03082nas a2200313   4500008004100000022001400041245013800055210006900193260001600262490000700278520206400285653001002349653002102359653002502380653002702405653003702432653001102469653001102480653000902491653001702500653001602517653003102533653002502564653001602589100001702605700002102622700001302643856011202656       2026                        eng d  a1741-255200aMethodological optimization for eliciting robust median nerve somatosensory evoked potentials for realtime single trial applications.0 aMethodological optimization for eliciting robust median nerve so  c2026 Jan 090 v233 a<p>Single-trial measurement of median nerve somatosensory evoked potentials (SEPs) with noninvasive electroencephalography (EEG) is challenging due to low signal-to-noise ratio (SNR), limiting its use in real-time neurorehabilitation applications. We describe and evaluate methodological optimizations for eliciting reliable median nerve SEPs measurable in real time, with reduced reliance on post-processing.In twelve healthy participants, two sessions each, SEPs were assessed at three pulse widths (0.1, 0.5, 1 ms), at a low-frequency stimulation (0.5 Hz ± 10%), and at an intensity sufficient to evoke consistent and robust sensory nerve action potentials and compound muscle action potentials. The evoked potential operant conditioning system platform was used to monitor responses in real time. Feasibility was also evaluated in a participant with incomplete spinal cord injury (iSCI).SEP P50 and N70 were reliably elicited in healthy participants, and in individual with iSCI, across all tested pulse widths with minimal discomfort. N70 amplitude increased significantly with pulse width (χ2= 17.64,= 0.0001,= 0.80), while P50 amplitude remained unchanged. SNR showed a significant pulse width-dependent increase (χ2= 7.82,= 0.02,= 0.35) with improvements of 40% and 52% at 0.5 and 1 ms, respectively. N70 single-trial separability significantly improved at 1 ms (AUC of 0.83,χ2= 8.17,= 0.017), including the iSCI participant (0.84-less impaired hand, 0.79-more impaired hand). Test-retest reliability (intraclass correlation coefficient = 0.70-0.84,< 0.05) was highest at 0.5 ms, indicating more consistent N70 and P50 measurements across sessions at a longer pulse width.Robust median nerve SEPs can be measured at single trials with methodological optimizations such as a longer pulse width (0.5-1 ms), low frequency (0.5 Hz), a consistent afferent excitation guided by nerve and muscle responses, and a robust EEG acquisition system. This setup can be useful for real time SEP-based brain computer interface applications for rehabilitation.</p>10aAdult10aComputer Systems10aElectric Stimulation10aElectroencephalography10aEvoked Potentials, Somatosensory10aFemale10aHumans10aMale10aMedian Nerve10aMiddle Aged10aReproducibility of Results10aSpinal Cord Injuries10aYoung Adult1 aGupta, Disha1 aBrangaccio, Jodi1 aHill, NJ  uhttps://www.neurotechcenter.org/publications/2026/methodological-optimization-eliciting-robust-median-nerve02458nas a2200145   4500008004100000245009900041210006900140300001400209520189200223100001702115700002102132700002102153700001302174856012502187       2026                        eng d00aA portable cortical evoked potential operant conditioning system (C-EPOCS): System development0 aportable cortical evoked potential operant conditioning system C  a2026–013 aThis study presents customizations and evaluations aimed at adapting the Cortical-Evoked Potential Operant Conditioning System (C-EPOCS) into a portable, user-friendly platform for real-time neurofeedback applications. A primary goal was to simplify the component-heavy setup by integrating electroencephalography (EEG) and electromyography (EMG) data acquisition into a single system-while still supporting cortical and muscle response assessment and real-time feedback. One key limitation of portable biosignal acquisition systems is their typically lower sampling rates (e.g., 300-600 Hz) compared to high-resolution systems (e.g., 3200 Hz), which are commonly used for detecting transient responses such as the H-reflex and M-wave. In a CEPOCS setup, these responses are useful for determining the target stimulation intensity and minimizing inter-session variability in effective afferent excitation. We evaluated whether lower-resolution EMG signals could still support the generation of H-reflex and M-wave recruitment curves for determining target stimulation intensity. Results showed that while EMG sampled at ~600 Hz and ~300 Hz produced greater dispersion in recruitment curve data, particularly at 300 Hz, they still yielded comparable estimates for stimulation intensities that elicit Hmax and Mthreshold, the key parameters for C-EPOCS. Additionally, we demonstrate the feasibility of using an automated response delineation algorithm under these conditions. Despite reduced signal clarity, the algorithm reliably identifies M-wave and H-reflex responses in real time. Overall, this study demonstrates the feasibility of a portable C-EPOCS system capable of providing immediate feedback based on both EMG and EEG signals. It also offers practical recommendations for selecting acquisition hardware to support reliable signal quality, real-time processing, and portability.1 aGupta, Disha1 aBrangaccio, Jodi1 aMojtabavi, Helia1 aHill, NJ  uhttps://www.neurotechcenter.org/publications/2026/portable-cortical-evoked-potential-operant-conditioning-system-c-epocs02837nas a2200169   4500008004100000245011000041210006900151300001100220490000700231520221500238100001702453700002102470700002102491700002102512700001302533856012102546       2025                        eng d00aExtracting robust single-trial somatosensory evoked potentials for non-invasive brain computer interfaces0 aExtracting robust singletrial somatosensory evoked potentials fo  a0560040 v223 aObjective: Reliable extraction of single-trial somatosensory evoked potentials (SEPs) is essential for developing brain-computer interface (BCI) applications to support rehabilitation after brain injury. For real-time feedback, these responses must be extracted prospectively on every trial, with minimal post-processing and artifact correction. However, noninvasive SEPs elicited by electrical stimulation at recommended parameter settings (0.1–0.2 msec pulse width, stimulation at or below motor threshold, 2–5 Hz frequency) are typically small and variable, often requiring averaging across multiple trials or extensive processing. Here, we describe and evaluate ways to optimize the stimulation setup to enhance the signal-to-noise ratio (SNR) of noninvasive single-trial SEPs, enabling more reliable extraction. Approach: SEPs were recorded with scalp electroencephalography in tibial nerve stimulation in thirteen healthy people, and two people with CNS injuries. Three stimulation frequencies (lower than recommended: 0.2 Hz, 1 Hz, 2 Hz) with a pulse width longer than recommended (1 msec), at a stimulation intensity based on H-reflex and M-wave at Soleus muscle were evaluated. Detectability of single-trial SEPs relative to background noise was tested offline and in a pseudo-online analysis, followed by a real-time demonstration. Main results. SEP N70 was observed predominantly at the central scalp regions. Online decoding performance was significantly higher with Laplacian filter. Generalization performance showed an expected degradation, at all frequencies, with an average decrease of 5.9% (multivariate) and 6.5% (univariate), with an AUC score ranging from 0.78–0.90. The difference across stimulation frequencies was not significant. In individuals with injuries, AUC of 0.86 (incomplete spinal cord injury) and 0.81 (stroke) was feasible. Real-time demonstration showed SEP detection with AUC of 0.89. Significance This study describes and evaluates a system for extracting single-trial SEPs in real-time, suitable for a BCI-based operant conditioning. It enhances SNR of individual SEPs by alternate electrical stimulation parameters, dry headset, and optimized signal processing.1 aGupta, Disha1 aBrangaccio, Jodi1 aMojtabavi, Helia1 aWolpaw, Jonathan1 aHill, NJ  uhttps://www.neurotechcenter.org/publications/2025/extracting-robust-single-trial-somatosensory-evoked-potentials-non02933nas a2200181   4500008004100000245013500041210006900176300001100245490000700256520224100263100001702504700002102521700002102542700002202563700002402585700001702609856012502626       2025                        eng d00aFrequency dependence of cortical somatosensory evoked response to peripheral nerve stimulation with controlled afferent excitation0 aFrequency dependence of cortical somatosensory evoked response t  a0260350 v223 aObjective: H-reflex targeted neuroplasticity (HrTNP) protocols comprise a promising rehabilitation approach to improve motor function after brain or spinal injury. In this operant conditioning protocol, concurrent measurement of cortical responses, such as somatosensory evoked potentials (SEPs), would be useful for examining supraspinal involvement and neuroplasticity mechanisms. To date, this potential has not been exploited. However, the stimulation parameters used in the HrTNP protocol deviate from the classically recommended settings for SEP measurements. Most notably, it demands a much longer pulse width, higher stimulation intensity, and lower frequency than traditional SEP settings. In this paper, we report SEP measurements performed within the HrTNP stimulation parameter constraints, specifically characterizing the effect of stimulation frequency.
