2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)最新文献_第10页

Automated Detection of Evoked Potentials Produced by Intracranial Electrical Stimulation 颅内电刺激诱发电位的自动检测

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123858

Eric R. Cole, Kevin P. Quimbo, Grant J. Stento, Chadd M. Funk, Lou T. Blanpain, Sina Dabiri, Nealen G. Laxpati, M. Kahana, Robert E. Gross

{"title":"Automated Detection of Evoked Potentials Produced by Intracranial Electrical Stimulation","authors":"Eric R. Cole, Kevin P. Quimbo, Grant J. Stento, Chadd M. Funk, Lou T. Blanpain, Sina Dabiri, Nealen G. Laxpati, M. Kahana, Robert E. Gross","doi":"10.1109/NER52421.2023.10123858","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123858","url":null,"abstract":"Neural responses to pulses of electrical stimulation, termed “evoked potentials”, can map brain connectivity and optimize deep brain stimulation as used in the treatment of neurological disease. As human neurotechnology now allows for simultaneous real-time sensing and stimulation at multiple channels throughout the brain, it will benefit from automated real-time detection of evoked potentials to prospectively guide brain stimulation targeting. Here we used intracranial brain stimulation data collected from 22 epilepsy patients undergoing seizure monitoring to design and evaluate an automated strategy for detecting evoked potentials produced by electrical brain stimulation. We evaluate and demonstrate the utility of two features - a high-frequency broadband power ratio, and cross-correlation across repeated stimulation trials - in detecting evoked potentials, showing that cross-correlation is a robust feature that can achieve 93% detection accuracy alone. We also show that combining these complementary features into a single metric improves detection performance over single features, and we present a complementary strategy for stimulation artifact rejection that improves detection performance of all features. In conclusion, we present an automated strategy for detecting evoked potentials that can be applied to large-scale brain data and used online to optimize brain stimulation targeting in applications such as Parkinson's disease, epilepsy, and more.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"331 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116233697","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}

引用次数: 0

An Automated Tactile Stimulator Apparatus for Neuromorphic Tactile Sensing 一种用于神经形态触觉感应的自动触觉刺激装置

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123897

Z. Chaudhry, Fangjie Li, Mark M. Iskarous, N. Thakor

{"title":"An Automated Tactile Stimulator Apparatus for Neuromorphic Tactile Sensing","authors":"Z. Chaudhry, Fangjie Li, Mark M. Iskarous, N. Thakor","doi":"10.1109/NER52421.2023.10123897","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123897","url":null,"abstract":"Tactile sensing is an active area of research in robotics and neural engineering, particularly in relation to sensory feedback for neural prostheses. Sensory feedback relies on neuromorphic models for touch, which must be characterized and validated through tactile sensing experiments. Currently, no standardized, automated method exists for performing these experiments. Thus, there exists a need for new methods/workflows for providing tactile stimulation in neuromorphic tactile sensing. In this work, we describe a rotary-drum tactile stimulator that provides complete user control over force and velocity setpoints and applied textures using PID tuning and an interchangeable, snap-in 3D-printed texture plate system. We achieve high accuracy and precision closed-loop force control (3.4% average deviation in force between first and last ten trials with 4.2% standard deviation) and open-loop velocity control (4.6% average deviation from velocity setpoint with 2.6% standard deviation). Additionally, the apparatus features an automated data pipeline, which records analog tactile sensor readings at each experimental condition, automatically segments them into individual palpation trials, and transforms them into neuromorphic spiking activity. Though designed to develop neuromorphic models of touch for prostheses, the apparatus is generalizable to a wide array of neural engineering experiments, including characterizing tactile sensors and generating tactile sensing databases.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125959678","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}

引用次数: 0

Single-Trial Detection in Rapid Serial Visual Presentation Task using the Lilac Chaser Visual Illusion 丁香追逐者视错觉快速序列视觉呈现任务的单次检测

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123869

Steve Jaimes, H. Cecotti

{"title":"Single-Trial Detection in Rapid Serial Visual Presentation Task using the Lilac Chaser Visual Illusion","authors":"Steve Jaimes, H. Cecotti","doi":"10.1109/NER52421.2023.10123869","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123869","url":null,"abstract":"Single-trial detection of event-related potentials (ERPs) with electroencephalography (EEG) signals during Rapid Serial Visual Presentation (RSVP) tasks is a difficult problem. It is also a difficult and tedious task for participants who must keep their attention throughout the total duration of the task. Long EEG experimental sessions can be boring and impact the quality of the recorded signals and the user experience as participant. It is necessary to provide tools that allow participants to better focus on the desired stimuli. Several approaches can be performed to enhance single-trial detection, including the development of machine learning techniques. In this paper, we propose to enhance the experimental conditions by adding the Lilac Chaser visual illusion. We assessed the effect of the Lilac Chaser visual illusion during an RSVP task with targets and non-targets with 10 participants with images of human faces. While the Lilac Chaser brings additional visual stimuli that can be considered as distractors during the task, the performance of single-trial detection using the area under the ROC curve as a measure of performance does not change (about 0.89). The results suggest that the Lilac Chaser can be added as a means for users to be self-aware about their attention to the task, without decreasing the performance of ERP single-trial detection.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127092809","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}

