Anatomical Likelihood Estimation Research Articles

Mindfulness-based randomized controlled trials led to brain structural changes: an anatomical likelihood meta-analysis

Mindfulness has become increasingly popular and the practice presents in many different forms. Research has been growing extensively with benefits shown across various outcomes. However, there is a lack of consensus over the efficacy of randomized controlled mindfulness interventions, both traditional and mind–body formats. This study aimed to investigate the structural brain changes in mindfulness-based interventions through a meta-analysis. Scopus, PubMed, Web of Science, and PsycINFO were searched up to April 2023. 11 studies (n = 581) assessing whole-brain voxel-based grey matter or cortical thickness changes after a mindfulness RCT were included. Anatomical likelihood estimation was used to carry out voxel-based meta-analysis with leave-one-out sensitivity analysis and behavioural analysis as follow-ups. One significant cluster (p < 0.001, Z = 4.76, cluster size = 632 mm3) emerged in the right insula and precentral gyrus region (MNI = 48, 10, 4) for structural volume increases in intervention group compared to controls. Behavioural analysis revealed that the cluster was associated with mental processes of attention and somesthesis (pain). Mindfulness interventions have the ability to affect neural plasticity in areas associated with better pain modulation and increased sustained attention. This further cements the long-term benefits and neuropsychological basis of mindfulness-based interventions.

Brain Areas Critical for Picture Naming: A Systematic Review and Meta-Analysis of Lesion-Symptom Mapping Studies.

Lesion-symptom mapping (LSM) studies have revealed brain areas critical for naming, typically finding significant associations between damage to left temporal, inferior parietal, and inferior fontal regions and impoverished naming performance. However, specific subregions found in the available literature vary. Hence, the aim of this study was to perform a systematic review and meta-analysis of published lesion-based findings, obtained from studies with unique cohorts investigating brain areas critical for accuracy in naming in stroke patients at least 1 month post-onset. An anatomic likelihood estimation (ALE) meta-analysis of these LSM studies was performed. Ten papers entered the ALE meta-analysis, with similar lesion coverage over left temporal and left inferior frontal areas. This small number is a major limitation of the present study. Clusters were found in left anterior temporal lobe, posterior temporal lobe extending into inferior parietal areas, in line with the arcuate fasciculus, and in pre- and postcentral gyri and middle frontal gyrus. No clusters were found in left inferior frontal gyrus. These results were further substantiated by examining five naming studies that investigated performance beyond global accuracy, corroborating the ALE meta-analysis results. The present review and meta-analysis highlight the involvement of left temporal and inferior parietal cortices in naming, and of mid to posterior portions of the temporal lobe in particular in conceptual-lexical retrieval for speaking.

Mapping a network for tics in Tourette syndrome using causal lesions and structural alterations.

Tics are sudden stereotyped movements or vocalizations. Cases of lesion-induced tics are invaluable, allowing for causal links between symptoms and brain structures. While a lesion network for tics has recently been identified, the degree to which this network translates to Tourette syndrome has not been fully elucidated. This is important given that patients with Tourette syndrome make up a large portion of tic cases; therefore, existing and future treatments should apply to these patients. The aim of this study was to first localize a causal network for tics from lesion-induced cases and then refine and validate this network in patients with Tourette syndrome. We independently performed 'lesion network mapping' using a large normative functional connectome (n = 1000) to isolate a brain network commonly connected to lesions causing tics (n = 19) identified through a systematic search. The specificity of this network to tics was assessed through comparison to lesions causing other movement disorders. Using structural brain coordinates from prior neuroimaging studies (n = 7), we then derived a neural network for Tourette syndrome. This was done using standard anatomical likelihood estimation meta-analysis and a novel method termed 'coordinate network mapping', which uses the same coordinates, yet maps their connectivity using the aforementioned functional connectome. Conjunction analysis was used to refine the network for lesion-induced tics to Tourette syndrome by identifying regions common to both lesion and structural networks. We then tested whether connectivity from this common network is abnormal in a separate resting-state functional connectivity MRI data set from idiopathic Tourette syndrome patients (n = 21) and healthy controls (n = 25). Results showed that lesions causing tics were distributed throughout the brain; however, consistent with a recent study, these were part of a common network with predominant basal ganglia connectivity. Using conjunction analysis, coordinate network mapping findings refined the lesion network to the posterior putamen, caudate nucleus, globus pallidus externus (positive connectivity) and precuneus (negative connectivity). Functional connectivity from this positive network to frontal and cingulate regions was abnormal in patients with idiopathic Tourette syndrome. These findings identify a network derived from lesion-induced and idiopathic data, providing insight into the pathophysiology of tics in Tourette syndrome. Connectivity to our cortical cluster in the precuneus offers an exciting opportunity for non-invasive brain stimulation protocols.

