Distinct functional subnetworks of cognitive domains in older adults with minor cognitive deficits.

Although past research has established a relationship between functional connectivity and cognitive function, less is known about which cognitive domains are associated with which specific functional networks. This study investigated associations between functional connectivity and global cognitive function and performance in the domains of memory, executive function and psychomotor speed in 166 older adults aged 75-91 years (mean = 80.3 ± 3.8) with minor cognitive deficits (Mini-Mental State Examination scores between 21 and 27). Functional connectivity was assessed within 10 standard large-scale resting-state networks and on a finer spatial resolution between 300 nodes in a functional connectivity matrix. No domain-specific associations with mean functional connectivity within large-scale resting-state networks were found. Node-level analysis revealed that associations between functional connectivity and cognitive performance differed across cognitive functions in strength, location and direction. Specific subnetworks of functional connections were found for each cognitive domain in which higher connectivity between some nodes but lower connectivity between other nodes were related to better cognitive performance. Our findings add to a growing body of literature showing differential sensitivity of functional connections to specific cognitive functions and may be a valuable resource for hypothesis generation of future studies aiming to investigate specific cognitive dysfunction with resting-state functional connectivity in people with beginning cognitive deficits.

Functional connectivity of the visual cortex in chronic migraine before and after medication withdrawal therapy.

Acute withdrawal of headache medication in chronic migraine patients with medication overuse may lead to a dramatic reduction in headache frequency and severity. However, the brain networks underlying chronic migraine and a favorable response to acute withdrawal are still poorly understood. The goal of the present study was to characterize the pattern of intrinsic magnetic resonance imaging (MRI) functional connectivity (FC) specific to chronic migraine and to identify changes in FC that characterize subjects with CM reverting to less frequent headaches. Subjects with chronic migraine (N = 99) underwent a resting-state functional MRI scan before and after three months of medication withdrawal therapy. In addition, we included four control groups who were scanned once: healthy participants (N = 27), patients with episodic migraine (N = 25), patients with chronic back pain (N = 22), and patients with clinical depression (N = 17). Using dual regression analysis, we compared whole-brain voxel-level functional connectivity with ten well-known resting-state networks between chronic migraine and control groups, and between responders to treatment (≥50 % reduction in monthly headache days) and non-responders (<50 % reduction), before and after treatment. Subjects with chronic migraine showed differences in FC with a number of RS-networks, most of which involved the visual cortex, compared with healthy controls. A comparison with patients with episodic migraine, chronic pain and depression showed differences in the same direction, suggesting that altered patterns of functional connectivity in chronic migraine patients could to some extent be explained by shared symptomatology with other pain, depression, or migraine conditions. A comparison between responders and non-responders indicated that effective withdrawal reduced FC with the visual cortex for responders. Interestingly, responders already differed in functional connectivity of the visual cortex at baseline compared with non-responders. Altogether, we show that chronic migraine and successful medication withdrawal therapy are linked to changes in the functional connectivity of the visual cortex. These neuroimaging findings provide new insights into the pathways underlying migraine chronification and its reversibility.

Functional connectivity in older adults-the effect of cerebral small vessel disease.

Ageing is associated with functional reorganization that is mainly characterized by declining functional connectivity due to general neurodegeneration and increasing incidence of disease. Functional connectivity has been studied across the lifespan; however, there is a paucity of research within the older groups (≥75 years) where neurodegeneration and disease prevalence are at its highest. In this cross-sectional study, we investigated associations between age and functional connectivity and the influence of cerebral small vessel disease (CSVD)-a common age-related morbidity-in 167 community-dwelling older adults aged 75-91 years (mean = 80.3 ± 3.8). Resting-state functional MRI was used to determine functional connectivity within ten standard networks and calculate the whole-brain graph theoretical measures global efficiency and clustering coefficient. CSVD features included white matter hyperintensities, lacunar infarcts, cerebral microbleeds, and atrophy that were assessed in each individual and a composite score was calculated. Both main and interaction effects (age*CSVD features) on functional connectivity were studied. We found stable levels of functional connectivity across the age range. CSVD was not associated with functional connectivity measures. To conclude, our data show that the functional architecture of the brain is relatively unchanged after 75 years of age and not differentially affected by individual levels of vascular pathology.