Approach: SEPs were acquired for tibial nerve stimulation at three stimulation frequencies (0.2, 1, and 2 Hz) in 13 subjects while maintaining the afferent volley by controlling the direct soleus muscle response via the Evoked Potential Operant Conditioning System. The amplitude and latency of the short-latency P40 and mid-latency N70 SEP components were measured at the central scalp region using non-invasive electroencephalography.
Main results: As frequency rose from 0.2 Hz, P40 amplitude and latency did not change. In contrast, N70 amplitude decreased significantly (39% decrease at 1 Hz, and 57% decrease at 2 Hz), presumably due to gating effects. N70 latency was not affected. Across all three frequencies, N70 amplitude increased significantly with stimulation intensity and correlated with M-wave amplitude.
Significance: We assess SEPs within an HrTNP protocol, focusing on P40 and N70, elicited with controlled afferent excitation at three stimulation frequencies. HrTNP conditioning protocols show promise for enhancing motor function after brain and spinal injuries. While SEPs offer valuable insights into supraspinal involvement, the stimulation parameters in HrTNP often differ from standard SEP measurement protocols. We address these deviations and provide recommendations for effectively integrating SEP assessments into HrTNP studies.


1 aGupta, Disha1 aBrangaccio, Jodi1 aMojtabavi, Helia1 aCarp, Jonathan, S1 aWolpaw, Jonathan, R1 aHill, Jeremy  uhttps://www.neurotechcenter.org/publications/2025/frequency-dependence-cortical-somatosensory-evoked-response-peripheral01902nas a2200241   4500008004100000245011900041210006900160300000800229490000800237520107300245100002401318700001701342700002101359700002501380700001301405700002201418700002301440700002401463700002201487700002101509700001101530856011901541       2025                        eng d00aSoleus H-reflex size versus stimulation rate in the presence of background muscle activity: a methodological study0 aSoleus Hreflex size versus stimulation rate in the presence of b  a2150 v2433 aHoffmann reflex (HR) operant conditioning (HROC) is an important intervention for neurorehabilitation. Current HROC paradigms elicit HRs at low rates (~ 0.2 Hz), minimizing rate-dependent depression (RDD). We investigated the impact of higher stimulation rates on HR size. Fifteen healthy participants maintained low background soleus electromyographic activity (EMG) while standing. Soleus HR and M-wave recruitment curves were obtained at rates of 0.2, 1, and 2 Hz twice, from which Mmax and Hmax were calculated. Seventy-five HRs were collected for each rate at a target M-wave size (~ 10 to 20% of Mmax). HR depression was minimal at higher stimulation rates. The mean HR amplitude was reliable across the two repetitions and three rates, with high intraclass correlation coefficient (ICC) values. HROC could be performed consistently at rates up to 2 Hz with minimal HR depression. Faster rates enable more conditioning trials per session, reducing session duration and/or number, thereby potentially accelerating conditioning and reducing participant burden.1 aBrangaccio, Jodi, A1 aGupta, Disha1 aMojtabavi, Helia1 aHardesty, Russell, L1 aHill, NJ1 aCarp, Jonathan, S1 aGemoets, Darren, E1 aVaughan, Theresa, M1 aNorton, James, JS1 aPerez, Monica, A1 aothers  uhttps://www.neurotechcenter.org/publications/2025/soleus-h-reflex-size-versus-stimulation-rate-presence-background02106nas a2200205   4500008004100000022001400041245008600055210006900141260001300210300001100223490000700234520142100241100002101662700002301683700002101706700002001727700001701747700001701764856011901781       2025                        eng d  a2468-067200aSyncGenie: A programmable event synchronization device for neuroscience research.0 aSyncGenie A programmable event synchronization device for neuros  c2025 Mar  ae006190 v213 a<p>In neuroscience, accurately correlating brain activity with stimuli and other events requires precise synchronization between neural data and event timing. To achieve this, purpose-built synchronization devices are often used to detect events. This paper introduces SyncGenie, a programmable synchronization device designed for a range of uses in neuroscience research-primarily as a "trigger box" to align neurophysiological data with physical stimulus events, among other possibilities. It can support both hardware-triggered and software-triggered pulse synchronization and can even serve as a cost-effective digitizer for real-time analysis of analog signals. We provide the complete circuit-board designs, 3D models, and Arduino code necessary to build and use SyncGenie. The board is designed for easy manufacturing and assembly, with components that can be seamlessly soldered. It includes a range of connector types required for common applications, such as 3.5 mm TRS, D-sub25, BNC, and JST-XH. Additionally, SyncGenie features a user-friendly interface that allows for experiment-specific adjustments without requiring coding expertise. Its programmability, supported by our public-domain Arduino library, provides the flexibility to adapt SyncGenie to diverse experimental protocols. Overall, SyncGenie offers enhanced functionality at a lower cost relative to commercially available trigger boxes.</p>1 aAlkhoury, Ludvik1 aScanavini, Giacomo1 aSwissler, Petras1 aShah, Sudhin, A1 aGupta, Disha1 aHill, Jeremy  uhttps://www.neurotechcenter.org/publications/2025/syncgenie-programmable-event-synchronization-device-neuroscience02042nas a2200217   4500008004100000245016300041210006900204520121400273100002301487700002701510700002501537700002801562700002101590700001601611700001701627700001601644700002001660700001101680700001101691856012201702       2025                        eng d00aTailored robotic training improves hand function and proprioceptive processing in stroke survivors with proprioceptive deficits: A randomized controlled trial0 aTailored robotic training improves hand function and propriocept3 aPrecision rehabilitation aims to tailor movement training to improve outcomes. We tested whether proprioceptively-tailored robotic training improves hand function and neural processing in stroke survivors. Using a robotic finger exoskeleton, we tested two proprioceptively-tailored approaches: Propriopixel Training, which uses robot-facilitated, gamified movements to enhance proprioceptive processing, and Virtual Assistance Training, which reduces robotic aid to increase reliance on self-generated feedback. In a randomized controlled trial, forty-six chronic stroke survivors completed nine 2-hour sessions of Standard, Propriopixel or Virtual training. Among participants with proprioceptive deficits, Propriopixel ((Box and Block Test: 7 +/- 4.2, p=0.002) and Virtual Assistance (4.5 +/- 4.4 , p=0.068) yielded greater gains in hand function (Standard: 0.8 +/- 2.3 blocks). Proprioceptive gains correlated with improvements in hand function. Tailored training enhanced neural sensitivity to proprioceptive cues, evidenced by a novel EEG biomarker, the proprioceptive Contingent Negative Variation. These findings support proprioceptively-tailored training as a pathway to precision neurorehabilitation.1 