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Matthias L. Schroeter

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YNICL Journal 2025 Journal Article

Boostering diagnosis of frontotemporal lobar degeneration with AI-driven neuroimaging – A systematic review and meta-analysis

  • Qiong Wu
  • Dimitra Kiakou
  • Karsten Mueller
  • Wolfgang Köhler
  • Matthias L. Schroeter

BACKGROUND AND OBJECTIVES: Frontotemporal lobar degeneration (FTLD) as the second most common dementia encompasses a range of syndromes and often shows overlapping symptoms with other subtypes or neurodegenerative diseases, which poses a significant clinical diagnostic challenge. Recent advancements in artificial intelligence (AI), specifically the application of machine learning (ML) algorithms to neuroimaging, have significantly progressed in addressing this challenge. This study aims to assess the diagnostic and predictive efficacy of neuroimaging feature-based AI algorithms for FTLD. METHODS: We conducted a systematic review and meta-analysis following PRISMA guidelines. We searched Pubmed, Scopus, and Web of Science for English-language, peer-reviewed studies using the following three umbrella terms: artificial intelligence, frontotemporal lobar degeneration, and neuroimaging modality. Our survey focused on computer-aided diagnosis for FTLD, employing machine/deep learning with neuroimaging radiomic features. RESULTS: The meta-analysis includes 75 articles with 20,601 subjects, including 8,051 FTLD patients. The results reveal that FTLD can be automatically classified against healthy controls (HC) with pooled sensitivity and specificity of 86% and 89%, respectively. Likewise, FTLD versus Alzheimer's disease (AD) classification exhibits pooled sensitivity and specificity of 84% and 81%, while FTLD versus Parkinson's disease (PD) demonstrates pooled sensitivity and specificity of 84% and 75%, respectively. Classification performance distinguishing FTLD from atypical Parkinsonian syndromes (APS) showed pooled sensitivity and specificity of 84% and 79%, respectively. Multiclass classification sensitivity ranges from 42% to 100%, with lower sensitivity occurring in higher class distinctions (e.g., 5-class and 11-class). DISCUSSION: Our study demonstrates the effectiveness of utilizing neuroimaging features to distinguish FTLD from HC, AD, APS, and PD in binary classification. Utilizing deep learning with multimodal neuroimaging data to differentiate FTLD subtypes and perform multiclassification among FTLD and other neurodegenerative disease holds promise for expediting diagnosis. In sum, the meta-analysis supports translation of machine learning tools in combination with imaging to clinical routine paving the way to precision medicine.

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YNIMG Journal 2023 Journal Article

Alterations in rhythmic and non‐rhythmic resting‐state EEG activity and their link to cognition in older age

  • Elena Cesnaite
  • Paul Steinfath
  • Mina Jamshidi Idaji
  • Tilman Stephani
  • Deniz Kumral
  • Stefan Haufe
  • Christian Sander
  • Tilman Hensch

While many structural and biochemical changes in the brain have previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.

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YNICL Journal 2023 Journal Article

Improving fMRI in Parkinson’s disease by accounting for brain region-specific activity patterns

  • Renzo Torrecuso
  • Karsten Mueller
  • Štefan Holiga
  • Tomáš Sieger
  • Josef Vymazal
  • Filip Ružička
  • Jan Roth
  • Evzen Ružička

In functional magnetic imaging (fMRI) in Parkinson's disease (PD), a paradigm consisting of blocks of finger tapping and rest along with a corresponding general linear model (GLM) is often used to assess motor activity. However, this method has three limitations: (i) Due to the strong magnetic field and the confined environment of the cylindrical bore, it is troublesome to accurately monitor motor output and, therefore, variability in the performed movement is typically ignored. (ii) Given the loss of dopaminergic neurons and ongoing compensatory brain mechanisms, motor control is abnormal in PD. Therefore, modeling of patients' tapping with a constant amplitude (using a boxcar function) and the expected Parkinsonian motor output are prone to mismatch. (iii) The motor loop involves structures with distinct hemodynamic responses, for which only one type of modeling (e.g., modeling the whole block of finger tapping) may not suffice to capture these structure's temporal activation. The first two limitations call for considering results from online recordings of the real motor output that may lead to significant sensitivity improvements. This was shown in previous work using a non-magnetic glove to capture details of the patients' finger movements in a so-called kinematic approach. For the third limitation, modeling motion initiation instead of the whole tapping block has been suggested to account for different temporal activation signatures of the motor loop's structures. In the present study we propose improvements to the GLM as a tool to study motor disorders. For this, we test the robustness of the kinematic approach in an expanded cohort (n = 31), apply more conservative statistics than in previous work, and evaluate the benefits of an event-related model function. Our findings suggest that the integration of the kinematic approach offers a general improvement in detecting activations in subcortical structures, such as the basal ganglia. Additionally, modeling motion initiation using an event-related design yielded superior performance in capturing medication-related effects in the putamen. Our results may guide adaptations in analysis strategies for functional motor studies related to PD and also in more general applications.

