Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923313
N. Pospelov, Egor Levchenko, V. Tiselko, Raisa Safronova, Ilya Zakharov, V. Sotskov, Konstantin V. Anokhin
We investigated the structure of the functional networks of the human brain using data from the OASIS dataset. To construct functional networks from BOLD signals, we used the method of dynamic time warping (DTW), which allows one to take into account possible distortions and nonlinear effects when comparing two time series. We investigated the resulting functional networks in terms of graph entropy, a recently proposed thermodynamic approach to describing dynamics in complex networks. The graph entropy approach provides tools to investigate the information flows in networks on different timescales. We showed a high heterogeneity of the resulting individual functional networks, expressed in a significant mismatch of the characteristic excitation diffusion times between subjects. We also constructed an artificial network model with a hierarchy of temporal scales to explain the detected multiscale nature of some functional networks. No differences were found between the healthy subjects and subjects with different levels of clinical dementia rating. We hypothesize that the heterogeneity we found may be related to the personality traits of the subjects, and we intend to investigate this issue further.
{"title":"Network entropy analysis reveals high heterogeneity of human functional networks","authors":"N. Pospelov, Egor Levchenko, V. Tiselko, Raisa Safronova, Ilya Zakharov, V. Sotskov, Konstantin V. Anokhin","doi":"10.1109/DCNA56428.2022.9923313","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923313","url":null,"abstract":"We investigated the structure of the functional networks of the human brain using data from the OASIS dataset. To construct functional networks from BOLD signals, we used the method of dynamic time warping (DTW), which allows one to take into account possible distortions and nonlinear effects when comparing two time series. We investigated the resulting functional networks in terms of graph entropy, a recently proposed thermodynamic approach to describing dynamics in complex networks. The graph entropy approach provides tools to investigate the information flows in networks on different timescales. We showed a high heterogeneity of the resulting individual functional networks, expressed in a significant mismatch of the characteristic excitation diffusion times between subjects. We also constructed an artificial network model with a hierarchy of temporal scales to explain the detected multiscale nature of some functional networks. No differences were found between the healthy subjects and subjects with different levels of clinical dementia rating. We hypothesize that the heterogeneity we found may be related to the personality traits of the subjects, and we intend to investigate this issue further.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127157614","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923322
E. Kuzmina, Dmitrii Kriukov, M. Lebedev
While the brain obviously performs very sophisticated functions, neurophysiological studies conducted over the last several decades have scrutinized a relatively simple phenomenon: a neuron’s firing rate is modulated when a subject performs a behavior or even mentally rehearses it, and such modulations are relatively consistent from one attempt to the other. It has become fashionable to attribute neuronal modulation to encoding various behavioral variables, such as arm movement direction. More recently, with the development of brain-computer interfaces, much work has been put into decoding information from neuronal firing rates, which strengthened the belief that neurons do encode various parameters. Yet, many researchers looked for alternative explanations of neuronal modulations rather than merely encoding. Such inquiries advanced with the development of multichannel recordings that yielded neuronal-ensemble data. Thus, in 2012, Churchland et al. published the paper entitled “Neural population dynamics during reaching” where they claimed that cortical neuronal ensembles act as dynamical system like a pendulum or a spring. In their view, neurons in such a dynamical system do not encode parameters – movement direction, muscle force etc. - but rather keep an action going. Importantly, such a dynamical system produces rhythmic, oscillatory patterns, which Churchland et al. called ‘dynamical rotations’ and plotted as circular trajectories using an analysis that they called jPCA. Since the proposed jPCA approach has become wildly popular, with the original paper getting hundreds of citations, and many follow-up publications emerging, further tackling of this method is important, and hopefully additional analyses could improve our understanding of how the brain works. Here we scrutinized the assumptions and restrictions of jPCA. By getting under the hood of jPCA we demonstrated the simplest case when it reveals rotations regardless of the data nature. It turns out that the necessary condition for rotations is hidden in the covariance matrix structure. Our work questions the unequivocal interpretation of data “rotations” and the conclusions made from it.