Aging Effect, Reproducibility, and Test-Retest Reliability of a New Cerebral Amyloid Angiopathy MRI Severity Marker-Cerebrovascular Reactivity to Visual Stimulation.

BACKGROUND: Decreased cerebrovascular reactivity, measured as changes in blood-oxygen-level-dependent (BOLD) signal, is a potential new cerebral amyloid angiopathy (CAA) severity marker. Before clinical application, the effect of aging on BOLD parameters, and reproducibility and test-retest reliability of these parameters should be assessed. PURPOSE: Assess the effect of healthy aging on cerebrovascular reactivity (BOLD amplitude, time to peak, and time to baseline). And determine reproducibility and test-retest reliability of these parameters. STUDY TYPE: Prospective-observational. POPULATION: Eighty-six healthy adults (mean age 56 years, 55% female), 10 presymptomatic D-CAA mutation carriers (mean age 34 years, 70% female), and 10 symptomatic D-CAA mutation carriers (mean age 54 years, 70% female). FIELD STRENGTH/SEQUENCE: 3-T, three-dimensional (3D) T1-weighted MRI and gradient echo BOLD fMRI. ASSESSMENT: To assess test-retest reliability of BOLD parameters, i.e. BOLD amplitude, time to peak, and time to baseline, BOLD fMRI scans were repeated three times immediately after each other, in both controls and mutation carriers. To assess reproducibility, BOLD fMRI scans were repeated with a 3-week interval for each subject. STATISTICAL TESTS: Linear regression analyses and two-way mixed absolute agreement intra-class correlation approach. RESULTS: Healthy aging was associated with decreased BOLD amplitude (ß = -0.711) and prolonged time to baseline (ß = 0.236) in the visual cortex after visual stimulation Reproducibility of BOLD amplitude was excellent (ICC 0.940) in the subgroup of healthy adults. Test-retest reliability for BOLD amplitude was excellent in healthy adults (ICC 0.856-0.910) and presymptomatic D-CAA mutation carriers (ICC 0.959-0.981). In symptomatic D-CAA mutation carriers, test-retest reliability was poor for all parameters (ICCs < 0.5). DATA CONCLUSION: Healthy aging is associated with decreased cerebrovascular reactivity, measured by changes in BOLD response to visual stimulation. The BOLD amplitude appears to be a robust measurement in healthy adults and presymptomatic D-CAA mutation carriers, but not in symptomatic D-CAA mutation carriers.

Clusterwise Independent Component Analysis (C-ICA): Using fMRI resting state networks to cluster subjects and find neurofunctional subtypes.

BACKGROUND: FMRI resting state networks (RSNs) are used to characterize brain disorders. They also show extensive heterogeneity across patients. Identifying systematic differences between RSNs in patients, i.e. discovering neurofunctional subtypes, may further increase our understanding of disease heterogeneity. Currently, no methodology is available to estimate neurofunctional subtypes and their associated RSNs simultaneously. NEW METHOD: We present an unsupervised learning method for fMRI data, called Clusterwise Independent Component Analysis (C-ICA). This enables the clustering of patients into neurofunctional subtypes based on differences in shared ICA-derived RSNs. The parameters are estimated simultaneously, which leads to an improved estimation of subtypes and their associated RSNs. RESULTS: In five simulation studies, the C-ICA model is successfully validated using both artificially and realistically simulated data (N = 30-40). The successful performance of the C-ICA model is also illustrated on an empirical data set consisting of Alzheimer's disease patients and elderly control subjects (N = 250). C-ICA is able to uncover a meaningful clustering that partially matches (balanced accuracy = .72) the diagnostic labels and identifies differences in RSNs between the Alzheimer and control cluster. COMPARISON WITH OTHER METHODS: Both in the simulation study and the empirical application, C-ICA yields better results compared to competing clustering methods (i.e., a two step clustering procedure based on single subject ICA's and a Group ICA plus dual regression variant thereof) that do not simultaneously estimate a clustering and associated RSNs. Indeed, the overall mean adjusted Rand Index, a measure for cluster recovery, equals 0.65 for C-ICA and ranges from 0.27 to 0.46 for competing methods. CONCLUSIONS: The successful performance of C-ICA indicates that it is a promising method to extract neurofunctional subtypes from multi-subject resting state-fMRI data. This method can be applied on fMRI scans of patient groups to study (neurofunctional) subtypes, which may eventually further increase understanding of disease heterogeneity.

