.01, sensitivity = 50%, specificity = 90%), and the combined model (AUC = 0.84, P < 0.01, sensitivity = 78%, specificity = 80%) all had the ability to distinguish PE patients from HCs.

CONCLUSION

Disturbances in GMV were revealed in the prefrontal-cingulate-thalamic areas of PE patients. The findings implied that decreased GMV in the dorsolateral prefrontal cortex and thalamus might be associated with the central pathological neural mechanism underlying the declined ejaculatory control while increased GMV in the middle cingulate gyrus might be the compensatory mechanism underlying PE.

Parkinson disease psychosis: from phenomenology to neurobiological mechanisms

Parkinson disease (PD) psychosis (PDP) is a spectrum of illusions, hallucinations and delusions that are associated with PD throughout its disease course. Psychotic phenomena can manifest from the earliest stages of PD and might follow a continuum from minor hallucinations to structured hallucinations and delusions. Initially, PDP was considered to be a complication associated with dopaminergic drug use. However, subsequent research has provided evidence that PDP arises from the progression of brain alterations caused by PD itself, coupled with the use of dopaminergic drugs. The combined dysfunction of attentional control systems, sensory processing, limbic structures, the default mode network and thalamocortical connections provides a conceptual framework to explain how new incoming stimuli are incorrectly categorized, and how aberrant hierarchical predictive processing can produce false percepts that intrude into the stream of consciousness. The past decade has seen the publication of new data on the phenomenology and neurobiological basis of PDP from the initial stages of the disease, as well as the neurotransmitter systems involved in PDP initiation and progression. In this Review, we discuss the latest clinical, neuroimaging and neurochemical evidence that could aid early identification of psychotic phenomena in PD and inform the discovery of new therapeutic targets and strategies.

Auto-Classification of Parkinson's Disease with Different Motor Subtypes Using Arterial Spin Labelling MRI Based on Machine Learning

The purpose of this study was to automatically classify different motor subtypes of Parkinson's disease (PD) on arterial spin labelling magnetic resonance imaging (ASL-MRI) data using support vector machine (SVM). This study included 38 subjects: 21 PD patients and 17 normal controls (NCs). Based on the Unified Parkinson's Disease Rating Scale (UPDRS) subscores, patients were divided into the tremor-dominant (TD) subtype and the postural instability gait difficulty (PIGD) subtype. The subjects were in a resting state during the acquisition of ASL-MRI data. The automated anatomical atlas 3 (AAL3) template was registered to obtain an ASL image of the same size and shape. We obtained the voxel values of 170 brain regions by considering the location coordinates of these regions and then normalized the data. The length of the feature vector depended on the number of voxel values in each brain region. Three binary classification models were utilized for classifying subjects' data, and we applied SVM to classify voxels in the brain regions. The left subgenual anterior cingulate cortex (ACC_sub_L) was clearly distinguished in both NCs and PD patients using SVM, and we obtained satisfactory diagnostic rates (accuracy = 92.31%, specificity = 96.97%, sensitivity = 84.21%, and AUCmax = 0.9585). For the right supramarginal gyrus (SupraMarginal_R), SVM distinguished the TD group from the other groups with satisfactory diagnostic rates (accuracy = 84.21%, sensitivity = 63.64%, specificity = 92.59%, and AUCmax = 0.9192). For the right intralaminar of thalamus (Thal_IL_R), SVM distinguished the PIGD group from the other groups with satisfactory diagnostic rates (accuracy = 89.47%, sensitivity = 70.00%, specificity = 6.43%, and AUCmax = 0.9464). These results are consistent with the changes in blood perfusion related to PD subtypes. In addition, the sensitive brain regions of the TD group and PIGD group involve the brain regions where the cerebellothalamocortical (CTC) and the striatal thalamocortical (STC) loops are located. Therefore, it is suggested that the blood perfusion patterns of the two loops may be different. These characteristic brain regions could become potential imaging markers of cerebral blood flow to distinguish TD from PIGD. Meanwhile, our findings provide an imaging basis for personalised treatment, thereby optimising clinical diagnostic and treatment approaches.

Cholinesterase Inhibitors for Treatment of Psychotic Symptoms in Alzheimer Disease and Parkinson Disease: A Meta-analysis

Importance

Psychotic symptoms greatly increase the burden of disease for people with neurodegenerative disorders and their caregivers. Cholinesterase inhibitors (ChEIs) may be effective treatment for psychotic symptoms in these disorders. Previous trials only evaluated neuropsychiatric symptoms as a secondary and an overall outcome, potentially blurring the outcomes noted with ChEI use specifically for psychotic symptoms.

