An algorithmic approach to develop the vocabulary of the nervous system and to use the vocabulary to communicate with the outside world is presented. The vocabulary is constructed using wavelet analysis of the recorded waveforms. Spikes of different frequency and amplitude from different channels are identified to construct unique signatures and relate them to physiological activities. A vocabulary-based communication of recorded action potentials renders two major advantages: a) it allows transmission of recorded data with large compression, thus, saving power and communication bandwidth of the integrated telemetry device; b) it helps easy mapping of alphabets in the vocabulary to muscular dynamics, which facilitates micro-stimulation based neural prostheses. In this work, we study the effectiveness of the proposed approach in neural data compression. Simulation results on pre-recorded data from the buccal nerves of a sea-slug shows that the proposed approach results in up to 80X compression
{"title":"Neural Data Compression with Wavelet Transform: A Vocabulary Based Approach","authors":"S. Narasimhan, M. Tabib-Azar, H. Chiel, S. Bhunia","doi":"10.1109/CNE.2007.369760","DOIUrl":"https://doi.org/10.1109/CNE.2007.369760","url":null,"abstract":"An algorithmic approach to develop the vocabulary of the nervous system and to use the vocabulary to communicate with the outside world is presented. The vocabulary is constructed using wavelet analysis of the recorded waveforms. Spikes of different frequency and amplitude from different channels are identified to construct unique signatures and relate them to physiological activities. A vocabulary-based communication of recorded action potentials renders two major advantages: a) it allows transmission of recorded data with large compression, thus, saving power and communication bandwidth of the integrated telemetry device; b) it helps easy mapping of alphabets in the vocabulary to muscular dynamics, which facilitates micro-stimulation based neural prostheses. In this work, we study the effectiveness of the proposed approach in neural data compression. Simulation results on pre-recorded data from the buccal nerves of a sea-slug shows that the proposed approach results in up to 80X compression","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"133 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":"114651718","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}
N. Livnat, O. Sarig-Nadir, R. Zajdman, D. Seliktar, S. Shoham
We are exploring a novel two-photon lithography technique for creating nerve guidance channels in PEGylated protein hydrogels for functional nerve regeneration. We have developed a two-photon lithography system for photoprinting of geometric landscapes at sub-micrometer spatial resolution. The photoprinting is accomplished in a light sensitive biocompatible precursor solution containing a biological backbone that is coupled to a synthetic polymer cross-linker. A non-toxic light-activated reaction is used to polymerize the precursor into the hydrogel matrix in the presence of cells and tissues. We show how PEGylated protein hydrogels made from fibrinogen and collagen are able to encourage outgrowth of neuronal and non-neuronal cells from explants of dorsal root ganglion (DRG) into the hydrogel matrix. In preliminary data, DRG cells are seen migrating out from the DRG and into channels inscribed into the hydrogel matrix. We aim to demonstrate the importance of three-dimensional (3D) spatial geometric resolution of the lithographic system in guiding nerve cells towards functional nerve regeneration.
{"title":"A Hydrogel-Based Nerve Regeneration Conduit with Sub-Micrometer Feature Control","authors":"N. Livnat, O. Sarig-Nadir, R. Zajdman, D. Seliktar, S. Shoham","doi":"10.1109/CNE.2007.369622","DOIUrl":"https://doi.org/10.1109/CNE.2007.369622","url":null,"abstract":"We are exploring a novel two-photon lithography technique for creating nerve guidance channels in PEGylated protein hydrogels for functional nerve regeneration. We have developed a two-photon lithography system for photoprinting of geometric landscapes at sub-micrometer spatial resolution. The photoprinting is accomplished in a light sensitive biocompatible precursor solution containing a biological backbone that is coupled to a synthetic polymer cross-linker. A non-toxic light-activated reaction is used to polymerize the precursor into the hydrogel matrix in the presence of cells and tissues. We show how PEGylated protein hydrogels made from fibrinogen and collagen are able to encourage outgrowth of neuronal and non-neuronal cells from explants of dorsal root ganglion (DRG) into the hydrogel matrix. In preliminary data, DRG cells are seen migrating out from the DRG and into channels inscribed into the hydrogel matrix. We aim to demonstrate the importance of three-dimensional (3D) spatial geometric resolution of the lithographic system in guiding nerve cells towards functional nerve regeneration.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"107 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":"116667378","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}
Entropy calculated on EEG has been shown to be a useful indicator of effects from insufficient oxygen supply. In this paper, the estimation of entropy is based on transition matrices instead of probability density functions. It is shown that the separation of sleep stages thereby can be improved. This suggests that by including time information given by the transition matrix in entropy estimates of the EEG, classification can be improved.
