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Karsten Mueller

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22 papers

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YNICL Journal 2026 Journal Article

Altered functional connectivity related to prepulse inhibition in functional movement disorder

David Voženílek
Karsten Mueller
Tereza Serranová
Lucia Nováková
Manuela Vaněčková
Petr Sojka

BACKGROUND: Functional neurological disorder (FND) is increasingly understood as a multinetwork disorder. Deficits in subcortical sensorimotor gating, indexed by reduced prepulse inhibition (PPI) of the startle reflex, are reported in FND and may reflect impaired filtering and contextual weighting of sensory input. However, the neural correlates linking impaired gating to intrinsic network dysfunction remain unclear. METHODS: We examined the relationship between PPI and resting-state functional connectivity in 38 patients with functional movement disorder (FMD) and 39 healthy controls (HC). PPI of the blink reflex was assessed using a standardized neurophysiological paradigm, and seed-based connectivity (SBC) analyses were performed in CONN toolbox using the default atlas comprising cortical and subcortical regions across the whole brain. To investigate a potential interaction between group and PPI size, we tested whether associations between PPI and SBC differed between FMD and HC groups. RESULTS: FMD patients exhibited significantly reduced PPI compared to HCs. Across several seeds-the left insular cortex, right supramarginal gyrus and bilateral anterior insula-significant Group × PPI interactions emerged in bilateral temporoparietal junction (TPJ). In HCs, higher PPI was associated with stronger connectivity between the insula and TPJ and between bilateral TPJ regions. These relationships were absent in FMD patients. CONCLUSIONS: Our findings demonstrate that effective sensorimotor gating depends on intact functional coupling within insula-TPJ circuits, key nodes of the salience and ventral attention networks. Disrupted modulation of this network in FMD suggests impaired top-down filtering of sensory information, providing a mechanistic link between sensory processing deficits and aberrant salience-network dynamics in FMD.

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.

YNICL Journal 2025 Journal Article

Short-term BCI intervention enhances functional brain connectivity associated with motor performance in chronic stroke

Khosrov A. Grigoryan
Karsten Mueller
Matthias Wagner
Diaa Masri
Kerrin J. Pine
Arno Villringer
Bernhard Sehm

BACKGROUND: Evidence suggests that brain-computer interface (BCI)-based rehabilitation strategies show promise in overcoming the limited recovery potential in the chronic phase of stroke. However, the specific mechanisms driving motor function improvements are not fully understood. OBJECTIVE: We aimed at elucidating the potential functional brain connectivity changes induced by BCI training in participants with chronic stroke. METHODS: A longitudinal crossover design was employed with two groups of participants over the span of 4 weeks to allow for within-subject (n = 21) and cross-group comparisons. Group 1 (n = 11) underwent a 6-day motor imagery-based BCI training during the second week, whereas Group 2 (n = 10) received the same training during the third week. Before and after each week, both groups underwent resting state functional MRI scans (4 for Group 1 and 5 for Group 2) to establish a baseline and monitor the effects of BCI training. RESULTS: Following BCI training, an increased functional connectivity was observed between the medial prefrontal cortex of the default mode network (DMN) and motor-related areas, including the premotor cortex, superior parietal cortex, SMA, and precuneus. Moreover, these changes were correlated with the increased motor function as confirmed with upper-extremity Fugl-Meyer assessment scores, measured before and after the training. CONCLUSIONS: Our findings suggest that BCI training can enhance brain connectivity, underlying the observed improvements in motor function. They provide a basis for developing novel rehabilitation approaches using non-invasive brain stimulation for targeting functionally relevant brain regions, thereby augmenting BCI-induced neuroplasticity and enhancing motor recovery.

YNICL Journal 2025 Journal Article

Sweet spot for resting-state functional MRI effect of deep brain stimulation in dystonia lies in the lower pallidal area

Pavel Filip
Andrej Lasica
Dimitra Kiakou
Karsten Mueller
Jiří Keller
Dušan Urgošík
Daniel Novák
Robert Jech