{"title":"Further Observations on the Rotational Structure in Neural Data","authors":"E. Kuzmina, Dmitrii Kriukov, M. Lebedev","doi":"10.1109/DCNA56428.2022.9923322","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923322","url":null,"abstract":"While the brain obviously performs very sophisticated functions, neurophysiological studies conducted over the last several decades have scrutinized a relatively simple phenomenon: a neuron’s firing rate is modulated when a subject performs a behavior or even mentally rehearses it, and such modulations are relatively consistent from one attempt to the other. It has become fashionable to attribute neuronal modulation to encoding various behavioral variables, such as arm movement direction. More recently, with the development of brain-computer interfaces, much work has been put into decoding information from neuronal firing rates, which strengthened the belief that neurons do encode various parameters. Yet, many researchers looked for alternative explanations of neuronal modulations rather than merely encoding. Such inquiries advanced with the development of multichannel recordings that yielded neuronal-ensemble data. Thus, in 2012, Churchland et al. published the paper entitled “Neural population dynamics during reaching” where they claimed that cortical neuronal ensembles act as dynamical system like a pendulum or a spring. In their view, neurons in such a dynamical system do not encode parameters – movement direction, muscle force etc. - but rather keep an action going. Importantly, such a dynamical system produces rhythmic, oscillatory patterns, which Churchland et al. called ‘dynamical rotations’ and plotted as circular trajectories using an analysis that they called jPCA. Since the proposed jPCA approach has become wildly popular, with the original paper getting hundreds of citations, and many follow-up publications emerging, further tackling of this method is important, and hopefully additional analyses could improve our understanding of how the brain works. Here we scrutinized the assumptions and restrictions of jPCA. By getting under the hood of jPCA we demonstrated the simplest case when it reveals rotations regardless of the data nature. It turns out that the necessary condition for rotations is hidden in the covariance matrix structure. Our work questions the unequivocal interpretation of data “rotations” and the conclusions made from it.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125825462","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923267
Elizaveta S. Dubinkina, E. Borovkova, A. Hramkov, A. Karavaev, Alexander V. Kurbako, M. Prokhorov
Currently, the measurement of stress is an important, relevant and unsolved problem. Despite the fact that it has been shown that various physiological indicators can be used to assess stress, a universal classical method for assessing the cognitive status of subjects in the analysis of non-invasively recorded signals has not yet been developed. The aim of the work was to study the possibility of using the perfusion index to assess the psychophysiological state of a person during the solution of cognitive tasks. It was conducted a special experiment, including the stages of classical stress tests: the Stroop Color World Test and the Mental Arithmetic Test. The experimental sample included 10 healthy volunteers aged 21±3 years without signs of mental disorders. It was recorded the signal of the perfusion index in calm and stress states. Further, according to the obtained psychophysiological indicators for each volunteer, the average value of the perfusion index at each stage of the experiment was calculated. It was found that the values of the perfusion index decreased during the solution of cognitive tasks. Thus, the difference in the values of the perfusion index at different stages of the experiment demonstrated the possibility of using this signal to detect stress.
{"title":"Changes in the Perfusion Index After Psycho-emotional Stress","authors":"Elizaveta S. Dubinkina, E. Borovkova, A. Hramkov, A. Karavaev, Alexander V. Kurbako, M. Prokhorov","doi":"10.1109/DCNA56428.2022.9923267","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923267","url":null,"abstract":"Currently, the measurement of stress is an important, relevant and unsolved problem. Despite the fact that it has been shown that various physiological indicators can be used to assess stress, a universal classical method for assessing the cognitive status of subjects in the analysis of non-invasively recorded signals has not yet been developed. The aim of the work was to study the possibility of using the perfusion index to assess the psychophysiological state of a person during the solution of cognitive tasks. It was conducted a special experiment, including the stages of classical stress tests: the Stroop Color World Test and the Mental Arithmetic Test. The experimental sample included 10 healthy volunteers aged 21±3 years without signs of mental disorders. It was recorded the signal of the perfusion index in calm and stress states. Further, according to the obtained psychophysiological indicators for each volunteer, the average value of the perfusion index at each stage of the experiment was calculated. It was found that the values of the perfusion index decreased during the solution of cognitive tasks. Thus, the difference in the values of the perfusion index at different stages of the experiment demonstrated the possibility of using this signal to detect stress.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"563 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116246429","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923122
I. Franović, Sebastian Eydam, N. Semenova, A. Zakharova
While coherence-incoherence patterns have been exhaustively studied in systems of coupled oscillators, their mechanisms of emergence and their relationship en route from complete coherence to incoherence in coupled excitable systems remain as yet unresolved. Here we disclose two types of solitary states in arrays of non-locally coupled excitable FitzHugh-Nagumo units with dominant repulsive over attractive interactions. While the prevailing type of solitary states is shown to derive its dynamical features from unbalanced two-cluster states in globally coupled networks, the minority type is fundamentally a consequence of non-locality of interactions. Apart from the states whose local structure is based on successive spiking of units, we also find solitary states where local excitability and slow-fast dynamics give rise to leap-frog activity characterized by an alternating order of units’ spiking. The main impact of noise on system’s behavior is shown to be the reduction of its multistability, whereby the solitary states are suppressed in favour of patched patterns.
