Urinary incontinence-related effects on functional connectivity circuits in persons with Parkinson's disease.

INTRODUCTION: Urinary incontinence (UI) is a common and disruptive symptom of Parkinson's disease (PD). This study aimed to identify neural correlates associated with UI among PD patients with UI (UI-PD) compared to those PD patients without UI (nonUI-PD) with the expectation of demonstrating increased functional connectivity (FC) between areas in the striatum and limbic system and decreased FC in executive areas. METHODS: rsfMRI and T1w data (n = 119) were retrieved from the Parkinson's Progression Markers Initiative (PPMI). Resting-state FC analyses assessed temporal covariance with anterior cingulate gyrus, precuneus, and putamen seed regions. RESULTS: The UI-PD group (n = 32, 16 females) showed significantly greater positive FC between the bilateral putamen seed and the right caudate and right thalamus (p < 0.01), relative to individuals with PD but who did not have UI (n = 87, 18 females). The UI-PD group showed greater negative FC between the anterior cingulate seed and right angular gyrus (p < 0.01) relative to nonUI-PD. CONCLUSION: Individuals with PD and UI display stronger FC within neural circuits likely affected by PD such as between the putamen and caudate, as well as within those associated with brain bladder control, compared to persons with PD and without UI. Clinical application based on this study's results can provide greater discernment of treatment strategies for UI-PD patients.

Social and leisure activity are associated with attenuated cortical loss in behavioral variant frontotemporal degeneration.

Behavioral variant frontotemporal degeneration (bvFTD) is clinically characterized by progressive decline in social and executive domains. Previous work suggests that early lifestyle factors such as education and occupational attainment may relate to structural integrity and moderate the rate of cognitive decline in bvFTD, but the role of other cognitively stimulating activities is understudied. We sought to investigate the effect of such activities on cortical thickness (CT) in bvFTD. bvFTD patients (n = 31) completed a baseline MRI scan, and informants for the patients completed the Lifetime of Experiences Questionnaire (LEQ), which measures specific activities considered to be undertaken primarily within one particular life phase, such as education (young-life), occupation (mid-life), and social/leisure activity (late-life). At baseline, linear models assessed the effect of LEQ scores from each life phase on regional CT. A subset (n = 19) of patients completed longitudinal MRI, and to evaluate the association of LEQ with longitudinal rates of CT decline, we derived individualized slopes of decline using linear mixed effects models and these were related to LEQ scores from each life phase. At baseline, a higher late-life LEQ score was associated with less atrophy in left superior and inferior anterior temporal regions as well as right middle temporal gyrus. Longitudinally, we observed that higher late-life LEQ scores were associated with an attenuated rate of CT loss in insular cortex. Late-life LEQ score was positively associated with both relatively preserved CT early in bvFTD and a slower rate of cortical loss in regions important for social functioning. These findings suggest that social and leisure activities may contribute to a form of resilience against pathologic effects of disease.

Polymer thick film technology for improved simultaneous dEEG/MRI recording: Safety and MRI data quality.

PURPOSE: To develop a 256-channel dense-array electroencephalography (dEEG) sensor net (the Ink-Net) using high-resistance polymer thick film (PTF) technology to improve safety and data quality during simultaneous dEEG/MRI. METHODS: Heating safety was assessed with temperature measurements in an anthropomorphic head phantom during a 30-min, induced-heating scan at 7T. MRI quality assessment used B1 field mapping and functional MRI (fMRI) retinotopic scans in three humans at 3T. Performance of the 256-channel PTF Ink-Net was compared with a 256-channel MR-conditional copper-wired electroencephalography (EEG) net and to scans with no sensor net. A visual evoked potential paradigm assessed EEG quality within and outside the 3T scanner. RESULTS: Phantom temperature measurements revealed nonsignificant heating (ISO 10974) in the presence of either EEG net. In human B1 field and fMRI scans, the Ink-Net showed greatly reduced cross-modal artifact and less signal degradation than the copper-wired net, and comparable quality to MRI without sensor net. Cross-modal ballistocardiogram artifact in the EEG was comparable for both nets. CONCLUSION: High-resistance PTF technology can be effectively implemented in a 256-channel dEEG sensor net for MR conditional use at 7T and with significantly improved structural and fMRI data quality as assessed at 3T. Magn Reson Med 77:895-903, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

State-dependent variability of dynamic functional connectivity between frontoparietal and default networks relates to cognitive flexibility.

The brain is a dynamic, flexible network that continuously reconfigures. However, the neural underpinnings of how state-dependent variability of dynamic functional connectivity (vdFC) relates to cognitive flexibility are unclear. We therefore investigated flexible functional connectivity during resting-state and task-state functional magnetic resonance imaging (rs-fMRI and t-fMRI, resp.) and performed separate, out-of-scanner neuropsychological testing. We hypothesize that state-dependent vdFC between the frontoparietal network (FPN) and the default mode network (DMN) relates to cognitive flexibility. Seventeen healthy subjects performed the Stroop color word test and underwent t-fMRI (Stroop computerized version) and rs-fMRI. Time series were extracted from a cortical atlas, and a sliding window approach was used to obtain a number of correlation matrices per subject. vdFC was defined as the standard deviation of connectivity strengths over these windows. Higher task-state FPN-DMN vdFC was associated with greater out-of-scanner cognitive flexibility, while the opposite relationship was present for resting-state FPN-DMN vdFC. Moreover, greater contrast between task-state and resting-state vdFC related to better cognitive performance. In conclusion, our results suggest that not only the dynamics of connectivity between these networks is seminal for optimal functioning, but also that the contrast between dynamics across states reflects cognitive performance.