INTRODUCTION: Deep brain stimulation (DBS) of the internal globus pallidus (GPi) is a well-established, effective treatment for dystonia. Substantial variability of therapeutic success has been the one of the drivers of an ongoing debate about proper stimulation site and settings, with several indications of the notional sweet spot pointing to the lower GPi or even subpallidal area. METHODS: The presented patient-blinded, random-order study with cross-sectional verification against healthy controls enrolled 17 GPi DBS idiopathic, cervical or generalised dystonia patients to compare the effect of the stimulation in the upper and lower GPi area, with the focus on sensorimotor network connectivity and local activity measured using functional magnetic resonance. RESULTS: Stimulation brought both these parameters to levels closer to the state detected in healthy controls. This effect was much more pronounced during the stimulation in the lower GPi area or beneath it than in slightly higher positions, with stimulation-related changes detected by both metrics of interest in the sensorimotor cortex, striatum, thalamus and cerebellum. CONCLUSIONS: All in all, this study not only replicated the results of previous studies on GPi DBS as a modality restoring sensorimotor network connectivity and local activity in dystonia towards the levels in healthy population, but also showed that lower GPi area or even subpallidal structures, be it white matter or even small, but essential nodes in the zona incerta as nucleus basalis of Meynert, are important regions to consider when programming DBS in dystonia patients.

YNICL Journal 2024 Journal Article

Structural and microstructural predictors of cognitive decline in deep brain stimulation of subthalamic nucleus in Parkinson’s disease

Pavel Filip
Josef Mana
Andrej Lasica
Jiří Keller
Dušan Urgošík
Jaromír May
Karsten Mueller
Robert Jech

BACKGROUND AND OBJECTIVES: The intricate relationship between deep brain stimulation (DBS) in Parkinson's disease (PD) and cognitive impairment has lately garnered substantial attention. The presented study evaluated pre-DBS structural and microstructural cerebral patterns as possible predictors of future cognitive decline in PD DBS patients. METHODS: Pre-DBS MRI data in 72 PD patients were combined with neuropsychological examinations and follow-up for an average of 2.3 years after DBS implantation procedure using a screening cognitive test validated for diagnosis of mild cognitive impairment in PD in a Czech population - Dementia Rating Scale 2. RESULTS: PD patients who would exhibit post-DBS cognitive decline were found to have, already at the pre-DBS stage, significantly lower cortical thickness and lower microstructural complexity than cognitively stable PD patients. Differences in the regions directly related to cognition as bilateral parietal, insular and cingulate cortices, but also occipital and sensorimotor cortex were detected. Furthermore, hippocampi, putamina, cerebellum and upper brainstem were implicated as well, all despite the absence of pre-DBS differences in cognitive performance and in the position of DBS leads or stimulation parameters between the two groups. CONCLUSIONS: Our findings indicate that the cognitive decline in the presented PD cohort was not attributable primarily to DBS of the subthalamic nucleus but was associated with a clinically silent structural and microstructural predisposition to future cognitive deterioration present already before the DBS system implantation.

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.

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.

YNIMG Journal 2023 Journal Article

Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill

Katja I. Paul
Karsten Mueller
Paul-Noel Rousseau
Annegret Glathe
Niels A. Taatgen
Fokie Cnossen
Peter Lanzer
Arno Villringer

Performing endovascular medical interventions safely and efficiently requires a diverse set of skills that need to be practised in dedicated training sessions. Here, we used multimodal magnetic resonance (MR) imaging to determine the structural and functional plasticity and core skills associated with skill acquisition. A training group learned to perform a simulator-based endovascular procedure, while a control group performed a simplified version of the task; multimodal MR images were acquired before and after training. Using a well-controlled interaction design, we found strong multimodal evidence for the role of the intraparietal sulcus (IPS) in endovascular skill acquisition that is in line with previous work implicating the structure in visuospatial transformations including simple visuo-motor and mental rotation tasks. Our results provide a unique window into the multimodal nature of rapid structural and functional plasticity of the human brain while learning a multifaceted and complex clinical skill. Further, our results provide a detailed description of the plasticity process associated with endovascular skill acquisition and highlight specific facets of skills that could enhance current medical pedagogy and be useful to explicitly target during clinical resident training.

YNICL Journal 2022 Journal Article

Symptom-severity-related brain connectivity alterations in functional movement disorders

Karsten Mueller
Filip Růžička
Matěj Slovák
Zuzana Forejtová
Petr Dušek
Pavel Dušek
Robert Jech
Tereza Serranová

