Safety, Tolerability, and Feasibility of Young Plasma Infusion in the Plasma for Alzheimer Symptom Amelioration Study: A Randomized Clinical Trial.

Importance: Young mouse plasma restores memory in aged mice, but, to our knowledge, the effects are unknown in patients with Alzheimer disease (AD). Objective: To assess the safety, tolerability, and feasibility of infusions of young fresh frozen plasma (yFFP) from donors age 18 to 30 years in patients with AD. Design, Setting, and Participants: The Plasma for Alzheimer Symptom Amelioration (PLASMA) study randomized 9 patients under a double-blind crossover protocol to receive 4 once-weekly infusions of either 1 unit (approximately 250 mL) of yFFP from male donors or 250 mL of saline, followed by a 6-week washout and crossover to 4 once-weekly infusions of an alternate treatment. Patients and informants were masked to treatment and subjective measurements. After an open-label amendment, 9 patients received 4 weekly yFFP infusions only and their subjective measurements were unmasked. Patients were enrolled solely at Stanford University, a tertiary academic medical center, from September 2014 to December 2016, when enrollment reached its target. Eighteen consecutive patients with probable mild to moderate AD dementia, a Mini-Mental State Examination (score of 12 to 24 inclusive), and an age of 50 to 90 years were enrolled. Thirty-one patients were screened and 13 were excluded: 11 failed the inclusion criteria and 2 declined to participate. Interventions: One unit of yFFP from male donors/placebo infused once weekly for 4 weeks. Main Outcome and Measures: The primary outcomes were the safety, tolerability, and feasibility of 4 weekly yFFP infusions. Safety end point analyses included all patients who received the study drug/placebo. Results: There was no difference in the age (mean [SD], 74.17 [7.96] years), sex (12 women [67%]), or baseline Mini-Mental State Examination score (mean [SD], 19.39 [3.24]) between the crossover (n = 9) and open-label groups (n = 9). There were no related serious adverse events. One patient discontinued participation because of urticaria and another because of an unrelated stroke. There was no statistically significant difference between the plasma (17 [94.4%]) and placebo (9 [100.0%]) cohorts for other adverse events, which were mild to moderate in severity. The most common adverse events in the plasma group included hypertension (3 [16.7%]), dizziness (2 [11.1%]), sinus bradycardia (3 [16.7%]), headache (3 [16.7%]), and sinus tachycardia (3 [16.7%]). The mean visit adherence (n = 18) was 86% (interquartile range, 87%-100%) and adherence, accounting for a reduction in the total visit requirement due to early patient discontinuation, was 96% (interquartile range, 89%-100%). Conclusions and Relevance: The yFFP treatment was safe, well tolerated, and feasible. The study's limitations were the small sample size, short duration, and change in study design. The results warrant further exploration in larger, double-blinded placebo-controlled clinical trials. Trial Registration: ClinicalTrials.gov Identifier: NCT02256306.

Functional parcellation using time courses of instantaneous connectivity.

Functional neuroimaging studies have led to understanding the brain as a collection of spatially segregated functional networks. It is thought that each of these networks is in turn composed of a set of distinct sub-regions that together support each network's function. Considering the sub-regions to be an essential part of the brain's functional architecture, several strategies have been put forward that aim at identifying the functional sub-units of the brain by means of functional parcellations. Current parcellation strategies typically employ a bottom-up strategy, creating a parcellation by clustering smaller units. We propose a novel top-down parcellation strategy, using time courses of instantaneous connectivity to subdivide an initial region of interest into sub-regions. We use split-half reproducibility to choose the optimal number of sub-regions. We apply our Instantaneous Connectivity Parcellation (ICP) strategy on high-quality resting-state FMRI data, and demonstrate the ability to generate parcellations for thalamus, entorhinal cortex, motor cortex, and subcortex including brainstem and striatum. We evaluate the subdivisions against available cytoarchitecture maps to show that our parcellation strategy recovers biologically valid subdivisions that adhere to known cytoarchitectural features.

