Structural parameters are superior to eigenvector centrality in detecting progressive supranuclear palsy with machine learning & multimodal MRI.

Progressive supranuclear palsy (PSP) is an atypical Parkinsonian syndrome characterized initially by falls and eye movement impairment. This multimodal imaging study aimed at eliciting structural and functional disease-specific brain alterations. T1-weighted and resting-state functional MRI were applied in multi-centric cohorts of PSP and matched healthy controls. Midbrain, cerebellum, and cerebellar peduncles showed severely low gray/white matter volume, whereas thinner cortical gray matter was observed in cingulate cortex, medial and temporal gyri, and insula. Eigenvector centrality analyses revealed regionally specific alterations. Multivariate pattern recognition classified patients correctly based on gray and white matter segmentations with up to 98 % accuracy. Highest accuracies were obtained when restricting feature selection to the midbrain. Eigenvector centrality indices yielded an accuracy around 70 % in this comparison; however, this result did not reach significance. In sum, the study reveals multimodal, widespread brain changes in addition to the well-known midbrain atrophy in PSP. Alterations in brain structure seem to be superior to eigenvector centrality parameters, in particular for prediction with machine learning approaches.

The Human Affectome.

Over the last decades, theoretical perspectives in the interdisciplinary field of the affective sciences have proliferated rather than converged due to differing assumptions about what human affective phenomena are and how they work. These metaphysical and mechanistic assumptions, shaped by academic context and values, have dictated affective constructs and operationalizations. However, an assumption about the purpose of affective phenomena can guide us to a common set of metaphysical and mechanistic assumptions. In this capstone paper, we home in on a nested teleological principle for human affective phenomena in order to synthesize metaphysical and mechanistic assumptions. Under this framework, human affective phenomena can collectively be considered algorithms that either adjust based on the human comfort zone (affective concerns) or monitor those adaptive processes (affective features). This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope the Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research.

Fronto-striatal alterations correlate with apathy severity in behavioral variant frontotemporal dementia.

Structural and functional changes in cortical and subcortical regions have been reported in behavioral variant frontotemporal dementia (bvFTD), however, a multimodal approach may provide deeper insights into the neural correlates of neuropsychiatric symptoms. In this multicenter study, we measured cortical thickness (CTh) and subcortical volumes to identify structural abnormalities in 37 bvFTD patients, and 37 age- and sex-matched healthy controls. For seed regions with significant structural changes, whole-brain functional connectivity (FC) was examined in a sub-cohort of N = 22 bvFTD and N = 22 matched control subjects to detect complementary alterations in brain network organization. To explore the functional significance of the observed structural and functional deviations, correlations with clinical and neuropsychological outcomes were tested where available. Significantly decreased CTh was observed in the bvFTD group in caudal middle frontal gyrus, left pars opercularis, bilateral superior frontal and bilateral middle temporal gyrus along with subcortical volume reductions in bilateral basal ganglia, thalamus, hippocampus, and amygdala. Resting-state functional magnetic resonance imaging showed decreased FC in bvFTD between: dorsal striatum and left caudal middle frontal gyrus; putamen and fronto-parietal regions; pallidum and cerebellum. Conversely, bvFTD showed increased FC between: left middle temporal gyrus and paracingulate gyrus; caudate nucleus and insula; amygdala and parahippocampal gyrus. Additionally, cortical thickness in caudal, lateral and superior frontal regions as well as caudate nucleus volume correlated negatively with apathy severity scores of the Neuropsychiatry Inventory Questionnaire. In conclusion, multimodal structural and functional imaging indicates that fronto-striatal regions have a considerable influence on the severity of apathy in bvFTD.

Engagement, Retention, and Acceptability in a Digital Health Program for Atopic Dermatitis: Prospective Interventional Study.