aFarrens, Andria, J1 aGarcia-Fernandez, Luis1 aRojas, Raymond, Diaz1 aEstrada, Jillian, Obeso1 aReinsdorf, Dylan1 aChan, Vicky1 aGupta, Disha1 aPerry, Joel1 aWolbrecht, Eric1 aDo, An1 aothers  uhttps://www.neurotechcenter.org/publications/2025/tailored-robotic-training-improves-hand-function-and-proprioceptive02783nas a2200157   4500008004100000245011100041210006900152490000700221520216800228100002702396700002202423700002302445700001702468700001702485856012302502       2025                        eng d00aTest-retest reliability of kinematic and EEG low-beta spectral features in a robot-based arm movement task0 aTestretest reliability of kinematic and EEG lowbeta spectral fea0 v113 aObjective.Low-beta (Lβ, 13-20 Hz) power plays a key role in upper-limb motor control and afferent processing, making it a strong candidate for a neurophysiological biomarker. We investigate the test-retest reliability of Lβpower and kinematic features from a robotic task over extended intervals between sessions to assess its potential for tracking longitudinal changes in sensorimotor function.Approach.We designed and optimized a testing protocol to evaluate Lβpower and kinematic features (maximal and mean speed, reaction time, and movement duration) in ten right-handed healthy individuals that performed a planar center-out task using a robotic device and EEG for data collection. The task was performed with both hands, and the experiment was repeated approximately 40 days later under similar conditions, to resemble real-life intervention periods. We first characterized the selected features within the task context for each session, then assessed intersession agreement, the test-retest reliability (Intraclass Correlation Coefficient, ICC), and established threshold values for meaningful changes in Lβpower using Bland-Altman plots and repeatability coefficients.Main Results.Lβpower showed the expected contralateral reduction during movement preparation and onset. Both Lβpower and kinematic features exhibited good to excellent test-retest reliability (ICC > 0.8), displaying no significant intersession differences. Kinematic results align with prior literature, reinforcing the robustness of these measures in tracking motor performance over time. Changes in Lβpower between sessions exceeding 11.4% for right-arm and 16.5% for left-arm movements reflect meaningful intersession differences.Significance.This study provides evidence that Lβpower remains stable over extended intersession intervals comparable to rehabilitation timelines. The strong reliability of both Lβpower and kinematic features supports their use in monitoring upper-extremity sensorimotor function longitudinally, with Lβpower emerging as a promising biomarker for tracking therapeutic outcomes, postulating it as a reliable feature for long-term applications. 1 aRueda-Parra, Sebastian1 aHardesty, Russell1 aGemoets, Darren, E1 aHill, Jeremy1 aGupta, Disha  uhttps://www.neurotechcenter.org/publications/2025/test-retest-reliability-kinematic-and-eeg-low-beta-spectral-features02169nas a2200301   4500008004100000022001400041245015400055210006900209260001300278300000800291490000900299520119500308653000901503653002101512653001101533653001101544653000901555653001601564653001301580653001101593653002601604100002701630700001901657700002301676700002801699700001701727856012301744       2024                        eng d  a2694-060400aMultidimensional feature analysis shows stratification in robotic-motor-training gains based on the level of pre-training motor impairment in stroke.0 aMultidimensional feature analysis shows stratification in roboti  c2024 Jul  a1-50 v20243 a<p>Stroke involves heterogeneity in injury and ongoing endogenous recovery, which are seldom stratified before testing post-stroke robot assisted motor training (RAMT). Pretraining variations, especially sensory-motor differences may also affect the gains achieved from the RAMT. Moreover, one assessment test may not effectively characterize the baseline sensory-motor status or the RAMT gains. Pre-therapy stratification may help personalize therapy and increase therapy gains. Towards this goal, we propose a data-driven approach to assess multiple functional scores with t-distributed stochastic neighbor embedding and affinity propagation clustering, both for pre-therapy and RAMT gains. Data included behavioral scores from 27 people with chronic stroke who underwent RAMT for finger movement. Three clusters were observed at start-of-therapy (SoT), concurrent with the overall impairment level. Four clusters were observed for the RAMT gains, indicating specific improvements. The SoT clusters showed agreement with the RAMT gain clusters, suggesting that the pre-therapy state, assessed across multiple domains, could be useful in guiding RAMT interventions to improve outcomes.</p>10aAged10aCluster Analysis10aFemale10aHumans10aMale10aMiddle Aged10aRobotics10aStroke10aStroke Rehabilitation1 aRueda-Parra, Sebastian1 aPerry, Joel, C1 aWolbrecht, Eric, T1 aReinkensmeyer, David, J1 aGupta, Disha  uhttps://www.neurotechcenter.org/publications/2024/multidimensional-feature-analysis-shows-stratification-robotic-motor02872nas a2200169   4500008004100000245007900041210006900120260000700189300000900196490000700205520235300212100002702565700002002592700002402612700001702636856004902653       2024                        eng d00aNeural correlates of bilateral proprioception and adaptation with training0 aNeural correlates of bilateral proprioception and adaptation wit  c03  a1-210 v193 aBilateral proprioception includes the ability to sense the position and motion of one hand relative to the other, without looking. This sensory ability allows us to perform daily activities seamlessly, and its impairment is observed in various neurological disorders such as cerebral palsy and stroke. It can undergo experience-dependent plasticity, as seen in trained piano players. If its neural correlates were better understood, it would provide a useful assay and target for neurorehabilitation for people with impaired proprioception. We designed a non-invasive electroencephalography-based paradigm to assess the neural features relevant to proprioception, especially focusing on bilateral proprioception, i.e., assessing the limb distance from the body with the other limb. We compared it with a movement-only task, with and without the visibility of the target hand. Additionally, we explored proprioceptive accuracy during the tasks. We tested eleven Controls and nine Skilled musicians to assess whether sensorimotor event-related spectral perturbations in μ (8-12Hz) and low-β (12-18Hz) rhythms differ in people with musical instrument training, which intrinsically involves a bilateral proprioceptive component, or when new sensor modalities are added to the task. The Skilled group showed significantly reduced μ and low-β suppression in bilateral tasks compared to movement-only, a significative difference relative to Controls. This may be explained by reduced top-down control due to intensive training, despite this, proprioceptive errors were not smaller for this group. Target visibility significantly reduced proprioceptive error in Controls, while no change was observed