Characterization of the logopenic variant of Primary Progressive Aphasia: A systematic review and meta-analysis.

The linguistic and anatomical variability of the logopenic variant of Primary Progressive Aphasia (lv-PPA) as defined by current diagnostic criteria has been the topic of an intense debate. The present review and meta-analysis aims at characterizing the profile of lv-PPA, by a comprehensive analysis of the available literature on the neuropsychological, neuroimaging, electrophysiological, pathological, and genetic features of lv-PPA. We conducted a systematic bibliographic search, leading to the inclusion of 207 papers. Of them, 12 were used for the Anatomical Likelihood Estimation meta-analysis on grey matter revealed by magnetic resonance imaging data. The results suggest that the current guidelines outline a relatively consistent syndrome, characterized by a core set of linguistic and, to a lesser extent, non-linguistic deficits, mirroring the involvement of left temporal and parietal regions typically affected by Alzheimer Disease pathology. Variations of the lv-PPA profile are discussed in terms of heterogeneity of the neuropsychological instruments and the diagnostic criteria adopted.

Extended functional connectivity of convergent structural alterations among individuals with PTSD: a neuroimaging meta-analysis

BackgroundPost-traumatic stress disorder (PTSD) is a debilitating disorder defined by the onset of intrusive, avoidant, negative cognitive or affective, and/or hyperarousal symptoms after witnessing or experiencing a traumatic event. Previous voxel-based morphometry studies have provided insight into structural brain alterations associated with PTSD with notable heterogeneity across these studies. Furthermore, how structural alterations may be associated with brain function, as measured by task-free and task-based functional connectivity, remains to be elucidated.MethodsUsing emergent meta-analytic techniques, we sought to first identify a consensus of structural alterations in PTSD using the anatomical likelihood estimation (ALE) approach. Next, we generated functional profiles of identified convergent structural regions utilizing resting-state functional connectivity (rsFC) and meta-analytic co-activation modeling (MACM) methods. Finally, we performed functional decoding to examine mental functions associated with our ALE, rsFC, and MACM brain characterizations.ResultsWe observed convergent structural alterations in a single region located in the medial prefrontal cortex. The resultant rsFC and MACM maps identified functional connectivity across a widespread, whole-brain network that included frontoparietal and limbic regions. Functional decoding revealed overlapping associations with attention, memory, and emotion processes.ConclusionsConsensus-based functional connectivity was observed in regions of the default mode, salience, and central executive networks, which play a role in the tripartite model of psychopathology. Taken together, these findings have important implications for understanding the neurobiological mechanisms associated with PTSD.

Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies

BackgroundNeuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact. MethodsWe identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an “extended network” by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes’ functional connectivity profiles to delineate subnetworks. ResultsAcross drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions’ functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal). ConclusionsThese outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.

Explore functional brain changes in bipolar disorder: A whole brain ALE meta-analysis

ABSTRACT Background: Previous functional magnetic resonance imaging (fMRI) studies showed inconsistent results for comparison between bipolar disorder (BD) and healthy controls (HC). Methods: An anatomic likelihood estimation (ALE) meta-analysis was used to explore the key regions of brain pathology in BD with different current mood states. Results: Depressed BD patients showed reduced regional homogeneity (ReHo) in the left claustrum and the left middle frontal gyrus (MFG), compared to HC. BD patients with mixed mood status showed decreased fractional amplitude of low frequency fluctuations (fALFF) in the right cerebellar tonsil, the bilateral MFG and the right superior frontal gyrus, compared to HC. Additionally, BD patients with mixed mood status showed increased fALFF in the right inferior occipital gyrus, the right culmen and the left lentiform nucleus, compared to HC. BD patients with mixed mood status showed decreased functional connectivity (FC) in the bilateral cerebellar tonsil, compared to HC. Conclusion: In the present study, key regions undergoing functional deficits in BD patients with different current mood states were obtained with the ALE meta-analysis. In addition, deficits in these regions in fMRI studies might work as biomarkers for early diagnosis of BD.