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YNICL Journal 2023 Journal Article

Longitudinal changes in surface based brain morphometry measures in amnestic mild cognitive impairment and Alzheimer’s Disease

  • Tobias Bachmann
  • Matthias L. Schroeter
  • Kewei Chen
  • Eric M. Reiman
  • Christopher M. Weise

BACKGROUND: Alzheimer's disease (AD) is associated with marked brain atrophy. While commonly used structural MRI imaging methods do not account for the complexity of human brain morphology, little is known about the longitudinal changes of cortical geometry and their relationship with cognitive decline in subjects with AD. METHODS: Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were used to perform two-sample t-tests to investigate longitudinal changes of cortical thickness (CTh) and three surface-based morphometry measures: fractal dimension (i.e. cortical complexity; FD), gyrification index (GI), and sulcal depth (SD) in subjects with AD, amnestic mild cognitive impairment (aMCI) in comparison to cognitively unimpaired controls (CU) in baseline and 2-year follow-up sMRI scans. In addition, correlations of the morphological measures with two-year cognitive decline as assessed by the modified AD Assessment Scale-Cognitive Subscale (ADAS-Cog 11) were calculated via regression analyses. RESULTS: Compared to CU, both AD and aMCI showed marked decreases in CTh. In contrast, analyses of FD and GI yielded a more nuanced decline of the respective measures with some areas showing increases in FD and GI. Overall changes in FD and GI were more pronounced in AD as compared to aMCI. Analyses of SD yielded widespread decreases. Interestingly, cognitive decline corresponded well with CTh declines in aMCI but not AD, whereas changes in FD corresponded with AD only but not aMCI, whereas GI and SD were associated with cognitive decline in aMCI and AD. CONCLUSION: Patterns of longitudinal changes in FD, GI and SD were only partially overlapping with CTh reductions. In AD, surface-based morphometry measures for brain-surface complexity showed better correspondence than CTh with cognitive decline over a two-year period of time. Being drawn from measures reflecting changes in more intricate aspects of human brain morphology, these data provide new insight into the complexity of AD-related brain atrophy and its relationship with cognitive decline.

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YNICL Journal 2023 Journal Article

Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging

  • Leonie Lampe
  • Hans-Jürgen Huppertz
  • Sarah Anderl-Straub
  • Franziska Albrecht
  • Tommaso Ballarini
  • Sandrine Bisenius
  • Karsten Mueller
  • Sebastian Niehaus

INTRODUCTION: Dementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI). METHODS: Atlas-based volumetry was performed on T1-weighted MRI data of 426 patients and 51 controls from the multi-centric German Research Consortium of Frontotemporal Lobar Degeneration including patients with behavioral variant frontotemporal dementia, Alzheimer's disease, the three subtypes of primary progressive aphasia, i.e., semantic, logopenic and nonfluent-agrammatic variant, and the atypical parkinsonian syndromes progressive supranuclear palsy and corticobasal syndrome. Support vector machine classification was used to classify each patient group against controls (binary classification) and all seven diagnostic groups against each other in a multi-syndrome classifier (multiclass classification). RESULTS: The binary classification models reached high prediction accuracies between 71 and 95% with a chance level of 50%. Feature importance reflected disease-specific atrophy patterns. The multi-syndrome model reached accuracies of more than three times higher than chance level but was far from 100%. Multi-syndrome model performance was not homogenous across dementia syndromes, with better performance in syndromes characterized by regionally specific atrophy patterns. Whereas diseases generally could be classified vs controls more correctly with increasing severity and duration, differentiation between diseases was optimal in disease-specific windows of severity and duration. DISCUSSION: Results suggest that automated methods applied to MR imaging data can support physicians in diagnosis of dementia syndromes. It is particularly relevant for orphan diseases beside frequent syndromes such as Alzheimer's disease.

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YNIMG Journal 2021 Journal Article

Mapping grip force to motor networks

  • Ladina Weitnauer
  • Stefan Frisch
  • Lester Melie-Garcia
  • Martin Preisig
  • Matthias L. Schroeter
  • Ines Sajfutdinow
  • Ferath Kherif
  • Bogdan Draganski

AIM: There is ongoing debate about the role of cortical and subcortical brain areas in force modulation. In a whole-brain approach, we sought to investigate the anatomical basis of grip force whilst acknowledging interindividual differences in connectivity patterns. We tested if brain lesion mapping in patients with unilateral motor deficits can inform whole-brain structural connectivity analysis in healthy controls to uncover the networks underlying grip force. METHODS: Using magnetic resonance imaging (MRI) and whole-brain voxel-based morphometry in chronic stroke patients (n=55) and healthy controls (n=67), we identified the brain regions in both grey and white matter significantly associated with grip force strength. The resulting statistical parametric maps (SPMs) provided seed areas for whole-brain structural covariance analysis in a large-scale community dwelling cohort (n=977) that included beyond volume estimates, parameter maps sensitive to myelin, iron and tissue water content. RESULTS: The SPMs showed symmetrical bilateral clusters of correlation between upper limb motor performance, basal ganglia, posterior insula and cortico-spinal tract. The covariance analysis with the seed areas derived from the SPMs demonstrated a widespread anatomical pattern of brain volume and tissue properties, including both cortical, subcortical nodes of motor networks and sensorimotor areas projections. CONCLUSION: We interpret our covariance findings as a biological signature of brain networks implicated in grip force. The data-driven definition of seed areas obtained from chronic stroke patients showed overlapping structural covariance patterns within cortico-subcortical motor networks across different tissue property estimates. This cumulative evidence lends face validity of our findings and their biological plausibility.

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YNICL Journal 2019 Journal Article

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

  • Franziska Albrecht
  • Sandrine Bisenius
  • Jane Neumann
  • Jennifer Whitwell
  • Matthias L. Schroeter

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-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. 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. 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. CONCLUSIONS: Our 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.

