1,720,963 research outputs found
Dissecting neural correlates of theory of mind and executive functions in behavioral variant frontotemporal dementia
Get PDFBehavioral variant frontotemporal dementia (bvFTD) is characterized by profound and early deficits in social cognition (SC) and executive functions (EF). To date it remains unclear whether deficits of the respective cognitive domains are based on the degeneration of distinct brain regions. In 103 patients with a diagnosis of bvFTD (possible/probable/definite: N = 40/58/5) from the frontotemporal lobar degeneration (FTLD) consortium Germany cohort (age 62.5±9.4 years, gender 38 female/65 male) we applied multimodal structural imaging, i.e. voxel-based morphometry, cortical thickness (CTH) and networks of structural covariance via source based morphometry. We cross-sectionally investigated associations with performance in a modified Reading the Mind in the Eyes Test (RMET; reflective of theory of mind - ToM) and five different tests reflective of EF (i.e. Hamasch-Five-Point Test, semantic and phonemic Fluency, Trail Making Test, Stroop interference). Finally, we investigated the conjunction of RMET correlates with functional networks commonly associated with SC respectively ToM and EF as extracted meta-analytically within the Neurosynth database. RMET performance was mainly associated with gray matter volume (GMV) and CTH within temporal and insular cortical regions and less within the prefrontal cortex (PFC), whereas EF performance was mainly associated with prefrontal regions (GMV and CTH). Overlap of RMET and EF associations was primarily located within the insula, adjacent subcortical structures (i.e. putamen) and the dorsolateral PFC (dlPFC). These patterns were more pronounced after adjustment for the respective other cognitive domain. Corroborative results were obtained in analyses of structural covariance networks. Overlap of RMET with meta-analytically extracted functional networks commonly associated with SC, ToM and EF was again primarily located within the temporal and insular region and the dlPFC. In addition, on a meta-analytical level, strong associations were found for temporal cortical RMET correlates with SC and ToM in particular. These data indicate a temporo-frontal dissociation of bvFTD related disturbances of ToM and EF, with atrophy of the anterior temporal lobe being critically involved in ToM deficits. The consistent overlap within the insular cortex may be attributable to the multimodal and integrative role of this region in socioemotional and cognitive processing
Neurofilaments and progranulin are related to atrophy in frontotemporal lobar degeneration – A transdiagnostic study cross‐validating atrophy and fluid biomarkers
Get PDFIntroduction: Frontotemporal lobar degeneration (FTLD) encompasses behavioral variant frontotemporal dementia (bvFTD), progressive supranuclear palsy, corticobasal syndrome/degeneration, and primary progressive aphasias (PPAs). We cross-validated fluid biomarkers and neuroimaging.Methods: Seven fluid biomarkers from cerebrospinal fluid and serum were related to atrophy in 428 participants including these FTLD subtypes, logopenic variant PPA (lvPPA), Alzheimer's disease (AD), and healthy subjects. Atrophy was assessed by structural magnetic resonance imaging and atlas-based volumetry.Results: FTLD subtypes, lvPPA, and AD showed specific profiles for neurofilament light chain, phosphorylated heavy chain, tau, phospho-tau, amyloid beta1-42 from serum/cerebrospinal fluid, and brain atrophy. Neurofilaments related to regional atrophy in bvFTD, whereas progranulin was associated with atrophy in semantic variant PPA. Ubiquitin showed no effects.Discussion: Results specify biomarker and atrophy patterns in FTLD and AD supporting differential diagnosis. They identify neurofilaments and progranulin in interaction with structural imaging as promising candidates for monitoring disease progression and therapy.Highlights: Study cross-validated neuroimaging and fluid biomarkers in dementia. Five kinds of frontotemporal lobar degeneration and two variants of Alzheimer's disease. Study identifies disease-specific fluid biomarker and atrophy profiles. Fluid biomarkers and atrophy interact in a disease-specific way. Neurofilaments and progranulin are proposed as biomarkers for diagnosis and therapy
Criminal behavior in frontotemporal dementia: A multimodal MRI study
