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.

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.

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.

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.

Longitudinal multimodal MRI as prognostic and diagnostic biomarker in presymptomatic familial frontotemporal dementia.

Developing and validating sensitive biomarkers for the presymptomatic stage of familial frontotemporal dementia is an important step in early diagnosis and for the design of future therapeutic trials. In the longitudinal Frontotemporal Dementia Risk Cohort, presymptomatic mutation carriers and non-carriers from families with familial frontotemporal dementia due to microtubule-associated protein tau (MAPT) and progranulin (GRN) mutations underwent a clinical assessment and multimodal MRI at baseline, 2-, and 4-year follow-up. Of the cohort of 73 participants, eight mutation carriers (three GRN, five MAPT) developed clinical features of frontotemporal dementia ('converters'). Longitudinal whole-brain measures of white matter integrity (fractional anisotropy) and grey matter volume in these converters (n = 8) were compared with healthy mutation carriers ('non-converters'; n = 35) and non-carriers (n = 30) from the same families. We also assessed the prognostic performance of decline within white matter and grey matter regions of interest by means of receiver operating characteristic analyses followed by stepwise logistic regression. Longitudinal whole-brain analyses demonstrated lower fractional anisotropy values in extensive white matter regions (genu corpus callosum, forceps minor, uncinate fasciculus, and superior longitudinal fasciculus) and smaller grey matter volumes (prefrontal, temporal, cingulate, and insular cortex) over time in converters, present from 2 years before symptom onset. White matter integrity loss of the right uncinate fasciculus and genu corpus callosum provided significant classifiers between converters, non-converters, and non-carriers. Converters' within-individual disease trajectories showed a relatively gradual onset of clinical features in MAPT, whereas GRN mutations had more rapid changes around symptom onset. MAPT converters showed more decline in the uncinate fasciculus than GRN converters, and more decline in the genu corpus callosum in GRN than MAPT converters. Our study confirms the presence of spreading predominant frontotemporal pathology towards symptom onset and highlights the value of multimodal MRI as a prognostic biomarker in familial frontotemporal dementia.

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.

Aberrant memory system connectivity and working memory performance in subjective cognitive decline.

Subjective cognitive decline, a perceived worsening of cognitive functioning without objective deficit on assessment, could indicate incipient dementia. However, the neural correlates of subjective cognitive decline as assessed by magnetic resonance imaging remain somewhat unclear. Here, we evaluated differences in functional connectivity across memory regions, and cognitive performance, between healthy older adults aged 50 to 85 with (n = 35, Age = 68.5 ±â€¯7.7, 22 female), and without (n = 48, Age = 67.0 ±â€¯8.8, 29 female) subjective cognitive decline. We also evaluated neurite density, fractional anisotropy, and mean diffusivity of the parahippocampal cingulum, cingulate gyrus cingulum, and uncinate fiber bundles in a subsample of participants (n = 37). Participants with subjective cognitive decline displayed lower average functional connectivity across regions of a putative posterior memory system, and lower retrosplenial-precuneus functional connectivity specifically, than those without memory complaints. Furthermore, participants with subjective cognitive decline performed poorer than controls on visual working memory. However, groups did not differ in cingulum or uncinate diffusion measures. Our results show differences in functional connectivity and visual working memory in participants with subjective cognitive decline that could indicate potential incipient dementia.

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.

Detection of mild cognitive impairment in a community-dwelling population using quantitative, multiparametric MRI-based classification.

Early and accurate mild cognitive impairment (MCI) detection within a heterogeneous, nonclinical population is needed to improve care for persons at risk of developing dementia. Magnetic resonance imaging (MRI)-based classification may aid early diagnosis of MCI, but has only been applied within clinical cohorts. We aimed to determine the generalizability of MRI-based classification probability scores to detect MCI on an individual basis within a general population. To determine classification probability scores, an AD, mild-AD, and moderate-AD detection model were created with anatomical and diffusion MRI measures calculated from a clinical Alzheimer's Disease (AD) cohort and subsequently applied to a population-based cohort with 48 MCI and 617 normal aging subjects. Each model's ability to detect MCI was quantified using area under the receiver operating characteristic curve (AUC) and compared with an MCI detection model trained and applied to the population-based cohort. The AD-model and mild-AD identified MCI from controls better than chance level (AUC = 0.600, p = 0.025; AUC = 0.619, p = 0.008). In contrast, the moderate-AD-model was not able to separate MCI from normal aging (AUC = 0.567, p = 0.147). The MCI-model was able to separate MCI from controls better than chance (p = 0.014) with mean AUC values comparable with the AD-model (AUC = 0.611, p = 1.0). Within our population-based cohort, classification models detected MCI better than chance. Nevertheless, classification performance rates were moderate and may be insufficient to facilitate robust MRI-based MCI detection on an individual basis. Our data indicate that multiparametric MRI-based classification algorithms, that are effective in clinical cohorts, may not straightforwardly translate to applications in a general population.