Structural gray matter differences in Problematic Usage of the Internet: a systematic review and meta-analysis

Problematic Usage of the Internet (PUI) has been linked to diverse structural gray matter changes in individual data studies. However, no quantitative synthesis across studies has been conducted. We aimed to identify gray matter regions showing significant spatial convergence across neuroimaging studies in PUI. We searched PubMed and PsycINFO up to 10/03/2021 and included original, cross-sectional comparative studies that examined structural gray matter imaging in PUI versus control groups; reported a whole-brain analysis; and provided peak coordinates for gray matter differences. From a total of 624 potentially relevant studies, 15 (including 355 individuals with PUI and 363 controls) were included in a meta-analysis of voxel-based morphometry studies. Anatomical likelihood estimation (ALE) meta-analysis was performed using extracted coordinates and identified significant spatial convergence in the medial/superior frontal gyri, the left anterior cingulate cortex/cingulate gyrus, and the left middle frontal/precentral gyri. Datasets contributing to these findings all indicated reduced gray matter in cases compared to controls. In conclusion, voxel-based morphometric studies indicate replicable gray matter reductions in the dorsolateral prefrontal cortex and anterior cingulate cortex in PUI, regions implicated in reward processing and top-down inhibitory control. Further studies are required to understand the nature of gray matter differences across PUI behaviors, as well as the contribution of particular mental health disorders, and the influence of variation in study and sample characteristics.

Meta-analysis of grey matter changes and their behavioral characterization in patients with alcohol use disorder

Alcohol Use Disorder (AUD) is associated with reductions in grey matter (GM) volume which can lead to changes in numerous brain functions. The results of previous studies on altered GM in AUD differ considerably in the regions identified. Three meta-analyses carried out between 2014 and 2017 yielded different results. The present study includes the considerable amount of newer research and delivers a state-of-the art meta-analysis in line with recently published guidelines. Additionally, we behaviorally characterized affected regions using fMRI metadata and identified related brain networks by determining their meta-analytic connectivity patterns. Twenty-seven studies with 1,045 AUD patients and 1,054 healthy controls were included in the analysis and analyzed by means of Anatomical Likelihood Estimation (ALE). GM alterations were identified in eight clusters covering different parts of the cingulate and medial frontal gyri, paracentral lobes, left post- and precentral gyri, left anterior and right posterior insulae and left superior frontal gyrus. The behavioral characterization associated these regions with specific cognitive, emotional, somatosensory and motor functions. Moreover, the clusters represent nodes within behaviorally relevant brain networks. Our results suggest that GM reduction in AUD could disrupt network communication responsible for the neurocognitive impairments associated with high chronic alcohol consumption.

Gray and white matter morphology in substance use disorders: a neuroimaging systematic review and meta-analysis

Substance use disorders (SUDs) are characterized by a compulsion to seek and consume one or more substances of abuse, with a perceived loss of control and a negative emotional state. Prolonged substance use seems to be associated with morphological changes of multiple neural circuits, in particular the frontal–striatal and limbic pathways. Such neuroadaptations are evident across several substance disorders, but may vary depending on the type of substance, consumption severity and/or other unknown factors. We therefore identified studies investigating the effects of SUDs using volumetric whole-brain voxel-based morphometry (VBM) in gray (GM) and white matter (WM). We performed a systematic review and meta-analysis of VBM studies using the anatomic likelihood estimation (ALE) method implemented in GingerALE (PROSPERO pre-registration CRD42017071222). Sixty studies met inclusion criteria and were included in the final quantitative meta-analysis, with a total of 614 foci, 94 experiments and 4938 participants. We found convergence and divergence in brain regions and volume effects (higher vs. lower volume) in GM and WM depending on the severity of the consumption pattern and type of substance used. Convergent pathology was evident across substances in GM of the insula, anterior cingulate cortex, putamen, and thalamus, and in WM of the thalamic radiation and internal capsule bundle. Divergent pathology between occasional use (cortical pathology) and addiction (cortical-subcortical pathology) provides evidence of a possible top-down neuroadaptation. Our findings indicate particular brain morphometry alterations in SUDs, which may inform our understanding of disease progression and ultimately therapeutic approaches.

