Browsing by Subject "Signal Processing, Computer-Assisted"

Now showing 1 - 7 of 7

Open Access
Circuit topology and control principle for a first magnetic stimulator with fully controllable waveform.
(Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2012-01) Goetz, SM; Pfaeffl, M; Huber, J; Singer, M; Marquardt, R; Weyh, T
Magnetic stimulation pulse sources are very inflexible high-power devices. The incorporated circuit topology is usually limited to a single pulse type. However, experimental and theoretical work shows that more freedom in choosing or even designing waveforms could notably enhance existing methods. Beyond that, it even allows entering new fields of application. We propose a technology that can solve the problem. Even in very high frequency ranges, the circuitry is very flexible and is able generate almost every waveform with unrivaled accuracy. This technology can dynamically change between different pulse shapes without any reconfiguration, recharging or other changes; thus the waveform can be modified also during a high-frequency repetitive pulse train. In addition to the option of online design and generation of still unknown waveforms, it amalgamates all existing device types with their specific pulse shapes, which have been leading an independent existence in the past years. These advantages were achieved by giving up the common basis of all magnetic stimulation devices so far, i.e., the high-voltage oscillator. Distributed electronics handle the high power dividing the high voltage and the required switching rate into small portions.
Open Access
Closed-loop systems in anesthesia: reality or fantasy?
(Anesth Analg, 2013-11) Miller, Timothy E; Gan, Tong J
Open Access
Compressive holography.
(2012) Lim, Se Hoon
Compressive holography estimates images from incomplete data by using sparsity priors. Compressive holography combines digital holography and compressive sensing. Digital holography consists of computational image estimation from data captured by an electronic focal plane array. Compressive sensing enables accurate data reconstruction by prior knowledge on desired signal. Computational and optical co-design optimally supports compressive holography in the joint computational and optical domain. This dissertation explores two examples of compressive holography : estimation of 3D tomographic images from 2D data and estimation of images from under sampled apertures. Compressive holography achieves single shot holographic tomography using decompressive inference. In general, 3D image reconstruction suffers from underdetermined measurements with a 2D detector. Specifically, single shot holographic tomography shows the uniqueness problem in the axial direction because the inversion is ill-posed. Compressive sensing alleviates the ill-posed problem by enforcing some sparsity constraints. Holographic tomography is applied for video-rate microscopic imaging and diffuse object imaging. In diffuse object imaging, sparsity priors are not valid in coherent image basis due to speckle. So incoherent image estimation is designed to hold the sparsity in incoherent image basis by support of multiple speckle realizations. High pixel count holography achieves high resolution and wide field-of-view imaging. Coherent aperture synthesis can be one method to increase the aperture size of a detector. Scanning-based synthetic aperture confronts a multivariable global optimization problem due to time-space measurement errors. A hierarchical estimation strategy divides the global problem into multiple local problems with support of computational and optical co-design. Compressive sparse aperture holography can be another method. Compressive sparse sampling collects most of significant field information with a small fill factor because object scattered fields are locally redundant. Incoherent image estimation is adopted for the expanded modulation transfer function and compressive reconstruction.
Open Access
Evaluation and resolution of many challenges of neural spike sorting: a new sorter.
(Journal of neurophysiology, 2021-12) Hall, Nathan J; Herzfeld, David J; Lisberger, Stephen G
We evaluate existing spike sorters and present a new one that resolves many sorting challenges. The new sorter, called "full binary pursuit" or FBP, comprises multiple steps. First, it thresholds and clusters to identify the waveforms of all unique neurons in the recording. Second, it uses greedy binary pursuit to optimally assign all the spike events in the original voltages to separable neurons. Third, it resolves spike events that are described more accurately as the superposition of spikes from two other neurons. Fourth, it resolves situations where the recorded neurons drift in amplitude or across electrode contacts during a long recording session. Comparison with other sorters on ground-truth data sets reveals many of the failure modes of spike sorting. We examine overall spike sorter performance in ground-truth data sets and suggest postsorting analyses that can improve the veracity of neural analyses by minimizing the intrusion of failure modes into analysis and interpretation of neural data. Our analysis reveals the tradeoff between the number of channels a sorter can process, speed of sorting, and some of the failure modes of spike sorting. FBP works best on data from 32 channels or fewer. It trades speed and number of channels for avoidance of specific failure modes that would be challenges for some use cases. We conclude that all spike sorting algorithms studied have advantages and shortcomings, and the appropriate use of a spike sorter requires a detailed assessment of the data being sorted and the experimental goals for analyses.NEW & NOTEWORTHY Electrophysiological recordings from multiple neurons across multiple channels pose great difficulty for spike sorting of single neurons. We propose methods that improve the ability to determine the number of individual neurons present in a recording and resolve near-simultaneous spike events from single neurons. We use ground-truth data sets to demonstrate the pros and cons of several current sorting algorithms and suggest strategies for determining the accuracy of spike sorting when ground-truth data are not available.