BACKGROUND: Patients with atopic dermatitis can experience chronic eczema with pruritus, skin pain, sleep problems, anxiety, and other problems that reduce their quality of life (QoL). Current treatments aim to improve these symptoms and reduce inflammation, but poor treatment adherence and disease understanding are key concerns in the long-term management of atopic dermatitis. Digital therapeutics can help with these and support patients toward a healthier lifestyle to improve their overall QoL. OBJECTIVE: The aim of the study is to test the feasibility of a digital health program tailored for atopic dermatitis through program engagement, retention, and acceptability. METHODS: Adults with atopic dermatitis were recruited in Iceland for a 6-week digital health program delivered through a smartphone app. Key components of the digital program were disease and trigger education; medication reminders; patient-reported outcomes (PROs) on energy levels, stress levels, and quality of sleep (referred to as QoL PROs); atopic dermatitis symptom PROs; guided meditation; and healthy lifestyle coaching. The primary outcome was program feasibility, as assessed by in-app retention and engagement. User satisfaction was assessed by the mHealth (ie, mobile health) App Usability Questionnaire (MAUQ). RESULTS: A total of 21 patients were recruited (17 female, mean age 31 years), 20 (95%) completed the program. On average, users were active in the app 6.5 days per week and completed 8.2 missions per day. The education content, medication reminders, and PROs had high user engagement and retention; all users who were exposed to the QoL PROs (n=17) interacted with these, and 20/21 (95%) users were continuously engaged with the education missions, medication missions, and symptom PROs. Continued engagement with the step counter and mind missions among exposed users was lower (17/21 and 13/20 participants, respectively). Medication reminder and education task completion remained high over time (at least 18/20, 90%), but weekly interactions declined. All assigned users completed atopic dermatitis symptom PROs on weeks 1-5 and only one did not do so on week 6; the reported number and total severity of atopic dermatitis symptoms reduced during the program. Regarding the QoL PROs, 16/17 (94%) and 14/17 (82%) users interacted with these at least 3 times in the first and last week of the program, respectively, and all reported improvements over time. User satisfaction was high with a total score of 6.2/7. CONCLUSIONS: We found high overall engagement and retention in a targeted digital health program among patients with atopic dermatitis, as well as high compliance with missions relating to medication reminders, patient education, and PROs. Symptom number and severity were reduced, and QoL PROs improved over time. We conclude that a digital health program is feasible and may provide added benefits for patients with atopic dermatitis, including the tracking and improvement of atopic dermatitis symptoms.

A Residual Marker of Cognitive Reserve Is Associated with Resting-State Intrinsic Functional Connectivity Along the Alzheimer's Disease Continuum.

BACKGROUND: Cognitive reserve (CR) explains inter-individual differences in the impact of the neurodegenerative burden on cognitive functioning. A residual model was proposed to estimate CR more accurately than previous measures. However, associations between residual CR markers (CRM) and functional connectivity (FC) remain unexplored. OBJECTIVE: To explore the associations between the CRM and intrinsic network connectivity (INC) in resting-state networks along the neuropathological-continuum of Alzheimer's disease (ADN). METHODS: Three hundred eighteen participants from the DELCODE cohort were stratified using cerebrospinal fluid biomarkers according to the A(myloid-ß)/T(au)/N(eurodegeneration) classification. CRM was calculated utilizing residuals obtained from a multilinear regression model predicting cognition from markers of disease burden. Using an independent component analysis in resting-state fMRI data, we measured INC of resting-state networks, i.e., default mode network (DMN), frontoparietal network (FPN), salience network (SAL), and dorsal attention network. The associations of INC with a composite memory score and CRM and the associations of CRM with the seed-to-voxel functional connectivity of memory-related were tested in general linear models. RESULTS: CRM was positively associated with INC in the DMN in the entire cohort. The A+T+N+ group revealed an anti-correlation between the SAL and the DMN. Furthermore, CRM was positively associated with anti-correlation between memory-related regions in FPN and DMN in ADN and A+T/N+. CONCLUSION: Our results provide evidence that INC is associated with CRM in ADN defined as participants with amyloid pathology with or without cognitive symptoms, suggesting that the neural correlates of CR are mirrored in network FC in resting-state.

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

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.

Linking early-life bilingualism and cognitive advantage in older adulthood.

Previous studies have identified bilingualism as a protective factor against dementia. Here we aimed to test whether being bilingual at different life stages impacts cognition and brain structure in older adulthood. We included 746 participants from the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). Assessment of bilingualism at 3 life stages (early: 13-30, middle: 30-65 and late: over 65 years old) was determined with the Lifetime of Experiences Questionnaire. Individuals reporting bilingualism (i.e., daily use of L2) in the early life stage outperformed monolinguals on learning & memory, working-memory, executive functions and language. Bilingualism in middle life stage showed a significant advantage on learning & memory, while no effect of bilingualism in old life stage was identified. Brain gray matter volume was not associated with L2 use and did not differ between groups. However, stronger correlations between brain gray matter volume in selected brain regions and cognitive performance were found in bilingual participants in the early and middle life stages. Our results indicate that bilingualism in early life might provide a long-lasting protective effect on cognition and shape the brain to sustain cognitive performance in older adulthood.