引用次数: 0

Screening of Mild Cognitive Impairment in Patients with Parkinson's Disease Using a Variational Mode Decomposition Based Deep-Learning 基于变分模态分解的深度学习筛选帕金森病患者轻度认知障碍

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123759

Madan Parajuli, A. Amara, M. Shaban

{"title":"Screening of Mild Cognitive Impairment in Patients with Parkinson's Disease Using a Variational Mode Decomposition Based Deep-Learning","authors":"Madan Parajuli, A. Amara, M. Shaban","doi":"10.1109/NER52421.2023.10123759","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123759","url":null,"abstract":"Parkinson's disease (PD) which is the second most common neurodegenerative disease in the United States is challenging for specialists to diagnose and grade. Prior to the onset of motor symptoms of PD, patients exhibit alteration in sleep architecture which plays a critical role in consolidating memory, a key cognitive process of the brain. Standard spectral and signal analysis techniques have been recently introduced to exploit the changes in the electroencephalography of sleep related to PD or its cognitive complications including dementia. However, the use of artificial intelligence for the automated detection of the progression of PD to mild cognitive impairment (MCI) or dementia in sleep EEG have not yet been investigated. In this paper, we introduce a novel highly accurate variational mode decomposition based deep-learning framework applied on sleep electroencephalography signals in order to classify PD subjects into patients exhibiting normal cognition (NC) or MCI. The proposed framework is capable of detecting MCI at a significantly high 4-fold cross validation accuracy, sensitivity, specificity and quadratic weighted Kappa score of almost 99% offering a rapid and supportive tool for specialists to monitor the progression of PD and ensure the early initiation of efficient therapeutic treatments that will accordingly improve the quality of life for patients and their caregivers.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130872045","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}

引用次数: 0

Optical Phantoms for Calibrating a Novel Neuroimaging System Targeting Central Nervous System Fluid Flow Dynamics 光学幻影用于校准一种针对中枢神经系统流体流动动力学的新型神经成像系统

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123860

Joseph P. Angelo, W. Coon, Matt Nagle, M. J. Fitch, Clara A. Scholl

{"title":"Optical Phantoms for Calibrating a Novel Neuroimaging System Targeting Central Nervous System Fluid Flow Dynamics","authors":"Joseph P. Angelo, W. Coon, Matt Nagle, M. J. Fitch, Clara A. Scholl","doi":"10.1109/NER52421.2023.10123860","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123860","url":null,"abstract":"Fluid flow dynamics in the brain's ventricles, interstitial spaces, and perivascular spaces, known as the “glymphatic system,” are hypothesized to play an important role in brain waste clearance. Healthy function of this complex fluid transporter is most active during sleep, may be critical for maintaining neurological health, and is hypothesized to be important for recovery after acute and chronic injury (e.g. concussion). At present, all sensors for monitoring brain fluid dynamics require invasive contrast agents (e.g. fluorescent dyes injected into cerebrospinal fluid, CSF) and/or are not portable or amenable to long-term repeated monitoring (e.g., magnetic resonance imaging (MRI) methods). We aim to adapt near infrared spectroscopy technologies, which traditionally track hemodynamic activity, to target fluid flow in the glymphatic system and to monitor the temporal dynamics of this water-dominated signal, with an eye toward future applications in continuous portable monitoring. Our goal is to extend frequency domain functional near infrared spectroscopy sensors (FD-fNIRS) to track these CSF-dominated fluid dynamics. In support of this aim, we developed two novel phantoms that mimic key elements of glymphatic system function to demonstrate application of novel FD-fNIRS sensors to human brains in a portable, noninvasive form factor amenable to repeated, continuous testing in a sleep lab-type environment.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130472042","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}

引用次数: 0

Averaged sparse local representation for the elimination of pseudo-HFOs from intracranial EEG recording in epilepsy 消除癫痫颅内脑电图记录中伪hfos的平均稀疏局部表示

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123789

Behrang Fazli Besheli, Zhiyi Sha, Thomas R. Henry, Jay R. Gavvala, S. Sheth, N. Ince