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YNICL Journal 2019 Journal Article

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

  • Franziska Albrecht
  • Tommaso Ballarini
  • Jane Neumann
  • Matthias L. Schroeter

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.

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YNICL Journal 2019 Journal Article

Regional gray matter changes and age predict individual treatment response in Parkinson's disease

  • Tommaso Ballarini
  • Karsten Mueller
  • Franziska Albrecht
  • Filip Růžička
  • Ondrej Bezdicek
  • Evžen Růžička
  • Jan Roth
  • Josef Vymazal

We aimed at testing the potential of biomarkers in predicting individual patient response to dopaminergic therapy for Parkinson's disease. Treatment efficacy was assessed in 30 Parkinson's disease patients as motor symptoms improvement from unmedicated to medicated state as assessed by the Unified Parkinson's Disease Rating Scale score III. Patients were stratified into weak and strong responders according to the individual treatment response. A multiple regression was implemented to test the prediction accuracy of age, disease duration and treatment dose and length. Univariate voxel-based morphometry was applied to investigate differences between the two groups on age-corrected T1-weighted magnetic resonance images. Multivariate support vector machine classification was used to predict individual treatment response based on neuroimaging data. Among clinical data, increasing age predicted a weaker treatment response. Additionally, weak responders presented greater brain atrophy in the left temporoparietal operculum. Support vector machine classification revealed that gray matter density in this brain region, including additionally the supplementary and primary motor areas and the cerebellum, was able to differentiate weak and strong responders with 74% accuracy. Remarkably, age and regional gray matter density of the left temporoparietal operculum predicted both and independently treatment response as shown in a combined regression analysis. In conclusion, both increasing age and reduced gray matter density are valid and independent predictors of dopaminergic therapy response in Parkinson's disease.

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YNIMG Journal 2019 Journal Article

When less is more: Structural correlates of core executive functions in young adults – A VBM and cortical thickness study

  • Christopher M. Weise
  • Tobias Bachmann
  • Matthias L. Schroeter
  • Dorothee Saur

Background The term executive functions (EF) describes a set of higher cognitive abilities/skills needed for goal-oriented and flexible behavior. In contrast to a multitude of functional neuroimaging studies of EF performance, only limited and partially inconclusive data is available for the structural-neuroanatomical underpinnings of EFs, particularly in healthy adults. Methods Here, we applied voxel-based morphometry (VBM) and additional analyses of cortical thickness (CTH; via surface-based morphometry) to a large sample of healthy young adults from the Human Connectome Project (N = 1110; Age 28. 8 ± 3. 7 years) with structural MRI data and test data reflective of three core EFs [i. e. cognitive flexibility (CF), inhibitory control (IC) and working memory (WM)]. Results For CF and IC, VBM analyses yielded a distinct and largely overlapping pattern of exclusively negative associations (CF>IC), most prominently within the medial prefrontal cortex, the insular cortex, central/precentral regions, subcortical and mesotemporal structures. A similar, yet less pronounced pattern of negative associations was found in analyses of CTH. In contrast, both VBM and CTH analyses yielded no significant associations with WM performance. Conclusions Brain regions we found negatively associated with measures of CF and IC have been repeatedly highlighted by functional imaging studies of EF performance. The here observed inverse relationship with brain structural parameters may be related to the young age of our study population and well established neurobiological mechanisms of cortical maturation (i. e. cortical thinning via synaptic pruning and cortical myelination).

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YNICL Journal 2018 Journal Article

Brain connectivity changes when comparing effects of subthalamic deep brain stimulation with levodopa treatment in Parkinson's disease

  • Karsten Mueller
  • Robert Jech
  • Filip Růžička
  • Štefan Holiga
  • Tommaso Ballarini
  • Ondrej Bezdicek
  • Harald E. Möller
  • Josef Vymazal

Levodopa and, later, deep brain stimulation (DBS) have become the mainstays of therapy for motor symptoms associated with Parkinson's disease (PD). Although these therapeutic options lead to similar clinical outcomes, the neural mechanisms underlying their efficacy are different. Therefore, investigating the differential effects of DBS and levodopa on functional brain architecture and associated motor improvement is of paramount interest. Namely, we expected changes in functional brain connectivity patterns when comparing levodopa treatment with DBS. Clinical assessment and functional magnetic resonance imaging (fMRI) was performed before and after implanting electrodes for DBS in the subthalamic nucleus (STN) in 13 PD patients suffering from severe levodopa-induced motor fluctuations and peak-of-dose dyskinesia. All measurements were acquired in a within subject-design with and without levodopa treatment, and with and without DBS. Brain connectivity changes were computed using eigenvector centrality (EC) that offers a data-driven and parameter-free approach-similarly to Google's PageRank algorithm-revealing brain regions that have an increased connectivity to other regions that are highly connected, too. Both levodopa and DBS led to comparable improvement of motor symptoms as measured with the Unified Parkinson's Disease Rating Scale motor score (UPDRS-III). However, this similar therapeutic effect was underpinned by different connectivity modulations within the motor system. In particular, EC revealed a major increase of interconnectedness in the left and right motor cortex when comparing DBS to levodopa. This was accompanied by an increase of connectivity of these motor hubs with the thalamus and cerebellum. We observed, for the first time, significant functional connectivity changes when comparing the effects of STN DBS and oral levodopa administration, revealing different treatment-specific mechanisms linked to clinical benefit in PD. Specifically, in contrast to levodopa treatment, STN DBS was associated with increased connectivity within the cortico-thalamo-cerebellar network. Moreover, given the favorable effects of STN DBS on motor complications, the changes in the patients' clinical profile might also contribute to connectivity changes associated with STN-DBS. Understanding the observed connectivity changes may be essential for enhancing the effectiveness of DBS treatment, and for better defining the pathophysiology of the disrupted motor network in PD.