Longitudinal Brain Atrophy Rates in Presymptomatic Carriers of Genetic Frontotemporal Dementia.

BACKGROUND AND OBJECTIVES: It is important to identify at what age brain atrophy rates in genetic frontotemporal dementia (FTD) start to accelerate and deviate from normal aging effects to find the optimal starting point for treatment. We investigated longitudinal brain atrophy rates in the presymptomatic stage of genetic FTD, using normative brain volumetry software. METHODS: Presymptomatic GRN, MAPT, and C9orf72 pathogenic variant carriers underwent longitudinal volumetric T1-weighted magnetic resonance imaging of the brain as part of a prospective cohort study. Images were automatically analyzed with Quantib® ND which consisted of volume measurements (CSF and sum of gray and white matter) of lobes, cerebellum, and hippocampus. All volumes were compared to reference centile curves based on a large population-derived sample of non-demented individuals (n=4951). Mixed-effects models were fitted to analyze atrophy rates of the different gene groups as a function of age. RESULTS: 34 GRN, eight MAPT, and 14 C9orf72 pathogenic variant carriers were included (mean age=52.1, standard deviation=7.2; 66% female). Mean follow-up duration of the study was 64±33 months (median=52; range 13-108). GRN pathogenic variant carriers showed faster decline than the reference centile curves for all brain areas, though relative volumes remained between 5th and 75th percentile between the ages of 45-70. In MAPT pathogenic variant carriers, frontal lobe volume was already at the 5th percentile at age 45, and showed further decline between the ages 50-60. Temporal lobe volume started in the 50th percentile at age 45, but showed fastest decline over time compared to other brain structures. Frontal, temporal, parietal and cerebellar volume already started below the 5th percentile compared to the reference centile curves at age 45 for C9orf72 pathogenic variant carriers, but there was minimal decline over time until the age of 60. DISCUSSION: We provide evidence for longitudinal brain atrophy in the presymptomatic stage of genetic FTD. The affected brain areas and the age after which atrophy rates start to accelerate and diverge from normal aging slopes differed between gene groups. These results highlight the value of normative volumetry software for disease-tracking and staging biomarkers in genetic FTD. These techniques could help in identifying the optimal time window for starting treatment and monitoring treatment response.

Finding a positive me: Affective and neural insights into the challenges of positive autobiographical memory reliving in borderline personality disorder.

BACKGROUND: This study aimed to investigate whether people with borderline personality disorder (BPD) can benefit from reliving positive autobiographical memories in terms of mood and state self-esteem and elucidate the neural processes supporting optimal memory reliving. Particularly the role of vividness and brain areas involved in autonoetic consciousness were studied, as key factors involved in improving mood and state self-esteem by positive memory reliving. METHODS: Women with BPD (N = 25), Healthy Controls (HC, N = 33) and controls with Low Self-Esteem (LSE, N = 22) relived four neutral and four positive autobiographical memories in an MRI scanner. After reliving each memory mood and vividness was rated. State self-esteem was assessed before and after the Reliving Autobiographical Memories (RAM) task. RESULTS: Overall, mood and state self-esteem were lower in participants with BPD compared to HC and LSE, but both the BPD and LSE group improved significantly after positive memory reliving. Moreover, participants with BPD indicated that they relived their memories with less vividness than HC but not LSE, regardless of valence. When reliving (vs reading) memories, participants with BPD showed increased precuneus and lingual gyrus activation compared to HC but not LSE, which was inversely related to vividness. DISCUSSION: Women with BPD seem to experience more challenges in reliving neutral and positive autobiographical memories with lower vividness and less deactivated precuneus potentially indicating altered autonoetic consciousness. Nevertheless, participants with BPD do benefit in mood and self-esteem from reliving positive memories. These findings underline the potential of positive autobiographical memory reliving and suggest that interventions may be further shaped to improve mood and strengthen self-views in people with BPD.

White Matter Hyperintensities and Apolipoprotein E Affect the Association Between Mean Arterial Pressure and Objective and Subjective Cognitive Functioning in Older Adults.

BACKGROUND: White matter hyperintensities (WMH) show a robust relationship with arterial pressure as well as objective and subjective cognitive functioning. In addition, APOE ɛ4 carriership may influence how arterial pressure affects cognitive functioning. OBJECTIVE: To determine the role of region-specific WMH burden and APOE ɛ4 carriership on the relationship between mean arterial pressure (MAP) and cognitive function as well as subjective cognitive decline (SCD). METHODS: The sample consisted of 87 cognitively unimpaired middle-aged to older adults aged 50-85. We measured WMH volume for the whole brain, anterior thalamic radiation (ATR), forceps minor, and superior longitudinal fasciculus (SLF). We examined whether WMH burden mediated the relationship between MAP and cognition (i.e., TMT-A score for processing speed; Stroop performance for executive function) as well as SCD (i.e., Frequency of Forgetting (FoF)), and whether APOE ɛ4 carriership moderated that mediation. RESULTS: WMH burden within SLF mediated the effect of MAP on Stroop performance. Both whole brain and ATR WMH burden mediated the effect of MAP on FoF score. In the MAP-WMH-Stroop relationship, the mediation effect of SLF WMH and the effect of MAP on SLF WMH were significant only in APOE ɛ4 carriers. In the MAP-WMH-FoF relationship, the effect of MAP on whole brain WMH burden was significant only in ɛ4 carriers. CONCLUSION: WMH burden and APOE genotype explain the link between blood pressure and cognitive function and may enable a more accurate assessment of the effect of high blood pressure on cognitive decline and risk for dementia.

Modelling the cascade of biomarker changes in GRN-related frontotemporal dementia.

OBJECTIVE: Progranulin-related frontotemporal dementia (FTD-GRN) is a fast progressive disease. Modelling the cascade of multimodal biomarker changes aids in understanding the aetiology of this disease and enables monitoring of individual mutation carriers. In this cross-sectional study, we estimated the temporal cascade of biomarker changes for FTD-GRN, in a data-driven way. METHODS: We included 56 presymptomatic and 35 symptomatic GRN mutation carriers, and 35 healthy non-carriers. Selected biomarkers were neurofilament light chain (NfL), grey matter volume, white matter microstructure and cognitive domains. We used discriminative event-based modelling to infer the cascade of biomarker changes in FTD-GRN and estimated individual disease severity through cross-validation. We derived the biomarker cascades in non-fluent variant primary progressive aphasia (nfvPPA) and behavioural variant FTD (bvFTD) to understand the differences between these phenotypes. RESULTS: Language functioning and NfL were the earliest abnormal biomarkers in FTD-GRN. White matter tracts were affected before grey matter volume, and the left hemisphere degenerated before the right. Based on individual disease severities, presymptomatic carriers could be delineated from symptomatic carriers with a sensitivity of 100% and specificity of 96.1%. The estimated disease severity strongly correlated with functional severity in nfvPPA, but not in bvFTD. In addition, the biomarker cascade in bvFTD showed more uncertainty than nfvPPA. CONCLUSION: Degeneration of axons and language deficits are indicated to be the earliest biomarkers in FTD-GRN, with bvFTD being more heterogeneous in disease progression than nfvPPA. Our data-driven model could help identify presymptomatic GRN mutation carriers at risk of conversion to the clinical stage.

Cerebral amyloid angiopathy is associated with decreased functional brain connectivity.

Cerebral amyloid angiopathy (CAA) is a major cause of intracerebral hemorrhage and neurological decline in the elderly. CAA results in focal brain lesions, but the influence on global brain functioning needs further investigation. Here we study functional brain connectivity in patients with Dutch type hereditary CAA using resting state functional MRI. Twenty-four DNA-proven Dutch CAA mutation carriers (11 presymptomatic, 13 symptomatic) and 29 age-matched control subjects were included. Using a set of standardized networks covering the entire cortex, we assessed both within- and between-network functional connectivity. We investigated group differences using general linear models corrected for age, sex and gray matter volume. First, all mutation carriers were contrasted against control subjects and subsequently presymptomatic- and symptomatic mutation carriers against control subjects separately, to assess in which stage of the disease differences could be found. All mutation carriers grouped together showed decreased connectivity in the medial and lateral visual networks, default mode network, executive control and bilateral frontoparietal networks. Symptomatic carriers showed diminished connectivity in all but one network, and between the left and right frontoparietal networks. Presymptomatic carriers also showed diminished connectivity, but only in the frontoparietal left network. In conclusion, global brain functioning is diminished in patients with CAA, predominantly in symptomatic CAA and can therefore be considered to be a late consequence of the disease.