Objective

To quantitatively assess the use of ChEIs for treatment of individual neuropsychiatric symptoms, specifically hallucinations and delusions, in patients with Alzheimer disease (AD), Parkinson disease (PD), and dementia with Lewy bodies (DLB).

Data Sources

A systematic search was performed in PubMed (MEDLINE), Embase, and PsychInfo, without year restrictions. Additional eligible studies were retrieved from reference lists. The final search cutoff date was April 21, 2022.

Study Selection

Studies were selected if they presented the results of placebo-controlled randomized clinical trials, including at least 1 donepezil, rivastigmine, or galantamine treatment arm in patients with AD, PD, or DLB; if they applied at least 1 neuropsychiatric measure including hallucinations and/or delusions; and if a full-text version of the study was available in the English language. Study selection was performed and checked by multiple reviewers.

Data Extraction and Synthesis

Original research data were requested on eligible studies. A 2-stage meta-analysis was then performed, using random-effects models. Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed for extracting data and assessing the data quality and validity. Data extraction was checked by a second reviewer.

Main Outcomes and Measures

Primary outcomes were hallucinations and delusions; secondary outcomes included all other individual neuropsychiatric subdomains as well as the total neuropsychiatric score.

Results

In total, 34 eligible randomized clinical trials were selected. Individual participant data on 6649 individuals (3830 [62.6%] women; mean [SD] age, 75.0 [8.2] years) were obtained from 17 trials (AD: n = 12; PD: n = 5; individual participant data were not available for DLB). An association with ChEI treatment was shown in the AD subgroup for delusions (-0.08; 95% CI, -0.14 to -0.03; P = .006) and hallucinations (-0.09; 95% CI, -0.14 to -0.04; P = .003) and in the PD subgroup for delusions (-0.14; 95% CI, -0.26 to -0.01; P = .04) and hallucinations (-0.08, 95% CI -0.13 to -0.03; P = .01).

Conclusions and Relevance

The results of this individual participant data meta-analysis suggest that ChEI treatment improves psychotic symptoms in patients with AD and PD with small effect sizes.

Structural and Functional Imaging Correlates of Visual Hallucinations in Parkinson's Disease

PURPOSE OF REVIEW

To review recent structural and functional MRI studies of visual hallucinations in Parkinson's disease.

RECENT FINDINGS

Previously, neuroimaging had shown inconsistent findings in patients with Parkinson's hallucinations, especially in studies examining grey matter volume. However, recent advances in structural and functional MRI techniques allow better estimates of structural connections, as well as the direction of connectivity in functional MRI. These provide more sensitive measures of changes in structural connectivity and allow models of the changes in directional functional connectivity to be tested. We identified 27 relevant studies and found that grey matter imaging continues to show heterogeneous findings in Parkinson's patients with visual hallucinations. Newer approaches in diffusion imaging and functional MRI are consistent with emerging models of Parkinson's hallucinations, suggesting shifts in attentional networks. In particular, reduced bottom-up, incoming sensory information, and over-weighting of top-down signals appear to be important drivers of visual hallucinations in Parkinson's disease.

Grey matter volume loss in Parkinson's disease psychosis and its relationship with serotonergic gene expression: A meta-analysis

BACKGROUND

Neuroanatomical alterations underlying psychosis in Parkinson's Disease (PDP) remain unclear. We carried out a meta-analysis of MRI studies investigating the neural correlates of PDP and examined its relation with dopaminergic and serotonergic receptor gene expression.

METHODS

PubMed, Web of Science and Embase were searched for MRI studies (k studies = 10) of PDP compared to PD patients without psychosis (PDnP). Seed-based d Mapping with Permutation of Subject Images and multiple linear regression analyses was used to examine the relationship between pooled estimates of grey matter volume (GMV) loss in PDP and D1/D2 and 5-HT1a/5-HT2a receptor gene expression estimates from Allen Human Brain Atlas.

RESULTS

We observed lower grey matter volume in parietal-temporo-occipital regions (PDP n = 211, PDnP, n = 298). GMV loss in PDP was associated with local expression of 5-HT1a (b = 0.109, p = 0.012) and 5-HT2a receptors (b= -0.106, p = 0.002) but not dopaminergic receptors.