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YNIMG Journal 2018 Journal Article

White matter microstructural variability mediates the relation between obesity and cognition in healthy adults

  • Rui Zhang
  • Frauke Beyer
  • Leonie Lampe
  • Tobias Luck
  • Steffi G. Riedel-Heller
  • Markus Loeffler
  • Matthias L. Schroeter
  • Michael Stumvoll

Obesity has been linked with structural and functional brain changes. However, the impact of obesity on brain and cognition in aging remains debatable, especially for white matter. We therefore aimed to determine the effects of obesity on white matter microstructure and potential implications for cognition in a well-characterized large cohort of healthy adults. In total, 1255 participants (50% females, 19–80 years, BMI 16. 8–50. 2 kg/m2) with diffusion-weighted magnetic resonance imaging at 3T were analysed. Tract-based spatial statistics (TBSS) probed whether body mass index (BMI) and waist-to-hip ratio (WHR) were related to fractional anisotropy (FA). We conducted partial correlations and mediation analyses to explore whether obesity or regional FA were related to cognitive performance. Analyses were adjusted for demographic, genetic, and obesity-associated confounders. Results showed that higher BMI and higher WHR were associated with lower FA in multiple white matter tracts (p < 0. 05, FWE-corrected). Mediation analyses provided evidence for indirect negative effects of higher BMI and higher WHR on executive functions and processing speed through lower FA in fiber tracts connecting (pre)frontal, visual, and associative areas (indirect paths, |ß| ≥ 0. 01; 99% |CI| > 0). This large cross-sectional study showed that obesity is correlated with lower FA in multiple white matter tracts in otherwise healthy adults, independent of confounders. Moreover, although effect sizes were small, mediation results indicated that visceral obesity was linked to poorer executive functions and lower processing speed through lower FA in callosal and associative fiber tracts. Longitudinal studies are needed to support this hypothesis.

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YNICL Journal 2017 Journal Article

Predicting behavioral variant frontotemporal dementia with pattern classification in multi-center structural MRI data

  • Sebastian Meyer
  • Karsten Mueller
  • Katharina Stuke
  • Sandrine Bisenius
  • Janine Diehl-Schmid
  • Frank Jessen
  • Jan Kassubek
  • Johannes Kornhuber

PURPOSE: Frontotemporal lobar degeneration (FTLD) is a common cause of early onset dementia. Behavioral variant frontotemporal dementia (bvFTD), its most common subtype, is characterized by deep alterations in behavior and personality. In 2011, new diagnostic criteria were suggested that incorporate imaging criteria into diagnostic algorithms. The study aimed at validating the potential of imaging criteria to individually predict diagnosis with machine learning algorithms. MATERIALS & METHODS: Brain atrophy was measured with structural magnetic resonance imaging (MRI) at 3 Tesla in a multi-centric cohort of 52 bvFTD patients and 52 healthy control subjects from the German FTLD Consortium's Study. Beside group comparisons, diagnosis bvFTD vs. controls was individually predicted in each subject with support vector machine classification in MRI data across the whole brain or in frontotemporal, insular regions, and basal ganglia known to be mainly affected based on recent meta-analyses. Multi-center effects were controlled for with a new method, "leave one center out" conjunction analyses, i.e. repeatedly excluding subjects from each center from the analysis. RESULTS: Group comparisons revealed atrophy in, most consistently, the frontal lobe in bvFTD beside alterations in the insula, basal ganglia and temporal lobe. Most remarkably, support vector machine classification enabled predicting diagnosis in single patients with a high accuracy of up to 84.6%, where accuracy was highest in a region-of-interest approach focusing on frontotemporal, insular regions, and basal ganglia in comparison with the whole brain approach. CONCLUSION: Our study demonstrates that MRI, a widespread imaging technology, can individually identify bvFTD with high accuracy in multi-center imaging data, paving the road to personalized diagnostic approaches in the future.

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YNIMG Journal 2017 Journal Article

Predicting brain-age from multimodal imaging data captures cognitive impairment

  • Franziskus Liem
  • Gaël Varoquaux
  • Jana Kynast
  • Frauke Beyer
  • Shahrzad Kharabian Masouleh
  • Julia M. Huntenburg
  • Leonie Lampe
  • Mehdi Rahim

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19–82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4. 29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

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YNICL Journal 2017 Journal Article

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data

  • Sandrine Bisenius
  • Karsten Mueller
  • Janine Diehl-Schmid
  • Klaus Fassbender
  • Timo Grimmer
  • Frank Jessen
  • Jan Kassubek
  • Johannes Kornhuber

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with a very high accuracy paving the road for its application in clinical settings.