Lifelong experiences as a proxy of cognitive reserve moderate the association between connectivity and cognition in Alzheimer's disease.

Alzheimer's disease (AD) is associated with alterations in functional connectivity (FC) of the brain. The FC underpinnings of CR, that is, lifelong experiences, are largely unknown. Resting-state FC and structural MRI were performed in 76 CSF amyloid-ß (Aß) negative healthy controls and 152 Aß positive individuals as an AD spectrum cohort (ADS; 55 with subjective cognitive decline, SCD; 52 with mild cognitive impairment; 45 with AD dementia). Following a region-of-interest (ROI) FC analysis, intrinsic network connectivity within the default-mode network (INC-DMN) and anti-correlation in INC between the DMN and dorsal attention network (DMN:DAN) were obtained as composite scores. CR was estimated by education and Lifetime Experiences Questionnaire (LEQ). The association between INC-DMN and MEM was attenuated by higher LEQ scores in the entire ADS group, particularly in SCD. In ROI analyses, higher LEQ scores were associated with higher FC within the DMN in ADS group. INC-DMN remains relatively intact despite memory decline in individuals with higher lifetime activity estimates, supporting a role for functional networks in maintaining cognitive function in AD.

Clinical Efficacy of a Digital Intervention for Patients with Atopic Dermatitis: a Prospective Single-Center Study.

INTRODUCTION: Improving disease awareness and treatment adherence is key for the long-term management of atopic dermatitis (AD). Digital interventions can support patients in disease self-management and adopting a healthier lifestyle through behavioral modifications. We aimed to test the clinical efficacy of a digital program in patients with AD. METHODS: Adults with mild-to-severe AD were recruited for a 6-week feasibility study. The intervention was delivered through a mobile app and consisted of symptom and trigger education, treatment reminders, lifestyle coaching, and healthy lifestyle support. Here we report the secondary outcomes of intervention efficacy on clinical symptoms, as assessed by Scoring Atopic Dermatitis (SCORAD) and Patient-Oriented Eczema Measure (POEM), on health-related quality of life (HR QoL) as assessed by Dermatology Life Quality Index (DLQI), and changes in behaviors related to disease management as assessed by a six-item questionnaire. RESULTS: Twenty of 21 patients (95.2%) completed the program (81% female, mean age 31.4 years, mean time from diagnosis 26.8 years). Clinical symptoms and patient-reported global severity improved by 44% and 46%, respectively, while HR QoL improved by 41% (p < 0.001 for all measures). Adherence to treatments and preventive measures improved from pre- to post-intervention, including skincare, avoidance of triggers, and disease-related knowledge. A significant interaction was observed between increased treatment adherence and clinical improvement, such that larger clinical improvements were observed in patients with higher treatment adherence. CONCLUSION: Patients with AD are open to and can benefit from a digitally delivered targeted intervention, as demonstrated by significant improvements in treatment adherence and related clinical outcomes.

Association of Cholinergic Basal Forebrain Volume and Functional Connectivity with Markers of Inflammatory Response in the Alzheimer's Disease Spectrum.

BACKGROUND: Inflammation has been described as a key pathogenic event in Alzheimer's disease (AD), downstream of amyloid and tau pathology. Preclinical and clinical data suggest that the cholinergic basal forebrain may moderate inflammatory response to different pathologies. OBJECTIVE: To study the association of cholinergic basal forebrain volume and functional connectivity with measures of neuroinflammation in people from the AD spectrum. METHODS: We studied 261 cases from the DELCODE cohort, including people with subjective cognitive decline, mild cognitive impairment, AD dementia, first degree relatives, and healthy controls. Using Bayesian ANCOVA, we tested associations of MRI indices of cholinergic basal forebrain volume and functional connectivity with cerebrospinal fluid (CSF) levels of sTREM2 as a marker of microglia activation, and serum levels of complement C3. Using Bayesian elastic net regression, we determined associations between basal forebrain measures and a large inflammation marker panel from CSF and serum. RESULTS: We found anecdotal to moderate evidence in favor of the absence of an effect of basal forebrain volume and functional connectivity on CSF sTREM2 and serum C3 levels both in Aß42/ptau-positive and negative cases. Bayesian elastic net regression identified several CSF and serum markers of inflammation that were associated with basal forebrain volume and functional connectivity. The effect sizes were moderate to small. CONCLUSION: Our data-driven analyses generate the hypothesis that cholinergic basal forebrain may be involved in the neuroinflammation response to Aß42 and phospho-tau pathology in people from the AD spectrum. This hypothesis needs to be tested in independent samples.

Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: evaluation in Alzheimer's disease.

BACKGROUND: Although convolutional neural networks (CNNs) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap as they allow the visualization of key input image features that drive the decision of the model. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge. METHODS: We trained a CNN for the detection of AD in N = 663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including in total N = 1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection. RESULTS: Across the three independent datasets, group separation showed high accuracy for AD dementia versus controls (AUC ≥ 0.91) and moderate accuracy for amnestic MCI versus controls (AUC ≈ 0.74). Relevance maps indicated that hippocampal atrophy was considered the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r ≈ -0.86, p < 0.001). CONCLUSION: The relevance maps highlighted atrophy in regions that we had hypothesized a priori. This strengthens the comprehensibility of the CNN models, which were trained in a purely data-driven manner based on the scans and diagnosis labels. The high hippocampus relevance scores as well as the high performance achieved in independent samples support the validity of the CNN models in the detection of AD-related MRI abnormalities. The presented data-driven and hypothesis-free CNN modeling approach might provide a useful tool to automatically derive discriminative features for complex diagnostic tasks where clear clinical criteria are still missing, for instance for the differential diagnosis between various types of dementia.

The neuroscience of social feelings: mechanisms of adaptive social functioning.

Social feelings have conceptual and empirical connections with affect and emotion. In this review, we discuss how they relate to cognition, emotion, behavior and well-being. We examine the functional neuroanatomy and neurobiology of social feelings and their role in adaptive social functioning. Existing neuroscience literature is reviewed to identify concepts, methods and challenges that might be addressed by social feelings research. Specific topic areas highlight the influence and modulation of social feelings on interpersonal affiliation, parent-child attachments, moral sentiments, interpersonal stressors, and emotional communication. Brain regions involved in social feelings were confirmed by meta-analysis using the Neurosynth platform for large-scale, automated synthesis of functional magnetic resonance imaging data. Words that relate specifically to social feelings were identfied as potential research variables. Topical inquiries into social media behaviors, loneliness, trauma, and social sensitivity, especially with recent physical distancing for guarding public and personal health, underscored the increasing importance of social feelings for affective and second person neuroscience research with implications for brain development, physical and mental health, and lifelong adaptive functioning.

Mediterranean Diet, Alzheimer Disease Biomarkers and Brain Atrophy in Old Age.

OBJECTIVE: To determine if following a Mediterranean-like diet (MeDi) relates to cognitive functions and in vivo biomarkers for Alzheimer's disease (AD), we analyzed cross-sectional data from the German Longitudinal Cognitive Impairment and Dementia Study METHOD: The sample (n=512, mean age: 69.5±5.9 years) included 169 cognitively normal participants and subjects at higher AD risk (53 AD relatives, 209 SCD and 81 MCI). We defined MeDi adherence based on the Food Frequency Questionnaire. Brain volume outcomes were generated via voxel-based morphometry on T1-MRI and cognitive performance with an extensive neuropsychological battery. AD-related biomarkers (Aß42/40 ratio, pTau181) in cerebrospinal fluid were assessed in n=226 individuals. We analyzed the associations between MeDi and the outcomes with linear regression models controlling for several covariates. Additionally, we applied hypothesis-driven mediation and moderation analysis. RESULTS: Higher MeDi adherence related to larger mediotemporal gray matter volume (p<0.05 FWE corrected), better memory (ß±SE = 0.03 ± 0.02; p=0.038), and less amyloid (Aß42/40 ratio, ß±SE = 0.003 ± 0.001; p=0.008) and pTau181 pathology (ß±SE = -1.96±0.68; p=0.004). Mediotemporal volume mediated the association between MeDi and memory (40% indirect mediation). Finally, MeDi favorably moderated the associations between Aß42/40 ratio, pTau181 and mediotemporal atrophy. Results were consistent correcting for ApoE-ε4 status. CONCLUSION: Our findings corroborate the view of MeDi as a protective factor against memory decline and mediotemporal atrophy. Importantly, they suggest that these associations might be explained by a decrease of amyloidosis and tau-pathology. Longitudinal and dietary intervention studies should further examine this conjecture and its treatment implications.

SERIAL-ORDER recall in working memory across the cognitive spectrum of Parkinson's disease and neuroimaging correlates.