{"title":"Averaged sparse local representation for the elimination of pseudo-HFOs from intracranial EEG recording in epilepsy","authors":"Behrang Fazli Besheli, Zhiyi Sha, Thomas R. Henry, Jay R. Gavvala, S. Sheth, N. Ince","doi":"10.1109/NER52421.2023.10123789","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123789","url":null,"abstract":"Interictal high-frequency oscillation (HFO) is considered a promising biomarker of the epileptogenic zone. The pseudo-HFOs originating from artifacts and noise might escape HFO detectors and mislead the seizure onset zone (SOZ) localization. The purpose of this study is to propose a new sparse representation framework fused with a random forest classifier to detect the real HFOs and eliminate the pseudo-ones. In this scheme, each candidate event that passed a conventional amplitude threshold-based detector was represented locally in a sparse fashion. Specifically, the signal is divided into overlapping windows and using orthogonal matching pursuit, only a few oscillatory atoms selected from a predefined redundant Gabor dictionary were used to approximate the signal locally. Later, the approximations in overlapping segments are averaged to increase the smoothness. Finally, the ability to reconstruct an event is translated to informative features and fed into a random forest classifier. This technique was tested on 10 minutes of interictal intracranial EEG (iEEG) recordings recorded from 11 patients with epilepsy. In this framework, three experts visually inspected 4466 events captured by the amplitude threshold-based HFO detector in iEEG recordings and labeled them as real-HFO or Pseudo-HFO. We reached 89.77% classification accuracy in these labeled events. Furthermore, the success of the method assessed by calculating the spatial overlap between the detected HFOs and SOZ channels. Compared to conventional amplitude threshold-based HFO detector, our method resulted a significant 18.27% improvement in the localization of SOZ.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131783355","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}

引用次数: 0

Computational Modeling of the LHb-VTA Pathway in Major Depression Disorder 重性抑郁症LHb-VTA通路的计算建模

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123804

Chenhao Bao, Meihong Zheng

{"title":"Computational Modeling of the LHb-VTA Pathway in Major Depression Disorder","authors":"Chenhao Bao, Meihong Zheng","doi":"10.1109/NER52421.2023.10123804","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123804","url":null,"abstract":"Major depression disorder (MDD) is a prevalent but severe psychiatric disorder, yet it is unclear how MDD is induced. Recently, accumulated evidence of in vivo animal experiments suggested that the lateral habenula (LHb) might play an important role in regulating the brain's dopamine (DA)ergic mechanism. Some abnormal changes and activities in the LHb region may lead to the excessive inhibition of the downstream DAergic neurons and thus induce MDD symptoms. However, how these abnormalities in the LHb cause the excessive inhibition of the DAergic neurons is still not clearly demonstrated. In this paper, we built a computational model for the pathway between the LHb and the ventral tegmental area (VTA) to simulate the different neurophysiological processes with the LHb regulation in healthy and MDD individuals. From the simulation results of the LHb-VTA pathway model we found that both the firing pattern conversion of the LHb neuron from regular tonic to burst, and the overexpression of Kir channel proteins on the LHb astrocyte membrane could more strongly inhibit the VTA DAergic neuron, which corresponds to the experimental results of previous in vivo animal studies. Our model and simulation results may shed light on future studies to further understand the pathology of MDD.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133789503","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}

引用次数: 0

Subject Generalization in Classifying Imagined and Spoken Speech with MEG 用脑磁图对想象言语和口语进行分类的主语泛化

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123722

Debadatta Dash, P. Ferrari, A. Babajani-Feremi, David F. Harwath, A. Borna, Jun Wang

{"title":"Subject Generalization in Classifying Imagined and Spoken Speech with MEG","authors":"Debadatta Dash, P. Ferrari, A. Babajani-Feremi, David F. Harwath, A. Borna, Jun Wang","doi":"10.1109/NER52421.2023.10123722","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123722","url":null,"abstract":"Speech decoding-based brain-computer interfaces (Speech-BCIs) decode speech directly from brain signals, which have the potential to offer faster and natural communication to patients with locked-in syndrome than the current BCI-spellers. On account of the huge cognitive variance among subjects, most of the current speech-BCI models have focused on subject-dependent decoding where the training and evaluation of the decoding algorithms use data from the same participants. These models do not generalize across individuals and, thus, are limited by the small data size that can be obtained from a single participant. Few studies have attempted subject-independent decoding but the performances are sub-par at best and significantly lower than subject-dependent models. To address this issue, we evaluated imagined and overt speech decoding with magnetoencephalography (MEG) recordings of eight speakers in a generalizable subject-independent setting. We used recent domain adaptation techniques including feature augmentation and curriculum learning to introduce generalizability to the decoding model. Our results indicated that domain adaptation techniques can be efficient in subject-independent decoding. The best performance was obtained with a curriculum learning based adaptation technique that resulted in decoding accuracy was close to that in subject-dependent decoding. Our findings show the possibility of subject generalization in neural speech decoding.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131565254","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}