Open Access
Stimulation Efficiency With Decaying Exponential Waveforms in a Wirelessly Powered Switched-Capacitor Discharge Stimulation System.
(IEEE transactions on bio-medical engineering, 2018-05) Lee, Hyung-Min; Howell, Bryan; Grill, Warren M; Ghovanloo, Maysam
The purpose of this study was to test the feasibility of using a switched-capacitor discharge stimulation (SCDS) system for electrical stimulation, and, subsequently, determine the overall energy saved compared to a conventional stimulator. We have constructed a computational model by pairing an image-based volume conductor model of the cat head with cable models of corticospinal tract (CST) axons and quantified the theoretical stimulation efficiency of rectangular and decaying exponential waveforms, produced by conventional and SCDS systems, respectively. Subsequently, the model predictions were tested in vivo by activating axons in the posterior internal capsule and recording evoked electromyography (EMG) in the contralateral upper arm muscles. Compared to rectangular waveforms, decaying exponential waveforms with time constants >500 μs were predicted to require 2%-4% less stimulus energy to activate directly models of CST axons and 0.4%-2% less stimulus energy to evoke EMG activity in vivo. Using the calculated wireless input energy of the stimulation system and the measured stimulus energies required to evoke EMG activity, we predict that an SCDS implantable pulse generator (IPG) will require 40% less input energy than a conventional IPG to activate target neural elements. A wireless SCDS IPG that is more energy efficient than a conventional IPG will reduce the size of an implant, require that less wireless energy be transmitted through the skin, and extend the lifetime of the battery in the external power transmitter.
Open Access
Stream segregation on a single electrode as a function of pulse rate in cochlear implant listeners.
(2010) Duran, Sara I
While cochlear implants usually provide a high level of speech recognition in quiet, speech recognition in noise and music appreciation remain challenging. In response to these issues, several studies have proposed increasing the number of channels of information through multiple pulse rate strategies. For the selection of pulse rates, studies of multi-rate strategies have considered implementation issues such as harmonics, pitch saturation, and tonotopic order but have not considered the fundamental perceptual question of whether two pulse rates can provide independent channels of information on a single electrode. This study measures stream segregation as an indicator of whether different pulse rates on the same electrode can be perceived independently. This approach differs from that of previous stream segregation studies which focused on stimulation of alternating electrodes, with the motivation of determining a relationship between electrode stream segregation and speech perception in challenging noisy environments. Stream segregation in this study was measured using two stimulus sequences following an A-B-A-B structure where A and B were different pulse rates stimulatingthe same electrode. The timing between A and B was controlled to provide either aregular or irregular gap between the two pulse trains. The threshold at which subjects could distinguish a regular rhythm from an irregular rhythm was used as an estimate of stream segregation since detecting an irregular rhythm is an easier task when the streams are fused. Stream segregation in cochlear implant users, as with normal hearing listeners, was hypothesized to be influenced by factors such as frequency and the relative timing between tones. To attempt to assess the relationship between these and stream segregation, subjects’ rate discrimination and gap detection abilities were also measured. The results of this study indicate that stream segregation can occur for two pulse rates on a single electrode; thus, it may be possible to use pulse rates to create additional channels of information. Further, the stream segregation results were not strongly correlated with the gap detection or rate discrimination results. The lack of correlation with the gap detection results suggests that the task was measuring a separate perceptual phenomenon rather than providing another measure of gap detection. The lack of correlation with the rate discrimination results suggests that discriminability may not be a limiting factor in selecting rates for segregation. These results may have implications for the future design of multi-rate speech processing strategies.
Open Access
The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.
(Molecular psychiatry, 2014-06) Di Martino, A; Yan, C-G; Li, Q; Denio, E; Castellanos, FX; Alaerts, K; Anderson, JS; Assaf, M; Bookheimer, SY; Dapretto, M; Deen, B; Delmonte, S; Dinstein, I; Ertl-Wagner, B; Fair, DA; Gallagher, L; Kennedy, DP; Keown, CL; Keysers, C; Lainhart, JE; Lord, C; Luna, B; Menon, V; Minshew, NJ; Monk, CS; Mueller, S; Müller, R-A; Nebel, MB; Nigg, JT; O'Hearn, K; Pelphrey, KA; Peltier, SJ; Rudie, JD; Sunaert, S; Thioux, M; Tyszka, JM; Uddin, LQ; Verhoeven, JS; Wenderoth, N; Wiggins, JL; Mostofsky, SH; Milham, MP
Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.