in the Skilled group. During visual tasks, Controls exhibited significant μ and low-β power reversals, with significant differences relative to proprioceptive-only tasks compared to the Skilled group—possibly due to reduced uncertainty and top-down control. These results provide support for sensorimotor μ and low-β suppression as potential neuromarkers for assessing proprioceptive ability. The identification of these features is significant as they could be used to quantify altered proprioceptive neural processing in skill and movement disorders. This in turn can be useful as an assay for pre and post sensory-motor intervention research.1 aRueda-Parra, Sebastian1 aPerry, Joel, C.1 aWolbrecht, Eric, T.1 aGupta, Disha  uhttps://doi.org/10.1371/journal.pone.029987303130nas a2200313   4500008004100000022001400041245013900055210006900194260001500263520206900278653002002347653002602367653002102393653002202414653001302436653001102449653002702460653002502487100001702512700001702529700001902546700002402565700002302589700002102612700001402633700002402647700002202671856012302693       2022                        eng d  a1940-087X00aThe Evoked Potential Operant Conditioning System (EPOCS): A Research Tool and an Emerging Therapy for Chronic Neuromuscular Disorders.0 aEvoked Potential Operant Conditioning System EPOCS A Research To  c2022 08 253 a<p>The Evoked Potential Operant Conditioning System (EPOCS) is a software tool that implements protocols for operantly conditioning stimulus-triggered muscle responses in people with neuromuscular disorders, which in turn can improve sensorimotor function when applied appropriately. EPOCS monitors the state of specific target muscles-e.g., from surface electromyography (EMG) while standing, or from gait cycle measurements while walking on a treadmill-and automatically triggers calibrated stimulation when pre-defined conditions are met. It provides two forms of feedback that enable a person to learn to modulate the targeted pathway's excitability. First, it continuously monitors ongoing EMG activity in the target muscle, guiding the person to produce a consistent level of activity suitable for conditioning. Second, it provides immediate feedback of the response size following each stimulation and indicates whether it has reached the target value. To illustrate its use, this article describes a protocol through which a person can learn to decrease the size of the Hoffmann reflex-the electrically-elicited analog of the spinal stretch reflex-in the soleus muscle. Down-conditioning this pathway's excitability can improve walking in people with spastic gait due to incomplete spinal cord injury. The article demonstrates how to set up the equipment; how to place stimulating and recording electrodes; and how to use the free software to optimize electrode placement, measure the recruitment curve of direct motor and reflex responses, measure the response without operant conditioning, condition the reflex, and analyze the resulting data. It illustrates how the reflex changes over multiple sessions and how walking improves. It also discusses how the system can be applied to other kinds of evoked responses and to other kinds of stimulation, e.g., motor evoked potentials to transcranial magnetic stimulation; how it can address various clinical problems; and how it can support research studies of sensorimotor function in health and disease.</p>10aChronic Disease10aConditioning, Operant10aElectromyography10aEvoked Potentials10aH-Reflex10aHumans10aNeuromuscular Diseases10aSpinal Cord Injuries1 aHill, Jeremy1 aGupta, Disha1 aEftekhar, Amir1 aBrangaccio, Jodi, A1 aNorton, James, J S1 aMcLeod, Michelle1 aFake, Tim1 aWolpaw, Jonathan, R1 aThompson, Aiko, K  uhttps://www.neurotechcenter.org/publications/2022/evoked-potential-operant-conditioning-system-epocs-research-tool-and02937nas a2200253   4500008004100000022001400041245009000055210006900145260001200214300001000226490000600236520216200242653002402404653003202428653002702460653001402487653003302501100001702534700002502551700002202576700001802598700001902616856004802635       2014                        eng d  a2213-158200aLocalizing ECoG electrodes on the cortical anatomy without post-implantation imaging.0 aLocalizing ECoG electrodes on the cortical anatomy without posti  c08/2014  a64-760 v63 a<p><b>INTRODUCTION: </b>Electrocorticographic (ECoG) grids are placed subdurally on the cortex in people undergoing cortical resection to delineate eloquent cortex. ECoG signals have high spatial and temporal resolution and thus can be valuable for neuroscientific research. The value of these data is highest when they can be related to the cortical anatomy. Existing methods that establish this relationship rely either on post-implantation imaging using computed tomography (CT), magnetic resonance imaging (MRI) or X-Rays, or on intra-operative photographs. For research purposes, it is desirable to localize ECoG electrodes on the brain anatomy even when post-operative imaging is not available or when intra-operative photographs do not readily identify anatomical landmarks.</p><p><b>METHODS: </b>We developed a method to co-register ECoG electrodes to the underlying cortical anatomy using only a pre-operative MRI, a clinical neuronavigation device (such as BrainLab VectorVision), and fiducial markers. To validate our technique, we compared our results to data collected from six subjects who also had post-grid implantation imaging available. We compared the electrode coordinates obtained by our fiducial-based method to those obtained using existing methods, which are based on co-registering pre- and post-grid implantation images.</p><p><b>RESULTS: </b>Our fiducial-based method agreed with the MRI-CT method to within an average of 8.24 mm (mean, median = 7.10 mm) across 6 subjects in 3 dimensions. It showed an average discrepancy of 2.7 mm when compared to the results of the intra-operative photograph method in a 2D coordinate system. As this method does not require post-operative imaging such as CTs, our technique should prove useful for research in intra-operative single-stage surgery scenarios. To demonstrate the use of our method, we applied our method during real-time mapping of eloquent cortex during a single-stage surgery. The results demonstrated that our method can be applied intra-operatively in the absence of post-operative imaging to acquire ECoG signals that can be valuable for neuroscientific investigations.</p>10aauditory processing10aelectrocorticography (ECoG)10aelectrode localization10afiducials10ainteraoperative localization1 aGupta, Disha1 aHill, Jeremy, Jeremy1 aAdamo, Matthew, A1 aRitaccio, A L1 aSchalk, Gerwin  uhttp://www.ncbi.nlm.nih.gov/pubmed/2537941702940nas a2200229   4500008004100000245006800041210006600109260001200175520223700187653002402424653002502448653002302473653002202496653002602518100001702544700002502561700001902586700002002605700001802625700001902643856004802662       2014                        eng d00aSimultaneous Real-Time Monitoring of Multiple Cortical Systems.0 aSimultaneous RealTime Monitoring of Multiple Cortical Systems  c10/20143 aOBJECTIVE:
Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance.
