A horizontal and vertical dipole layer model was developed for three dimensional dipole layer imaging of brain electrical activity. Horizontal dipole layer being parallel to the brain surface has been used in previous head models. In the present study, the dipole layer distribution in the sagittal plane was also estimated from the scalp electroencephalogram. The parametric projection filter was applied to an inverse problem in a homogeneous plane head model under various signal conditions. The present simulation results suggest that the depth information of dipole sources could be observed by our method.
{"title":"3D Cortical Dipole Imaging of Brain Electrical Activity using Horizontal and Sagittal Dipole Layers","authors":"J. Hori, B. He","doi":"10.1109/CNE.2007.369651","DOIUrl":"https://doi.org/10.1109/CNE.2007.369651","url":null,"abstract":"A horizontal and vertical dipole layer model was developed for three dimensional dipole layer imaging of brain electrical activity. Horizontal dipole layer being parallel to the brain surface has been used in previous head models. In the present study, the dipole layer distribution in the sagittal plane was also estimated from the scalp electroencephalogram. The parametric projection filter was applied to an inverse problem in a homogeneous plane head model under various signal conditions. The present simulation results suggest that the depth information of dipole sources could be observed by our method.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131746434","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}
A model that predicts psychophysical ability to discriminate electrical stimulation trains is presented. Our model is a leaky integrator, which operates based on the hypothesis that the perceived intensity of a stimulus train is a function of the total number of action potentials evoked over the volume of stimulated neurons. The model predictions are validated with our experimental results obtained from four Long Evans rats on a two-alternative behavioral task. The rats were stimulated in the whisker barrel cortex using frequency, amplitude, and duration modulation. Our results demonstrate that the rats generalized the perception of frequency, amplitude, and duration of stimulation, in a manner consistent with the model. The surprising finding of our work is that the model is able to accurately predict the psychophysical discrimination of intensity, without accounting for the neural network properties of the somatosensory cortex.
{"title":"Somatosensory Feedback for Brain-Machine Interfaces: Perceptual Model and Experiments in Rat Whisker Somatosensory Cortex","authors":"G. Fridman, H. T. Blair, A. Blaisdell, J. Judy","doi":"10.1109/CNE.2007.369689","DOIUrl":"https://doi.org/10.1109/CNE.2007.369689","url":null,"abstract":"A model that predicts psychophysical ability to discriminate electrical stimulation trains is presented. Our model is a leaky integrator, which operates based on the hypothesis that the perceived intensity of a stimulus train is a function of the total number of action potentials evoked over the volume of stimulated neurons. The model predictions are validated with our experimental results obtained from four Long Evans rats on a two-alternative behavioral task. The rats were stimulated in the whisker barrel cortex using frequency, amplitude, and duration modulation. Our results demonstrate that the rats generalized the perception of frequency, amplitude, and duration of stimulation, in a manner consistent with the model. The surprising finding of our work is that the model is able to accurately predict the psychophysical discrimination of intensity, without accounting for the neural network properties of the somatosensory cortex.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122937867","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}
The characteristics of impedance for the electrode-electrolyte interface are important in the electrode researches for biomedical applications. So, the equivalent circuit models for the interface have been researched and developed. However, the applications of such previous models are limited in terms of the frequency range, type of electrode or electrolyte. In this paper, a new electrical circuit model was proposed and demonstrated its capability of fitting the experimental results more accurately than before. A new electrical circuit model consists of three resistors and two constant phase elements. Electrochemical impedance spectroscopy was used to characterize the interface for several materials of Au, Pt, and stainless steel electrode in 0.9% NaCl solution. The new model and the previous model were applied to fit the measured impedance results, and were compared their goodness of fit
{"title":"Fitting Improvement Using a New Electrical Circuit Model for the Electrode-Electrolyte Interface","authors":"J. Chang, Jungil Park, Y. Pak, J. Pak","doi":"10.1109/CNE.2007.369737","DOIUrl":"https://doi.org/10.1109/CNE.2007.369737","url":null,"abstract":"The characteristics of impedance for the electrode-electrolyte interface are important in the electrode researches for biomedical applications. So, the equivalent circuit models for the interface have been researched and developed. However, the applications of such previous models are limited in terms of the frequency range, type of electrode or electrolyte. In this paper, a new electrical circuit model was proposed and demonstrated its capability of fitting the experimental results more accurately than before. A new electrical circuit model consists of three resistors and two constant phase elements. Electrochemical impedance spectroscopy was used to characterize the interface for several materials of Au, Pt, and stainless steel electrode in 0.9% NaCl solution. The new model and the previous model were applied to fit the measured impedance results, and were compared their goodness of fit","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127643785","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}
Y. Tran, R. Thuraisingham, N. Wijesuriya, H.T. Nguyen, A. Craig
Brain computer interface (BCI) technology as its name implies, relies upon decoding brain signals into operational commands. Aside from needing effective means of control, successful BCIs need to remain stable in varying physiological conditions. BCIs need to be developed with mechanisms to recognise and respond to physiological states (such as stress and fatigue) that can disrupt user capability. This paper compares a spectral analysis of EEG signals technique with a nonlinear method of sample entropy to detect changes in brain dynamics during moments of stress and fatigue. The results demonstrated few changes in the spectral frequency bands of the EEG during fatigue and stress conditions. However, when the EEG signals were analysed with the nonlinear technique of sample entropy the results indicated a reduction of complexity during moments of fatigue and stress and an increase in complexity during moments of engagement to the task.