{"title":"Solitary states in arrays of excitable FitzHugh-Nagumo units","authors":"I. Franović, Sebastian Eydam, N. Semenova, A. Zakharova","doi":"10.1109/DCNA56428.2022.9923122","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923122","url":null,"abstract":"While coherence-incoherence patterns have been exhaustively studied in systems of coupled oscillators, their mechanisms of emergence and their relationship en route from complete coherence to incoherence in coupled excitable systems remain as yet unresolved. Here we disclose two types of solitary states in arrays of non-locally coupled excitable FitzHugh-Nagumo units with dominant repulsive over attractive interactions. While the prevailing type of solitary states is shown to derive its dynamical features from unbalanced two-cluster states in globally coupled networks, the minority type is fundamentally a consequence of non-locality of interactions. Apart from the states whose local structure is based on successive spiking of units, we also find solitary states where local excitability and slow-fast dynamics give rise to leap-frog activity characterized by an alternating order of units’ spiking. The main impact of noise on system’s behavior is shown to be the reduction of its multistability, whereby the solitary states are suppressed in favour of patched patterns.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117331814","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923294
Mikhail Kuznetsov, S. Vrazhevsky, E. Kopysova
The article suggests a robust control algorithm for a quadrotor tracking control problem considering a linearised quadrotor model. The main achievement obtained is a controller with a guarantee of finding output signals within the boundaries given by differentiable functions. The proposed method is used for a quadcopter model separately for each degree of freedom. The results are verified using computer simulation.
{"title":"Quadrotor Control under Prespecified State-Space Bounds","authors":"Mikhail Kuznetsov, S. Vrazhevsky, E. Kopysova","doi":"10.1109/DCNA56428.2022.9923294","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923294","url":null,"abstract":"The article suggests a robust control algorithm for a quadrotor tracking control problem considering a linearised quadrotor model. The main achievement obtained is a controller with a guarantee of finding output signals within the boundaries given by differentiable functions. The proposed method is used for a quadcopter model separately for each degree of freedom. The results are verified using computer simulation.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128721971","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923156
M. Brovkova, A.O. Sokolov, O. V. Ushakova, Torgashova O.Yu, M. A. Solomin, V. Martynov, A.S. Bolshakov
The article presents a platform for the collection of technological data, their analysis, including the use of machine learning algorithms, storage, visualization and notification of potential events in the future, the prerequisites of which are data flows that reflect the current state of the machining process based on the concept of event-driven (streaming) event processing akin to middleware command router.
{"title":"Intelligent Monitoring Platform for Digital Manufacturing Based on the Concept of Event-Driven (Streaming) Event Processing Akin to Middleware Command Router","authors":"M. Brovkova, A.O. Sokolov, O. V. Ushakova, Torgashova O.Yu, M. A. Solomin, V. Martynov, A.S. Bolshakov","doi":"10.1109/DCNA56428.2022.9923156","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923156","url":null,"abstract":"The article presents a platform for the collection of technological data, their analysis, including the use of machine learning algorithms, storage, visualization and notification of potential events in the future, the prerequisites of which are data flows that reflect the current state of the machining process based on the concept of event-driven (streaming) event processing akin to middleware command router.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126374075","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923193
Galiya Markova, S. Bartsev
We demonstrate the possibility of identification of certain stimuli time series, which is received by simple recurrent neural network while playing a reflexive game “Even-Odd” (Matching Pennies), using its neural activity patterns. For successful identification by the method of neural network-based decoding, a non-linear decoder with at least 6 neurons on the hidden layer is required. This result indicates the presence of attractors of neural activity, which allow the trained recurrent neural network to determine the type of the received stimuli sequence and form the right response.
{"title":"Decoding the Neural Activity of Recurrent Neural Network Playing a Reflexive Game","authors":"Galiya Markova, S. Bartsev","doi":"10.1109/DCNA56428.2022.9923193","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923193","url":null,"abstract":"We demonstrate the possibility of identification of certain stimuli time series, which is received by simple recurrent neural network while playing a reflexive game “Even-Odd” (Matching Pennies), using its neural activity patterns. For successful identification by the method of neural network-based decoding, a non-linear decoder with at least 6 neurons on the hidden layer is required. This result indicates the presence of attractors of neural activity, which allow the trained recurrent neural network to determine the type of the received stimuli sequence and form the right response.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127895743","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923178
V. Maksimenko, S. Gordleeva, N. Grigorev, A. Savosenkov, Alexander Kuc, Anna Udoratina, V. Grubov, Anna Kolchina, S. Kurkin, V. Kazantsev, A. Hramov
Our preliminary behavioral experiments suggest that the response time decreases when subjects respond to the repeatedly presented visual stimuli. A potential explanation is that the brain preactivates neural ensembles responsible for stimulus processing. If so, activating these areas before the experiment may reduce the response time immediately, opening ways for exciting practical applications. To test this opportunity, we apply transcranial magnetic stimulation (TMS) before the subjects start performing a perceptual decision-making task. Having compared the response time between the TMS and control groups, we observed a significant change confirming our hypothesis.