We sought to determine if Parkinson's disease (PD) with mild cognitive impairment (MCI) is associated with a greater SERIAL-ORDER (mental manipulation) than ANY-ORDER (auditory span, storage) deficit in working memory (WM). We investigated WM combining neuropsychological measures with the study of brain functional connectivity. A cohort of 160 patients with idiopathic PD, classified as PD-MCI (n = 87) or PD with normal cognition (PD-NC; n = 73), and 70 matched healthy controls were studied. Verbal WM was assessed with the Backward Digit Span Task (BDT; Lamar et al., 2007, Neuropsychologia, 45, 245), measuring SERIAL-ORDER and ANY-ORDER recall. Resting-state MRI data were collected for 15 PD-MCI, 15 PD-NC and 30 controls. Hypothesis-driven seed-based functional connectivity of the dorsolateral prefrontal cortex (DLPFC) was compared between the three groups and correlated with BDT performance. We found the main effect of the test (impairment in SERIAL ORDER > ANY ORDER) and group ((NC = PD-NC) > PD-MCI) in BDT performance that was even more pronounced in SERIAL ORDER when controlling for ANY ORDER variability but not vice versa. Furthermore, PD-MCI compared to other groups were characterized by the functional disconnection between the bilateral DLPFC and the cerebellum. In functional correlations, DLPFC connectivity was positively related to both SERIAL- and ANY-ORDER performance. In conclusion, PD-MCI patients evidenced greater SERIAL-ORDER (manipulation and cognitive control) than ANY-ORDER (storage) working memory impairment than PD-NC and controls with a disrupted DLPFC resting-state connectivity that was also related to the verbal WM performance.

Differential effects of deep brain stimulation and levodopa on brain activity in Parkinson's disease.

Levodopa is the first-line treatment for Parkinson's disease, although the precise mechanisms mediating its efficacy remain elusive. We aimed to elucidate treatment effects of levodopa on brain activity during the execution of fine movements and to compare them with deep brain stimulation of the subthalamic nuclei. We studied 32 patients with Parkinson's disease using functional MRI during the execution of finger-tapping task, alternating epochs of movement and rest. The task was performed after withdrawal and administration of a single levodopa dose. A subgroup of patients (n = 18) repeated the experiment after electrode implantation with stimulator on and off. Investigating levodopa treatment, we found a significant interaction between both factors of treatment state (off, on) and experimental task (finger tapping, rest) in bilateral putamen, but not in other motor regions. Specifically, during the off state of levodopa medication, activity in the putamen at rest was higher than during tapping. This represents an aberrant activity pattern probably indicating the derangement of basal ganglia network activity due to the lack of dopaminergic input. Levodopa medication reverted this pattern, so that putaminal activity during finger tapping was higher than during rest, as previously described in healthy controls. Within-group comparison with deep brain stimulation underlines the specificity of our findings with levodopa treatment. Indeed, a significant interaction was observed between treatment approach (levodopa, deep brain stimulation) and treatment state (off, on) in bilateral putamen. Our functional MRI study compared for the first time the differential effects of levodopa treatment and deep brain stimulation on brain motor activity. We showed modulatory effects of levodopa on brain activity of the putamen during finger movement execution, which were not observed with deep brain stimulation.

Capgras Delusion in Posterior Cortical Atrophy-A Quantitative Multimodal Imaging Single Case Study.

Although Alzheimer's disease presents homogeneous histopathology, it causes several clinical phenotypes depending on brain regions involved. Beside the most abundant memory variant, several atypical variants exist. Among them posterior cortical atrophy (PCA) is associated with severe visuospatial/visuoperceptual deficits in the absence of significant primary ocular disease. Here, we report for the first time a case of Capgras delusion-a delusional misidentification syndrome, where patients think that familiar persons are replaced by identical "doubles" or an impostor-in a patient with PCA. The 57-year-old female patient was diagnosed with PCA and developed Capgras delusion 8 years after first symptoms. The patient did not recognize her husband, misidentified him as a stranger, and perceived him as a threat. Such misidentifications did not happen for other persons. Events could be interrupted by reassuring the husband's identity by the patient's female friend or children. We applied in-depth multimodal neuroimaging phenotyping and used single-subject voxel-based morphometry to identify atrophy changes specifically related to the development of the Capgras delusion. The latter, based on structural T1 magnetic resonance imaging, revealed progressive gray matter volume decline in occipital and temporoparietal areas, involving more the right than the left hemisphere, especially at the beginning. Correspondingly, the right fusiform gyrus was already affected by atrophy at baseline, whereas the left fusiform gyrus became involved in the further disease course. At baseline, glucose hypometabolism as measured by positron emission tomography (PET) with F18-fluorodesoxyglucose (FDG-PET) was evident in the parietooccipital cortex, more pronounced right-sided, and in the right frontotemporal cortex. Amyloid accumulation as assessed by PET with F18-florbetaben was found in the gray matter of the neocortex indicating underlying Alzheimer's disease. Appearance of the Capgras delusion was related to atrophy in the right posterior cingulate gyrus/precuneus, as well as right middle frontal gyrus/frontal eye field, supporting right frontal areas as particularly relevant for Capgras delusion. Atrophy in these regions respectively might affect the default mode and dorsal attention networks as shown by meta-analytical co-activation and resting state functional connectivity analyses. This case elucidates the brain-behavior relationship in PCA and Capgras delusion.