A Bayesian spatial model for neuroimaging data based on biologically informed basis functions.

The dominant approach to neuroimaging data analysis employs the voxel as the unit of computation. While convenient, voxels lack biological meaning and their size is arbitrarily determined by the resolution of the image. Here, we propose a multivariate spatial model in which neuroimaging data are characterised as a linearly weighted combination of multiscale basis functions which map onto underlying brain nuclei or networks or nuclei. In this model, the elementary building blocks are derived to reflect the functional anatomy of the brain during the resting state. This model is estimated using a Bayesian framework which accurately quantifies uncertainty and automatically finds the most accurate and parsimonious combination of basis functions describing the data. We demonstrate the utility of this framework by predicting quantitative SPECT images of striatal dopamine function and we compare a variety of basis sets including generic isotropic functions, anatomical representations of the striatum derived from structural MRI, and two different soft functional parcellations of the striatum derived from resting-state fMRI (rfMRI). We found that a combination of ∼50 multiscale functional basis functions accurately represented the striatal dopamine activity, and that functional basis functions derived from an advanced parcellation technique known as Instantaneous Connectivity Parcellation (ICP) provided the most parsimonious models of dopamine function. Importantly, functional basis functions derived from resting fMRI were more accurate than both structural and generic basis sets in representing dopamine function in the striatum for a fixed model order. We demonstrate the translational validity of our framework by constructing classification models for discriminating parkinsonian disorders and their subtypes. Here, we show that ICP approach is the only basis set that performs well across all comparisons and performs better overall than the classical voxel-based approach. This spatial model constitutes an elegant alternative to voxel-based approaches in neuroimaging studies; not only are their atoms biologically informed, they are also adaptive to high resolutions, represent high dimensions efficiently, and capture long-range spatial dependencies, which are important and challenging objectives for neuroimaging data.

Functional anatomy of the human thalamus at rest.

In the present work, we used resting state-fMRI to investigate the functional anatomy of the thalamus at rest by applying an Independent Component Analysis to delineate thalamic substructures into stable and reproducible parcels for the left and right thalamus. We determined 15 functionally distinct thalamic parcels, which differed in laterality and size but exhibited a correspondence with 18 cytoarchitectonally defined nuclei. We characterized their structural connectivity in determining DWI based cortical fiber pathways and found selected projections to different cortical areas. In contrast, the functional connections of these parcels were not confined to certain cortical areas or lobes. We, finally evaluated cortical projections and found particular subcortical and cortical pattern for each parcel, which partly exhibited a correspondence with the thalamo-cortical connectivity maps of the mouse.

Attention-Deficit/Hyperactivity Disorder symptoms coincide with altered striatal connectivity.

BACKGROUND: Cortico-striatal network dysfunction in attention-deficit/hyperactivity disorder (ADHD) is generally investigated by comparing functional connectivity of the main striatal sub-regions (i.e., putamen, caudate, and nucleus accumbens) between an ADHD and a control group. However, dimensional analyses based on continuous symptom measures might help to parse the high phenotypic heterogeneity in ADHD. Here, we focus on functional segregation of regions in the striatum and investigate cortico-striatal networks using both categorical and dimensional measures of ADHD. METHODS: We computed whole-brain functional connectivity for six striatal sub-regions that resulted from a novel functional parcellation technique. We compared functional connectivity maps between adolescents with ADHD (N=169) and healthy controls (N=122), and investigated dimensional ADHD-related measures by relating striatal connectivity to ADHD symptom scores (N=444). Finally, we examined whether altered connectivity of striatal sub-regions related to motor and cognitive performance. RESULTS: We observed no case-control differences in functional connectivity patterns of the six striatal networks. In contrast, inattention and hyperactivity/impulsivity symptom scores were associated with increases in functional connectivity in the networks of posterior putamen and ventral caudate. Increased connectivity of posterior putamen with motor cortex and cerebellum was associated with decreased motor performance. CONCLUSIONS: Our findings support hypotheses of cortico-striatal network dysfunction in ADHD by demonstrating that dimensional symptom measures are associated with changes in functional connectivity. These changes were not detected by categorical ADHD versus control group analyses, highlighting the important contribution of dimensional analyses to investigating the neurobiology of ADHD.