{"title":"Detecting neural changes during stress and fatigue effectively: a comparison of spectral analysis and sample entropy","authors":"Y. Tran, R. Thuraisingham, N. Wijesuriya, H.T. Nguyen, A. Craig","doi":"10.1109/CNE.2007.369682","DOIUrl":"https://doi.org/10.1109/CNE.2007.369682","url":null,"abstract":"Brain computer interface (BCI) technology as its name implies, relies upon decoding brain signals into operational commands. Aside from needing effective means of control, successful BCIs need to remain stable in varying physiological conditions. BCIs need to be developed with mechanisms to recognise and respond to physiological states (such as stress and fatigue) that can disrupt user capability. This paper compares a spectral analysis of EEG signals technique with a nonlinear method of sample entropy to detect changes in brain dynamics during moments of stress and fatigue. The results demonstrated few changes in the spectral frequency bands of the EEG during fatigue and stress conditions. However, when the EEG signals were analysed with the nonlinear technique of sample entropy the results indicated a reduction of complexity during moments of fatigue and stress and an increase in complexity during moments of engagement to the task.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128469926","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}
The aim of this study was to obtain an insight of how fear memory is encoded in the electrophysiological signals of the rat. We recorded local field potentials (LFPs) of the lateral amygdala (LA) and the medial geniculate nucleus (MGm) in the rat's brain during retrieval of fear memory. The rats were trained to freeze when they hear the conditioned tone (CS+) using Pavlovian fear conditioning. Total 10 adult rats were used for this experiment and 10-second of noise-free LFPs was used for analysis. We found increased theta power spectrum of neural activity in the LA and the MGm during retrieval of fear memory similar with the previous report. The linear functional connectivity between the LA and the MGm also increased after fear conditioning, specifically during CS+ presentation. In addition, approximate entropy (ApEn), a nonlinear measure of complexity and irregularity of signals, indicated that there was more information processing during fear state. These results show that recall of fear memory can be distinguished from the rest state of brain using linear and nonlinear properties of electrophysiological signals. These electrophysiological properties of fear memory would be used in neuro-engineering field to modify or decode the neural activity for clinical application
{"title":"Analysis of fear memory signals in the rat amygdala and thalamus","authors":"Hyeran Jang, Sumin Chang, Mookyoung Han, K. Baek, Dongil Chung, Jaeseung Jeong","doi":"10.1109/CNE.2007.369763","DOIUrl":"https://doi.org/10.1109/CNE.2007.369763","url":null,"abstract":"The aim of this study was to obtain an insight of how fear memory is encoded in the electrophysiological signals of the rat. We recorded local field potentials (LFPs) of the lateral amygdala (LA) and the medial geniculate nucleus (MGm) in the rat's brain during retrieval of fear memory. The rats were trained to freeze when they hear the conditioned tone (CS+) using Pavlovian fear conditioning. Total 10 adult rats were used for this experiment and 10-second of noise-free LFPs was used for analysis. We found increased theta power spectrum of neural activity in the LA and the MGm during retrieval of fear memory similar with the previous report. The linear functional connectivity between the LA and the MGm also increased after fear conditioning, specifically during CS+ presentation. In addition, approximate entropy (ApEn), a nonlinear measure of complexity and irregularity of signals, indicated that there was more information processing during fear state. These results show that recall of fear memory can be distinguished from the rest state of brain using linear and nonlinear properties of electrophysiological signals. These electrophysiological properties of fear memory would be used in neuro-engineering field to modify or decode the neural activity for clinical application","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128742631","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}
The most common treatment for patients with hydrocephalus is the surgical implantation of a cerebrospinal-fluid (CSF) shunt. A leading cause of shunt failure is the obstruction of the ventricular catheter. The goal of this project is to design a ventricular catheter that will resist occlusion through the use of micromachining and micro-electro-mechanical systems (MEMS) technologies. We designed, fabricated, and tested a second-generation magnetic microactuator. The preliminary results show that the fabricated microactuators can produce the force necessary to break an adherent cellular layer grown over the microactuator surface.
