Sujith Vijayan, ShiNung Ching, Patrick L Purdon, Emery N Brown, Nancy J Kopell
{"title":"Biophysical Modeling of Alpha Rhythms During Halothane-Induced Unconsciousness.","authors":"Sujith Vijayan, ShiNung Ching, Patrick L Purdon, Emery N Brown, Nancy J Kopell","doi":"10.1109/NER.2013.6696130","DOIUrl":"https://doi.org/10.1109/NER.2013.6696130","url":null,"abstract":"<p><p>During the induction of general anesthesia there is a shift in power from the posterior regions of the brain to the frontal cortices; this shift in power is called anteriorization. For many anesthetics, a prominent feature of anteriorization is a shift specifically in the alpha band (8-13 Hz) from posterior to frontal cortices. Here we present a biophysical computational model that describes thalamocortical circuit-level dynamics underlying anteriorization of the alpha rhythm in the case of halothane. Halothane potentiates GABA<sub>A</sub> and increases potassium leak conductances. According to our model, an increase in potassium leak conductances hyperpolarizes and silences the high-threshold thalamocortical (HTC) cells, a specialized subset of thalamocortical cells that fire at the alpha frequency at relatively depolarized membrane potentials (>-60 mV) and are thought to be the generators of quiet awake occipital alpha. At the same time the potentiation of GABA<sub>A</sub> imposes an alpha time scale on both the cortical and the thalamic component of the frontal portion of our model. The alpha activity in the frontal component is further strengthened by reciprocal thalamocortical feedback. Thus, we argue that the dual molecular targets of halothane induce the anteriorization of the alpha rhythm by increasing potassium leak conductances, which abolishes occipital alpha, and by potentiating GABA<sub>A</sub>, which induces frontal alpha. These results provide a computational modeling formulation for studying highly detailed biophysical mechanisms of anesthetic action in silico.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"1104-1107"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2013.6696130","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32721181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Justin D Foster, Oren Freifeld, Paul Nuyujukian, Stephen I Ryu, Michael J Black, Krishna V Shenoy
{"title":"Combining Wireless Neural Recording and Video Capture for the Analysis of Natural Gait.","authors":"Justin D Foster, Oren Freifeld, Paul Nuyujukian, Stephen I Ryu, Michael J Black, Krishna V Shenoy","doi":"10.1109/NER.2011.5910623","DOIUrl":"https://doi.org/10.1109/NER.2011.5910623","url":null,"abstract":"<p><p>Neural control of movement is typically studied in constrained environments where there is a reduced set of possible behaviors. This constraint may unintentionally limit the applicability of findings to the generalized case of unconstrained behavior. We hypothesize that examining the unconstrained state across multiple behavioral contexts will lead to new insights into the neural control of movement and help advance the design of neural prosthetic decode algorithms. However, to pursue electrophysiological studies in such a manner requires a more flexible framework for experimentation. We propose that head-mounted neural recording systems with wireless data transmission, combined with markerless computer-vision based motion tracking, will enable new, less constrained experiments. As a proof-of-concept, we recorded and wirelessly transmitted broadband neural data from 32 electrodes in premotor cortex while acquiring single-camera video of a rhesus macaque walking on a treadmill. We demonstrate the ability to extract behavioral kinematics using an automated computer vision algorithm without use of markers and to predict kinematics from the neural data. Together these advances suggest that a new class of \"freely moving monkey\" experiments should be possible and should help broaden our understanding of the neural control of movement.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2011 ","pages":"613-616"},"PeriodicalIF":0.0,"publicationDate":"2011-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2011.5910623","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33340724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A multi-timescale adaptive threshold model for the SAI tactile afferent to predict response to mechanical vibration.","authors":"Anila F Jahangiri, Gregory J Gerling","doi":"10.1109/NER.2011.5910511","DOIUrl":"https://doi.org/10.1109/NER.2011.5910511","url":null,"abstract":"<p><p>The Leaky Integrate and Fire (LIF) model of a neuron is one of the best known models for a spiking neuron. A current limitation of the LIF model is that it may not accurately reproduce the dynamics of an action potential. There have recently been some studies suggesting that a LIF coupled with a multi-timescale adaptive threshold (MAT) may increase LIF's accuracy in predicting spikes in cortical neurons. We propose a mechanotransduction process coupled with a LIF model with multi-timescale adaptive threshold to model slowly adapting type I (SAI) mechanoreceptor in monkey's glabrous skin. In order to test the performance of the model, the spike timings predicted by this MAT model are compared with neural data. We also test a fixed threshold variant of the model by comparing its outcome with the neural data. Initial results indicate that the MAT model predicts spike timings better than a fixed threshold LIF model only.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"152-155"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2011.5910511","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30053389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Julie Dethier, Vikash Gilja, Paul Nuyujukian, Shauki A Elassaad, Krishna V Shenoy, Kwabena Boahen