CONCLUSION

Widespread GMV loss in the parieto-temporo-occipital regions may underlie PDP. Association between grey matter volume and local expression of serotonergic receptor genes may suggest a role for serotonergic receptors in PDP.

Internet addiction-induced brain structure and function alterations: a systematic review and meta-analysis of voxel-based morphometry and resting-state functional connectivity studies

Internet addiction (IA) is a growing social concern and has been intensively studied in recent years. Previous imaging studies have shown that IA may impair brain structure and function, but with no robust conclusions. We conducted a systematic review and meta-analysis of neuroimaging studies in IA. Two separate meta-analyses were conducted for voxel-based morphometry (VBM) studies and resting-state functional connectivity (rsFC) studies. All meta-analyses were performed using two analysis methods activation likelihood estimation (ALE) and seed-based d mapping with permutation of subject images (SDM-PSI). The ALE analysis of VBM studies revealed less gray matter volume (GMV) in the supplementary motor area (SMA) (1176 mm³), anterior cingulate cortex (ACC) (one cluster size is 744 mm³ and the other is 688 mm³), and orbitofrontal cortex (OFC) (624 mm³) in subjects with IA. The SDM-PSI analysis showed less GMV in the ACC (56 voxels). The ALE analysis of rsFC studies showed stronger rsFC from posterior cingulate cortex (PCC) (880 mm³) or insula (712 mm³) to the whole brain in subjects with IA; however, the SDM-PSI analysis revealed no obvious rsFC alteration. These changes may underlie the core symptoms of IA, which include emotional regulation disorder, distraction, and impaired executive control. Our results reflect the common features of neuroimaging studies related to IA in recent years and may potentially help inform the development of more effective diagnostic and treatment approaches.

Non-visual hallucinations in Parkinson's disease: a systematic review

BACKGROUND

Non-visual hallucinations in Parkinson's disease (PD) can be prevalent and distressing. Most existing research has however, focused on visual hallucinations as well as related risk factors. The current study thus conducted a systematic review to collate existing evidence on non-visual hallucinations in PD, focusing on their prevalence, phenomenology, and clinical-cognitive correlates.

METHODS

Ninety-one relevant studies were included from a systematic search across PsycINFO APA, PubMed, and Web of Science, for peer-reviewed publications in the English language, from 1970 to the present. These comprised a mix of case (30 studies; n = 56) and group design (62 studies; n = 7346) studies, divided into three somewhat overlapping collections to address our three research foci.

RESULTS

Prevalence estimates for hallucinations were: auditory 1.5-72.0%, olfactory 1.6-21.0%, somatic-tactile 0.4-22.5%, gustatory 1.0-15.0%, and sensed presence 0.9-73.3%. Phenomenological inquiries revealed descriptions of vivid, consuming events replete with elaborate detail, adversely affecting PD patients in different ways. Overt experiences of multisensory hallucinations were also highly variable (0.4-80%) but exceedingly common, reported by almost half of the 45 included prevalence studies. There was some evidence for modality-specific hallucination predictors, but this was largely tentative, pending robust replication.

CONCLUSIONS

Marked prevalence figures coupled with phenomenological descriptions implicating distress denote that non-visual and multisensory hallucinations in PD are of clinical significance. More direct research and clinical attention need to be devoted to the study and management of such hallucinatory experiences.

Structural and Functional Neural Alterations in Internet Addiction: A Study Protocol for Systematic Review and Meta-Analysis

A growing number of neuroimaging studies have revealed abnormal brain structural and functional alterations in subjects with internet addiction (IA), however, with conflicting conclusions. We plan to conduct a systematic review and meta-analysis on the studies of voxelbased morphometry (VBM) and resting-state functional connectivity (rsFC), to reach a consolidated conclusion and point out the future direction in this field. A comprehensive search of rsFC and VBM studies of IA will be conducted in the PubMed, Cochrane Library, and Web of Science databases to retrieve studies published from the inception dates to August 2021. If the extracted data are feasible, activation likelihood estimation and seed-based d mapping methods will be used to meta-analyze the brain structural and functional changes in IA patients. This study will hopefully reach a consolidated conclusion on the impact of IA on human brain or point out the future direction in this field.