{"title":"Magnetic Microactuators for MEMS-Enabled Ventricular Catheters for Hydrocephalus","authors":"S.A. Lee, J. Pinney, M. Bergsneider, J. Judy","doi":"10.1109/CNE.2007.369613","DOIUrl":"https://doi.org/10.1109/CNE.2007.369613","url":null,"abstract":"The most common treatment for patients with hydrocephalus is the surgical implantation of a cerebrospinal-fluid (CSF) shunt. A leading cause of shunt failure is the obstruction of the ventricular catheter. The goal of this project is to design a ventricular catheter that will resist occlusion through the use of micromachining and micro-electro-mechanical systems (MEMS) technologies. We designed, fabricated, and tested a second-generation magnetic microactuator. The preliminary results show that the fabricated microactuators can produce the force necessary to break an adherent cellular layer grown over the microactuator surface.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"9 Suppl 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116933178","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}
Realistic finite element (FE) head models for neuro-electromagnetic imaging are getting more attention due to their analytic advantages over conventional models. To improve the numerical efficiency, we have previously developed a novel mesh generation scheme that produces FE head models automatically that are content-adaptive to given MR images. MRI content-adaptive FE meshes (cMeshes) represent the electrically conducting domain more effectively with less number of nodes and elements, thus lessen the computational loads. In general, the cMesh generation is affected by the selection of feature maps derived from MRI. In this study, we have tested the effects of various feature maps on the generation of cMesh FE head models. Also we have evaluated the quality of cMesh FE head models to check their suitability for neuro-electromagnetic imaging using EEG and MEG. The results suggest that the cMesh FE head models with properly selected feature maps do show acceptable quality to be used in neuro-electromagnetic imaging.
{"title":"Mesh Quality Analysis of MRI Content-adaptive FE Head Models for Neuro-Electromagnetic Imaging","authors":"W.H. Lee, T. Kim, Y.H. Kim, S.Y. Lee","doi":"10.1109/CNE.2007.369658","DOIUrl":"https://doi.org/10.1109/CNE.2007.369658","url":null,"abstract":"Realistic finite element (FE) head models for neuro-electromagnetic imaging are getting more attention due to their analytic advantages over conventional models. To improve the numerical efficiency, we have previously developed a novel mesh generation scheme that produces FE head models automatically that are content-adaptive to given MR images. MRI content-adaptive FE meshes (cMeshes) represent the electrically conducting domain more effectively with less number of nodes and elements, thus lessen the computational loads. In general, the cMesh generation is affected by the selection of feature maps derived from MRI. In this study, we have tested the effects of various feature maps on the generation of cMesh FE head models. Also we have evaluated the quality of cMesh FE head models to check their suitability for neuro-electromagnetic imaging using EEG and MEG. The results suggest that the cMesh FE head models with properly selected feature maps do show acceptable quality to be used in neuro-electromagnetic imaging.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115134304","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}
We have developed a noninvasive, unobtrusive magnetic wireless tongue-computer interface, called "Tongue Drive", to provide people with severe disabilities with flexible and effective computer access and environment control. A small permanent magnet secured on the tongue using a tongue clip, tissue adhesive, or tongue piercing is utilized as a marker to track tongue movements. The magnetic field variations due to the marker movements are detected by an array of magnetic sensors mounted on a headset outside the mouth or an orthodontic brace inside. The sensor outputs are then processed and translated into different user control commands after being wirelessly transmitted to a portable computer (PC or PDA). These commands can be used to access a computer by substituting the mouse or keyboard functions. They can also be customized to operate a powered wheelchair, a phone, or other equipments. For human trials, we have developed a prototype system with 6 direct commands on a baseball helmet and successfully tested it. The Tongue Drive system response time for >95% correctly completed commands is about 1.5 s.