APPROACH:
We study these questions using electrocorticographic signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (six for offline parameter optimization, six for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main Results: Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelopes. These decoders were trained separately and executed simultaneously in real time.
SIGNIFICANCE:
This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic.10aauditory processing10aElectrocorticography10amovement intention10arealtime decoding10asimultaneous decoding1 aGupta, Disha1 aHill, Jeremy, Jeremy1 aBrunner, Peter1 aGunduz, Aysegul1 aRitaccio, A L1 aSchalk, Gerwin  uhttp://www.ncbi.nlm.nih.gov/pubmed/2508016102948nas a2200445   4500008004100000022001400041245008900055210006900144260001200213300001000225490000900235520165000244653002501894653001201919653002201931653001001953653002001963653002701983653002702010653003802037653001102075653002602086653004002112653000902152653000902161653002302170653002902193653003602222653002502258653002902283653001702312653002202329100001702351700001702368700001102385700001602396700002502412700001702437856004802454       2013                        eng d  a1872-624000aNovel inter-hemispheric white matter connectivity in the BTBR mouse model of autism.0 aNovel interhemispheric white matter connectivity in the BTBR mou  c06/2013  a26-330 v15133 aAlterations in the volume, density, connectivity and functional activation of white matter tracts are reported in some individuals with autism and may contribute to their abnormal behaviors. The BTBR (BTBR T+tf/J) inbred strain of mouse, is used to model facets of autism because they develop low social behaviors, stereotypical and immune changes similar to those found in people with autism. Previously, it was thought a total absence of corpus callosal interhemispheric connective tissues in the BTBR mice may underlie their abnormal behaviors. However, postnatal lesions of the corpus callosum do not precipitate social behavioral problems in other strains of mice suggesting a flaw in this theory. In this study we used digital pathological methods to compare subcortical white matter connective tracts in the BTBR strain of mice with those found in the C57Bl/6 mouse and those reported in a standardized mouse brain atlas. We report, for the first time, a novel connective subcortical interhemispheric bridge of tissue in the posterior, but not anterior, cerebrum of the BTBR mouse. These novel connective tissues are comprised of myelinated fibers, with reduced myelin basic protein levels (MBP) compared to levels in the C57Bl/6 mouse. We used electrophysiological analysis and found increased inter-hemispheric connectivity in the posterior hemispheres of the BTBR strain compared with the anterior hemispheres. The conduction velocity was slower than that reported in normal mice. This study shows there is novel abnormal interhemispheric connectivity in the BTBR strain of mice, which may contribute to their behavioral abnormalities.10aAnalysis of Variance10aAnimals10aAutistic Disorder10aBrain10aCorpus Callosum10aDisease Models, Animal10aElectroencephalography10aEnzyme-Linked Immunosorbent Assay10aFemale10aFunctional Laterality10aImage Processing, Computer-Assisted10aMale10aMice10aMice, Inbred C57BL10aMice, Neurologic Mutants10aMicrotubule-Associated Proteins10aMyelin Basic Protein10aNerve Fibers, Myelinated10aNeuroimaging10aSpectrum Analysis1 aMiller, V, M1 aGupta, Disha1 aNeu, N1 aCotroneo, A1 aBoulay, Chadwick, B.1 aSeegal, R, F  uhttp://www.ncbi.nlm.nih.gov/pubmed/2357070700478nas a2200097   4500008004100000245011700041210006900158260001200227100001700239856012400256       2012                        eng d00aECoG: A Step Closer to the Brain @ The Brain Computer Interfacing Workshop, University Old dominion, Norfolk, VA0 aECoG A Step Closer to the Brain The Brain Computer Interfacing W  c05/20121 aGupta, Disha  uhttps://www.neurotechcenter.org/publications/2012/ecog-step-closer-brain-brain-computer-interfacing-workshop-university01889nas a2200469   4500008004100000022001400041245008900055210006900144260001200213300001100225490000700236520052900243653001800772653002900790653002500819653004300844653003100887653002100918653002200939653001800961100001800979700002300997700002001020700001901040700001801059700002201077700002001099700001701119700002301136700002001159700001601179700001801195700002101213700001901234700001701253700001901270700002201289700002001311700002101331700001901352856004801371       2012                        eng d  a1525-506900aProceedings of the Third International Workshop on Advances in Electrocorticography.0 aProceedings of the Third International Workshop on Advances in E  c12/2012  a605-130 v253 aThe Third International Workshop on Advances in Electrocorticography (ECoG) was convened in Washington, DC, on November 10-11, 2011. As in prior meetings, a true multidisciplinary fusion of clinicians, scientists, and engineers from many disciplines gathered to summarize contemporary experiences in brain surface recordings. The proceedings of this meeting serve as evidence of a very robust and transformative field but will yet again require revision to incorporate the advances that the following year will surely bring.10aBrain Mapping10abrain-computer interface10aElectrocorticography10aGamma-frequency electroencephalography10ahigh-frequency oscillation10aNeuroprosthetics10aSeizure detection10aSubdural grid1 aRitaccio, A L1 aBeauchamp, Michael1 aBosman, Conrado1 aBrunner, Peter1 aChang, Edward1 aCrone, Nathan, E.1 aGunduz, Aysegul1 aGupta, Disha1 aKnight, Robert, T.1 aLeuthardt, Eric1 aLitt, Brian1 aMoran, Daniel1 aOjemann, Jeffrey1 aParvizi, Josef1 aRamsey, Nick1 aRieger, Jochem1 aViventi, Jonathan1 aVoytek, Bradley1 aWilliams, Justin1 aSchalk, Gerwin  uhttp://www.ncbi.nlm.nih.gov/pubmed/2316009610628nas a2200313   4500008004100000022001400041245012900055210006900184260001200253520965800265653001209923653003109935653002509966653002409991653002910015653001310044653003110057653000810088653001710096653001310113100002510126700001710151700001910168700002010187700002210207700001810229700001910247856004810266       2012                        eng d  a1940-087X00aRecording Human Electrocorticographic (ECoG) Signals for Neuroscientific Research and Real-time Functional Cortical Mapping.0 aRecording Human Electrocorticographic ECoG Signals for Neuroscie  c05/20123 a<p><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">Neuroimaging studies of human cognitive, sensory, and motor processes are usually based on noninvasive techniques such as electroencephalography (EEG), magnetoencephalography or functional magnetic-resonance imaging. These techniques have either inherently low temporal or low spatial resolution, and suffer from low signal-to-noise ratio and/or poor high-frequency sensitivity. Thus, they are suboptimal for exploring the short-lived spatio-temporal dynamics of many of the underlying brain processes. In contrast, the invasive technique of electrocorticography (ECoG) provides brain signals that have an exceptionally high signal-to-noise ratio, less susceptibility to artifacts than EEG, and a high spatial and temporal resolution (i.e., &lt;1 cm/&lt;1 millisecond, respectively). ECoG involves measurement of electrical brain signals using electrodes that are implanted subdurally on the surface of the brain. Recent studies have shown that ECoG amplitudes in certain frequency bands carry substantial information about task-related activity, such as motor execution and planning,&nbsp;</span><span class="highlight" style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">auditory</span><span style="font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;">&nbsp;processing and visual-spatial attention. Most of this information is captured in the high gamma range (around 70-110 Hz). Thus, gamma activity has been proposed as a robust and general indicator of local cortical function. ECoG can also reveal functional connectivity and resolve finer task-related