Functional Magnetic Resonance Imaging in Alzheimer' Disease Drug Development.

While now commonly applied for studying human brain function the value of functional magnetic resonance imaging in drug development has only recently been recognized. Here we describe the different functional magnetic resonance imaging techniques applied in Alzheimer's disease drug development with their applications, implementation guidelines, and potential pitfalls

The effect of risperidone on reward-related brain activity is robust to drug-induced vascular changes

Dopamine (DA) mediated brain activity is intimately linked to reward-driven cerebralresponses, while aberrant reward processing has been implicated in several psychiatricdisorders. fMRI has been a valuable tool in understanding the mechanism by which DAmodulators alter reward-driven responses and how they may exert their therapeuticeffect. However, the potential effects of a pharmacological compound on aspects ofneurovascular coupling may cloud the interpretability of the BOLD contrast. Here, weassess the effects of risperidone on reward driven BOLD signals produced by rewardanticipation and outcome, while attempting to control for potential drug effects onregional cerebral blood flow (CBF) and cerebrovascular reactivity (CVR). Healthy malevolunteers (n = 21) each received a single oral dose of either 0.5 mg, 2 mg of risperi-done or placebo in a double-blind, placebo-controlled, randomised, three-period cross-over study design. Participants underwent fMRI scanning while performing the widelyused Monetary Incentive Delay (MID) task to assess drug impact on reward function.Measures of CBF (Arterial Spin Labelling) and breath-hold challenge induced BOLD sig-nal changes (as a proxy for CVR) were also acquired and included as covariates. Risperi-done produced divergent, dose-dependent effects on separate phases of rewardprocessing, even after controlling for potential nonneuronal influences on the BOLDsignal. These data suggest the D2 antagonist risperidone has a wide-ranging influenceon DA-mediated reward function independent of nonneuronal factors. We also illus-trate that assessment of potential vascular confounds on the BOLD signal may beadvantageous when investigating CNS drug action and advocate for the inclusion ofthese additional measures into future study designs

The effect of risperidone on reward‐related brain activity is robust to drug‐induced vascular changes

Dopamine (DA) mediated brain activity is intimately linked to reward-driven cerebralresponses, while aberrant reward processing has been implicated in several psychiatricdisorders. fMRI has been a valuable tool in understanding the mechanism by which DAmodulators alter reward-driven responses and how they may exert their therapeuticeffect. However, the potential effects of a pharmacological compound on aspects ofneurovascular coupling may cloud the interpretability of the BOLD contrast. Here, weassess the effects of risperidone on reward driven BOLD signals produced by rewardanticipation and outcome, while attempting to control for potential drug effects onregional cerebral blood flow (CBF) and cerebrovascular reactivity (CVR). Healthy malevolunteers (n = 21) each received a single oral dose of either 0.5 mg, 2 mg of risperi-done or placebo in a double-blind, placebo-controlled, randomised, three-period cross-over study design. Participants underwent fMRI scanning while performing the widelyused Monetary Incentive Delay (MID) task to assess drug impact on reward function.Measures of CBF (Arterial Spin Labelling) and breath-hold challenge induced BOLD sig-nal changes (as a proxy for CVR) were also acquired and included as covariates. Risperi-done produced divergent, dose-dependent effects on separate phases of rewardprocessing, even after controlling for potential nonneuronal influences on the BOLDsignal. These data suggest the D2 antagonist risperidone has a wide-ranging influenceon DA-mediated reward function independent of nonneuronal factors. We also illus-trate that assessment of potential vascular confounds on the BOLD signal may beadvantageous when investigating CNS drug action and advocate for the inclusion ofthese additional measures into future study designs

JuSpace:A tool for spatial correlation analyses of magnetic resonance imaging data with nuclear imaging derived neurotransmitter maps

Recent studies have shown that drug‐induced spatial alteration patterns in resting state functional activity as measured using magnetic resonance imaging (rsfMRI) are associated with the distribution of specific receptor systems targeted by respective compounds. Based on this approach, we introduce a toolbox (JuSpace) allowing for cross‐modal correlation of MRI‐based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, and GABAergic (gamma‐aminobutric acid) neurotransmission. We apply JuSpace to two datasets covering Parkinson's disease patients (PD) and risperidone‐induced changes in rsfMRI and cerebral blood flow (CBF). Consistently with the predominant neurodegeneration of dopaminergic and serotonergic system in PD, we find significant spatial associations between rsfMRI activity alterations in PD and dopaminergic (D2) and serotonergic systems (5‐HT1b). Risperidone induced CBF alterations were correlated with its main targets in serotonergic and dopaminergic systems. JuSpace provides a biologically meaningful framework for linking neuroimaging to underlying neurotransmitter information

