International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering最新文献

{"title":"Simulating lesions in multi-layer, multi-columnar model of neocortex.","authors":"Beata Strack,&nbsp;Kimberle M Jacobs,&nbsp;Krzysztof J Cios","doi":"10.1109/ner.2013.6696064","DOIUrl":"https://doi.org/10.1109/ner.2013.6696064","url":null,"abstract":"<p><p>The paper presents results of modeling global and focal loss of layers in a multi-columnar model of neocortex. Specifically, the spread of activity across columns in conditions of inhibitory blockade is compared. With very low inhibition activity spreads through all layers, however, deep layers are critical for spread of activity when inhibition is only moderately blocked.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":"2013 ","pages":"835-838"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ner.2013.6696064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9347533","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":"Electrochemical sensing via selective surface modification of iridium microelectrodes to create a platinum black interface.","authors":"Paras R Patel,&nbsp;Matthew D Gibson,&nbsp;Kip A Ludwig,&nbsp;Nicholas B Langhals","doi":"10.1109/NER.2013.6696095","DOIUrl":"https://doi.org/10.1109/NER.2013.6696095","url":null,"abstract":"<p><p>The ability to selectively deposit platinum black (PtB) on iridium microelectrodes and functionalize the surface for the purposes of choline sensing was investigated in this study. Platinum black was deposited by cycling 100-200 times between 0.5 V and -0.7 V in a solution of 1 mM K₂PtCl₆ in 0.1 M KCl. Deposition of PtB showed good chemical stability as well as good adhesion following insertion into agarose gel as a model for brain insertion. Electrode sites were also tested for their oxidative capabilities of hydrogen peroxide during which they showed high current change in response to small concentration changes - attributable to the high surface area of the PtB. Sites were then coated with an enzyme solution containing choline oxidase, and a permselective layer of meta-phenylenediamine was added to filter interferents. Electrode sites yielded a high sensitivity to choline compared to interferents including ascorbic acid and dopamine.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"961-964"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2013.6696095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32453450","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":"Change in physiological signals during mindfulness meditation.","authors":"Asieh Ahani,&nbsp;Helane Wahbeh,&nbsp;Meghan Miller,&nbsp;Hooman Nezamfar,&nbsp;Deniz Erdogmus,&nbsp;Barry Oken","doi":"10.1109/NER.2013.6696199","DOIUrl":"https://doi.org/10.1109/NER.2013.6696199","url":null,"abstract":"<p><p>Mindfulness meditation (MM) is an inward mental practice, in which a resting but alert state of mind is maintained. MM intervention was performed for a population of older people with high stress levels. This study assessed signal processing methodologies of electroencephalographic (EEG) and respiration signals during meditation and control condition to aid in quantification of the meditative state. EEG and respiration data were collected and analyzed on 34 novice meditators after a 6-week meditation intervention. Collected data were analyzed with spectral analysis and support vector machine classification to evaluate an objective marker for meditation. We observed meditation and control condition differences in the alpha, beta and theta frequency bands. Furthermore, we established a classifier using EEG and respiration signals with a higher accuracy at discriminating between meditation and control conditions than one using the EEG signal only. EEG and respiration based classifier is a viable objective marker for meditation ability. Future studies should quantify different levels of meditation depth and meditation experience using this classifier. Development of an objective physiological meditation marker will allow the mind-body medicine field to advance by strengthening rigor of methods.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"1738-1381"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2013.6696199","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32275706","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":"Modeling of topology-dependent neural network plasticity induced by activity-dependent electrical stimulation.","authors":"Ruiye Ni,&nbsp;Noah M Ledbetter,&nbsp;Dennis L Barbour","doi":"10.1109/NER.2013.6696063","DOIUrl":"https://doi.org/10.1109/NER.2013.6696063","url":null,"abstract":"<p><p>Activity-dependent electrical stimulation can induce cerebrocortical reorganization <i>in vivo</i> by activating brain areas using stimulation derived from the statistics of neural or muscular activity. Due to the nature of synaptic plasticity, network topology is likely to influence the effectiveness of this type of neuromodulation, yet its effect under different network topologies is unclear. To address this issue, we simulated small-scale three-neuron networks to explore topology-dependent network plasticity. The induced neuroplastic changes were evaluated by network coherence and unit-pair mutual information measures. We demonstrated that involvement of monosynaptic feedforward and reciprocal connections is more likely to lead to persistent decreased network coherence and increased network mutual information independent of the global network topology. On the contrary, disynaptic feedforward connections exhibit heterogeneous coherence and unit-pair mutual information sensitivity that depends strongly upon the network context.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"831-834"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2013.6696063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32585540","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":"Adaptive Parametric Spectral Estimation with Kalman Smoothing for Online Early Seizure Detection.","authors":"Yun S Park,&nbsp;Leigh R Hochberg,&nbsp;Emad N Eskandar,&nbsp;Sydney S Cash,&nbsp;Wilson Truccolo","doi":"10.1109/NER.2013.6696207","DOIUrl":"https://doi.org/10.1109/NER.2013.6696207","url":null,"abstract":"<p><p>Tracking spectral changes in neural signals, such as local field potentials (LFPs) and scalp or intracranial electroencephalograms (EEG, iEEG), is an important problem in early detection and prediction of seizures. Most approaches have focused on either parametric or nonparametric spectral estimation methods based on moving time windows. Here, we explore an adaptive (time-varying) parametric ARMA approach for tracking spectral changes in neural signals based on the fixed-interval Kalman smoother. We apply the method to seizure detection based on spectral features of intracortical LFPs recorded from a person with pharmacologically intractable focal epilepsy. We also devise and test an approach for real-time tracking of spectra based on the adaptive parametric method with the fixed-interval Kalman smoother. The order of ARMA models is determined via the AIC computed in moving time windows. We quantitatively demonstrate the advantages of using the adaptive parametric estimation method in seizure detection over nonparametric alternatives based exclusively on moving time windows. Overall, the adaptive parametric approach significantly improves the statistical separability of interictal and ictal epochs.