A multi-subject, multi-modal human neuroimaging dataset.

We describe data acquired with multiple functional and structural neuroimaging modalities on the same nineteen healthy volunteers. The functional data include Electroencephalography (EEG), Magnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) data, recorded while the volunteers performed multiple runs of hundreds of trials of a simple perceptual task on pictures of familiar, unfamiliar and scrambled faces during two visits to the laboratory. The structural data include T1-weighted MPRAGE, Multi-Echo FLASH and Diffusion-weighted MR sequences. Though only from a small sample of volunteers, these data can be used to develop methods for integrating multiple modalities from multiple runs on multiple participants, with the aim of increasing the spatial and temporal resolution above that of any one modality alone. They can also be used to integrate measures of functional and structural connectivity, and as a benchmark dataset to compare results across the many neuroimaging analysis packages. The data are freely available from https://openfmri.org/.

A Parametric Empirical Bayesian Framework for the EEG/MEG Inverse Problem: Generative Models for Multi-Subject and Multi-Modal Integration.

We review recent methodological developments within a parametric empirical Bayesian (PEB) framework for reconstructing intracranial sources of extracranial electroencephalographic (EEG) and magnetoencephalographic (MEG) data under linear Gaussian assumptions. The PEB framework offers a natural way to integrate multiple constraints (spatial priors) on this inverse problem, such as those derived from different modalities (e.g., from functional magnetic resonance imaging, fMRI) or from multiple replications (e.g., subjects). Using variations of the same basic generative model, we illustrate the application of PEB to three cases: (1) symmetric integration (fusion) of MEG and EEG; (2) asymmetric integration of MEG or EEG with fMRI, and (3) group-optimization of spatial priors across subjects. We evaluate these applications on multi-modal data acquired from 18 subjects, focusing on energy induced by face perception within a time-frequency window of 100-220 ms, 8-18 Hz. We show the benefits of multi-modal, multi-subject integration in terms of the model evidence and the reproducibility (over subjects) of cortical responses to faces.

Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics.

Noise-normalization has been shown to partly compensate for the localization bias towards superficial sources in minimum norm estimation. However, it has been argued that in order to make inferences for the case of multiple sources, localization properties alone are insufficient. Instead, multiple measures of resolution should be applied to both point-spread and cross-talk functions (PSFs and CTFs). Here, we demonstrate that noise-normalization affects the shapes of PSFs, but not of CTFs. We evaluated PSFs and CTFs for the MNE, dSPM and sLORETA inverse operators, on the metrics dipole localization error (DLE), spatial dispersion (SD) and overall amplitude (OA). We used 306-channel MEG configurations obtained from 17 subjects in a real experiment, including individual noise covariance matrices and head geometries. We confirmed that for PSFs DLE improved after noise normalization, and is zero for sLORETA. However, SD was generally lower for the unnormalized MNE. OA distributions were similar for all three methods, indicating that all three methods may greatly underestimate some sources relative to others. The reliability of differences between methods across subjects was demonstrated using distributions of standard deviations and p-values from paired t-tests. As predicted, the shapes of CTFs were the same for all methods, reflecting the general resolution limits of the inverse problem. This means that noise-normalization is of no consequence where linear estimation procedures are used as "spatial filters." While low DLE is advantageous for the localization of a single source, or possibly a few spatially distinct sources, the benefit for the case of complex source distributions is not obvious. We suggest that software packages for source estimation should include comprehensive tools for evaluating the performance of different methods.

Dynamic statistical parametric mapping for analyzing ictal magnetoencephalographic spikes in patients with intractable frontal lobe epilepsy.

The purpose of this study is to assess the clinical value of spatiotemporal source analysis for analyzing ictal magnetoencephalography (MEG). Ictal MEG and simultaneous scalp EEG was recorded in five patients with medically intractable frontal lobe epilepsy. Dynamic statistical parametric maps (dSPMs) were calculated at the peak of early ictal spikes for the purpose of estimating the spatiotemporal cortical source distribution. DSPM solutions were mapped onto a cortical surface, which was derived from each patient's MRI. Equivalent current dipoles (ECDs) were calculated using a single-dipole model for comparison with dSPMs. In all patients, dSPMs tended to have a localized activation, consistent with the clinically determined ictal onset zone, whereas most ECDs were considered to be inappropriate sources according to their goodness-of-fit values. Analyzing ictal MEG spikes by using dSPMs may provide useful information in presurgical evaluation of epilepsy.