Get PDFThe behavioral variant of frontotemporal dementia (bvFTD) is related to a variety of social misbehaviors, including criminal behavior (CB) due to deep changes in cognition, behavior, and personality. Recent work suggests that impairment in emotional processing, along with disinhibition, constitutes the necessary elements for CB in bvFTD. However, the underlying neurobiological mechanisms are still unclear. Therefore, we aim at investigating structural and functional brain changes related to CB in bvFTD using magnetic resonance imaging (MRI) with the German Consortium for Frontotemporal Lobar Degeneration (FTLD). Our study comprised 87 patients with bvFTD and 26 healthy controls recruited within different locations of the FTLD Consortium. A subset of 21 patients with bvFTD showed CB, including theft, physical violence, sexual assault, drug abuse, and violations against traffic law. Voxel-based morphometry was performed, generating gray matter density (GMD) images obtained from high-resolution T1-weighted MR images. In addition, surface-based morphometry was performed by reconstruction of cortical thickness using a projection-based thickness approach. Both GMD and cortical thickness were further analyzed in order to detect group differences between bvFTD with and without CB. Resting-state functional MRI was available for a subgroup of 56 patients with bvFTD, including 16 patients showing CB. On a behavioral level, CB in bvFTD was associated with a higher frequency of disinhibition, lower frequency of apathy, and better performance in verbal fluency. Comparing bvFTD with and without CB, we obtained reduced GMD and reduced cortical thickness in the temporal lobe, predominantly in the left hemisphere. Impairment in brain structure was correlated with the Frontal Systems Behavior Scale, particularly with disinhibition, in the left superior temporal gyrus in interaction with CB in bvFTD. Investigating functional MRI data, CB was associated with significant functional brain dysconnectivity, particularly between the left anterior superior temporal gyrus and widely distributed cortical regions, including areas in the vicinity of the precentral sulcus and the inferior frontal junction, related to executive functions. Our study revealed structural and functional brain differences between bvFTD with and without CB, showing CB-related reduced GMD and cortical thickness in the left temporal lobe, indicating disinhibition as the main driver for CB. Interestingly, brain degeneration in the temporal lobe is discussed with CB in bvFTD in the current literature, dominantly affecting the right hemisphere. Our study investigates specifically the neural correlates of CB in bvFTD with MRI, modifying this view. Further work is necessary to shed more light on the role of the temporal lobe in bvFTD with CB
Structural correlates of language processing in primary progressive aphasia
Get PDFUnderstanding the relationships between brain structure and language behavior in primary progressive aphasia provides crucial information about these diseases’ pathomechanisms. However, previous investigations have been limited from providing a statistically reliable view of broad language abilities by sample size, variant focus, and task focus. In this study, the authors aimed to determine the relationship between brain structure and language behavior in primary progressive aphasia, to determine the degree to which task-associated regions were atrophied across disease variants, and to determine the degree to which task-related atrophy overlaps across disease variants. Participants were 118 primary progressive aphasia patients and 61 healthy, age-matched controls tested from 2011 to 2018 in the German Consortium for Frontotemporal Lobar Degeneration cohort. Diagnosis of primary progressive aphasia required progressive deterioration of mainly speech and language for ≥ 2 years, and variant was diagnosed by the criteria of Gorno-Tempini et al.2 Twenty-one participants not fulfilling a specific subtype were classified as mixed-variant and excluded. Language tasks of interest included the Boston Naming Test, a German adaptation of the Repeat and Point task, phonemic and category fluency tasks, and the reading/writing subtest of the Aachen Aphasia Test. Brain structure was measured by cortical thickness. We observed networks of language task-associated temporal, frontal, and parietal cortex. Overlapping task-associated atrophy was observed in the left lateral, ventral, and medial temporal lobe, middle and superior frontal gyrus, supramarginal gyrus, and insula. Some regions, primarily in the perisylvian region were associated with language behavior despite showing no significant atrophy. The results crucially extend less powerful studies associating brain and language measures in primary progressive aphasia. Cross-variant atrophy in task-associated regions suggests partially shared underlying deficits, whereas unique atrophy reinforces variant-specific deficits. Language task-related regions that are not obviously atrophied suggest regions of future network disruption and encourage understanding of task deficits beyond clearly atrophied cortex. These results may pave the way for new treatment approaches
Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging
Get PDFIntroductionDementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI).MethodsAtlas-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).ResultsThe 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.DiscussionResults 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
Neurofilaments and progranulin are related to atrophy in frontotemporal lobar degeneration – A transdiagnostic study cross‐validating atrophy and fluid biomarkers
No full textAbstract INTRODUCTION Frontotemporal lobar degeneration (FTLD) encompasses behavioral variant frontotemporal dementia (bvFTD), progressive supranuclear palsy, corticobasal syndrome/degeneration, and primary progressive aphasias (PPAs). We cross‐validated fluid biomarkers and neuroimaging. METHODS Seven fluid biomarkers from cerebrospinal fluid and serum were related to atrophy in 428 participants including these FTLD subtypes, logopenic variant PPA (lvPPA), Alzheimer's disease (AD), and healthy subjects. Atrophy was assessed by structural magnetic resonance imaging and atlas‐based volumetry. RESULTS FTLD subtypes, lvPPA, and AD showed specific profiles for neurofilament light chain, phosphorylated heavy chain, tau, phospho‐tau, amyloid beta 1‐42 from serum/cerebrospinal fluid, and brain atrophy. Neurofilaments related to regional atrophy in bvFTD, whereas progranulin was associated with atrophy in semantic variant PPA. Ubiquitin showed no effects. DISCUSSION Results specify biomarker and atrophy patterns in FTLD and AD supporting differential diagnosis. They identify neurofilaments and progranulin in interaction with structural imaging as promising candidates for monitoring disease progression and therapy. Highlights Study cross‐validated neuroimaging and fluid biomarkers in dementia. Five kinds of frontotemporal lobar degeneration and two variants of Alzheimer's disease. Study identifies disease‐specific fluid biomarker and atrophy profiles. Fluid biomarkers and atrophy interact in a disease‐specific way. Neurofilaments and progranulin are proposed as biomarkers for diagnosis and therapy
Criminal Behavior in Frontotemporal Dementia: A Multimodal MRI Study
No full textABSTRACT The behavioral variant of frontotemporal dementia (bvFTD) is related to a variety of social misbehaviors, including criminal behavior (CB) due to deep changes in cognition, behavior, and personality. Recent work suggests that impairment in emotional processing, along with disinhibition, constitutes the necessary elements for CB in bvFTD. However, the underlying neurobiological mechanisms are still unclear. Therefore, we aim at investigating structural and functional brain changes related to CB in bvFTD using magnetic resonance imaging (MRI) with the German Consortium for Frontotemporal Lobar Degeneration (FTLD). Our study comprised 87 patients with bvFTD and 26 healthy controls recruited within different locations of the FTLD Consortium. A subset of 21 patients with bvFTD showed CB, including theft, physical violence, sexual assault, drug abuse, and violations against traffic law. Voxel‐based morphometry was performed, generating gray matter density (GMD) images obtained from high‐resolution T1‐weighted MR images. In addition, surface‐based morphometry was performed by reconstruction of cortical thickness using a projection‐based thickness approach. Both GMD and cortical thickness were further analyzed in order to detect group differences between bvFTD with and without CB. Resting‐state functional MRI was available for a subgroup of 56 patients with bvFTD, including 16 patients showing CB. On a behavioral level, CB in bvFTD was associated with a higher frequency of disinhibition, lower frequency of apathy, and better performance in verbal fluency. Comparing bvFTD with and without CB, we obtained reduced GMD and reduced cortical thickness in the temporal lobe, predominantly in the left hemisphere. Impairment in brain structure was correlated with the Frontal Systems Behavior Scale, particularly with disinhibition, in the left superior temporal gyrus in interaction with CB in bvFTD. Investigating functional MRI data, CB was associated with significant functional brain dysconnectivity, particularly between the left anterior superior temporal gyrus and widely distributed cortical regions, including areas in the vicinity of the precentral sulcus and the inferior frontal junction, related to executive functions. Our study revealed structural and functional brain differences between bvFTD with and without CB, showing CB‐related reduced GMD and cortical thickness in the left temporal lobe, indicating disinhibition as the main driver for CB. Interestingly, brain degeneration in the temporal lobe is discussed with CB in bvFTD in the current literature, dominantly affecting the right hemisphere. Our study investigates specifically the neural correlates of CB in bvFTD with MRI, modifying this view. Further work is necessary to shed more light on the role of the temporal lobe in bvFTD with CB