The functional neural architecture of dysfunctional reward processing in autism

Functional imaging studies have found differential neural activation patterns during reward-paradigms in patients with autism spectrum disorder (ASD) compared to neurotypical controls. However, publications report conflicting results on the directionality and location of these aberrant activations. We here quantitatively summarized relevant fMRI papers in the field using the anatomical likelihood estimation (ALE) algorithm.Patients with ASD consistently showed hypoactivations in the striatum across studies, mainly in the right putamen and accumbens. These regions are functionally involved in the processing of rewards and are enrolled in extensive neural networks involving limbic, cortical, thalamic and mesencephalic regions.The striatal hypo-activations found in our ALE meta-analysis, which pooled over contrasts derived from the included studies on reward-processing in ASD, highlight the role of the striatum as a key neural correlate of impaired reward processing in autism. These changes were present for studies using social and non-social stimuli alike. The involvement of these regions in extensive networks associated with the processing of both positive and negative emotion alike might hint at broader impairments of emotion processing in the disorder.

Neuro-transcriptomic signatures for mood disorder morbidity and suicide mortality

Suicidal behaviors are strongly linked with mood disorders, but the specific neurobiological and functional gene-expression correlates for this linkage remain elusive. We performed neuroimaging-guided RNA-sequencing in two studies to test the hypothesis that imaging-localized gray matter volume (GMV) loss in mood disorders, harbors gene-expression changes associated with disease morbidity and related suicide mortality in an independent postmortem cohort. To do so, first, we conducted study 1 using an anatomical likelihood estimation (ALE) MRI meta-analysis including a total of 47 voxel-based morphometry (VBM) publications (i.e. 26 control versus (vs) major depressive disorder (MDD) studies, and 21 control vs bipolar disorder (BD) studies) in 2387 (living) participants. Study 1 meta-analysis identified a selective anterior insula cortex (AIC) GMV loss in mood disorders. We then used this results to guide study 2 postmortem tissue dissection and RNA-Sequencing of 100 independent donor brain samples with a life-time history of MDD (N = 30), BD (N = 37) and control (N = 33). In study 2, exploratory factor-analysis identified a higher-order factor representing number of Axis-1 diagnoses (e.g. substance use disorders/psychosis/anxiety, etc.), referred to here as morbidity and suicide-completion referred to as mortality. Comparisons of case-vs-control, and factor-analysis defined higher-order-factor contrast variables revealed that the imaging-identified AIC GMV loss sub-region harbors differential gene-expression changes in high morbidity-&-mortality versus low morbidity-&-mortality cohorts in immune, inflammasome, and neurodevelopmental pathways. Weighted gene co-expression network analysis further identified co-activated gene modules for psychiatric morbidity and mortality outcomes. These results provide evidence that AIC anatomical signature for mood disorders are possible correlates for gene-expression abnormalities in mood morbidity and suicide mortality.

Parcellation-based tractographic modeling of the dorsal attention network.

IntroductionThe dorsal attention network (DAN) is an important mediator of goal‐directed attentional processing. Multiple cortical areas, such as the frontal eye fields, intraparietal sulcus, superior parietal lobule, and visual cortex, have been linked in this processing. However, knowledge of network connectivity has been devoid of structural specificity.MethodsUsing attention‐related task‐based fMRI studies, an anatomic likelihood estimation (ALE) of the DAN was generated. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co‐registered onto the ALE in MNI coordinate space and visually assessed for inclusion in the network. DSI‐based fiber tractography was performed to determine the structural connections between relevant cortical areas comprising the network.ResultsTwelve cortical regions were found to be part of the DAN: 6a, 7AM, 7PC, AIP, FEF, LIPd, LIPv, MST, MT, PH, V4t, VIP. All regions demonstrated consistent u‐shaped interconnections between adjacent parcellations. The superior longitudinal fasciculus connects the frontal, parietal, and occipital areas of the network.ConclusionsWe present a tractographic model of the DAN. This model comprises parcellations within the frontal, parietal, and occipital cortices principally linked through the superior longitudinal fasciculus. Future studies may refine this model with the ultimate goal of clinical application.

Anorexia nervosa and diffusion weighted imaging: An open methodological question raised by a systematic review and a fractional anisotropy anatomical likelihood estimation meta-analysis.