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YNIMG Journal 2015 Journal Article

Identifying neural correlates of visual consciousness with ALE meta-analyses

  • Sandrine Bisenius
  • Sabrina Trapp
  • Jane Neumann
  • Matthias L. Schroeter

Neural correlates of consciousness (NCC) have been a topic of study for nearly two decades. In functional imaging studies, several regions have been proposed to constitute possible candidates for NCC, but as of yet, no quantitative summary of the literature on NCC has been done. The question whether single (striate or extrastriate) regions or a network consisting of extrastriate areas that project directly to fronto-parietal regions are necessary and sufficient neural correlates for visual consciousness is still highly debated [e. g. , Rees et al. , 2002, Nat Rev. Neurosci 3, 261–270; Tong, 2003, Nat Rev. Neurosci 4, 219–229]. The aim of this work was to elucidate this issue and give a synopsis of the present state of the art by conducting systematic and quantitative meta-analyses across functional magnetic resonance imaging (fMRI) studies using several standard paradigms for conscious visual perception. In these paradigms, consciousness is operationalized via perceptual changes, while the visual stimulus remains invariant. An activation likelihood estimation (ALE) meta-analysis was performed, representing the best approach for voxel-wise meta-analyses to date. In addition to computing a meta-analysis across all paradigms, separate meta-analyses on bistable perception and masking paradigms were conducted to assess whether these paradigms show common or different NCC. For the overall meta-analysis, we found significant clusters of activation in inferior and middle occipital gyrus; fusiform gyrus; inferior temporal gyrus; caudate nucleus; insula; inferior, middle, and superior frontal gyri; precuneus; as well as in inferior and superior parietal lobules. These results suggest a subcortical-extrastriate-fronto-parietal network rather than a single region that constitutes the necessary NCC. The results of our exploratory paradigm-specific meta-analyses suggest that this subcortical-extrastriate-fronto-parietal network might be differentially activated as a function of the paradigms used to probe for NCC.

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YNIMG Journal 2015 Journal Article

Investigating the dynamics of the brain response to music: A central role of the ventral striatum/nucleus accumbens

  • Karsten Mueller
  • Thomas Fritz
  • Toralf Mildner
  • Maxi Richter
  • Katrin Schulze
  • Jöran Lepsien
  • Matthias L. Schroeter
  • Harald E. Möller

Ventral striatal activity has been previously shown to correspond well to reward value mediated by music. Here, we investigate the dynamic brain response to music and manipulated counterparts using functional magnetic resonance imaging (fMRI). Counterparts of musical excerpts were produced by either manipulating the consonance/dissonance of the musical fragments or playing them backwards (or both). Results show a greater involvement of the ventral striatum/nucleus accumbens both when contrasting listening to music that is perceived as pleasant and listening to a manipulated version perceived as unpleasant (backward dissonant), as well as in a parametric analysis for increasing pleasantness. Notably, both analyses yielded a ventral striatal response that was strongest during an early phase of stimulus presentation. A hippocampal response to the musical stimuli was also observed, and was largely mediated by processing differences between listening to forward and backward music. This hippocampal involvement was again strongest during the early response to the music. Auditory cortex activity was more strongly evoked by the original (pleasant) music compared to its manipulated counterparts, but did not display a similar decline of activation over time as subcortical activity. These findings rather suggest that the ventral striatal/nucleus accumbens response during music listening is strongest in the first seconds and then declines.

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YNICL Journal 2015 Journal Article

Resting-state functional magnetic resonance imaging of the subthalamic microlesion and stimulation effects in Parkinson's disease: Indications of a principal role of the brainstem

  • Štefan Holiga
  • Karsten Mueller
  • Harald E. Möller
  • Dušan Urgošík
  • Evžen Růžička
  • Matthias L. Schroeter
  • Robert Jech

During implantation of deep-brain stimulation (DBS) electrodes in the target structure, neurosurgeons and neurologists commonly observe a "microlesion effect" (MLE), which occurs well before initiating subthalamic DBS. This phenomenon typically leads to a transitory improvement of motor symptoms of patients suffering from Parkinson's disease (PD). Mechanisms behind MLE remain poorly understood. In this work, we exploited the notion of ranking to assess spontaneous brain activity in PD patients examined by resting-state functional magnetic resonance imaging in response to penetration of DBS electrodes in the subthalamic nucleus. In particular, we employed a hypothesis-free method, eigenvector centrality (EC), to reveal motor-communication-hubs of the highest rank and their reorganization following the surgery; providing a unique opportunity to evaluate the direct impact of disrupting the PD motor circuitry in vivo without prior assumptions. Penetration of electrodes was associated with increased EC of functional connectivity in the brainstem. Changes in connectivity were quantitatively related to motor improvement, which further emphasizes the clinical importance of the functional integrity of the brainstem. Surprisingly, MLE and DBS were associated with anatomically different EC maps despite their similar clinical benefit on motor functions. The DBS solely caused an increase in connectivity of the left premotor region suggesting separate pathophysiological mechanisms of both interventions. While the DBS acts at the cortical level suggesting compensatory activation of less affected motor regions, the MLE affects more fundamental circuitry as the dysfunctional brainstem predominates in the beginning of PD. These findings invigorate the overlooked brainstem perspective in the understanding of PD and support the current trend towards its early diagnosis.