Brain Damage With Heart Failure: Cardiac Biomarker Alterations and Gray Matter Decline.

RATIONALE: Heart failure (HF) following heart damage leads to a decreased blood flow due to a reduced pump efficiency of the heart muscle. A consequence can be insufficient oxygen supply to the organism including the brain. While HF clearly shows neurological symptoms, such as fatigue, nausea, and dizziness, the implications for brain structure are not well understood. Few studies show regional gray matter decrease related to HF; however, the underlying mechanisms leading to the observed brain changes remain unclear. OBJECTIVE: To study the relationship between impaired heart function, hampered blood circulation, and structural brain change in a case-control study. METHODS AND RESULTS: Within a group of 80 patients of the Leipzig Heart Center, we investigated a potential correlation between HF biomarkers and the brain's gray matter density (GMD) obtained by magnetic resonance imaging. We observed a significant positive correlation between cardiac ejection fraction and GMD across the whole frontal and parietal medial cortex reflecting the consequence of HF onto the brain's gray matter. Moreover, we also obtained a relationship between GMD and the NT-proBNP (N-terminal prohormone of brain natriuretic peptide)-a biomarker that is used for screening, diagnosis, and prognosis of HF. Here, we found a significant negative correlation between NT-proBNP and GMD in the medial and posterior cingulate cortex but also in precuneus and hippocampus, which are key regions implicated in structural brain changes in dementia. CONCLUSIONS: We obtained significant correlations between brain structure and markers of heart failure including ejection fraction and NT-proBNP. A diminished GMD was found with decreased ejection fraction and increased NT-proBNP in wide brain regions including the whole frontomedian cortex as well as hippocampus and precuneus. Our observations might reflect structural brain damage in areas that are related to cognition; however, whether these structural changes facilitate the development of cognitive alterations has to be proven by further longitudinal studies.

Multimodal MRI analysis of basal forebrain structure and function across the Alzheimer's disease spectrum.

BACKGROUND: Dysfunction of the cholinergic basal forebrain (cBF) is associated with cognitive decline in Alzheimer's disease (AD). Multimodal MRI allows for the investigation of cBF changes in-vivo. In this study we assessed alterations in cBF functional connectivity (FC), mean diffusivity (MD), and volume across the spectrum of AD. We further assessed effects of amyloid pathology on these changes. METHODS: Participants included healthy controls, and subjects with subjective cognitive decline (SCD), mild cognitive impairment (MCI), or AD dementia (ADD) from the multicenter DELCODE study. Resting-state functional MRI (rs-fMRI) and structural MRI data was available for 477 subjects, and a subset of 243 subjects also had DTI data available. Differences between diagnostic groups were investigated using seed-based FC, volumetric, and MD analyses of functionally defined anterior (a-cBF) and posterior (p-cBF) subdivisions of a cytoarchitectonic cBF region-of-interest. In complementary analyses groups were stratified according to amyloid status based on CSF Aß42/40 biomarker data, which was available in a subset of participants. RESULTS: a-cBF and p-cBF subdivisions showed regional FC profiles that were highly consistent with previously reported patterns, but there were only minimal differences between diagnostic groups. Compared to controls, cBF volumes and MD were significantly different in MCI and ADD but not in SCD. The Aß42/40 stratified analyses largely matched these results. CONCLUSIONS: We reproduced subregion-specific FC profiles of the cBF in a clinical sample spanning the AD spectrum. At least in this multicentric cohort study, cBF-FC did not show marked changes along the AD spectrum, and multimodal MRI did not provide more sensitive measures of AD-related cBF changes compared to volumetry.

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

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.