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.

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.

Serotonergic and cholinergic modulation of functional brain connectivity: A comparison between young and older adults.

Aging is accompanied by changes in neurotransmission. To advance our understanding of how aging modifies specific neural circuitries, we examined serotonergic and cholinergic stimulation with resting state functional magnetic resonance imaging (RS-fMRI) in young and older adults. The instant response to the selective serotonin reuptake inhibitor citalopram (30 mg) and the acetylcholinesterase inhibitor galantamine (8 mg) was measured in 12 young and 17 older volunteers during a randomized, double blind, placebo-controlled, crossover study. A powerful dataset consisting of 522 RS-fMRI scans was obtained by acquiring multiple scans per subject before and after drug administration. Group × treatment interaction effects on voxelwise connectivity with ten functional networks were investigated (p < .05, FWE-corrected) using a non-parametric multivariate analysis technique with cerebrospinal fluid, white matter, heart rate and baseline measurements as covariates. Both groups showed a decrease in sensorimotor network connectivity after citalopram administration. The comparable findings after citalopram intake are possibly due to relatively similar serotonergic systems in the young and older subjects. Galantamine altered connectivity between the occipital visual network and regions that are implicated in learning and memory in the young subjects. The lack of a cholinergic response in the elderly might relate to the well-known association between cognitive and cholinergic deterioration at older age.

A comprehensive analysis of resting state fMRI measures to classify individual patients with Alzheimer's disease.

Alzheimer's disease (AD) patients show altered patterns of functional connectivity (FC) on resting state functional magnetic resonance imaging (RSfMRI) scans. It is yet unclear which RSfMRI measures are most informative for the individual classification of AD patients. We investigated this using RSfMRI scans from 77 AD patients (MMSE = 20.4 ± 4.5) and 173 controls (MMSE = 27.5 ± 1.8). We calculated i) FC matrices between resting state components as obtained with independent component analysis (ICA), ii) the dynamics of these FC matrices using a sliding window approach, iii) the graph properties (e.g., connection degree, and clustering coefficient) of the FC matrices, and iv) we distinguished five FC states and administered how long each subject resided in each of these five states. Furthermore, for each voxel we calculated v) FC with 10 resting state networks using dual regression, vi) FC with the hippocampus, vii) eigenvector centrality, and viii) the amplitude of low frequency fluctuations (ALFF). These eight measures were used separately as predictors in an elastic net logistic regression, and combined in a group lasso logistic regression model. We calculated the area under the receiver operating characteristic curve plots (AUC) to determine classification performance. The AUC values ranged between 0.51 and 0.84 and the highest were found for the FC matrices (0.82), FC dynamics (0.84) and ALFF (0.82). The combination of all measures resulted in an AUC of 0.85. We show that it is possible to obtain moderate to good AD classification using RSfMRI scans. FC matrices, FC dynamics and ALFF are most discriminative and the combination of all the resting state measures improves classification accuracy slightly.

Catecholaminergic Neuromodulation Shapes Intrinsic MRI Functional Connectivity in the Human Brain.

UNLABELLED: The brain commonly exhibits spontaneous (i.e., in the absence of a task) fluctuations in neural activity that are correlated across brain regions. It has been established that the spatial structure, or topography, of these intrinsic correlations is in part determined by the fixed anatomical connectivity between regions. However, it remains unclear which factors dynamically sculpt this topography as a function of brain state. Potential candidate factors are subcortical catecholaminergic neuromodulatory systems, such as the locus ceruleus-norepinephrine system, which send diffuse projections to most parts of the forebrain. Here, we systematically characterized the effects of endogenous central neuromodulation on correlated fluctuations during rest in the human brain. Using a double-blind placebo-controlled crossover design, we pharmacologically increased synaptic catecholamine levels by administering atomoxetine, an NE transporter blocker, and examined the effects on the strength and spatial structure of resting-state MRI functional connectivity. First, atomoxetine reduced the strength of inter-regional correlations across three levels of spatial organization, indicating that catecholamines reduce the strength of functional interactions during rest. Second, this modulatory effect on intrinsic correlations exhibited a substantial degree of spatial specificity: the decrease in functional connectivity showed an anterior-posterior gradient in the cortex, depended on the strength of baseline functional connectivity, and was strongest for connections between regions belonging to distinct resting-state networks. Thus, catecholamines reduce intrinsic correlations in a spatially heterogeneous fashion. We conclude that neuromodulation is an important factor shaping the topography of intrinsic functional connectivity. SIGNIFICANCE STATEMENT: The human brain shows spontaneous activity that is strongly correlated across brain regions. The factors that dynamically sculpt these inter-regional correlation patterns are poorly understood. Here, we test the hypothesis that they are shaped by the catecholaminergic neuromodulators norepinephrine and dopamine. We pharmacologically increased synaptic catecholamine levels and measured the resulting changes in intrinsic fMRI functional connectivity. At odds with common understanding of catecholamine function, we found (1) overall reduced inter-regional correlations across several levels of spatial organization; and (2) a remarkable spatial specificity of this modulatory effect. Our results identify norepinephrine and dopamine as important factors shaping intrinsic functional connectivity and advance our understanding of catecholamine function in the central nervous system.