Brain activity and connectivity changes in response to nutritive natural sugars, non-nutritive natural sugar replacements and artificial sweeteners.

INTRODUCTION: The brain plays an important regulatory role in directing energy homeostasis and eating behavior. The increased ingestion of sugars and sweeteners over the last decades makes investigating the effects of these substances on the regulatory function of the brain of particular interest. We investigated whole brain functional response to the ingestion of nutrient shakes sweetened with either the nutritive natural sugars glucose and fructose, the low- nutritive natural sugar replacement allulose or the non-nutritive artificial sweetener sucralose. METHODS: Twenty healthy, normal weight, adult males underwent functional MRI on four separate visits. In a double-blind randomized study setup, participants received shakes sweetened with glucose, fructose, allulose or sucralose. Resting state functional MRI was performed before and after ingestion. Changes in Blood Oxygen Level Dependent (BOLD) signal, functional network connectivity and voxel based connectivity by Eigenvector Centrality Mapping (ECM) were measured. RESULTS: Glucose and fructose led to significant decreased BOLD signal in the cingulate cortex, insula and the basal ganglia. Glucose led to a significant increase in eigen vector centrality throughout the brain and a significant decrease in eigen vector centrality in the midbrain. Sucralose and allulose had no effect on BOLD signal or network connectivity but sucralose did lead to a significant increase in eigen vector centrality values in the cingulate cortex, central gyri and temporal lobe. DISCUSSION: Taken together our findings show that even in a shake containing fat and protein, the type of sweetener can affect brain responses and might thus affect reward and satiety responses and feeding behavior. The sweet taste without the corresponding energy content of the non-nutritive sweeteners appeared to have only small effects on the brain. Indicating that the while ingestion of nutritive sugars could have a strong effect on feeding behavior, both in a satiety aspect as well as rewarding aspects, non-nutritive sweeteners appear to not have these effects. TRIAL REGISTRATION: This study is registered at clinicaltrials.gov under number NCT02745730.

Pre-trained MRI-based Alzheimer's disease classification models to classify memory clinic patients.

Anatomical magnetic resonance imaging (MRI), diffusion MRI and resting state functional MRI (rs-fMRI) have been used for Alzheimer's disease (AD) classification. These scans are typically used to build models for discriminating AD patients from control subjects, but it is not clear if these models can also discriminate AD in diverse clinical populations as found in memory clinics. To study this, we trained MRI-based AD classification models on a single centre data set consisting of AD patients (N = 76) and controls (N = 173), and used these models to assign AD scores to subjective memory complainers (N = 67), mild cognitive impairment (MCI) patients (N = 61), and AD patients (N = 61) from a multi-centre memory clinic data set. The anatomical MRI scans were used to calculate grey matter density, subcortical volumes and cortical thickness, the diffusion MRI scans were used to calculate fractional anisotropy, mean, axial and radial diffusivity, and the rs-fMRI scans were used to calculate functional connectivity between resting state networks and amplitude of low frequency fluctuations. Within the multi-centre memory clinic data set we removed scan site differences prior to applying the models. For all models, on average, the AD patients were assigned the highest AD scores, followed by MCI patients, and later followed by SMC subjects. The anatomical MRI models performed best, and the best performing anatomical MRI measure was grey matter density, separating SMC subjects from MCI patients with an AUC of 0.69, MCI patients from AD patients with an AUC of 0.70, and SMC patients from AD patients with an AUC of 0.86. The diffusion MRI models did not generalise well to the memory clinic data, possibly because of large scan site differences. The functional connectivity model separated SMC subjects and MCI patients relatively good (AUC = 0.66). The multimodal MRI model did not improve upon the anatomical MRI model. In conclusion, we showed that the grey matter density model generalises best to memory clinic subjects. When also considering the fact that grey matter density generally performs well in AD classification studies, this feature is probably the best MRI-based feature for AD diagnosis in clinical practice.