{"title":"Spiking Neural Network Decoder for Brain-Machine Interfaces.","authors":"Julie Dethier, Vikash Gilja, Paul Nuyujukian, Shauki A Elassaad, Krishna V Shenoy, Kwabena Boahen","doi":"10.1109/NER.2011.5910570","DOIUrl":"https://doi.org/10.1109/NER.2011.5910570","url":null,"abstract":"<p><p>We used a spiking neural network (SNN) to decode neural data recorded from a 96-electrode array in premotor/motor cortex while a rhesus monkey performed a point-to-point reaching arm movement task. We mapped a Kalman-filter neural prosthetic decode algorithm developed to predict the arm's velocity on to the SNN using the Neural Engineering Framework and simulated it using <i>Nengo</i>, a freely available software package. A 20,000-neuron network matched the standard decoder's prediction to within 0.03% (normalized by maximum arm velocity). A 1,600-neuron version of this network was within 0.27%, and run in real-time on a 3GHz PC. These results demonstrate that a SNN can implement a statistical signal processing algorithm widely used as the decoder in high-performance neural prostheses (Kalman filter), and achieve similar results with just a few thousand neurons. Hardware SNN implementations-neuromorphic chips-may offer power savings, essential for realizing fully-implantable cortically controlled prostheses.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2011.5910570","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31968953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Thalamic bursts mediate pattern recognition","authors":"M. Jändel","doi":"10.1109/NER.2009.5109358","DOIUrl":"https://doi.org/10.1109/NER.2009.5109358","url":null,"abstract":"A new functional model for burst firing in the dorsal thalamus is proposed where thalamocortical pattern recognition systems, based on kernel machine principles, are connected by burst signaling. The systems include input trapping in the dorsal thalamus, cortical learning state memory and processing in the thalamic reticular nucleus. Misclassified events are captured as training examples in the waking state and the pattern recognition systems are trained by extensive thalamic bursting in deep sleep.","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"43 1","pages":"562-565"},"PeriodicalIF":0.0,"publicationDate":"2009-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75651835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of Matched-Filtering to Extract EEG Features and Decouple Signal Contributions from Multiple Seizure Foci in Brain Malformations.","authors":"Catherine Stamoulis, Bernard S Chang","doi":"10.1109/NER.2009.5109346","DOIUrl":"https://doi.org/10.1109/NER.2009.5109346","url":null,"abstract":"<p><p>Developmental brain malformations often cause intractable and in many cases generalized and/or multifocal seizures. Surgical intervention is not possible in these cases as it is difficult to isolate the epileptogenic foci. Scalp EEG signals recorded during such seizures include coupled contributions from different sources. If it was possible to decouple these contributions based on differences in both their signatures and inter-arrival times at different electrodes, it would subsequently be possible to estimate the locations of the seizure foci. For this purpose, we applied matched filtering to scalp EEG data from 3 patients with multifocal seizures, using patient-specific source-related short EEG segments as the template waveforms. These segments were assumed to be seizure-related based on distinct sets of inter-arrival times at different channels and alternating signal polarities. We present preliminary results and demonstrate that matched filtering can be successfully applied to extract decoupled signal components from the EEG, generated by potentially distinct sources, and thus with distinct inter-arrival times but partially overlapping spectra.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2009 ","pages":"514-517"},"PeriodicalIF":0.0,"publicationDate":"2009-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2009.5109346","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"28958863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. P. O'Sullivan, J. Baker, B. Philip, M. Orazem, K. Otto, C. Butson
{"title":"In Vivo Application of Electrical Rejuvenation Pulses to Chronically Implanted Neural Macroelectrodes in Nonhuman Primates for Regulation of Interface Properties","authors":"K. P. O'Sullivan, J. Baker, B. Philip, M. Orazem, K. Otto, C. Butson","doi":"10.1109/NER52421.2023.10123750","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123750","url":null,"abstract":"Chronically implanted neural electrodes have become an increasingly important tool in both research and clinical applications, where long-term viability and stability of the electrode-tissue interface (ETI) may be a critical factor in device performance. However, chronic implantation of electrodes in brain tissue typically results in distinct changes to the electrode-tissue interface (ETI), observed as a semicircular arc “tissue component” in Nyquist plots of electrochemical impedance spectroscopy (EIS) measurements. These alterations to electrode-tissue interface properties can interfere with electrode recording characteristics, increase stimulation thresholds, and may create unpredictable behavior in closed-loop applications where neural recordings are used as a control signal. Previous work1,2has demonstrated the potential for direct-current electrical rejuvenation to reduce the impact of “tissue component” impedance on measured EIS spectra in microelectrodes chronically implanted in rodents. Our aim here is to further investigate this phenomenon using macroelectrodes in nonhuman primates (NHPs). Scaled versions of human deep brain stimulation (DBS) and electrocorticography (ECoG) electrodes were chronically implanted in an adult male rhesus macaque nonhuman primate. Both direct-current and alternating-current electrical rejuvenation pulses were found to be sufficiently effective at reducing the appearance of “tissue component” in EIS measurements and dropping impedance, with further investigation needed to determine optimal parameters.","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"34 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73596748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}