{"title":"EEG entropy estimation using a Markov model of the EEG for sleep stage separation in human neonates","authors":"N. Lofgren, N. Outram, M. Thordstein","doi":"10.1109/CNE.2007.369753","DOIUrl":"https://doi.org/10.1109/CNE.2007.369753","url":null,"abstract":"Entropy calculated on EEG has been shown to be a useful indicator of effects from insufficient oxygen supply. In this paper, the estimation of entropy is based on transition matrices instead of probability density functions. It is shown that the separation of sleep stages thereby can be improved. This suggests that by including time information given by the transition matrix in entropy estimates of the EEG, classification can be improved.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"81 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":"116769558","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}
Sung-Phil Kim, J. Simeral, L. Hochberg, J. Donoghue, G. Friehs, Michael J. Black
Basic neural prosthetic control of a computer cursor has been recently demonstrated by Hochberg et al. (2006) using the BrainGate system (Cyberkinetics Neurotechnology Systems, Inc.). While these results demonstrate the feasibility of intracortically-driven prostheses for humans with paralysis, a practical cursor-based computer interface requires more precise cursor control and the ability to "click" on areas of interest. Here we present the first practical point and click device that decodes both continuous states (e.g. cursor kinematics) and discrete states (e.g. click states) from a single neural population in human motor cortex. We describe a probabilistic multi-state decoder and the necessary training paradigms that enable point and click cursor control by a human with tetraplegia using an implanted microelectrode array. We present results from multiple recording sessions and quantify the point and click performance
{"title":"Multi-state decoding of point-and-click control signals from motor cortical activity in a human with tetraplegia","authors":"Sung-Phil Kim, J. Simeral, L. Hochberg, J. Donoghue, G. Friehs, Michael J. Black","doi":"10.1109/CNE.2007.369715","DOIUrl":"https://doi.org/10.1109/CNE.2007.369715","url":null,"abstract":"Basic neural prosthetic control of a computer cursor has been recently demonstrated by Hochberg et al. (2006) using the BrainGate system (Cyberkinetics Neurotechnology Systems, Inc.). While these results demonstrate the feasibility of intracortically-driven prostheses for humans with paralysis, a practical cursor-based computer interface requires more precise cursor control and the ability to \"click\" on areas of interest. Here we present the first practical point and click device that decodes both continuous states (e.g. cursor kinematics) and discrete states (e.g. click states) from a single neural population in human motor cortex. We describe a probabilistic multi-state decoder and the necessary training paradigms that enable point and click cursor control by a human with tetraplegia using an implanted microelectrode array. We present results from multiple recording sessions and quantify the point and click performance","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":"122256382","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}
This paper introduces a new method to improve at the same time the comprehension of the discomfort for partially sighted and the efficiency of visual aids. It presents an objective and non invasive analysis allowing to understand the patient-signal interaction. This system interacts with a sensory input: eye movements. Analysis in real time of eye movements permits to specify patient adaptation and cognitive behavior relating to a difficulty to identify visual signal. This personalized method will permit to adapt all visual information to patient need with an image processing commanded and controlled by the eyes. The final objective is to create self-adaptive visual aids by synchronizing image processing to patient eye movements.
{"title":"Eye movements : sensory input to command and control adaptive visual aids","authors":"A. Scherlen, V. Gautier","doi":"10.1109/CNE.2007.369669","DOIUrl":"https://doi.org/10.1109/CNE.2007.369669","url":null,"abstract":"This paper introduces a new method to improve at the same time the comprehension of the discomfort for partially sighted and the efficiency of visual aids. It presents an objective and non invasive analysis allowing to understand the patient-signal interaction. This system interacts with a sensory input: eye movements. Analysis in real time of eye movements permits to specify patient adaptation and cognitive behavior relating to a difficulty to identify visual signal. This personalized method will permit to adapt all visual information to patient need with an image processing commanded and controlled by the eyes. The final objective is to create self-adaptive visual aids by synchronizing image processing to patient eye movements.","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":"128594162","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}
T. Gritsun, S. Vogt, G. Engler, C. Moll, A. Engel, S. Kondra, L. Ramrath, U.G. Hofinann
A simple method to produce multi-wire bundles by spinning is demonstrated, yielding nine recording sites. These so called "niotrodes" are then used in an acute experiment to record from several positions along trajectories into rat's basal ganglia. Niotrodes with an impedance in the range of 300kOhm@1kHz display the capability to record both single and multi unit activity and seem to be able to map a small volume in the brain with high density. A novel spike detection operator and further improvements towards a multi-multi-unit array are suggested.