Preserved cortical thickness, surface area and volume in adolescents with PTSD after childhood sexual abuse.

Exposure to childhood adverse events is associated with severe consequences for general health and structural and functional changes in the brain of its survivors. In order to unravel and in the end influence the pathway linking adversity and pathology, neuroimaging research is crucial. Up till now studies in minors are scarce and differ in type of adversity or methodology. Almost all studies report lower cortical thickness, but in a broad variety of regions. In this study we investigated cortical thickness measures and clinical data in a well circumscribed group of adolescents with PTSD related to childhood sexual abuse (CSA) (N = 21) and a healthy non-traumatised control group (N = 21). The ventromedial PFC (vmPFC), ACC, insula, and middle/superior temporal gyrus were chosen as ROI's due to their respective roles in emotion and information processing. No significant effect of group was found for cortical thickness, surface area or volume in any of the ROIs. This is in line with the results of research in adult women with sexual abuse related PTSD, suggesting that this may be specific to this group, independent of age. Recent research points to differential biological and pathological consequences of different types of childhood adversity.

Classification using fractional anisotropy predicts conversion in genetic frontotemporal dementia, a proof of concept.

Frontotemporal dementia is a highly heritable and devastating neurodegenerative disease. About 10-20% of all frontotemporal dementia is caused by known pathogenic mutations, but a reliable tool to predict clinical conversion in mutation carriers is lacking. In this retrospective proof-of-concept case-control study, we investigate whether MRI-based and cognition-based classifiers can predict which mutation carriers from genetic frontotemporal dementia families will develop symptoms ('convert') within 4 years. From genetic frontotemporal dementia families, we included 42 presymptomatic frontotemporal dementia mutation carriers. We acquired anatomical, diffusion-weighted imaging, and resting-state functional MRI, as well as neuropsychological data. After 4 years, seven mutation carriers had converted to frontotemporal dementia ('converters'), while 35 had not ('non-converters'). We trained regularized logistic regression models on baseline MRI and cognitive data to predict conversion to frontotemporal dementia within 4 years, and quantified prediction performance using area under the receiver operating characteristic curves. The prediction model based on fractional anisotropy, with highest contribution of the forceps minor, predicted conversion to frontotemporal dementia beyond chance level (0.81 area under the curve, family-wise error corrected P = 0.025 versus chance level). Other MRI-based and cognitive features did not outperform chance level. Even in a small sample, fractional anisotropy predicted conversion in presymptomatic frontotemporal dementia mutation carriers beyond chance level. After validation in larger data sets, conversion prediction in genetic frontotemporal dementia may facilitate early recruitment into clinical trials.

Stuck in a negative me: fMRI study on the role of disturbed self-views in social feedback processing in borderline personality disorder.

BACKGROUND: Interpersonal difficulties in borderline personality disorder (BPD) could be related to the disturbed self-views of BPD patients. This study investigates affective and neural responses to positive and negative social feedback (SF) of BPD patients compared with healthy (HC) and low self-esteem (LSE) controls and how this relates to individual self-views. METHODS: BPD (N = 26), HC (N = 32), and LSE (N = 22) performed a SF task in a magnetic resonance imaging scanner. Participants received 15 negative, intermediate and positive evaluative feedback words putatively given by another participant and rated their mood and applicability of the words to the self. RESULTS: BPD had more negative self-views than HC and felt worse after negative feedback. Applicability of feedback was a less strong determinant of mood in BPD than HC. Increased precuneus activation was observed in HC to negative compared with positive feedback, whereas in BPD, this was similarly low for both valences. HC showed increased temporoparietal junction (TPJ) activation to positive v. negative feedback, while BPD showed more TPJ activation to negative feedback. The LSE group showed a different pattern of results suggesting that LSE cannot explain these findings in BPD. CONCLUSIONS: The negative self-views that BPD have, may obstruct critically examining negative feedback, resulting in lower mood. Moreover, where HC focus on the positive feedback (based on TPJ activation), BPD seem to focus more on negative feedback, potentially maintaining negative self-views. Better balanced self-views may make BPD better equipped to deal with potential negative feedback and more open to positive interactions.