Patients with autism spectrum disorders display reproducible functional connectivity alterations

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Preserved Navigation abilities and Spatio-Temporal Memory in individuals with Autism Spectrum Disorder

International audienceCerebellar abnormalities have been reported in autism spectrum disorder (ASD). Beyond its role in hallmark features of ASD, the cerebellum and its connectivity with forebrain structures also play a role in navigation. However, the current understanding of navigation abilities in ASD is equivocal, as is the impact of the disorder on the functional anatomy of the cerebellum. In the present study, we investigated the navigation behavior of a population of ASD and typically developing (TD) adults related to their brain anatomy as assessed by structural and functional MRI at rest. We used the Starmaze task, which permits assessing and distinguishing two complex navigation behaviors, one based on allocentric and the other on egocentric learning of a route with multiple decision points. Compared to TD controls, individuals with ASD showed similar exploration, learning, and strategy performance and preference. In addition, there was no difference in the structural or functional anatomy of the cerebellar circuits involved in navigation between the two groups. The findings of our work suggest that navigation abilities, spatio-temporal memory, and their underlying circuits are preserved in individuals with ASD

Preserved Navigation abilities and Spatio-Temporal Memory in individuals with Autism Spectrum Disorder

International audienceCerebellar abnormalities have been reported in autism spectrum disorder (ASD). Beyond its role in hallmark features of ASD, the cerebellum and its connectivity with forebrain structures also play a role in navigation. However, the current understanding of navigation abilities in ASD is equivocal, as is the impact of the disorder on the functional anatomy of the cerebellum. In the present study, we investigated the navigation behavior of a population of ASD and typically developing (TD) adults related to their brain anatomy as assessed by structural and functional MRI at rest. We used the Starmaze task, which permits assessing and distinguishing two complex navigation behaviors, one based on allocentric and the other on egocentric learning of a route with multiple decision points. Compared to TD controls, individuals with ASD showed similar exploration, learning, and strategy performance and preference. In addition, there was no difference in the structural or functional anatomy of the cerebellar circuits involved in navigation between the two groups. The findings of our work suggest that navigation abilities, spatio-temporal memory, and their underlying circuits are preserved in individuals with ASD

Cerebral blood flow and cardiovascular risk effects on resting brain regional homogeneity

Regional homogeneity (ReHo) is a measure of local functional brain connectivity that has been reported to be altered in a wide range of neuropsychiatric disorders. Computed from brain resting-state functional MRI time series, ReHo is also sensitive to fluctuations in cerebral blood flow (CBF) that in turn may be influenced by cerebrovascular health. We accessed cerebrovascular health with Framingham cardiovascular risk score (FCVRS). We hypothesize that ReHo signal may be influenced by regional CBF; and that these associations can be summarized as FCVRS→CBF→ReHo. We used three independent samples to test this hypothesis. A test-retest sample of N = 30 healthy volunteers was used for test-retest evaluation of CBF effects on ReHo. Amish Connectome Project (ACP) sample (N = 204, healthy individuals) was used to evaluate association between FCVRS and ReHo and testing if the association diminishes given CBF. The UKBB sample (N = 6,285, healthy participants) was used to replicate the effects of FCVRS on ReHo. We observed strong CBF→ReHo links (p<2.5 × 10−3) using a three-point longitudinal sample. In ACP sample, marginal and partial correlations analyses demonstrated that both CBF and FCVRS were significantly correlated with the whole-brain average (p<10−6) and regional ReHo values, with the strongest correlations observed in frontal, parietal, and temporal areas. Yet, the association between ReHo and FCVRS became insignificant once the effect of CBF was accounted for. In contrast, CBF→ReHo remained significantly linked after adjusting for FCVRS and demographic covariates (p<10−6). Analysis in N = 6,285 replicated the FCVRS→ReHo effect (p = 2.7 × 10−27). In summary, ReHo alterations in health and neuropsychiatric illnesses may be partially driven by region-specific variability in CBF, which is, in turn, influenced by cardiovascular factors

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis.

BACKGROUND: Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. METHODS: We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split). RESULTS: In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. LIMITATIONS: The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects. CONCLUSIONS: This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

BackgroundUnderstanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed.MethodsWe quantified resting state EEG alpha peak metrics, power spectrum (PS, 2–32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants’ MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%–30% split).ResultsIn the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52–0.62, specificity 0.59–0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset.LimitationsThe statistical power to detect weak effects—of the magnitude of those found in the training dataset—in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset’s effects.ConclusionsThis suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects