Exposure and neuronal excitation by wireless power transfer for auricular vagus nerve stimulation

Inductive wireless power transfer (WPT) can be used to power implanted as well as wearable medical devices, such as a percutaneous auricular vagus nerve stimulation device. This device is placed on the neck of the patient and is connected to needle electrodes in the auricle. With regard to WPT, limitations on exposure to electric and magnetic fields should not be exceeded. Furthermore, these fields should not interfere with the therapeutic goal of stimulation, i.e., with unintended peripheral nerve stimulation in the auricle. These effects are investigated by numerical simulation of induced internal fields in the head and neck and, for the first time, subsequent neuronal simulations, quantifying the potential of neuronal excitation by the fields in the auricle in particular. Internal electric field values were in the range of 1\%-5\% of the ICNIRP 2010 basic restrictions, and current densities were in the range of 30\%-45\% of the ICNIRP 1998 basic restrictions, indicating that all tested configurations are conform the guidelines. Basic restrictions on heating of tissue turned out not to be of relevance for this application. Thresholds for neuronal stimulation were two orders of magnitude higher than the induced fields, suggesting that there is almost no risk for unintended stimulation

Cognitive Neuroscience Neuroimaging Repository for the Adult Lifespan

With recent advances in neuroimaging technology, it is now possible to image human brain function in vivo, which revolutionized the cognitive neuroscience field. However, like any other newly developed technique, the acquisition of neuroimaging data is costly and logistically challenging. Furthermore, studying human cognition requires acquiring a large amount of neuroimaging data, which might not be feasible to do by every researcher in the field. Here, we describe our group's efforts to acquire one of the largest neuroimaging datasets that aims to investigate the neural substrates of age-related cognitive decline, which will be made available to share with other investigators. Our neuroimaging repository includes up to 14 different functional images for more than 486 subjects across the entire adult lifespan in addition to their 3 structural images. Currently, data from 234 participants have been acquired, including all 14 functional and 3 structural images, which is planned to increased to 375 participants in the next few years. A complete battery of neuropsychological tests was also administered to all participants. The neuroimaging and accompanying psychometric data will be available through an online and easy-to-use data sharing website

HEiMDaL: Highly Efficient Method for Detection and Localization of wake-words

Streaming keyword spotting is a widely used solution for activating voice assistants. Deep Neural Networks with Hidden Markov Model (DNN-HMM) based methods have proven to be efficient and widely adopted in this space, primarily because of the ability to detect and identify the start and end of the wake-up word at low compute cost. However, such hybrid systems suffer from loss metric mismatch when the DNN and HMM are trained independently. Sequence discriminative training cannot fully mitigate the loss-metric mismatch due to the inherent Markovian style of the operation. We propose an low footprint CNN model, called HEiMDaL, to detect and localize keywords in streaming conditions. We introduce an alignment-based classification loss to detect the occurrence of the keyword along with an offset loss to predict the start of the keyword. HEiMDaL shows 73% reduction in detection metrics along with equivalent localization accuracy and with the same memory footprint as existing DNN-HMM style models for a given wake-word

Selective Association between Cortical Thickness and Reference Abilities in Normal Aging

A previous study of reference abilities and cortical thickness reported that association between reference abilities and cortical thickness summarized over large ROIs suppressed was suppressed after controlling for mean cortical thickness and global cognition. In this manuscript, we showed that preserving detailed spatial patterns of cortical thickness can identify reference-ability-specific association besides the association explained by global cognition and mean cortical thickness. We identified associations between cortical thickness and 3 cognitive reference abilities after controlling for mean thickness, global cognition, and linear chronological age: (1) memory, (2) perceptual speed, and (3) vocabulary. Global cognition was correlated with mean overall thickness but also was found to have a regionally specific pattern of associations. Nonlinear associations between cortical thickness and cognition were not observed, neither were nonlinear age effects. Age-by-thickness interactions were also absent. This implies that all thickness-cognition relations and age associations are independent of age and that consequently no age range is inherently special, since brain-behavioral findings are invariant across the whole age range

Feasibility of pulse rate variability as feedback in closed-loop percutaneous auricular vagus nerve stimulation

Percutaneous auricular vagus nerve stimulation (pVNS) is a novel approach of treating cardiovascular and inflammatory diseases, as well as pain and neurological conditions. The treatment can be optimized by using biosignals as objective measures and feedback-control. One suitable biofeedback could be the use of pulse rate and pulse rate variability (PRV) derived from optical pulse plethysmography (PPG) instead of heart rate and heart rate variability (HRV) derived from electrocardiogram (ECG). For this purpose, a single-lead ECG on the thorax and a PPG on the earlobe were measured simultaneously on 10 healthy subjects for 420 s during three different respiratory phases. The data was analyzed and compared with scatterplots, the Pearson correlation coefficient and a Bland-Altman analysis. The outcomes show a very high correlation of heart rates from PPG and ECG (ri= 0.9663) and SDNN values (rsdnn= 0.9791). Comparison of RMSSD values showed a high positive correlation (rrmssd= 0.7963) but a mean overestimation of 10 ms in RMSSD values measured with the PPG. The results presented suggest that PRV could be and alternative biofeedback used in pVNS

White Matter Tract Covariance Patterns Predict Age-Declining Cognitive Abilities

Previous studies investigating the relationship of white matter (WM) integrity to cognitive abilities and aging have either focused on a global measure or a few selected WM tracts. Ideally, contribution from all of the WM tracts should be evaluated at the same time. However, the high collinearity among WM tracts precludes systematic examination of WM tracts simultaneously without sacrificing statistical power due to stringent multiple-comparison corrections. Multivariate covariance techniques enable comprehensive simultaneous examination of all WM tracts without being penalized for high collinearity among observations. METHOD: In this study, Scaled Subprofile Modeling (SSM) was applied to the mean integrity of 18 major WM tracts to extract covariance patterns that optimally predicted four cognitive abilities (perceptual speed, episodic memory, fluid reasoning, and vocabulary) in 346 participants across ages 20 to 79years old. Using expression of the covariance patterns, age-independent effects of white matter integrity on cognition and the indirect effect of WM integrity on age-related differences in cognition were tested separately, but inferences from the indirect analyses were cautiously made given that cross-sectional data set was used in the analysis. RESULTS: A separate covariance pattern was identified that significantly predicted each cognitive ability after controlling for age except for vocabulary, but the age by WM covariance pattern interaction was not significant for any of the three abilities. Furthermore, each of the patterns mediated the effect of age on the respective cognitive ability. A distinct set of WM tracts was most influential in each of the three patterns. The WM covariance pattern accounting for fluid reasoning showed the most number of influential WM tracts whereas the episodic memory pattern showed the least number. CONCLUSION: Specific patterns of WM tracts make significant contributions to the age-related differences in perceptual speed, episodic memory, and fluid reasoning but not vocabulary. Other measures of brain health will need to be explored to reveal the major influences on the vocabulary ability

The Role of Education and Verbal Abilities in Altering the Effect of Age-Related Gray Matter Differences on Cognition

Evidence suggests that individual variability in lifetime exposures influences how cognitive performance changes with advancing age. Brain maintenance and cognitive reserve are theories meant to account for preserved performance despite advancing age. These theories differ in their causal mechanisms. Brain maintenance predicts more advantageous lifetime exposures will reduce age-related neural differences. Cognitive reserve predicts that lifetime exposures will not directly reduce these differences but minimize their impact on cognitive performance. The present work used moderated-mediation modeling to investigate the contributions of these mechanisms at explaining variability in cognitive performance among a group of 39 healthy younger (mean age (standard deviation) 25.9 (2.92) and 45 healthy older adults (65.2 (2.79)). Cognitive scores were computed using composite measures from three separate domains (speed of processing, fluid reasoning, and memory), while their lifetime exposures were estimated using education and verbal IQ measures. T1-weighted MR images were used to measure cortical thickness and subcortical volumes. Results suggest a stronger role for cognitive reserve mechanisms in explaining age-related cognitive variability: even with age-related reduced gray matter, individuals with greater lifetime exposures could perform better given their quantity of brain measures