spatial-temporal dynamics, thereby advancing our understanding of large-scale cortical processes. It has especially proven useful for advancing brain-computer interfacing (BCI) technology for decoding a user's intentions to enhance or improve communication and control. Nevertheless, human ECoG data are often hard to obtain because of the risks and limitations of the invasive procedures involved, and the need to record within the constraints of clinical settings. Still, clinical monitoring to localize epileptic foci offers a unique and valuable opportunity to collect human ECoG data. We describe our methods for collecting recording ECoG, and demonstrate how to use these signals for important real-time applications such as clinical mapping and brain-computer interfacing. Our example uses the BCI2000 software platform and the SIGFRIED method, an application for real-time mapping of brain functions. This procedure yields information that clinicians can subsequently use to guide the complex and laborious process of functional mapping by electrical stimulation. PREREQUISITES AND PLANNING: Patients with drug-resistant partial epilepsy may be candidates for resective surgery of an epileptic focus to minimize the frequency of seizures. Prior to resection, the patients undergo monitoring using subdural electrodes for two purposes: first, to localize the epileptic focus, and second, to identify nearby critical brain areas (i.e., eloquent cortex) where resection could result in long-term functional deficits. To implant electrodes, a craniotomy is performed to open the skull. Then, electrode grids and/or strips are placed on the cortex, usually beneath the dura. A typical grid has a set of 8 x 8 platinum-iridium electrodes of 4 mm diameter (2.3 mm exposed surface) embedded in silicon with an inter-electrode distance of 1cm. A strip typically contains 4 or 6 such electrodes in a single line. The locations for these grids/strips are planned by a team of neurologists and neurosurgeons, and are based on previous EEG monitoring, on a structural MRI of the patient's brain, and on relevant factors of the patient's history. Continuous recording over a period of 5-12 days serves to localize epileptic foci, and electrical stimulation via the implanted electrodes allows clinicians to map eloquent cortex. At the end of the monitoring period, explantation of the electrodes and therapeutic resection are performed together in one procedure. In addition to its primary clinical purpose, invasive monitoring also provides a unique opportunity to acquire human ECoG data for neuroscientific research. The decision to include a prospective patient in the research is based on the planned location of their electrodes, on the patient's performance scores on neuropsychological assessments, and on their informed consent, which is predicated on their understanding that participation in research is optional and is not related to their treatment. As with all research involving human subjects, the research protocol must be approved by the hospital's institutional review board. The decision to perform individual experimental tasks is made day-by-day, and is contingent on the patient's endurance and willingness to participate. Some or all of the experiments may be prevented by problems with the clinical state of the patient, such as post-operative facial swelling, temporary aphasia, frequent seizures, post-ictal fatigue and confusion, and more general pain or discomfort. At the Epilepsy Monitoring Unit at Albany Medical Center in Albany, New York, clinical monitoring is implemented around the clock using a 192-channel Nihon-Kohden Neurofax monitoring system. Research recordings are made in collaboration with the Wadsworth Center of the New York State Department of Health in Albany. Signals from the ECoG electrodes are fed simultaneously to the research and the clinical systems via splitter connectors. To ensure that the clinical and research systems do not interfere with each other, the two systems typically use separate grounds. In fact, an epidural strip of electrodes is sometimes implanted to provide a ground for the clinical system. Whether research or clinical recording system, the grounding electrode is chosen to be distant from the predicted epileptic focus and from cortical areas of interest for the research. Our research system consists of eight synchronized 16-channel g.USBamp amplifier/digitizer units (g.tec, Graz, Austria). These were chosen because they are safety-rated and FDA-approved for invasive recordings, they have a very low noise-floor in the high-frequency range in which the signals of interest are found, and they come with an SDK that allows them to be integrated with custom-written research software. In order to capture the high-gamma signal accurately, we acquire signals at 1200Hz sampling rate-considerably higher than that of the typical EEG experiment or that of many clinical monitoring systems. A built-in low-pass filter automatically prevents aliasing of signals higher than the digitizer can capture. The patient's eye gaze is tracked using a monitor with a built-in Tobii T-60 eye-tracking system (Tobii Tech., Stockholm, Sweden). Additional accessories such as joystick, bluetooth Wiimote (Nintendo Co.), data-glove (5(th) Dimension Technologies), keyboard, microphone, headphones, or video camera are connected depending on the requirements of the particular experiment. Data collection, stimulus presentation, synchronization with the different input/output accessories, and real-time analysis and visualization are accomplished using our BCI2000 software. BCI2000 is a freely available general-purpose software system for real-time biosignal data acquisition, processing and feedback. It includes an array of pre-built modules that can be flexibly configured for many different purposes, and that can be extended by researchers' own code in C++, MATLAB or Python. BCI2000 consists of four modules that communicate with each other via a network-capable protocol: a Source module that handles the acquisition of brain signals from one of 19 different hardware systems from different manufacturers; a Signal Processing module that extracts relevant ECoG features and translates them into output signals; an Application module that delivers stimuli and feedback to the subject; and the Operator module that provides a graphical interface to the investigator. A number of different experiments may be conducted with any given patient. The priority of experiments will be determined by the location of the particular patient's electrodes. However, we usually begin our experimentation using the SIGFRIED (SIGnal modeling For Realtime Identification and Event Detection) mapping method, which detects and displays significant task-related activity in real time. The resulting functional map allows us to further tailor subsequent experimental protocols and may also prove as a useful starting point for traditional mapping by electrocortical stimulation (ECS). Although ECS mapping remains the gold standard for predicting the clinical outcome of resection, the process of ECS mapping is time consuming and also has other problems, such as after-discharges or seizures. Thus, a passive functional mapping technique may prove valuable in providing an initial estimate of the locus of eloquent cortex, which may then be confirmed and refined by ECS. The results from our passive SIGFRIED mapping technique have been shown to exhibit substantial concurrence with the results derived using ECS mapping. The protocol described in this paper establishes a general methodology for gathering human ECoG data, before proceeding to illustrate how experiments can be initiated using the BCI2000 software platform. Finally, as a specific example, we describe how to perform passive functional mapping using the BCI2000-based SIGFRIED system.