{"title":"A Simple Microelectrode Bundle for Deep Brain Recordings","authors":"T. Gritsun, S. Vogt, G. Engler, C. Moll, A. Engel, S. Kondra, L. Ramrath, U.G. Hofinann","doi":"10.1109/CNE.2007.369625","DOIUrl":"https://doi.org/10.1109/CNE.2007.369625","url":null,"abstract":"A simple method to produce multi-wire bundles by spinning is demonstrated, yielding nine recording sites. These so called \"niotrodes\" are then used in an acute experiment to record from several positions along trajectories into rat's basal ganglia. Niotrodes with an impedance in the range of 300kOhm@1kHz display the capability to record both single and multi unit activity and seem to be able to map a small volume in the brain with high density. A novel spike detection operator and further improvements towards a multi-multi-unit array are suggested.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"47 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":"131087435","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}
In this paper, we propose a new feature extraction algorithm for brain-computer interfaces (BCIs). This algorithm is based on inverse models and uses the novel concept of fuzzy region of interest (ROI). It can automatically identify the relevant ROIs and their reactive frequency bands. The activity in these ROIs can be used as features for any classifier. A first evaluation of the algorithm, using a support vector machine (SVM) as classifier, is reported on data set IV from BCI competition 2003. Results are promising as we reached an accuracy on the test set ranging from 85 % to 86 % whereas the winner of the competition on this data set reached 84%.
{"title":"FuRIA: A Novel Feature Extraction Algorithm for Brain-Computer Interfaces using Inverse Models and Fuzzy Regions of Interest","authors":"F. Lotte, A. Lécuyer, B. Arnaldi","doi":"10.1109/CNE.2007.369640","DOIUrl":"https://doi.org/10.1109/CNE.2007.369640","url":null,"abstract":"In this paper, we propose a new feature extraction algorithm for brain-computer interfaces (BCIs). This algorithm is based on inverse models and uses the novel concept of fuzzy region of interest (ROI). It can automatically identify the relevant ROIs and their reactive frequency bands. The activity in these ROIs can be used as features for any classifier. A first evaluation of the algorithm, using a support vector machine (SVM) as classifier, is reported on data set IV from BCI competition 2003. Results are promising as we reached an accuracy on the test set ranging from 85 % to 86 % whereas the winner of the competition on this data set reached 84%.","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":"131152010","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 report on a new hydraulic drive system for a microdrive, which enables the recording of multi-unit activity of waking animals. Our principal motivation for inventing this device was to simplify the task of positioning electrodes, which consumes a considerable amount of time and requires a high level of skill. The microdrive is cylindrical and has a diameter of 23.5 mm, a height of 37 mm, and a weight of 15 g. It allows for up to 22 electrodes, which are arranged on a 0.35 mm grid. The new microdrive is based on hydraulics to reduce its size and to facilitate its construction such as wiring of the electrodes. Fine movement of electrodes is realized by computer-controlled fluid supply system which can control a minimum of 0.004 mm3 amount of fluid. Although in a single-direction movement, each electrode can be positioned at any depth up to approximately 4 mm. The microdrive was evaluated under acute and chronic recording experiments and is shown to be capable of automatically positioning each electrode and successfully recording the neural signals of waking rats.
{"title":"Independent hydraulic positioning for an implantable multi-electrode array","authors":"T. Sato, T. Suzuki, K. Mabuchi","doi":"10.1109/CNE.2007.369615","DOIUrl":"https://doi.org/10.1109/CNE.2007.369615","url":null,"abstract":"We report on a new hydraulic drive system for a microdrive, which enables the recording of multi-unit activity of waking animals. Our principal motivation for inventing this device was to simplify the task of positioning electrodes, which consumes a considerable amount of time and requires a high level of skill. The microdrive is cylindrical and has a diameter of 23.5 mm, a height of 37 mm, and a weight of 15 g. It allows for up to 22 electrodes, which are arranged on a 0.35 mm grid. The new microdrive is based on hydraulics to reduce its size and to facilitate its construction such as wiring of the electrodes. Fine movement of electrodes is realized by computer-controlled fluid supply system which can control a minimum of 0.004 mm3 amount of fluid. Although in a single-direction movement, each electrode can be positioned at any depth up to approximately 4 mm. The microdrive was evaluated under acute and chronic recording experiments and is shown to be capable of automatically positioning each electrode and successfully recording the neural signals of waking rats.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"47 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":"125498661","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}
P. Artemiadis, G. Shakhnarovich, C. Vargas-Irwin, J. Donoghue, Michael J. Black