Multimodal MRI of grey matter, white matter, and functional connectivity in cognitively healthy mutation carriers at risk for frontotemporal dementia and Alzheimer's disease.

BACKGROUND: Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are associated with divergent differences in grey matter volume, white matter diffusion, and functional connectivity. However, it is unknown at what disease stage these differences emerge. Here, we investigate whether divergent differences in grey matter volume, white matter diffusion, and functional connectivity are already apparent between cognitively healthy carriers of pathogenic FTD mutations, and cognitively healthy carriers at increased AD risk. METHODS: We acquired multimodal magnetic resonance imaging (MRI) brain scans in cognitively healthy subjects with (n=39) and without (n=36) microtubule-associated protein Tau (MAPT) or progranulin (GRN) mutations, and with (n=37) and without (n=38) apolipoprotein E ε4 (APOE4) allele. We evaluated grey matter volume using voxel-based morphometry, white matter diffusion using tract-based spatial statistics (TBSS), and region-to-network functional connectivity using dual regression in the default mode network and salience network. We tested for differences between the respective carriers and controls, as well as for divergence of those differences. For the divergence contrast, we additionally performed region-of-interest TBSS analyses in known areas of white matter diffusion differences between FTD and AD (i.e., uncinate fasciculus, forceps minor, and anterior thalamic radiation). RESULTS: MAPT/GRN carriers did not differ from controls in any modality. APOE4 carriers had lower fractional anisotropy than controls in the callosal splenium and right inferior fronto-occipital fasciculus, but did not show grey matter volume or functional connectivity differences. We found no divergent differences between both carrier-control contrasts in any modality, even in region-of-interest analyses. CONCLUSIONS: Concluding, we could not find differences suggestive of divergent pathways of underlying FTD and AD pathology in asymptomatic risk mutation carriers. Future studies should focus on asymptomatic mutation carriers that are closer to symptom onset to capture the first specific signs that may differentiate between FTD and AD.

Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison.

Neuroimaging MRI data in scientific research is increasingly pooled, but the reliability of such studies may be hampered by the use of different hardware elements. This might introduce bias, for example when cross-sectional studies pool data acquired with different head coils, or when longitudinal clinical studies change head coils halfway. In the present study, we aimed to estimate this possible bias introduced by using different head coils to create awareness and to avoid misinterpretation of results. We acquired, with both an 8 channel and 32 channel head coil, T1-weighted, diffusion tensor imaging and resting state fMRI images at 3T MRI (Philips Achieva) with stable acquisition parameters in a large group of cognitively healthy participants (n = 77). Standard analysis methods, i.e., voxel-based morphometry, tract-based spatial statistics and resting state functional network analyses, were used in a within-subject design to compare 8 and 32 channel head coil data. Signal-to-noise ratios (SNR) for both head coils showed similar ranges, although the 32 channel SNR profile was more homogeneous. Our data demonstrates specific patterns of gray and white matter volume differences between head coils (relative volume change of 6 to 9%), related to altered image contrast and therefore, altered tissue segmentation. White matter connectivity (fractional anisotropy and diffusivity measures) showed hemispherical dependent differences between head coils (relative connectivity change of 4 to 6%), and functional connectivity in resting state networks was higher using the 32 channel head coil in posterior cortical areas (relative change up to 27.5%). This study shows that, even when acquisition protocols are harmonized, the results of standardized analysis models can be severely affected by the use of different head coils. Researchers should be aware of this when combining multiple neuroimaging MRI datasets, to prevent coil-related bias and avoid misinterpretation of their findings.

When I relive a positive me: Vivid autobiographical memories facilitate autonoetic brain activation and enhance mood.