Individual classification of Alzheimer's disease with diffusion magnetic resonance imaging.

Diffusion magnetic resonance imaging (MRI) is a powerful non-invasive method to study white matter integrity, and is sensitive to detect differences in Alzheimer's disease (AD) patients. Diffusion MRI may be able to contribute towards reliable diagnosis of AD. We used diffusion MRI to classify AD patients (N=77), and controls (N=173). We use different methods to extract information from the diffusion MRI data. First, we use the voxel-wise diffusion tensor measures that have been skeletonised using tract based spatial statistics. Second, we clustered the voxel-wise diffusion measures with independent component analysis (ICA), and extracted the mixing weights. Third, we determined structural connectivity between Harvard Oxford atlas regions with probabilistic tractography, as well as graph measures based on these structural connectivity graphs. Classification performance for voxel-wise measures ranged between an AUC of 0.888, and 0.902. The ICA-clustered measures ranged between an AUC of 0.893, and 0.920. The AUC for the structural connectivity graph was 0.900, while graph measures based upon this graph ranged between an AUC of 0.531, and 0.840. All measures combined with a sparse group lasso resulted in an AUC of 0.896. Overall, fractional anisotropy clustered into ICA components was the best performing measure. These findings may be useful for future incorporation of diffusion MRI into protocols for AD classification, or as a starting point for early detection of AD using diffusion MRI.

Time related effects on functional brain connectivity after serotonergic and cholinergic neuromodulation.

Psychopharmacological research, if properly designed, may offer insight into both timing and area of effect, increasing our understanding of the brain's neurotransmitter systems. For that purpose, the acute influence of the selective serotonin reuptake inhibitor citalopram (30 mg) and the acetylcholinesterase inhibitor galantamine (8 mg) was repeatedly measured in 12 healthy young volunteers with resting state functional magnetic resonance imaging (RS-fMRI). Eighteen RS-fMRI scans were acquired per subject during this randomized, double blind, placebo-controlled, crossover study. Within-group comparisons of voxelwise functional connectivity with 10 functional networks were examined (P < 0.05, FWE-corrected) using a non-parametric multivariate approach with cerebrospinal fluid, white matter, heart rate, and baseline measurements as covariates. Although both compounds did not change cognitive performance on several tests, significant effects were found on connectivity with multiple resting state networks. Serotonergic stimulation primarily reduced connectivity with the sensorimotor network and structures that are related to self-referential mechanisms, whereas galantamine affected networks and regions that are more involved in learning, memory, and visual perception and processing. These results are consistent with the serotonergic and cholinergic trajectories and their functional relevance. In addition, this study demonstrates the power of using repeated measures after drug administration, which offers the chance to explore both combined and time specific effects. Hum Brain Mapp 38:308-325, 2017. © 2016 Wiley Periodicals, Inc.

Biomarkers, designs, and interpretations of resting-state fMRI in translational pharmacological research: A review of state-of-the-Art, challenges, and opportunities for studying brain chemistry.

A decade of research and development in resting-state functional MRI (RSfMRI) has opened new translational and clinical research frontiers. This review aims to bridge between technical and clinical researchers who seek reliable neuroimaging biomarkers for studying drug interactions with the brain. About 85 pharma-RSfMRI studies using BOLD signal (75% of all) or arterial spin labeling (ASL) were surveyed to investigate the acute effects of psychoactive drugs. Experimental designs and objectives include drug fingerprinting dose-response evaluation, biomarker validation and calibration, and translational studies. Common biomarkers in these studies include functional connectivity, graph metrics, cerebral blood flow and the amplitude and spectrum of BOLD fluctuations. Overall, RSfMRI-derived biomarkers seem to be sensitive to spatiotemporal dynamics of drug interactions with the brain. However, drugs cause both central and peripheral effects, thus exacerbate difficulties related to biological confounds, structured noise from motion and physiological confounds, as well as modeling and inference testing. Currently, these issues are not well explored, and heterogeneities in experimental design, data acquisition and preprocessing make comparative or meta-analysis of existing reports impossible. A unifying collaborative framework for data-sharing and data-mining is thus necessary for investigating the commonalities and differences in biomarker sensitivity and specificity, and establishing guidelines. Multimodal datasets including sham-placebo or active control sessions and repeated measurements of various psychometric, physiological, metabolic and neuroimaging phenotypes are essential for pharmacokinetic/pharmacodynamic modeling and interpretation of the findings. We provide a list of basic minimum and advanced options that can be considered in design and analyses of future pharma-RSfMRI studies. Hum Brain Mapp 38:2276-2325, 2017. © 2017 Wiley Periodicals, Inc.