Structural correlates of language processing in primary progressive aphasia
No full textAbstract Understanding the relationships between brain structure and language behaviour in primary progressive aphasia provides crucial information about these diseases’ pathomechanisms. However, previous investigations have been limited from providing a statistically reliable view of broad language abilities by sample size, variant focus and task focus. In this study, the authors aimed to determine the relationship between brain structure and language behaviour in primary progressive aphasia, to determine the degree to which task-associated regions were atrophied across disease variants and to determine the degree to which task-related atrophy overlaps across disease variants. Participants were 118 primary progressive aphasia patients and 61 healthy, age-matched controls tested from 2011 to 2018 in the German Consortium for Frontotemporal Lobar Degeneration cohort. Diagnosis of primary progressive aphasia required progressive deterioration of mainly speech and language for ≥ 2 years, and variant was diagnosed by the criteria of Gorno-Tempini et al. (Classification of primary progressive aphasia and its variants. Neurology. 2011;76(11):1006-1014). Twenty-one participants not fulfilling a specific subtype were classified as mixed-variant and excluded. Language tasks of interest included the Boston naming test, a German adaptation of the Repeat and Point task, phonemic and category fluency tasks and the reading/writing subtest of the Aachen Aphasia Test. Brain structure was measured by cortical thickness. We observed networks of language task-associated temporal, frontal and parietal cortex. Overlapping task-associated atrophy was observed in the left lateral, ventral and medial temporal lobes, middle and superior frontal gyri, supramarginal gyrus and insula. Some regions, primarily in the perisylvian region, were associated with language behaviour despite showing no significant atrophy. The results crucially extend less powerful studies associating brain and language measures in primary progressive aphasia. Cross-variant atrophy in task-associated regions suggests partially shared underlying deficits, whereas unique atrophy reinforces variant-specific deficits. Language task-related regions that are not obviously atrophied suggest regions of future network disruption and encourage understanding of task deficits beyond clearly atrophied cortex. These results may pave the way for new treatment approaches
Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes
Get PDFIMPORTANCE: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context. OBJECTIVE: Multi-class prediction is key for building computational aid systems for differential diagnosis. We compared support vector machine, random forest, gradient boosting, and deep feed-forward neural networks for the classification of different neurodegenerative syndromes based on structural magnetic resonance imaging. DESIGN, SETTING, AND PARTICIPANTS: Atlas-based volumetry was performed on multi-centric T1-weighted MRI data from 940 subjects, i.e., 124 healthy controls and 816 patients with ten different neurodegenerative diseases, leading to a multi-diagnostic multi-class classification task with eleven different classes. INTERVENTIONS: N.A. MAIN OUTCOMES AND MEASURES: Cohen’s kappa, accuracy, and F1-score to assess model performance. RESULTS: Overall, the neural network produced both the best performance measures and the most robust results. The smaller classes however were better classified by either the ensemble learning methods or the support vector machine, while performance measures for small classes were comparatively low, as expected. Diseases with regionally specific and pronounced atrophy patterns were generally better classified than diseases with widespread and rather weak atrophy. CONCLUSIONS AND RELEVANCE: Our study furthermore underlines the necessity of larger data sets but also calls for a careful consideration of different machine learning methods that can handle the type of data and the classification task best
- …