Anorexia nervosa (AN) is characterized by white matter abnormalities in neuroimaging studies. Fractional anisotropy (FA) is a diffusion tensor imaging (DTI) index that is considered an instrument for the evaluation of white matter alterations. However, the literature has recently pointed out the role of the partial volume effect (PVE) as a confounding factor for the identification of juxtaposed tissues. Our goal was to review the DTI literature in AN and evaluate possible confounding factors linked to the reported results. A systematic review of the literature was conducted to identify Diffusion Tensor Imaging studies of individuals with AN and, subsequently, an anatomical likelihood estimation (ALE) meta-analysis was performed on studies published before March 18, 2019. Twenty-four studies (AN = 517, controls = 542) were included in the qualitative systematic review of the literature. Ten published studies underwent the ALE-analysis (AN = 210, controls = 229), plus data from an unpublished cohort (AN = 38, controls = 38). Two clusters of decreased FA were identified, namely in the left corona radiata, and in the left thalamus. Only one article took the PVE correction analysis into account. The alterations identified must be considered within the limits of a possible methodological bias regarding PVE and free water and re-analysis of the data may be recommended. The preliminary data showed that the alteration of white matter pathways between the limbic structures and brain cortex may be linked to the processing of somatosensory information that could play a key role in the psychopathology of the disorder.

Localised grey matter atrophy in multiple sclerosis is network-based: a coordinate-based meta-analysis

To test the network degeneration hypothesis in multiple sclerosis (MS) with a two-stage coordinate-based meta-analysis by: (1) characterising regional selectivity of grey matter (GM) atrophy and (2) testing for functional connectivity involving these regions. Meta-analytic sources included 33 journal articles (1,666 MS patients and 1,269 healthy controls) with coordinate-based results from voxel-based morphometry analysis demonstrating GM atrophy. Mass univariate and multivariate coordinate-based meta-analyses were performed to identify a convergent pattern of GM atrophy and determine inter-regional co-activation (as a surrogate of functional connectivity), with anatomical likelihood estimation and functional meta-analytic connectivity modelling, respectively. Localised GM atrophy was demonstrated in the thalamus, putamen, caudate, sensorimotor cortex, insula, superior temporal gyrus, and cingulate gyrus. This convergent pattern of atrophy displayed significant inter-regional functional co-activations. In MS, GM atrophy was regionally selective, and these regions were functionally connected. The meta-analytic model-based results of this study are intended to guide future development of quantitative neuroimaging markers for diagnosis, evaluating disease progression, and monitoring treatment response.

Insular volume reductions in patients with major depressive disorder

BackgroundMajor Depressive Disorder (MDD) is one of the most common mental disorders. Converging evidence suggests that the insula plays an important role in the pathophysiology of MDD. Little is known regarding in which insula subregion volume alterations occur in patients with MDD. MethodsWe analyzed voxel-based morphometry in T1-weighted MRI scans of unmedicated DSM-IV MDD patients (n = 26) and in age, education, and sex matched healthy controls (HC, n = 26). Furthermore, we performed a quantitative meta-analysis across 14 structural MRI MDD studies by applying the anatomical likelihood estimation technique to identify concordant volume reductions in MDD in the insula cortex. ResultsWe found significantly reduced grey matter volumes (GMV) in patients with MDD compared to HCs in the left mid-insula and in the right and left caudate nucleus. The left mid-insular volume reduction in our sample was consistent with the coordinate-based meta-analysis results. ConclusionsThe findings highlight the role of the mid-insula in the psychopathology of MDD. The mid-insula subregion might be associated with reduced interoceptive abilities in patients with MDD that is the ability to process information of “how the body feels”. In addition, the caudate nucleus has been described as being part of a network that mediates emotional and motivational processes which seems to be affected in MDD.

Atrophy in midbrain & cerebral/cerebellar pedunculi is characteristic for progressive supranuclear palsy - A double-validation whole-brain meta-analysis.