Altered functional connectivity of the amygdaloid input nuclei in adolescents and young adults with autism spectrum disorder: a resting state fMRI study.

BACKGROUND: Amygdala dysfunction is hypothesized to underlie the social deficits observed in autism spectrum disorders (ASD). However, the neurobiological basis of this hypothesis is underspecified because it is unknown whether ASD relates to abnormalities of the amygdaloid input or output nuclei. Here, we investigated the functional connectivity of the amygdaloid social-perceptual input nuclei and emotion-regulation output nuclei in ASD versus controls. METHODS: We collected resting state functional magnetic resonance imaging (fMRI) data, tailored to provide optimal sensitivity in the amygdala as well as the neocortex, in 20 adolescents and young adults with ASD and 25 matched controls. We performed a regular correlation analysis between the entire amygdala (EA) and the whole brain and used a partial correlation analysis to investigate whole-brain functional connectivity uniquely related to each of the amygdaloid subregions. RESULTS: Between-group comparison of regular EA correlations showed significantly reduced connectivity in visuospatial and superior parietal areas in ASD compared to controls. Partial correlation analysis revealed that this effect was driven by the left superficial and right laterobasal input subregions, but not the centromedial output nuclei. CONCLUSIONS: These results indicate reduced connectivity of specifically the amygdaloid sensory input channels in ASD, suggesting that abnormal amygdalo-cortical connectivity can be traced down to the socio-perceptual pathways.

The Quest for EEG Power Band Correlation with ICA Derived fMRI Resting State Networks.

The neuronal underpinnings of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) resting state networks (RSNs) are still unclear. To investigate the underlying mechanisms, specifically the relation to the electrophysiological signal, we used simultaneous recordings of electroencephalography (EEG) and fMRI during eyes open resting state (RS). Earlier studies using the EEG signal as independent variable show inconclusive results, possibly due to variability in the temporal correlations between RSNs and power in the low EEG frequency bands, as recently reported (Goncalves et al., 2006, 2008; Meyer et al., 2013). In this study we use three different methods including one that uses RSN timelines as independent variable to explore the temporal relationship of RSNs and EEG frequency power in eyes open RS in detail. The results of these three distinct analysis approaches support the hypothesis that the correlation between low EEG frequency power and BOLD RSNs is instable over time, at least in eyes open RS.

Electrophysiological correlation patterns of resting state networks in single subjects: a combined EEG-fMRI study.

With combined EEG-fMRI a powerful combination of methods was developed in the last decade that seems promising for answering fundamental neuroscientific questions by measuring functional processes of the human brain simultaneously with two complementary modalities. Recently, resting state networks (RSNs), representing brain regions of coherent BOLD fluctuations, raised major interest in the neuroscience community. Since RSNs are reliably found across subjects and reflect task related networks, changes in their characteristics might give insight to neuronal changes or damage, promising a broad range of scientific and clinical applications. The question of how RSNs are linked to electrophysiological signal characteristics becomes relevant in this context. In this combined EEG-fMRI study we investigated the relationship of RSNs and their correlated electrophysiological signals [electrophysiological correlation patterns (ECPs)] using a long (34 min) resting state scan per subject. This allowed us to study ECPs on group as well as on single subject level, and to examine the temporal stability of ECPs within each subject. We found that the correlation patterns obtained on group level show a large inter-subject variability. During the long scan the ECPs within a subject show temporal fluctuations, which we interpret as a result of the complex temporal dynamic of the RSNs.