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A method of dynamic topography for EEG in epilepsy
てんかん脳波のダイナミック・トポグラフィの一方法

Motohiro Yoneya, Masayoshi Kowada
1986 Journal of the Japan Epilepsy Society  
A clinical application in case of focal epilepsy was presented. Our display made it possible to analyze sequentially dynamic correlation between epiletogenic discharge and basic activity. J. Jpn.  ...  Fig. 3 Flow chart of dynamic EEG topography EEGs are converted into digital data at 64 samples per second and spectral analysis is carried out.  ... 
doi:10.3805/jjes.4.1 fatcat:lvbjcok25vaaxhxvawnslub6zq

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

Michael J. Prerau, Ritchie E. Brown, Matt T. Bianchi, Jeffrey M. Ellenbogen, Patrick L. Purdon
2017 Physiology  
During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG).  ...  We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate  ...  The authors have developed a companion series of interactive online tutorials for this review at sleepeeg.org.  ... 
doi:10.1152/physiol.00062.2015 pmid:27927806 pmcid:PMC5343535 fatcat:tlyosfzsvncxnceu2orvcn3gl4

An Evaluation of Autoregressive Spectral Estimation Model Order for Brain-Computer Interface Applications

Dean J. Krusienski, Dennis J. McFarland, Jonathan R. Wolpaw
2006 2006 International Conference of the IEEE Engineering in Medicine and Biology Society  
Autoregressive (AR) spectral estimation is a popular method for modeling the electroencephalogram (EEG), and therefore the frequency domain EEG phenomena that are used for control of a brain-computer interface  ...  The present study confirms this by evaluating the EEG spectra of data obtained during control of SMR-BCI using different AR model orders and model evaluation criteria.  ...  However, for SMR-BCI applications, the EEG is actively modulated and the dynamics are likely atypical of the EEG examined in the previous studies.  ... 
doi:10.1109/iembs.2006.259822 pmid:17946038 fatcat:dn7u4iuwn5fxpicu76xdro5weu

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Jennifer J. Heisz, Anthony R. McIntosh
2013 Journal of Visualized Experiments  
MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.  ...  However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics.  ...  The interpretation of results from more traditional applications of neuroimaging data, such as ERP and spectral power, are augmented by measures of complexity like MSE; MSE provides a way to capture the  ... 
doi:10.3791/50131 pmid:23851571 pmcid:PMC3729183 fatcat:64fr5onqijdslne7tnupx5zkoy

Mind Monitoring via Mobile Brain-Body Imaging [chapter]

Scott Makeig
2009 Lecture Notes in Computer Science  
Joint modeling of this data should attempt to identify individualized modes of brain/body activity and/or reactivity that appear in the operator's brain and/or behavior in distinct cognitive contexts,  ...  and eye movements and, to the extent possible, her or his multisensory input.  ...  EEG Modulation EEG dynamics have long been characterized by their diverse spectral profiles.  ... 
doi:10.1007/978-3-642-02812-0_85 fatcat:ais24h4jijeuhcknb5qwsgh3qa

Fusion of electroencephalographic dynamics and musical contents for estimating emotional responses in music listening

Yuan-Pin Lin, Yi-Hsuan Yang, Tzyy-Ping Jung
2014 Frontiers in Neuroscience  
However, if EEG dynamics were only available from a small set of electrodes (likely the case in real-life applications), the music modality would play a complementary role and augment the EEG results from  ...  This study aimed to assess the applicability of a multimodal approach by leveraging the EEG dynamics and acoustic characteristics of musical contents for the classification of emotional valence and arousal  ...  Such evidence might in part facilitated the use of spectral dynamics within/between channels for the EEG-based emotion classification, e.g., spectra in individual channels and spectral asymmetry in left-right  ... 
doi:10.3389/fnins.2014.00094 pmid:24822035 pmcid:PMC4013455 fatcat:rahfs7a5dfguxptjoq3k7hluty

Using dynamic time warping for quantifying effects of sinusoidal oscillation deviations during EEG time series prediction and for finding interesting EEG and fMRI changes

Dinov Martin
2015 BMC Neuroscience  
changes in the EEG or fMRI.  ...  While comparing spectra is useful, it is incorrect to assume that the entirety of the spectral density is due to oscillatory activity proper (especially sinusoidal) [5] .  ...  Dynamic time warping (DTW) has successfully been used in feature extraction and analysis of brain data [1, 2] .  ... 
doi:10.1186/1471-2202-16-s1-p63 pmcid:PMC4697472 fatcat:anl3tsrlrnachiyxacaxomuky4

Applying machine learning EEG signal classification to emotion‑related brain anticipatory activity

Marco Bilucaglia, Gian Marco Duma, Giovanni Mento, Luca Semenzato, Patrizio E. Tressoldi
2021 F1000Research  
Considering the relevance of emotion in human cognition and behaviour, an important application of machine learning has been found in the field of emotion identification based on neurophysiological activity  ...  The results show a clear increase in classification accuracy with temporal dynamic features.  ...  Thammasan N, Fukui KI, Numao M: Application of deep belief networks in EEG-based dynamic music-emotion recognition.  ... 
doi:10.12688/f1000research.22202.2 fatcat:jnxxvmtlwvh5ja4fxf3fsrmhx4