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"1410-1413"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2013.6696207","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32203880","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":"Early Detection of Human Epileptic Seizures Based on Intracortical Local Field Potentials.","authors":"Yun S Park, Leigh R Hochberg, Emad N Eskandar, Sydney S Cash, Wilson Truccolo","doi":"10.1109/NER.2013.6695937","DOIUrl":"10.1109/NER.2013.6695937","url":null,"abstract":"<p><p>The unpredictability of re-occurring seizures dramatically impacts the quality of life and autonomy of people with epilepsy. Reliable early seizure detection could open new therapeutic possibilities and thus substantially improve quality of life and autonomy. Though many seizure detection studies have shown the potential of scalp electroencephalogram (EEG) and intracranial EEG (iEEG) signals, reliable early detection of human seizures remains elusive in practice. Here, we examined the use of intracortical local field potentials (LFPs) recorded from 4×4-mm² 96-microelectrode arrays (MEA) for early detection of human epileptic seizures. We adopted a framework consisting of (1) sampling of intracortical LFPs; (2) denoising of LFPs with the Kalman filter; (3) spectral power estimation in specific frequency bands using 1-sec moving time windows; (4) extraction of statistical features, such as the mean, variance, and Fano factor (calculated across channels) of the power in each frequency band; and (5) cost-sensitive support vector machine (SVM) classification of ictal and interictal samples. We tested the framework in one-participant dataset, including 4 seizures and corresponding interictal recordings preceding each seizure. The participant was a 52-year-old woman suffering from complex partial seizures. LFPs were recorded from an MEA implanted in the participant's left middle temporal gyrus. In this participant, spectral power in 0.3-10 Hz, 20-55 Hz, and 125-250 Hz changed significantly between ictal and interictal epochs. The examined seizure detection framework provided an event-wise sensitivity of 100% (4/4) and only one 20-sec-long false positive event in interictal recordings (likely an undetected subclinical event under further visual inspection), and a detection latency of 4.35 ± 2.21 sec (mean ± std) with respect to iEEG-identified seizure onsets. These preliminary results indicate that intracortical MEA recordings may provide key signals to quickly and reliably detect human seizures.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"323-326"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3961001/pdf/nihms557023.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32203946","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 Pre-Clinical Framework for Neural Control of a Therapeutic Upper-Limb Exoskeleton.","authors":"Amy Blank,&nbsp;Marcia K O'Malley,&nbsp;Gerard E Francisco,&nbsp;Jose L Contreras-Vidal","doi":"10.1109/NER.2013.6696144","DOIUrl":"https://doi.org/10.1109/NER.2013.6696144","url":null,"abstract":"<p><p>In this paper, we summarize a novel approach to robotic rehabilitation that capitalizes on the benefits of patient intent and real-time assessment of impairment. Specifically, an upper-limb, physical human-robot interface (the MAHI EXO-II robotic exoskeleton) is augmented with a non-invasive brain-machine interface (BMI) to include the patient in the control loop, thereby making the therapy 'active' and engaging patients across a broad spectrum of impairment severity in the rehabilitation tasks. Robotic measures of motor impairment are derived from real-time sensor data from the MAHI EXO-II and the BMI. These measures can be validated through correlation with widely used clinical measures and used to drive patient-specific therapy sessions adapted to the capabilities of the individual, with the MAHI EXO-II providing assistance or challenging the participant as appropriate to maximize rehabilitation outcomes. This approach to robotic rehabilitation takes a step towards the seamless integration of BMIs and intelligent exoskeletons to create systems that can monitor and interface with brain activity and movement. Such systems will enable more focused study of various issues in development of devices and rehabilitation strategies, including interpretation of measurement data from a variety of sources, exploration of hypotheses regarding large scale brain function during robotic rehabilitation, and optimization of device design and training programs for restoring upper limb function after stroke.</p>","PeriodicalId":73414,"journal":{"name":"International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering","volume":" ","pages":"1159-1162"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/NER.2013.6696144","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32387511","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":"Biophysical Modeling of Alpha Rhythms During Halothane-Induced Unconsciousness.","authors":"Sujith Vijayan,&nbsp;ShiNung Ching,&nbsp;Patrick L Purdon,&nbsp;Emery N Brown,&nbsp;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_A 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_A 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_A, 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}

{"title":"Combining Wireless Neural Recording and Video Capture for the Analysis of Natural Gait.","authors":"Justin D Foster,&nbsp;Oren Freifeld,&nbsp;Paul Nuyujukian,&nbsp;Stephen I Ryu,&nbsp;Michael J Black,&nbsp;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":"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://www.ncbi.nlm.nih.gov/pmc/articles/PMC3148011/pdf/nihms309787.pdf","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}