ObjectiveProgressive supranuclear palsy (PSP) is an atypical parkinsonian syndrome characterized by vertical gaze palsy and postural instability. Midbrain atrophy is suggested as a hallmark, but it has not been validated systematically in whole-brain imaging.MethodsWe conducted whole-brain meta-analyses identifying disease-related atrophy in structural MRI. Eighteen studies were identified (N = 315 PSP, 393 controls) and separated into gray or white matter analyses (15/12). All patients were diagnosed according to the National Institute of Neurological Disorders and Stroke and the Society for PSP (NINDS-SPSP criteria, Litvan et al. (1996a)), which are now considered as PSP-Richardson syndrome (Höglinger et al., 2017). With overlay analyses, we double-validated two meta-analytical algorithms: anatomical likelihood estimation and seed-based D mapping. Additionally, we conducted region-of-interest effect size meta-analyses on radiological biomarkers and subtraction analyses differentiating PSP from Parkinson's disease.ResultsWhole brain meta-analyses revealed consistent gray matter atrophy in bilateral thalamus, anterior insulae, midbrain, and left caudate nucleus. White matter alterations were consistently detected in bilateral superior/middle cerebellar pedunculi, cerebral pedunculi, and midbrain atrophy. Region-of-interest meta-analyses demonstrated that midbrain metrics generally perform very well in distinguishing PSP from other parkinsonian syndromes with strong effect sizes. Subtraction analyses identified the midbrain as differentiating between PSP and Parkinson's disease.ConclusionsOur meta-analyses identify gray matter atrophy of the midbrain and white matter atrophy of the cerebral/cerebellar pedunculi and midbrain as characteristic for PSP. Results support the incorporation of structural MRI data, and particularly these structures, into the revised PSP diagnostic criteria.

FDG-PET hypometabolism is more sensitive than MRI atrophy in Parkinson's disease: A whole-brain multimodal imaging meta-analysis.

Recently, revised diagnostic criteria for Parkinson's disease (PD) were introduced (Postuma et al., 2015). Yet, except for well-established dopaminergic imaging, validated imaging biomarkers for PD are still missing, though they could improve diagnostic accuracy.We conducted systematic meta-analyses to identify PD-specific markers in whole-brain structural magnetic resonance imaging (MRI), [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) and diffusion tensor imaging (DTI) studies. Overall, 74 studies were identified including 2323 patients and 1767 healthy controls. Studies were first grouped according to imaging modalities (MRI 50; PET 14; DTI 10) and then into subcohorts based on clinical phenotypes. To ensure reliable results, we combined established meta-analytical algorithms - anatomical likelihood estimation and seed-based D mapping - and cross-validated them in a conjunction analysis.Glucose hypometabolism was found using FDG-PET extensively in bilateral inferior parietal cortex and left caudate nucleus with both meta-analytic methods. This hypometabolism pattern was confirmed in subcohort analyses and related to cognitive deficits (inferior parietal cortex) and motor symptoms (caudate nucleus). Structural MRI showed only small focal gray matter atrophy in the middle occipital gyrus that was not confirmed in subcohort analyses. DTI revealed fractional anisotropy reductions in the cingulate bundle near the orbital and anterior cingulate gyri in PD.Our results suggest that FDG-PET reliably identifies consistent functional brain abnormalities in PD, whereas structural MRI and DTI show only focal alterations and rather inconsistent results. In conclusion, FDG-PET hypometabolism outperforms structural MRI in PD, although both imaging methods do not offer disease-specific imaging biomarkers for PD.

Using coordinate-based meta-analyses to explore structural imaging genetics.

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

Atrophy in Midbrain &amp;amp; Cerebral/Cerebellar Pedunculi is Specific for Progressive Supranuclear Palsy - A Cross-Validation Whole-Brain Meta-Analysis

Objective: Progressive supranuclear palsy (PSP) is an atypical parkinsonian syndrome characterized by vertical gaze palsy and postural instability. Midbrain atrophy is suggested as a hallmark, but it has not been validated systematically in whole-brain imaging. Methods: We conducted whole-brain meta-analyses identifying disease-specific atrophy in structural MRI. Eighteen studies were identified (N=315 PSP, 393 controls) and separated into gray or white matter analyses (15/12). With overlay analyses, we cross-validated two meta-analytical algorithms: anatomical likelihood estimation and seed-based D mapping. Results: Whole brain meta-analyses revealed consistent gray matter atrophy in bilateral thalamus, anterior insulae, midbrain, and left caudate nucleus. White matter alterations were consistently detected in bilateral superior/middle cerebellar pedunculi, cerebral pedunculi, and midbrain atrophy. Conclusions: Our meta-analyses identify gray matter atrophy of the midbrain and white matter atrophy of the cerebral/cerebellar pedunculi and midbrain as specific to PSP. We support the incorporation of structural MRI data, and particularly these structures, into the revised PSP diagnostic criteria.