</span></p>10aBCI200010abrain-computer interfacing10aElectrocorticography10aepilepsy monitoring10afunctional brain mapping10aissue 6410aMagnetic Resonance Imaging10aMRI10aneuroscience10aSIGFRIED1 aHill, Jeremy, Jeremy1 aGupta, Disha1 aBrunner, Peter1 aGunduz, Aysegul1 aAdamo, Matthew, A1 aRitaccio, A L1 aSchalk, Gerwin  uhttp://www.ncbi.nlm.nih.gov/pubmed/2278213100453nas a2200097   4500008004100000245009900041210006900140260001200209100001700221856011700238       2012                        eng d00aTreatments/Interventions for Autism @ Autism Outreach Albany Workshop www.autism-outreach.com 0 aTreatmentsInterventions for Autism Autism Outreach Albany Worksh  c09/20121 aGupta, Disha  uhttps://www.neurotechcenter.org/publications/2012/treatmentsinterventions-autism-autism-outreach-albany-workshop00465nas a2200097   4500008004100000245011000041210006900151260001200220100001700232856011800249       2011                        eng d00aAuditory Processing and Anticipation @ The 3rd International Workshop on Advances in Electrocorticography0 aAuditory Processing and Anticipation The 3rd International Works  c11/20111 aGupta, Disha  uhttps://www.neurotechcenter.org/publications/2011/auditory-processing-and-anticipation-3rd-international-workshop02102nas a2200229   4500008004100000245013500041210007100176260001200247490000700259520133100266653002101597653001601618653001701634653002701651653003501678653002501713653002501738100001701763700002101780700002301801856004801824       2011                        eng d00aSpace–time network connectivity and cortical activations preceding spike wave discharges in human absence epilepsy: a MEG study.0 aSpace–time network connectivity and cortical activations precedi  c05/20110 v493 aTo describe the spatial and temporal profiles of connectivity networks and sources preceding generalized spike-and-wave discharges (SWDs) in human absence epilepsy. Nonlinear associations of MEG signals and cluster indices obtained within the framework of graph theory were determined, while source localization in the frequency domain was performed in the low frequency bands with dynamic imaging of coherent sources. The results were projected on a three-dimensional surface rendering of the brain using a semi-realistic head model and MRI images obtained for each of the five patients studied. An increase in clustering and a decrease in path length preceding SWD onset and a rhythmic pattern of increasing and decreasing connectivity were seen during SWDs. Beamforming showed a consistent appearance of a low frequency frontal cortical source prior to the first generalized spikes. This source was preceded by a low frequency occipital source. The changes in the connectivity networks with the onset of SWDs suggest a pathologically predisposed state towards synchronous seizure networks with increasing connectivity from interictal to preictal and ictal state, while the occipital and frontal low frequency early preictal sources demonstrate that SWDs are not suddenly arising but gradually build up in a dynamic network.10aAbsence epilepsy10aBeamforming10aConnectivity10aMagnetoencephalography10aNonlinear association analysis10aSmall world networks10aSpike wave discharge1 aGupta, Disha1 aOssenblok, Pauly1 aLuijtelaar, Gilles  uhttp://www.ncbi.nlm.nih.gov/pubmed/2153362000520nas a2200085   4500008004100000245016800041210006900209100001700278856013900295       2010                        eng d00aDynamic imaging of ‘generalized’ seizure activity: clinical MEG workshop @ Sleep and Epilepsy update: 12th annual international clinical symposium Kempenhaeghe0 aDynamic imaging of generalized seizure activity clinical MEG wor1 aGupta, Disha  uhttps://www.neurotechcenter.org/publications/2010/dynamic-imaging-%E2%80%98generalized%E2%80%99-seizure-activity-clinical-meg-workshop01698nas a2200265   4500008004100000022001400041245008600055210006900141260001200210300000900222490000900231520087600240653001501116653002801131653003301159653002701192653001301219653001101232653003501243653003101278653003201309100002601341700001701367856004801384       2009                        eng d  a1557-170X00aSeizure prediction for epilepsy using a multi-stage phase synchrony based system.0 aSeizure prediction for epilepsy using a multistage phase synchro  c09/2009  a25-80 v20093 aSeizure onset prediction in epilepsy is a challenge which is under investigation using many and varied signal processing techniques. Here we present a multi-stage phase synchrony based system that brings to bear the advantages of many techniques in each substage. The 1(st) stage of the system unmixes continuous long-term (2-4 days) multichannel scalp EEG using spatially constrained Independent Component Analysis and estimates the long term significant phase synchrony dynamics of narrowband (2-8 Hz and 8-14 Hz) seizure components. It then projects multidimensional features onto a 2-D map using Neuroscale and evaluates the probability of predictive events using Gaussian Mixture Models. We show the possibility of seizure onset prediction within a prediction window of 35-65 minutes with a sensitivity of 65-100% and specificity of 65-80% across epileptic patients.10aAlgorithms10aArtificial Intelligence10aDiagnosis, Computer-Assisted10aElectroencephalography10aEpilepsy10aHumans10aPattern Recognition, Automated10aReproducibility of Results10aSensitivity and Specificity1 aJames, Christopher, J1 aGupta, Disha  uhttp://www.ncbi.nlm.nih.gov/pubmed/1996510401751nas a2200145   4500008004100000020002200041245009600063210006900159260004200228520117100270100001701441700002601458700002101484856010001505       2008                        eng d  a978-0-86341-934-800aPhase synchronization with ICA for epileptic seizure onset prediction in the long term EEG.0 aPhase synchronization with ICA for epileptic seizure onset predi  aSanta Margherita LigurebIETc07/20083 aThe apparently unpredictable nature of epileptic seizures can be devastating for people with epilepsy. Current medical interventions can help 75% of patients while 25% have to live with uncontrolled seizures. This motivates the search for a seizure prediction prototype using electroencephalograms (electrical signals that capture brain activity). The concept of phase synchrony has attracted much attention recently in the context of seizure prediction but is still in need of further study. The basis of our analysis is to track changes in synchrony in brain signals at and before seizure onset. The novel concept in our analysis is the use of unmixed signals as opposed to scalp EEG signals for phase synchrony analysis. The unmixing is performed by a Blind Source Separation technique called Independent component Analysis (ICA). ICA seeks underlying independent source signals from the EEG and it allows multivariate analysis using spatial as well as temporal information inherent to EEG signals. The present study on long-term continuous EEG data sets indicates that the concept of using phase synchronization with ICA may prove useful for predicting seizures.1 aGupta, Disha1 aJames, Christopher, J1 aGray, William, P  uhttp://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4609101&abstractAccess=no&userType=inst00795nas a2200217   4500008004100000245007400041210006900115260006800184653003100252653002800283653002600311653002800337653003500365653002300400653002400423100001500447700001700462700001700479700002600496856005500522       2007                        eng d00aFlux-continuous schemes for solving EEG source localization problems.0 aFluxcontinuous schemes for solving EEG source localization probl  aGlasgow, UKbCivil-Comp Press, Curran Associates, Inc.c07/200710acontrol volume distributed10aelectroencephalographic10afinite element method10aflux-continuous schemes10aindependent component analysis10aPoisson's equation10asource localization1 aPal, Mayur1 aGupta, Disha1 aEdwards, M G1 aJames, Christopher, J  uhttp://www.ctresources.info/ccp/paper.html?id=431201751nas a2200229   4500008004100000022001400041245012300055210006900178260001200247300001100259490000900270520101400279653001501293653002701308653001101335653003001346653001301376653004101389100001701430700002601447856004801473       2007                        