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YNIMG Journal 2014 Journal Article

Impact of image acquisition on voxel-based-morphometry investigations of age-related structural brain changes

  • Daniel-Paolo Streitbürger
  • André Pampel
  • Gunnar Krueger
  • Jöran Lepsien
  • Matthias L. Schroeter
  • Karsten Mueller
  • Harald E. Möller

A growing number of magnetic resonance imaging studies employ voxel-based morphometry (VBM) to assess structural brain changes. Recent reports have shown that image acquisition parameters may influence VBM results. For systematic evaluation, gray-matter-density (GMD) changes associated with aging were investigated by VBM employing acquisitions with different radiofrequency head coils (12-channel matrix coil vs. 32-channel array), different pulse sequences (MP-RAGE vs. MP2RAGE), and different voxel dimensions (1mm vs. 0. 8mm). Thirty-six healthy subjects, classified as young, middle-aged, or elderly, participated in the study. Two-sample and paired t-tests revealed significant effects of acquisition parameters (coil, pulse sequence, and resolution) on the estimated age-related GMD changes in cortical and subcortical regions. Potential advantages in tissue classification and segmentation were obtained for MP2RAGE. The 32-channel coil generally outperformed the 12-channel coil, with more benefit for MP2RAGE. Further improvement can be expected from higher resolution if the loss in SNR is accounted for. Use of inconsistent acquisition parameters in VBM analyses is likely to introduce systematic bias. Overall, acquisition and protocol changes require careful adaptations of the VBM analysis strategy before generalized conclusion can be drawn.

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YNICL Journal 2013 Journal Article

Neural correlates of the DemTect in Alzheimer's disease and frontotemporal lobar degeneration – A combined MRI & FDG-PET study

  • Timo B. Woost
  • Juergen Dukart
  • Stefan Frisch
  • Henryk Barthel
  • Osama Sabri
  • Karsten Mueller
  • Matthias L. Schroeter

Valid screening devices are critical for an early diagnosis of dementia. The DemTect is such an internationally accepted tool. We aimed to characterize the neural networks associated with performance on the DemTect's subtests in two frequent dementia syndromes: early Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). Voxel-based group comparisons of cerebral glucose utilization (as measured by F-18-fluorodeoxyglucose positron emission tomography) and gray matter atrophy (as measured by structural magnetic resonance imaging) were performed on data from 48 subjects with AD (n = 21), FTLD (n = 14) or subjective cognitive impairment (n = 13) as a control group. We performed group comparisons and correlation analyses between multimodal imaging data and performance on the DemTect's subtests. Group comparisons showed regional patterns consistent with previous findings for AD and FTLD. Interestingly, atrophy dominated in FTLD, whereas hypometabolism in AD. Across diagnostic groups performance on the "wordlist" subtest was positively correlated with glucose metabolism in the left temporal lobe. The "number transcoding" subtest was significantly associated with glucose metabolism in both a predominantly left lateralized frontotemporal network and a parietooccipital network including parts of the basal ganglia. Moreover, this subtest was associated with gray matter density in an extensive network including frontal, temporal, parietal and occipital areas. No significant correlates were observed for the "supermarket task" subtest. Scores on the "digit span reverse" subtest correlated with glucose metabolism in the left frontal cortex, the bilateral putamen, the head of caudate nucleus and the anterior insula. Disease-specific correlation analyses could partly verify or extend the correlates shown in the analyses across diagnostic groups. Correlates of gray matter density were found in FTLD for the "number transcoding" subtest and the "digit span reverse" subtest. Correlates of glucose metabolism were found in AD for the "wordlist" subtest and in FTLD for the "digit span reverse" subtest. Our study contributes to the understanding of the neural correlates of cognitive deficits in AD and FTLD and supports an external validation of the DemTect providing preliminary conclusions about disease-specific correlates.

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YNICL Journal 2013 Journal Article

Relationship between imaging biomarkers, age, progression and symptom severity in Alzheimer's disease

  • Juergen Dukart
  • Karsten Mueller
  • Arno Villringer
  • Ferath Kherif
  • Bogdan Draganski
  • Richard Frackowiak
  • Matthias L. Schroeter

The early diagnostic value of glucose hypometabolism and atrophy as potential neuroimaging biomarkers of mild cognitive impairment (MCI) and Alzheimer's disease (AD) have been extensively explored using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (MRI). The vast majority of previous imaging studies neglected the effects of single factors, such as age, symptom severity or time to conversion in MCI thus limiting generalisability of results across studies. Here, we investigated the impact of these factors on metabolic and structural differences. FDG-PET and MRI data from AD patients (n = 80), MCI converters (n = 65) and MCI non-converters (n = 64) were compared to data of healthy subjects (n = 79). All patient groups were split into subgroups by age, time to conversion (for MCI), or symptom severity and compared to the control group. AD patients showed a strongly age-dependent pattern, with younger patients showing significantly more extensive reductions in gray matter volume and glucose utilisation. In the MCI converter group, the amount of glucose utilisation reduction was linked to the time to conversion but not to atrophy. Our findings indicate that FDG-PET might be more closely linked to future cognitive decline whilst MRI being more closely related to the current cognitive state reflects potentially irreversible damage.