引用次数: 0

Spatio-Temporal Analysis of LTP-like Neuroplasticity in Pigs 猪ltp样神经可塑性的时空分析

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123814

Mikkel Bjerre Danyar, H. Clark, Nickolaj Ajay Atchuthan, Lasse Krøgh Daugbjerg, Amalie Koch Andersen, T. Janjua, W. Jensen

{"title":"Spatio-Temporal Analysis of LTP-like Neuroplasticity in Pigs","authors":"Mikkel Bjerre Danyar, H. Clark, Nickolaj Ajay Atchuthan, Lasse Krøgh Daugbjerg, Amalie Koch Andersen, T. Janjua, W. Jensen","doi":"10.1109/NER52421.2023.10123814","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123814","url":null,"abstract":"In our laboratory, we have recently established a large animal model of LTP-like pain and extracted cortical features as objective measurements of nociception. We have previ-ously reported an increase in the S1 cortical activity for both local-field potentials (LFP) and spike activity up to 90 min after induction of high-frequency stimulation. Our analysis so far has been based on averaging signals obtained from an intracortical array, thus losing any spatial information. The aim of this work was therefore to investigate spatio-temporal neural changes. In-tracortical EEG recordings from pigs (n=7) were acquired using a 16-channel microelectrode array (MEA) placed in S1. To as-sess the cortical response, electrical stimulation was delivered to the ulnar nerve. Each experiment was divided into four blocks (T0-T3). The intervention group (n=5) received LTP between T0 and T1. We extracted the N1-P1 amplitude as a feature in the LFP signal range and the area under the curve (AUC) of the PSTH response as a feature to represent the spike signals. We found that LTP induced spatio-temporal changes in both the LFP and spike activity in the T2 and T3 phases, which is in line with our previous results [1]. However, in the present work, we additionally observed that the location of the maximal activity moved spatially between T0 and T2 (3/5 animals for LFP activity, 4/5 animals for spike activity). Also, we observed a cortical suppression in the T3 phase associ-ated with long-term depression. A more detailed understanding of the cortical response and plasticity to nociception may poten-tially be a more suitable platform to investigate the efficacy of novel drugs to treat pain.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132733797","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}

引用次数: 0

Individual temporal and spatial dynamics of learning to control central Beta activity in neurofeedback training 神经反馈训练中控制中枢β活动的个体时空动态学习

2023 11th International IEEE/EMBS Conference on Neural Engineering (NER) Pub Date : 2023-04-24 DOI: 10.1109/NER52421.2023.10123781

Elmeri Syrjänen, Joana Silva, E. Åstrand

{"title":"Individual temporal and spatial dynamics of learning to control central Beta activity in neurofeedback training","authors":"Elmeri Syrjänen, Joana Silva, E. Åstrand","doi":"10.1109/NER52421.2023.10123781","DOIUrl":"https://doi.org/10.1109/NER52421.2023.10123781","url":null,"abstract":"Neurofeedback (NFB) and Brain-Computer Interface (BCI) research seldom present within-session individual learning dynamics. This is even though a large proportion of NFB and BCI users cannot learn neural self-regulation required to control the feedback. Understanding the time course and learning variability between participants might allow us to design better NFB and BCI protocols to promote learning of neural self-regulation. The importance of developing novel NFB and BCI protocols becomes apparent, considering the clinical utility of these techniques. Tuning the brain to perform optimally could provide for long-term non-pharmacological treatment without any drug-associated side effects. This paper reports the strategies used by participants and the individual dynamics of central Beta NFB downregulation training and associated mental strategies for nine participants. The results showed that all participants could learn to downregulate their central Beta power in a single session, however, the dynamics of learning differed between participants. We visually identified two learning dynamics; 1) a continual decrease in Beta power and 2) an initial decrease followed by a stable level of Beta power. Topographic plots indicated high spatial variability in Beta power decreases in participants. Responses from end-of-session debriefing indicated that all participants felt they could control the feedback. Although participants could control the feedback, an optimal mental strategy for controlling central Beta power was not revealed.","PeriodicalId":201841,"journal":{"name":"2023 11th International IEEE/EMBS Conference on Neural Engineering (NER)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131946444","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}

引用次数: 0