Age-related brain atrophy in cats without apparent neurological and behavioral signs using voxel-based morphometry

Introduction

Brain atrophy is observed with aging and may cause cognitive decline or dysfunction. Aging cats may demonstrate behavioral changes related to cognitive dysfunction. In the clinical veterinary field, although the conventional region of interest method by manual or semiauto tracing on magnetic resonance imaging is used to detect atrophy of regional structures, such as the hippocampus, it is difficult to assess atrophy globally. Voxel-based morphometry (VBM) has been developed to detect global and regional abnormalities in humans. The purpose of the present study investigates whether the feline brain volume decreases with aging using VBM analysis.

Materials

A total of 65 cats, aged 17-200 months, without apparent neurological and behavioral signs were included in the statistical analysis.

Results

We observed that the gray matter in the bilateral parietal lobes was decreased significantly with aging. The regions that showed decreased volume included the right postcruciate, cingulate gyrus, rostral suprasylvian/ectosylvian gyri, and the left postcruciate gyrus. No significant reduction in white matter was observed. Together, our results show that age-related brain atrophy can be detected using VBM analysis.

Discussion

The age-related atrophy of the parietal cortex may not cause neurological and behavioral signs in cats. Therefore, veterinarians should consider age when assessing the relation between morphometric and functional abnormalities of the parietal cortex in cats.

Aberrant brain gray matter and functional networks topology in end stage renal disease patients undergoing maintenance hemodialysis with cognitive impairment

Purpose

To characterize the topological properties of gray matter (GM) and functional networks in end-stage renal disease (ESRD) patients undergoing maintenance hemodialysis to provide insights into the underlying mechanisms of cognitive impairment.

Materials and methods

In total, 45 patients and 37 healthy controls were prospectively enrolled in this study. All subjects completed resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion kurtosis imaging (DKI) examinations and a Montreal cognitive assessment scale (MoCA) test. Differences in the properties of GM and functional networks were analyzed, and the relationship between brain properties and MoCA scores was assessed. Cognitive function was predicted based on functional networks by applying the least squares support vector regression machine (LSSVRM) and the whale optimization algorithm (WOA).

Results

We observed disrupted topological organizations of both functional and GM networks in ESRD patients, as indicated by significantly decreased global measures. Specifically, ESRD patients had impaired nodal efficiency and degree centrality, predominantly within the default mode network, limbic system, frontal lobe, temporal lobe, and occipital lobe. Interestingly, the involved regions were distributed laterally. Furthermore, the MoCA scores significantly correlated with decreased standardized clustering coefficient (γ), standardized characteristic path length (λ), and nodal efficiency of the right insula and the right superior temporal gyrus. Finally, optimized LSSVRM could predict the cognitive scores of ESRD patients with great accuracy.

Conclusion

Disruption of brain networks may account for the progression of cognitive dysfunction in ESRD patients. Implementation of prediction models based on neuroimaging metrics may provide more objective information to promote early diagnosis and intervention.

A Multimodal Neuroimaging and Neuropsychological Study of Visual Hallucinations in Alzheimer’s Disease

Background: Hallucinations in Alzheimer’s disease (AD) have been linked to more severe cognitive and functional decline. However, research on visual hallucinations (VH), the most common type of hallucinations in AD, is limited. Objective: To investigate the cognitive and cerebral macrostructural and metabolic features associated with VH in AD. Methods: Twenty-four AD patients with VH, 24 with no VH (NVH), and 24 cognitively normal (CN) matched controls were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Differences in regional gray matter (GM) volumes and cognitive performance were investigated with whole brain voxel-based morphometry analyses of MRI structural brain scans, and analyses of neuropsychological tests. Glucose metabolic changes were explored in a subsample of patients who had FDG-PET scans available. Results: More severe visuoconstructive and attentional deficits were found in AD VH compared with NVH. GM atrophy and hypometabolism were detected in occipital and temporal areas in VH patients in comparison with CN. On the other hand, NVH patients had atrophy and hypometabolism mainly in temporal areas. No differences in GM volume and glucose metabolism were found in the direct comparison between AD VH and NVH. Conclusion: In addition to the pattern of brain abnormalities typical of AD, occipital alterations were observed in patients with VH compared with CN. More severe visuoconstructive and attentional deficits were found in AD VH when directly compared with NVH, and might contribute to the emergence of VH in AD.