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YNIMG Journal 2011 Journal Article

Investigating brain response to music: A comparison of different fMRI acquisition schemes

  • Karsten Mueller
  • Toralf Mildner
  • Thomas Fritz
  • Jöran Lepsien
  • Christian Schwarzbauer
  • Matthias L. Schroeter
  • Harald E. Möller

Functional magnetic resonance imaging (fMRI) in auditory experiments is a challenge, because the scanning procedure produces considerable noise that can interfere with the auditory paradigm. The noise might either mask the auditory material presented, or interfere with stimuli designed to evoke emotions because it sounds loud and rather unpleasant. Therefore, scanning paradigms that allow interleaved auditory stimulation and image acquisition appear to be advantageous. The sparse temporal sampling (STS) technique uses a very long repetition time in order to achieve a stimulus presentation in the absence of scanner noise. Although only relatively few volumes are acquired for the resulting data sets, there have been recent studies where this method has furthered remarkable results. A new development is the interleaved silent steady state (ISSS) technique. Compared with STS, this method is capable of acquiring several volumes in the time frame between the auditory trials (while the magnetization is kept in a steady state during stimulus presentation). In order to draw conclusions about the optimum fMRI procedure with auditory stimulation, different echo-planar imaging (EPI) acquisition schemes were compared: Continuous scanning, STS, and ISSS. The total acquisition time of each sequence was adjusted to about 12. 5min. The results indicate that the ISSS approach exhibits the highest sensitivity in detecting subtle activity in sub-cortical brain regions.

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YNIMG Journal 2010 Journal Article

Differential effects of global and cerebellar normalization on detection and differentiation of dementia in FDG-PET studies

  • Juergen Dukart
  • Karsten Mueller
  • Annette Horstmann
  • Barbara Vogt
  • Stefan Frisch
  • Henryk Barthel
  • Georg Becker
  • Harald E. Möller

FDG-PET ([18F]fluorodeoxyglucose positron emission tomography) is frequently used to improve the differential diagnosis of dementia. However, a fundamental methodological issue of the reference area for the intensity normalization procedure is still unsolved. Here, we systematically compared the two most commonly used normalization methods to the cerebral and to the cerebellar metabolic rate for glucose with regard to detection and differentiation of dementia syndromes. FDG-PET imaging was performed on 19 subjects with early Alzheimer's disease, 13 subjects with early frontotemporal lobar degeneration and 10 subjects complaining of memory impairment, which had not been confirmed by comprehensive clinical testing. Images were normalized to either the cerebral or the cerebellar metabolic rate for glucose. Differences in relative regional glucose metabolism were assessed by voxelwise comparison. Analysis using the two normalization procedures revealed remarkable differential effects. Whereas cerebellar normalization was superior in identifying dementia patients in comparison to control subjects, cerebral normalization showed better results for differential diagnosis between types of dementia. These effects were shown for both, Alzheimer's disease and frontotemporal lobar degeneration. Relative hypermetabolism in comparison to the control group was only detected in both kinds of dementia using global normalization. The results indicate that normalization has a decisive impact on diagnostic accuracy in dementia. While cerebellar normalization seems to be more sensitive for early diagnosis, cerebral global normalization might be superior for differential diagnostic purposes in dementia syndromes.

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YNIMG Journal 2009 Journal Article

Neural correlates of Alzheimer's disease and mild cognitive impairment: A systematic and quantitative meta-analysis involving 1351 patients

  • Matthias L. Schroeter
  • Timo Stein
  • Nina Maslowski
  • Jane Neumann

Alzheimer's disease is the most common form of dementia. Its prodromal stage amnestic mild cognitive impairment is characterized by deficits of anterograde episodic memory. The development of standardized imaging inclusion criteria has to be regarded as a prerequisite for future diagnostic systems. Moreover, successful treatment requires isolating imaging markers predicting the disease. Accordingly, we conducted a systematic and quantitative meta-analysis to reveal the prototypical neural correlates of Alzheimer's disease and its prodromal stage. To prevent any a priori assumptions and enable a data-driven approach only studies applying quantitative automated whole brain analysis were included. Finally, 40 studies were identified involving 1351 patients and 1097 healthy control subjects reporting either atrophy or decreases in glucose utilization and perfusion. The currently most sophisticated and best-validated of coordinate-based voxel-wise meta-analyses was applied (anatomical likelihood estimates). The meta-analysis reveals that early Alzheimer's disease affects structurally the (trans-)entorhinal and hippocampal regions, functionally the inferior parietal lobules and precuneus. Results further may suggest that atrophy in the (trans-)entorhinal area/hippocampus and hypometabolism/hypoperfusion in the inferior parietal lobules predicts most reliably the progression from amnestic mild cognitive impairment to Alzheimer's disease, whereas changes in the posterior cingulate cortex and precuneus are unspecific. Fully developed Alzheimer's disease involved additionally a frontomedian-thalamic network. In conclusion, the meta-analysis characterizes the prototypical neural substrates of Alzheimer's disease and its prodromal stage amnestic mild cognitive impairment. By isolating predictive markers it enables successful treatment strategies in the future and contributes to standardized imaging inclusion criteria for Alzheimer's disease as suggested for future diagnostic systems.