Structural and functional connectivity in children and adolescents with and without attention deficit/hyperactivity disorder.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD) has frequently been associated with changes in resting-state functional connectivity, and decreased white matter (WM) integrity. In the current study, we investigated functional connectivity within Default Mode and frontal control resting-state networks (RSNs) in children with and without ADHD. We hypothesized the RSNs of interest would show a pattern of impaired functional integration and segregation and corresponding changes in WM structure. METHODS: Resting-state fMRI and diffusion-weighted imaging data were acquired from 35 participants with ADHD and 36 matched typically developing peers, aged 6 through 18 years. Functional connectivity was assessed using independent component analysis. Network topology and WM connectivity were further investigated using graph theoretical measures and tract-based spatial statistics (TBSS). RESULTS: Resting-state fMRI analyses showed increased functional connectivity in right inferior frontal gyrus (IFG), and bilateral medial prefrontal cortex (mPFC) within the Default Mode and frontal control networks. Furthermore, a more diffuse spatial pattern of functional connectivity was found in children with ADHD. We found no group differences in structural connectivity as assessed with TBSS or graph theoretical measures. CONCLUSIONS: Resting-state networks show a more diffuse pattern of connectivity in children with ADHD. The increases in functional connectivity in right IFG and bilateral mPFC in children with ADHD may reflect reduced or delayed functional segregation of prefrontal brain regions. As these functional changes were not accompanied by changes in WM, they may precede the development of the frequently reported changes in WM structure.

Abnormal functional architecture of amygdala-centered networks in adolescent posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) is a prevalent, debilitating, and difficult to treat psychiatric disorder. Very little is known of how PTSD affects neuroplasticity in the developing adolescent brain. Whereas multiple lines of research implicate amygdala-centered network dysfunction in the pathophysiology of adult PTSD, no study has yet examined the functional architecture of amygdala subregional networks in adolescent PTSD. Using intrinsic functional connectivity analysis, we investigated functional connectivity of the basolateral (BLA) and centromedial (CMA) amygdala in 19 sexually abused adolescents with PTSD relative to 23 matched controls. Additionally, we examined whether altered amygdala subregional connectivity coincides with abnormal grey matter volume of the amygdaloid complex. Our analysis revealed abnormal amygdalar connectivity and morphology in adolescent PTSD patients. More specifically, PTSD patients showed diminished right BLA connectivity with a cluster including dorsal and ventral portions of the anterior cingulate and medial prefrontal cortices (p < 0.05, corrected). In contrast, PTSD patients showed increased left CMA connectivity with a cluster including the orbitofrontal and subcallosal cortices (p < 0.05, corrected). Critically, these connectivity changes coincided with diminished grey matter volume within BLA and CMA subnuclei (p < 0.05, corrected), with CMA connectivity shifts additionally relating to more severe symptoms of PTSD. These findings provide unique insights into how perturbations in major amygdalar circuits could hamper fear regulation and drive excessive acquisition and expression of fear in PTSD. As such, they represent an important step toward characterizing the neurocircuitry of adolescent PTSD, thereby informing the development of reliable biomarkers and potential therapeutic targets.

Combining multiple anatomical MRI measures improves Alzheimer's disease classification.

Several anatomical MRI markers for Alzheimer's disease (AD) have been identified. Hippocampal volume, cortical thickness, and grey matter density have been used successfully to discriminate AD patients from controls. These anatomical MRI measures have so far mainly been used separately. The full potential of anatomical MRI scans for AD diagnosis might thus not yet have been used optimally. In this study, we therefore combined multiple anatomical MRI measures to improve diagnostic classification of AD. For 21 clinically diagnosed AD patients and 21 cognitively normal controls, we calculated (i) cortical thickness, (ii) cortical area, (iii) cortical curvature, (iv) grey matter density, (v) subcortical volumes, and (vi) hippocampal shape. These six measures were used separately and combined as predictors in an elastic net logistic regression. We made receiver operating curve plots and calculated the area under the curve (AUC) to determine classification performance. AUC values for the single measures ranged from 0.67 (cortical thickness) to 0.94 (grey matter density). The combination of all six measures resulted in an AUC of 0.98. Our results demonstrate that the different anatomical MRI measures contain complementary information. A combination of these measures may therefore improve accuracy of AD diagnosis in clinical practice. Hum Brain Mapp 37:1920-1929, 2016. © 2016 Wiley Periodicals, Inc.