{"title":"Anterior TMS Speeds up Responses in Perceptual Decision-making Task","authors":"V. Maksimenko, S. Gordleeva, N. Grigorev, A. Savosenkov, Alexander Kuc, Anna Udoratina, V. Grubov, Anna Kolchina, S. Kurkin, V. Kazantsev, A. Hramov","doi":"10.1109/DCNA56428.2022.9923178","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923178","url":null,"abstract":"Our preliminary behavioral experiments suggest that the response time decreases when subjects respond to the repeatedly presented visual stimuli. A potential explanation is that the brain preactivates neural ensembles responsible for stimulus processing. If so, activating these areas before the experiment may reduce the response time immediately, opening ways for exciting practical applications. To test this opportunity, we apply transcranial magnetic stimulation (TMS) before the subjects start performing a perceptual decision-making task. Having compared the response time between the TMS and control groups, we observed a significant change confirming our hypothesis.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124762139","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923088
B. Brzhozovskii, V. Martynov, E. Zinina
The paper presents the results of the correlation analysis of the relationship between the parameters characterizing the properties of the metal product surface layer with the parameters of signals reflecting the process of their low-temperature plasma treatment. It has been established that current signal parameters reflect the process of changing chemical and electrical (surface) properties, while the temperature signal parameters reflect the surface layer physical and mechanical (volumetric) properties.
{"title":"The results of the correlation analysis of the relationship between indicators characterizing the surface layer properties and signals reflecting the process of low-temperature plasma treatment of metal products","authors":"B. Brzhozovskii, V. Martynov, E. Zinina","doi":"10.1109/DCNA56428.2022.9923088","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923088","url":null,"abstract":"The paper presents the results of the correlation analysis of the relationship between the parameters characterizing the properties of the metal product surface layer with the parameters of signals reflecting the process of their low-temperature plasma treatment. It has been established that current signal parameters reflect the process of changing chemical and electrical (surface) properties, while the temperature signal parameters reflect the surface layer physical and mechanical (volumetric) properties.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129834890","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}
Pub Date : 2022-09-14DOI: 10.1109/DCNA56428.2022.9923254
A. Bugakova, Varvara Nikolaeva, A. Gorin, Anna Muraveva, E. Kuzmina, M. Lebedev
Motor imagery is a popular maneuver for controlling an EEG-based brain-computer interfaces (BCIs). Yet, little is known about motor imagery under different postural conditions, such as standing or supported standing in the case of neurological impairment. This lack of knowledge seriously impedes the development of practical BCIs needed for neurorehabilitation. Here we examined EEG modulations during motor imagery performed while subjects either sat or stood. Data were collected in three subjects who imagined their hands moving. we compared the accuracy of BCI prediction in two conditions: sitting and standing. At this point we report that different EEG patterns occur during sitting versus standing, and in both cases, EEG is modulated by motor imagery, which makes BCI technology applicable to different postural conditions.
{"title":"EEG during Motor Imagery under Different Postural Conditions – Case Study","authors":"A. Bugakova, Varvara Nikolaeva, A. Gorin, Anna Muraveva, E. Kuzmina, M. Lebedev","doi":"10.1109/DCNA56428.2022.9923254","DOIUrl":"https://doi.org/10.1109/DCNA56428.2022.9923254","url":null,"abstract":"Motor imagery is a popular maneuver for controlling an EEG-based brain-computer interfaces (BCIs). Yet, little is known about motor imagery under different postural conditions, such as standing or supported standing in the case of neurological impairment. This lack of knowledge seriously impedes the development of practical BCIs needed for neurorehabilitation. Here we examined EEG modulations during motor imagery performed while subjects either sat or stood. Data were collected in three subjects who imagined their hands moving. we compared the accuracy of BCI prediction in two conditions: sitting and standing. At this point we report that different EEG patterns occur during sitting versus standing, and in both cases, EEG is modulated by motor imagery, which makes BCI technology applicable to different postural conditions.","PeriodicalId":110836,"journal":{"name":"2022 6th Scientific School Dynamics of Complex Networks and their Applications (DCNA)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130968135","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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