Autobiographical memory is vital for our well-being and therefore used in therapeutic interventions. However, not much is known about the (neural) processes by which reliving memories can have beneficial effects. This study investigates what brain activation patterns and memory characteristics facilitate the effectiveness of reliving positive autobiographical memories for mood and sense of self. Particularly, the role of vividness and autonoetic consciousness is studied. Participants (N = 47) with a wide range of trait self-esteem relived neutral and positive memories while their bold responses, experienced vividness of the memory, mood, and state self-esteem were recorded. More vivid memories related to better mood and activation in amygdala, hippocampus and insula, indicative of increased awareness of oneself (i.e., prereflective aspect of autonoetic consciousness). Lower vividness was associated with increased activation in the occipital lobe, PCC, and precuneus, indicative of a more distant mode of reliving. While individuals with lower trait self-esteem increased in state self-esteem, they showed less deactivation of the lateral occipital cortex during positive memories. In sum, the vividness of the memory seemingly distinguished a more immersed and more distant manner of memory reliving. In particular, when reliving positive memories higher vividness facilitated increased prereflective autonoetic consciousness, which likely is instrumental in boosting mood.

A multimodal MRI-based classification signature emerges just prior to symptom onset in frontotemporal dementia mutation carriers.

BACKGROUND: Multimodal MRI-based classification may aid early frontotemporal dementia (FTD) diagnosis. Recently, presymptomatic FTD mutation carriers, who have a high risk of developing FTD, were separated beyond chance level from controls using MRI-based classification. However, it is currently unknown how these scores from classification models progress as mutation carriers approach symptom onset. In this longitudinal study, we investigated multimodal MRI-based classification scores between presymptomatic FTD mutation carriers and controls. Furthermore, we contrasted carriers that converted during follow-up ('converters') and non-converting carriers ('non-converters'). METHODS: We acquired anatomical MRI, diffusion tensor imaging and resting-state functional MRI in 55 presymptomatic FTD mutation carriers and 48 healthy controls at baseline, and at 2, 4, and 6 years of follow-up as available. At each time point, FTD classification scores were calculated using a behavioural variant FTD classification model. Classification scores were tested in a mixed-effects model for mean differences and differences over time. RESULTS: Presymptomatic mutation carriers did not have higher classification score increase over time than controls (p=0.15), although carriers had higher FTD classification scores than controls on average (p=0.032). However, converters (n=6) showed a stronger classification score increase over time than non-converters (p<0.001). CONCLUSIONS: Our findings imply that presymptomatic FTD mutation carriers may remain similar to controls in terms of MRI-based classification scores until they are close to symptom onset. This proof-of-concept study shows the promise of longitudinal MRI data acquisition in combination with machine learning to contribute to early FTD diagnosis.

Cholinergic and serotonergic modulation of resting state functional brain connectivity in Alzheimer's disease.

Disruption of cholinergic and serotonergic neurotransmitter systems is associated with cognitive, emotional and behavioural symptoms of Alzheimer's disease (AD). To investigate the responsiveness of these systems in AD we measured the effects of a single-dose of the selective serotonin reuptake inhibitor citalopram and acetylcholinesterase inhibitor galantamine in 12 patients with AD and 12 age-matched controls on functional brain connectivity with resting state functional magnetic resonance imaging. In this randomized, double blind, placebo-controlled crossover study, functional magnetic resonance images were repeatedly obtained before and after dosing, resulting in a dataset of 432 scans. Connectivity maps of ten functional networks were extracted using a dual regression method and drug vs. placebo effects were compared between groups with a multivariate analysis with signals coming from cerebrospinal fluid and white matter as covariates at the subject level, and baseline and heart rate measurements as confound regressors in the higher-level analysis (at p < 0.05, corrected). A galantamine induced difference between groups was observed for the cerebellar network. Connectivity within the cerebellar network and between this network and the thalamus decreased after galantamine vs. placebo in AD patients, but not in controls. For citalopram, voxelwise network connectivity did not show significant group × treatment interaction effects. However, we found default mode network connectivity with the precuneus and posterior cingulate cortex to be increased in AD patients, which could not be detected within the control group. Further, in contrast to the AD patients, control subjects showed a consistent reduction in mean connectivity with all networks after administration of citalopram. Since AD has previously been characterized by reduced connectivity between the default mode network and the precuneus and posterior cingulate cortex, the effects of citalopram on the default mode network suggest a restoring potential of selective serotonin reuptake inhibitors in AD. The results of this study also confirm a change in cerebellar connections in AD, which is possibly related to cholinergic decline.