{"title":"A Magnetic Wireless Tongue-Computer Interface","authors":"Xueliang Huo, Jia Wang, Maysam Ghovanloo","doi":"10.1109/CNE.2007.369676","DOIUrl":"https://doi.org/10.1109/CNE.2007.369676","url":null,"abstract":"We have developed a noninvasive, unobtrusive magnetic wireless tongue-computer interface, called \"Tongue Drive\", to provide people with severe disabilities with flexible and effective computer access and environment control. A small permanent magnet secured on the tongue using a tongue clip, tissue adhesive, or tongue piercing is utilized as a marker to track tongue movements. The magnetic field variations due to the marker movements are detected by an array of magnetic sensors mounted on a headset outside the mouth or an orthodontic brace inside. The sensor outputs are then processed and translated into different user control commands after being wirelessly transmitted to a portable computer (PC or PDA). These commands can be used to access a computer by substituting the mouse or keyboard functions. They can also be customized to operate a powered wheelchair, a phone, or other equipments. For human trials, we have developed a prototype system with 6 direct commands on a baseball helmet and successfully tested it. The Tongue Drive system response time for >95% correctly completed commands is about 1.5 s.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127358645","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}
Microelectrode array recordings from single neurons generate multidimensional data (spike trains) that contains vast amount of information on underlying neural dynamics. Typically, the data analysis procedure is very time consuming, which greatly hinders the experimental throughputs. Bioinformatics community also deals with high dimensional data sets and the underlying mathematics of data analysis used in this field is very similar to that used in neural informatics. Here, we attempt to use the well-established data analysis procedure (Bayesian network inference) in Bioinformatics and utilized it to estimate the functional connectivity of cultured neural networks based on multichannel spike trains. The basic analysis procedure could be easily extended to in vivo neural spike data analysis for various neural engineering applications
{"title":"Bayesian Network Inference to Estimate the Functional Connectivity of Cultured Neuronal Networks","authors":"Sungwon Jung, Doheon Lee, Y. Nam","doi":"10.1109/CNE.2007.369766","DOIUrl":"https://doi.org/10.1109/CNE.2007.369766","url":null,"abstract":"Microelectrode array recordings from single neurons generate multidimensional data (spike trains) that contains vast amount of information on underlying neural dynamics. Typically, the data analysis procedure is very time consuming, which greatly hinders the experimental throughputs. Bioinformatics community also deals with high dimensional data sets and the underlying mathematics of data analysis used in this field is very similar to that used in neural informatics. Here, we attempt to use the well-established data analysis procedure (Bayesian network inference) in Bioinformatics and utilized it to estimate the functional connectivity of cultured neural networks based on multichannel spike trains. The basic analysis procedure could be easily extended to in vivo neural spike data analysis for various neural engineering applications","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126622314","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}
The development of wireless ambulatory EEG is crucial in enabling the longer term monitoring of a patient in their everyday environment. The analysis presented here will aid the designer of a wireless EEG headset in improving the ratio of battery lifetime to battery size, with the aim of minimising the size and weight of the device. Data compression is proposed as a method to reduce the power used by the wireless transceiver, shown to dominate the system power budget. Graphs are presented which show the power available to perform varying degrees of compression in order to achieve the required lifetime or battery volume
{"title":"A Key Power Trade-off in Wireless EEG Headset Design","authors":"D. Yates, E. Rodríguez-Villegas","doi":"10.1109/CNE.2007.369707","DOIUrl":"https://doi.org/10.1109/CNE.2007.369707","url":null,"abstract":"The development of wireless ambulatory EEG is crucial in enabling the longer term monitoring of a patient in their everyday environment. The analysis presented here will aid the designer of a wireless EEG headset in improving the ratio of battery lifetime to battery size, with the aim of minimising the size and weight of the device. Data compression is proposed as a method to reduce the power used by the wireless transceiver, shown to dominate the system power budget. Graphs are presented which show the power available to perform varying degrees of compression in order to achieve the required lifetime or battery volume","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126746183","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}
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