The direct neural control of external prosthetic devices such as robot hands requires the accurate decoding of neural activity representing continuous movement. This requirement becomes formidable when multiple degrees of freedom (DoFs) are to be controlled as in the case of the fingers of a robotic hand. In this paper a methodology is proposed for estimating grasp aperture using the spiking activity of multiple neurons recorded with an electrode array implanted in the arm/hand area of primary motor cortex (Ml). Grasp aperture provides a reasonable approximation to the hand configuration during grasping tasks, while it offers a large reduction in the number of DoFs that must be estimated. A family of state space models with hidden variables is used to decode each finger grasp aperture with respect to the thumb from a population of motor-cortical neurons. The firing rates of multiple neurons in Ml were found to be correlated with grasp aperture and were used as inputs to our decoding algorithm. The proposed decoding architecture was evaluated off-line by decoding pre-recorded neural activity from monkey motor cortex during a natural grasping task. We found that our model was able to accurately reconstruct finger grasp aperture from a small population of cells. This demonstrates the first decoding of continuous grasp aperture from Ml suggesting the feasibility for neural control of prosthetic robotic hands from neuronal population signals
{"title":"Decoding grasp aperture from motor-cortical population activity","authors":"P. Artemiadis, G. Shakhnarovich, C. Vargas-Irwin, J. Donoghue, Michael J. Black","doi":"10.1109/CNE.2007.369723","DOIUrl":"https://doi.org/10.1109/CNE.2007.369723","url":null,"abstract":"The direct neural control of external prosthetic devices such as robot hands requires the accurate decoding of neural activity representing continuous movement. This requirement becomes formidable when multiple degrees of freedom (DoFs) are to be controlled as in the case of the fingers of a robotic hand. In this paper a methodology is proposed for estimating grasp aperture using the spiking activity of multiple neurons recorded with an electrode array implanted in the arm/hand area of primary motor cortex (Ml). Grasp aperture provides a reasonable approximation to the hand configuration during grasping tasks, while it offers a large reduction in the number of DoFs that must be estimated. A family of state space models with hidden variables is used to decode each finger grasp aperture with respect to the thumb from a population of motor-cortical neurons. The firing rates of multiple neurons in Ml were found to be correlated with grasp aperture and were used as inputs to our decoding algorithm. The proposed decoding architecture was evaluated off-line by decoding pre-recorded neural activity from monkey motor cortex during a natural grasping task. We found that our model was able to accurately reconstruct finger grasp aperture from a small population of cells. This demonstrates the first decoding of continuous grasp aperture from Ml suggesting the feasibility for neural control of prosthetic robotic hands from neuronal population signals","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"12 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":"127500037","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 motor imagery detection is a very important problem in the asynchronous control for direct brain computer interface. To address this issue, this paper proposes a novel detection method based on subband entropy analysis in a selected frequency band. The basic idea of this method is that, in some specific frequency band, the complexity (or randomness) of brain signal during the stage of concentrating on the motor imagery is lower than that of free thinking. Once the optimal frequency band is selected, the subband entropy $an indicator of complexity and randomness - can be used for detecting the motor imagery. In this work, we develop the method using only one dipolar EEG channel. Furthermore, we propose a system calibration method based on an empirical measurement what we refer as unsupervised discriminative index (UDI). The proposed calibration method is rapid and able to avoid a typical problem of asynchronous BCI training that is the correct labeling of continuous EEG signal. The proposed method not only improve the accuracy of the detection but free from parameter tweaking. The experiment conducted on three different subjects shows advantage of the proposed method over the conventional framework based on fixed-band filter and energy feature. A detection accuracy up to 77% at false positive rate of 2% was obtained without any subject training.
{"title":"Selective Subband Entropy for Motor Imagery Detection in Asynchronous Brain Computer Interface","authors":"T. H. Dat, Z. Haihong, Wang Chuanchu, G. Cuntai","doi":"10.1109/CNE.2007.369684","DOIUrl":"https://doi.org/10.1109/CNE.2007.369684","url":null,"abstract":"The motor imagery detection is a very important problem in the asynchronous control for direct brain computer interface. To address this issue, this paper proposes a novel detection method based on subband entropy analysis in a selected frequency band. The basic idea of this method is that, in some specific frequency band, the complexity (or randomness) of brain signal during the stage of concentrating on the motor imagery is lower than that of free thinking. Once the optimal frequency band is selected, the subband entropy $an indicator of complexity and randomness - can be used for detecting the motor imagery. In this work, we develop the method using only one dipolar EEG channel. Furthermore, we propose a system calibration method based on an empirical measurement what we refer as unsupervised discriminative index (UDI). The proposed calibration method is rapid and able to avoid a typical problem of asynchronous BCI training that is the correct labeling of continuous EEG signal. The proposed method not only improve the accuracy of the detection but free from parameter tweaking. The experiment conducted on three different subjects shows advantage of the proposed method over the conventional framework based on fixed-band filter and energy feature. A detection accuracy up to 77% at false positive rate of 2% was obtained without any subject training.","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"4 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":"129469230","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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