eng d  a1557-170X00aNarrowband vs. broadband phase synchronization analysis applied to independent components of ictal and interictal EEG.0 aNarrowband vs broadband phase synchronization analysis applied t  c08/2007  a3864-70 v20073 aThis paper presents a comparison of the use of broadband and narrow band signals for phase synchronization analysis as applied to Independent Components of ictal and interictal scalp EEG in the context of seizure onset detection and prediction. Narrow band analysis for phase synchronization is found to be better performed in the present context than the broad band signal analysis. It has been observed that the phase synchronization of Independent Components in a narrow band (particularly the Gamma band) shows a prominent trend of increasing and decreasing synchronization at seizure onset near the epileptogenic area (spatially). This information is not always found to be consistent in analysis with the raw EEG signals, which may show spurious synchronization happening due to volume conduction effects. These observations lead us to believe that tracking changes in phase synchronization of narrow band activity, on continuous data records will be of great value in the context of seizure prediction.10aAlgorithms10aElectroencephalography10aHumans10aPredictive Value of Tests10aSeizures10aSignal Processing, Computer-Assisted1 aGupta, Disha1 aJames, Christopher, J  uhttp://www.ncbi.nlm.nih.gov/pubmed/1800284202201nas a2200289   4500008004100000022001400041245012000055210006900175260000900244300001100253490001200264520126500276653001501541653002801556653003301584653002701617653001301644653001101657653003501668653003301703653003101736653003201767100002601799700002101825700001701846856004801863       2007                        eng d  a1557-170X00aSpace-time ICA versus Ensemble ICA for ictal EEG analysis with component differentiation via Lempel-Ziv complexity.0 aSpacetime ICA versus Ensemble ICA for ictal EEG analysis with co  c2007  a5473-60 v08/20073 aIn this proof-of-principle study we analyzed intracranial electroencephalogram recordings in patients with intractable focal epilepsy. We contrast two implementations of Independent Component Analysis (ICA) - Ensemble (or spatial) ICA (E-ICA) and Space-Time ICA (ST-ICA) in separating out the ictal components underlying the measurements. In each case we assess the outputs of the ICA algorithms by means of a non-linear method known as the Lempel-Ziv (LZ) complexity. LZ complexity quantifies the complexity of a time series and is well suited to the analysis of non-stationary biomedical signals of short length. Our results show that for small numbers of intracranial recordings, standard E-ICA results in marginal improvements in the separation as measured by the LZ complexity changes. ST-ICA using just 2 recording channels both near and far from the epileptic focus result in more distinct ictal components--although at this stage there is a subjective element to the separation process for ST-ICA. Our results are promising showing that it is possible to extract meaningful information from just 2 recording electrodes through ST-ICA, even if they are not directly over the seizure focus. This work is being further expanded for seizure onset analysis.10aAlgorithms10aArtificial Intelligence10aDiagnosis, Computer-Assisted10aElectroencephalography10aEpilepsy10aHumans10aPattern Recognition, Automated10aPrincipal Component Analysis10aReproducibility of Results10aSensitivity and Specificity1 aJames, Christopher, J1 aAbásolo, Daniel1 aGupta, Disha  uhttp://www.ncbi.nlm.nih.gov/pubmed/1800325001706nas a2200145   4500008004100000020002200041245006000063210005800123260006100181520118300242100001701425700002601442700002101468856007101489       2006                        eng d  a978-0-86341-658-300aDe-noising epileptic EEG using ICA and phase synchrony.0 aDenoising epileptic EEG using ICA and phase synchrony  aGlasgow, ScotlandbIET, Curran Associates, Inc.c07/20063 aA multi-channel recording of scalp electroencephalogram (EEG) is a non-invasive tool important for analysis and treatment of patients with epilepsy. These recordings are usually contaminated with artifacts and background activity, which may sometimes render them misleading or useless. Epileptic EEG is also useful for seizure detection, localisation and prediction. It would be useful to de-noise epileptic EEG in order to improve the efficiency of such diagnostic and prognostic procedures. The basic method of denoising a signal is through filtering, but filtering physiological signals is not trivial and highly subjective as the information is spread over different frequency bands and different measurement channels. This paper demonstrates a system for objectively de-noising epileptic EEG using Independent Component Analysis (ICA). In the standard implementation of ICA it is generally required to subjectively choose independent components (ICs) relevant to the epileptic activity; here we automate this process through the concept of phase synchronisation between ICs. In this manner de-noising the epileptic EEG with ICA becomes an objective (and automated) process.1 aGupta, Disha1 aJames, Christopher, J1 aGray, William, P  uhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=422523502816nas a2200133   4500008004000000245009700040210006900137260004700206490000800253520226700261100001702528700002602545856011102571       0                           engd00aAdvances in Epileptic Seizure Onset Prediction in the EEG with ICA and Phase Synchronization0 aAdvances in Epileptic Seizure Onset Prediction in the EEG with I  aSouthampton, UKbUniversity of Southampton0 vPhD3 aSeizure onset prediction in epilepsy is a challenge which is under investigation using many and varied signal processing techniques, across the world. This research thesis contributes to the advancement of digital signal analysis of neurophysiological signals of epileptic patients. It has been studied especially in the context of epileptic seizure onset prediction, with a motivation to help epileptic patients by advancing the knowledge on the possibilities of seizure prediction and inching towards a clinically viable seizure predictor. In this work, a synchrony based multi-stage system is analyzed that brings to bear the advantages of many techniques in each substage. The 1st stage of the system unmixes and de-noises continuous long-term (2-4 days) multichannel scalp Electroencephalograms using spatially constrained Independent Component Analysis. The 2d stage estimates the long term significant phase synchrony dynamics of narrowband (2-8 Hz and 8-14 Hz) seizure components. The synchrony dynamics are assessed with a novel statistic, the PLV-d, analyzing the joint synchrony in two frequency bands of interest. The 3rd stage creates multidimensional features of these synchrony dynamics for two classes (‘seizure free’ and ‘seizure predictive’) which are then projected onto a 2-dimensional map using a supervised Neuroscale, a topographic projection scheme based on a Radial Basis Neural Network. The 4th stage evaluates the probability of occurrence of predictive events using Gaussian Mixture Models used in supervised and semi-supervised forms. Preliminary analysis is performed on shorter data segments and the final system is based on nine patient’s long term (2-4 days each) continuous data. The training and testing for feature extraction analysis is performed on five patient datasets. The features extracted and the parameters ascertained with this analysis are then applied on the remaining four long-term datasets as a test of performance. The analysis is tested against random predictors as well. We show the possibility of seizure onset prediction (performing better than a random predictor) within a prediction window of 35-65 minutes with a sensitivity of 65-100% and specificity of 60-100% across the epileptic patients.1 aGupta, Disha1 aJames, Christopher, J  uhttps://www.neurotechcenter.org/publications/advances-epileptic-seizure-onset-prediction-eeg-ica-and-phase