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YNIMG Journal 2007 Journal Article

Neurovascular coupling is impaired in cerebral microangiopathy—An event-related Stroop study

  • Matthias L. Schroeter
  • Simone Cutini
  • Margarethe M. Wahl
  • Rainer Scheid
  • D. Yves von Cramon

Small-vessel disease or cerebral microangiopathy is a common finding in elderly people leading finally to subcortical ischemic vascular dementia. Because cerebral microangiopathy impairs vascular reactivity and affects mainly the frontal lobes, we hypothesized that brain activation decreases during an event-related color–word matching Stroop task. 12 patients suffering from cerebral microangiopathy were compared with 12 age-matched controls. As an imaging method we applied functional near-infrared spectroscopy, because it is particularly sensitive to the microvasculature. The Stroop task led to activations in the lateral prefrontal cortex. Generally, the amplitude of the hemodynamic response was reduced in patients in tight correlation with behavioral slowing during the Stroop task and with neuropsychological deficits, namely attentional and executive dysfunction. Interestingly, patients showed an early deoxygenation of blood right after stimulation onset, and a delay of the hemodynamic response. Whereas the amplitude of the hemodynamic response is reduced in the frontal lobes also with normal aging, data suggest that impairments of neurovascular coupling are specific for cerebral microangiopathy. In summary, our findings indicate frontal dysfunction and impairments of neurovascular coupling in cerebral microangiopathy.

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YNIMG Journal 2007 Journal Article

Towards a nosology for frontotemporal lobar degenerations—A meta-analysis involving 267 subjects

  • Matthias L. Schroeter
  • Karolina Raczka
  • Jane Neumann
  • D. Yves von Cramon

Frontotemporal lobar degeneration is the second most common diagnosis of dementia in individuals younger than 65 years. We conducted a systematic and quantitative meta-analysis to examine neural correlates of frontotemporal lobar degeneration and its subtypes and to place the disease in a framework of cognitive neuropsychiatry. MedLine and Current Contents search engines were used to identify functional and anatomical imaging studies investigating frontotemporal lobar degeneration between 1980 and 2005. Studies were included, if they were peer-reviewed, applied internationally recognized diagnostic criteria, were original studies, and had results normalized to a stereotactic space. 19 studies were identified reporting either atrophy or decreases in glucose utilization. Finally, the analysis involved 267 subjects suffering from frontotemporal lobar degeneration and 351 control subjects. A quantitative meta-analysis was performed. Maxima of the studies resulted in activation likelihood estimates. The meta-analysis revealed specific neural networks for each of the three clinically defined subtypes of frontotemporal lobar degeneration, namely frontotemporal dementia, semantic dementia, and progressive non-fluent aphasia. Networks did not overlap as shown by a conjunction analysis, and they corresponded to clinical characteristics. The study relates the clinical features of each subtype of frontotemporal lobar degeneration specifically to its neural substrate. By ‘triple dissociating’ frontotemporal lobar degenerations into three clinicoanatomical prototypes, the study contributes to placing these disorders in cognitive neuropsychiatry and suggests a respective nosology.

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YNIMG Journal 2006 Journal Article

Investigating the post-stimulus undershoot of the BOLD signal—a simultaneous fMRI and fNIRS study

  • Matthias L. Schroeter
  • Thomas Kupka
  • Toralf Mildner
  • Kâmil Uludağ
  • D. Yves von Cramon

Measuring the hemodynamic response with functional magnetic resonance imaging (fMRI) together with functional near-infrared spectroscopy (fNIRS) may overcome limitations of single-method approaches. Accordingly, we measured the event-related hemodynamic response with both imaging methods simultaneously in young subjects during visual stimulation. An intertrial interval of 60 s was chosen to include the prolonged post-stimulus undershoot of the blood oxygenation level dependent (BOLD) signal. During visual stimulation, the BOLD signal, oxy-, and total hemoglobin (Hb) increased, whereas deoxy-Hb decreased. The post-stimulus period was characterized by an undershoot of the BOLD signal, oxy-Hb, and an overshoot of deoxy-Hb. Total Hb as measured by fNIRS returned to baseline immediately after the end of stimulation. Results suggest that the post-stimulus events as measured by fNIRS are dominated by a prolonged high-level oxygen consumption in the microvasculature. The contribution of a delayed return of blood volume to the BOLD post-stimulus undershoot in post-capillary veins as suggested by the Balloon and Windkessel models remains ambiguous. Temporal changes in the BOLD signal were highly correlated with deoxy-Hb, with lower correlation values for oxy- and total Hb. Furthermore, data show that fNIRS covers the outer 1 cm of the brain cortex. These results were confirmed by simultaneous fMRI/fNIRS measurements during rest. In conclusion, multimodal imaging approaches may contribute to the understanding of neurovascular coupling.

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YNIMG Journal 2004 Journal Article

Prefrontal activation due to Stroop interference increases during development—an event-related fNIRS study

  • Matthias L. Schroeter
  • Stefan Zysset
  • Margarethe Wahl
  • D.Yves von Cramon

Although it is well known that executive processes supported by the frontal lobe develop during childhood and adolescence, only one functional imaging study has used the Stroop task to investigate the relationship between frontal lobe function and cognition from a developmental point of view. Hence, we measured brain activation in the lateral prefrontal cortex of children with functional near-infrared imaging during an event-related, color–word matching Stroop task and compared results with a previous study, conducted with the same paradigm in adults. In children, the Stroop task elicited significant brain activation in the left lateral prefrontal cortex comparable to adults. However, the hemodynamic response occurred later in children than adults. Individual brain activation due to Stroop interference varied much more in children than adults, which was paralleled by a higher behavioral variance in children. Data suggest that children differed in their individual cognitive development independent of their chronological age more than adults. Brain activation due to Stroop interference increased with age in the dorsolateral prefrontal cortex in correlation with an improvement of behavioral performance. In conclusion, our results indicate that neuromaturational processes regarding resolution of Stroop interference may depend on increased ability to recruit frontal neural resources.

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v2026.09.13