BACKGROUND: Functional movement disorders, a common cause of neurological disabilities, can occur with heterogeneous motor manifestations including functional weakness. However, the underlying mechanisms related to brain function and connectivity are unknown. OBJECTIVE: To identify brain connectivity alterations related to functional weakness we assessed network centrality changes in a group of patients with heterogeneous motor manifestations using task-free functional MRI in combination with different network centrality approaches. METHODS: Task-free functional MRI was performed in 48 patients with heterogeneous motor manifestations including 28 patients showing functional weakness and 65 age- and sex-matched healthy controls. Functional connectivity differences were assessed using different network centrality approaches, i.e. global correlation, eigenvector centrality, and intrinsic connectivity. Motor symptom severity was assessed using The Simplified Functional Movement Disorders Rating Scale and correlated with network centrality. RESULTS: Comparing patients with and without functional weakness showed significant network centrality differences in the left temporoparietal junction and precuneus. Patients with functional weakness showed increased centrality in the same anatomical regions when comparing functional weakness with healthy controls. Moreover, in the same regions, patients with functional weakness showed a positive correlation between motor symptom severity and network centrality. This correlation was shown to be specific to functional weakness with an interaction analysis, confirming a significant difference between patients with and without functional weakness. CONCLUSIONS: We identified the temporoparietal junction and precuneus as key regions involved in brain connectivity alterations related to functional weakness. We propose that both regions may be promising targets for phenotype-specific non-invasive brain stimulation.

YNICL Journal 2020 Journal Article

Disentangling brain functional network remodeling in corticobasal syndrome – A multimodal MRI study

Tommaso Ballarini
Franziska Albrecht
Karsten Mueller
Robert Jech
Janine Diehl-Schmid
Klaus Fliessbach
Jan Kassubek
Martin Lauer

OBJECTIVE: The clinical diagnosis of corticobasal syndrome (CBS) represents a challenge for physicians and reliable diagnostic imaging biomarkers would support the diagnostic work-up. We aimed to investigate the neural signatures of CBS using multimodal T1-weighted and resting-state functional magnetic resonance imaging (MRI). METHODS: Nineteen patients with CBS (age 67.0 ± 6.0 years; mean±SD) and 19 matched controls (66.5 ± 6.0) were enrolled from the German Frontotemporal Lobar Degeneration Consortium. Changes in functional connectivity and structure were respectively assessed with eigenvector centrality mapping complemented by seed-based analysis and with voxel-based morphometry. In addition to mass-univariate statistics, multivariate support vector machine (SVM) classification tested the potential of multimodal MRI to differentiate patients and controls. External validity of SVM was assessed on independent CBS data from the 4RTNI database. RESULTS: A decrease in brain interconnectedness was observed in the right central operculum, middle temporal gyrus and posterior insula, while widespread connectivity increases were found in the anterior cingulum, medial superior-frontal gyrus and in the bilateral caudate nuclei. Severe and diffuse gray matter volume reduction, especially in the bilateral insula, putamen and thalamus, characterized CBS. SVM classification revealed that both connectivity (area under the curve 0.81) and structural abnormalities (0.80) distinguished CBS from controls, while their combination led to statistically non-significant improvement in discrimination power, questioning the additional value of functional connectivity over atrophy. SVM analyses based on structural MRI generalized moderately well to new data, which was decisively improved when guided by meta-analytically derived disease-specific regions-of-interest. CONCLUSIONS: Our data-driven results show impairment of functional connectivity and brain structure in CBS and explore their potential as imaging biomarkers.

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.

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.

YNICL Journal 2017 Journal Article

General and selective brain connectivity alterations in essential tremor: A resting state fMRI study

Karsten Mueller
Robert Jech
Martina Hoskovcová
Olga Ulmanová
Dušan Urgošík
Josef Vymazal
Evžen Růžička

Although essential tremor is the most common movement disorder, there is little knowledge about the pathophysiological mechanisms of this disease. Therefore, we explored brain connectivity based on slow spontaneous fluctuations of blood oxygenation level dependent (BOLD) signal in patients with essential tremor (ET). A cohort of 19 ET patients and 23 healthy individuals were scanned in resting condition using functional magnetic resonance imaging (fMRI). General connectivity was assessed by eigenvector centrality (EC) mapping. Selective connectivity was analyzed by correlations of the BOLD signal between the preselected seed regions and all the other brain areas. These measures were then correlated with the tremor severity evaluated by the Fahn-Tolosa-Marin Tremor Rating Scale (FTMTS). Compared to healthy subjects, ET patients were found to have lower EC in the cerebellar hemispheres and higher EC in the anterior cingulate and in the primary motor cortices bilaterally. In patients, the FTMTS score correlated positively with the EC in the putamen. In addition, the FTMTS score correlated positively with selective connectivity between the thalamus and other structures (putamen, pre-supplementary motor area (pre-SMA), parietal cortex), and between the pre-SMA and the putamen. We observed a selective coupling between a number of areas in the sensorimotor network including the basal ganglia and the ventral intermediate nucleus of thalamus, which is widely used as neurosurgical target for tremor treatment. Finally, ET was marked by suppression of general connectivity in the cerebellum, which is in agreement with the concept of ET as a disorder with cerebellar damage.

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.

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.

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.

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.

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.

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.

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.

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.

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.