A systematic review on resting state functional connectivity in patients with neurodegenerative disease and hallucinations

Hallucinations are a complex and multidimensional phenomenon which can differ based on the involved pathology, typology and sensory modality. Hallucinations are common in patients with neurodegenerative diseases. Recent sparse evidence from resting state functional magnetic resonance imaging (rs-fMRI) studies has identified altered functional connectivity in those patients within several brain networks, such as the default mode, attentional and sensory ones, without, however, providing an organized picture of the mechanisms involved. This systematic review, following PRISMA guidelines, aims at critically analyzing the current literature on the brain networks associated with the phenomenon of hallucinations in patients with neurodegenerative diseases. Ten rs-fMRI studies fulfilled our selection criteria. All these studies focused on synucleinopathies, and most of them focused on visual hallucinations and were characterized by a heterogeneous methodology. Thus, instead of offering a definite picture of the mechanisms underlying hallucinations in neurodegeneration, this systematic review encourages further research especially concerning tauopathies. Notwithstanding, the findings overall suggest a disruption in the top-down (associated with memory intrusion and difficulty of inhibition) and in the bottom-up processes (associated with the sensory areas involved in the hallucinations). Further investigations are needed in order to disentangle the brain mechanisms involved in hallucinations and to overcome possible limitations characterizing the current literature.

Investigation of structural brain changes in Charles Bonnet Syndrome

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Reduced grey matter in the occipital cortex in eye disease groups.

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Widespread altered diffusivity in eye disease groups.

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No cortical or white matter changes associated with presence of visual hallucinations.

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Negative association between hippocampal volume and Hallucination severity.

Background and objectives

In Charles Bonnet Syndrome (CBS), visual hallucinations (VH) are experienced by people with sight loss due to eye disease or lesional damage to early visual pathways. The aim of this cross-sectional study was to investigate structural brain changes using magnetic resonance imaging (MRI) in CBS.

Methods

Sixteen CBS patients, 17 with eye disease but no VH, and 19 normally sighted people took part. Participants were imaged on a 3T scanner, with 1 mm resolution T1 weighted structural imaging, and diffusion tensor imaging with 64 diffusion directions.

Results

The three groups were well matched for age, sex and cognitive scores (MMSE). The two eye disease groups were matched on visual acuity. Compared to the sighted controls, we found reduced grey matter in the occipital cortex in both eye disease groups. We also found reductions of fractional anisotropy and increased diffusivity in widespread areas, including occipital tracts, the corpus callosum, and the anterior thalamic radiation. We did not find any significant differences between the eye disease participants with VH versus without VH, but did observe a negative association between hippocampal volume and VH severity in the CBS group.

Discussion

Our findings suggest that although there are cortical and subcortical effects associated with sight loss, structural changes do not explain the occurrence of VHs. CBS may relate instead to connectivity or excitability changes in brain networks linked to vision.

Focusing on Comorbidity-A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

BACKGROUND

In mental health, comorbidities are the norm rather than the exception. However, current meta-analytic methods for summarizing the neural correlates of mental disorders do not consider comorbidities, reducing them to a source of noise and bias rather than benefitting from their valuable information.

OBJECTIVES

We describe and validate a novel neuroimaging meta-analytic approach that focuses on comorbidities. In addition, we present the protocol for a meta-analysis of all major mental disorders and their comorbidities.

METHODS

The novel approach consists of a modification of Seed-based d Mapping-with Permutation of Subject Images (SDM-PSI) in which the linear models have no intercept. As in previous SDM meta-analyses, the dependent variable is the brain anatomical difference between patients and controls in a voxel. However, there is no primary disorder, and the independent variables are the percentages of patients with each disorder and each pair of potentially comorbid disorders. We use simulations to validate and provide an example of this novel approach, which correctly disentangled the abnormalities associated with each disorder and comorbidity. We then describe a protocol for conducting the new meta-analysis of all major mental disorders and their comorbidities. Specifically, we will include all voxel-based morphometry (VBM) studies of mental disorders for which a meta-analysis has already been published, including at least 10 studies. We will use the novel approach to analyze all included studies in two separate single linear models, one for children/adolescents and one for adults.

DISCUSSION

The novel approach is a valid method to focus on comorbidities. The meta-analysis will yield a comprehensive atlas of the neuroanatomy of all major mental disorders and their comorbidities, which we hope might help develop potential diagnostic and therapeutic tools.