Efficient feature selection and linear discrimination of EEG signals

Germán Rodríguez-Bermúdez, Pedro J. García-Laencina, Joaquín Roca-González, Joaquín Roca-Dorda
2013 Neurocomputing  
This work describes the fundamentals of EEG signals and its basic concepts related with nonlinear dynamics and chaotic measures of complexity and stability.  ...  After that, a short review of the most common EEG-based applications is given in medical and non-medical contexts.  ...  Medical applications It is assumed that the EEG must reflect the dynamic of the brain and, of course, psychiatric disorders and pathological states.  ... 
doi:10.1016/j.neucom.2013.01.001 fatcat:mopspmhn35d4jbnyety5cgsxuy

Modelling non-stationary variance in EEG time series by state space GARCH model

Kin Foon Kevin Wong, Andreas Galka, Okito Yamashita, Tohru Ozaki
2006 Computers in Biology and Medicine  
The method is illustrated by an application to EEG data recorded during the onset of anaesthesia.  ...  We present a new approach to modelling non-stationarity in EEG time series by a generalized state space approach.  ...  Acknowledgements The authors would like to thank Dr Roy John and Dr Leslie Prichep for providing the EEG data set and for dedicating their precious time to giving the authors comments and guidance.  ... 
doi:10.1016/j.compbiomed.2005.10.001 pmid:16293239 fatcat:ijlokxvurrddfoiixnfisvnrky

Time-frequency analysis of electroencephalogram series

S. Blanco, R. Quian Quiroga, O. A. Rosso, S. Kochen
1995 Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics  
In this paper we propose a method, based on the Gabor transform, to quantify and visualize the time evolution of the traditional frequency bands defined in the analysis of electroencephalogram (EEG) series  ...  We found an optimal correlation between EEG visual inspection and the proposed method in the characterization of paroxism, spikes, and other transient alterations of background activity.  ...  ACKNOWLEDGMENTS This work was supported by the Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) and Fundacion Alberto J. Roemmers (Argentina). We are grateful to Dr. J. P. N.  ... 
doi:10.1103/physreve.51.2624 pmid:9962925 fatcat:yc7fvkczxfhkrh3pwrhtewffyq

Revealing spatio-spectral electroencephalographic dynamics of musical mode and tempo perception by independent component analysis

Yuan-Pin Lin, Jeng-Ren Duann, Wenfeng Feng, Jyh-Horng Chen, Tzyy-Ping Jung
2014 Journal of NeuroEngineering and Rehabilitation  
In conjunction with advanced dry and mobile EEG technology, the EEG results might facilitate the translation from laboratory-oriented research to real-life applications for music therapy, training and  ...  Method: This study used independent component analysis (ICA) to systematically assess spatio-spectral EEG dynamics associated with the changes of musical mode and tempo.  ...  Acknowledgments Yuan-Pin Lin was supported in part by the Taiwan National Science Council Program (NSC97-2917-I-002-119). Tzyy-Ping Jung is in part supported by a gift from Abraxis Bioscience, LLC.  ... 
doi:10.1186/1743-0003-11-18 pmid:24581119 pmcid:PMC3941612 fatcat:fo63k2txvzbj5bg67hc7mfjfgq

Study on non-linear bistable dynamics model based EEG signal discrimination analysis method

Xiaoguo Ying, Han Lin, Guohua Hui
2015 Bioengineered  
EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index.  ...  In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed.  ...  Funding This work is financially supported by National Natural Science Foundation (Grant No. 81000645), and Key Laboratory of Forestry Intelligent Monitoring and Information Technology of Zhejiang Province  ... 
doi:10.1080/21655979.2015.1065360 pmid:26176364 pmcid:PMC4825826 fatcat:gmho5jeuqbh63nzdw3tnem25by

Synchrony and Complexity in State-Related EEG Networks: An Application of Spectral Graph Theory

Amir Hossein Ghaderi, Bianca R Baltaretu, Masood Nemati Andevari, Vishal Bharmauria, Fuat Balci
2020 Neural Computation  
To answer these questions, we tested the application of the spectral graph theory and the Shannon entropy as alternative approaches in neuroimaging.  ...  We specifically tested the alpha rhythm in the resting-state eye closed (rsEC) and the resting-state eye open (rsEO) conditions, a well-studied classical example of synchrony in neuroimaging EEG.  ...  In the rsEC and the rsEO matrices, each row/column represents an EEG channel (not applicable for random distribution matrices).  ... 
doi:10.1162/neco_a_01327 pmid:32946707 fatcat:szrlgjbln5fwhjfdxzfmer55xa

Model-based Bayesian filtering of cardiac contaminants from biomedical recordings

R Sameni, M B Shamsollahi, C Jutten
2008 Physiological Measurement  
as the EEG, EMG, and also for canceling maternal cardiac signals from fetal ECG/MCG.  ...  In this paper, it is shown that this framework may be effectively used for removing cardiac contaminants such as the ECG, MCG, and ballistocardiographic artifacts from different biomedical recordings such  ...  Acknowledgment This work was partially supported by Iran Telecommunication Research Center (ITRC), the French Embassy in Iran (PAI Gundishapur), and by the Center for International Research and Collaboration  ... 
doi:10.1088/0967-3334/29/5/006 pmid:18460766 fatcat:ca6obhcz6rg47ipu7muspvqgfy
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