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Hack RL, Aigner M, Musalek M, Crevenna R, Konicar L. Brain regulation training improves emotional competences in patients with alcohol use disorder. Soc Cogn Affect Neurosci 2024; 19:nsae048. [PMID: 38915188 PMCID: PMC11297497 DOI: 10.1093/scan/nsae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 05/14/2024] [Accepted: 06/22/2024] [Indexed: 06/26/2024] Open
Abstract
Alcohol use disorder (AUD) is defined as the impaired ability to stop or control alcohol use despite adverse social, occupational, or health consequences and still represents one of the biggest challenges for society regarding health conditions, social consequences, and financial costs, including the high relapse rates after traditional alcohol rehabilitation treatment. Especially, the deficient emotional competence in AUD is said to play a key role in the development of AUD and hinders the interruption of substance compulsion, often leading to a viscous circle of relapse. Although the empirical evidence of a neurophysiological basis of AUD is solid and increases even further, clinical interventions based on neurophysiology are still rare for individuals with AUD. This randomized controlled trial investigates changes in emotional competences, alcohol-related cognitions, and drinking behavior before and after an established alcohol rehabilitation treatment (control group: nCG = 29) compared to before and after an optimized, add-on neurofeedback (NF) training (experimental group: nEG = 27). Improvements on the clinical-psychological level, i.e. increases in emotional competences as well as life satisfaction, were found after the experimental electroencephalography (EEG) NF training. Neurophysiological measurements via resting-state EEG indicate decreases in low beta frequency band, while alpha and theta bands remained unaffected.
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Affiliation(s)
- Ramona L Hack
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna 1090, Austria
- Anton-Proksch-Institute, Vienna, Vienna 1230, Austria
| | - Martin Aigner
- Clinical Department of Psychiatry and Psychotherapeutic Medicine, University Hospital Tulln, Tulln 3430, Austria
| | | | - Richard Crevenna
- Department of Physical Medicine, Rehabilitation and Occupational Medicine, Medical University of Vienna, Vienna 1090, Austria
| | - Lilian Konicar
- Department of Child and Adolescent Psychiatry, Medical University of Vienna, Vienna 1090, Austria
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Cheng MY, Yu CL, An X, Wang L, Tsai CL, Qi F, Wang KP. Evaluating EEG neurofeedback in sport psychology: a systematic review of RCT studies for insights into mechanisms and performance improvement. Front Psychol 2024; 15:1331997. [PMID: 39156814 PMCID: PMC11328324 DOI: 10.3389/fpsyg.2024.1331997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 07/01/2024] [Indexed: 08/20/2024] Open
Abstract
Electroencephalographic Neurofeedback Training (EEG NFT) aims to improve sport performance by teaching athletes to control their mental states, leading to better cognitive, emotional, and physical outcomes. The psychomotor efficiency hypothesis suggests that optimizing brain function could enhance athletic ability, indicating the potential of EEG NFT. However, evidence for EEG-NFT's ability to alter critical brain activity patterns, such as sensorimotor rhythm and frontal midline theta-key for concentration and relaxation-is not fully established. Current research lacks standardized methods and comprehensive studies. This shortfall is due to inconsistent EEG target selection and insufficient focus on coherence in training. This review aims to provide empirical support for EEG target selection, conduct detailed control analyses, and examine the specificity of electrodes and frequencies to relation to the psychomotor efficiency hypothesis. Following the PRISMA method, 2,869 empirical studies were identified from PubMed, Science Direct, Web of Science, Embase, CNKI, and PsycINFO. Thirteen studies met the inclusion criteria: (i) proficient skill levels; (ii) use of EEG; (iii) neurofeedback training (NFT); (iv) motor performance metrics (reaction time, precision, dexterity, balance); (v) control group for NFT comparison; (vi) peer-reviewed English-language publication; and (vii) randomized controlled trial (RCT) design. Studies indicate that NFT can enhance sports performance, including improvements in shooting accuracy, golf putting, and overall motor skills, as supported by the psychomotor efficiency hypothesis. EEG NFT demonstrates potential in enhancing sports performance by optimizing performers' mental states and psychomotor efficiency. However, the current body of research is hampered by inconsistent methodologies and a lack of standardized EEG target selection. To strengthen the empirical evidence supporting EEG NFT, future studies need to focus on standardizing target selection, employing rigorous control analyses, and investigating underexplored EEG markers. These steps are vital to bolster the evidence for EEG NFT and enhance its effectiveness in boosting sport performance.
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Affiliation(s)
- Ming-Yang Cheng
- School of Psychology, Beijing Sport University, Beijing, China
| | - Chien-Lin Yu
- Department of Physical Education and Sport Sciences, National Taiwan Normal University, Taipei City, Taiwan
| | - Xin An
- School of Psychology, Beijing Sport University, Beijing, China
| | - Letong Wang
- School of Psychology, Beijing Sport University, Beijing, China
| | - Chi-Lun Tsai
- Department of Sport Psychology, Faculty of Sport Science, Universität Leipzig, Leipzig, Germany
| | - Fengxue Qi
- Sports, Exercise and Brain Sciences Laboratory, Beijing Sport University, Beijing, China
| | - Kuo-Pin Wang
- Center for Cognitive Interaction Technology, Bielefeld University, Bielefeld, Germany
- Neurocognition and Action - Biomechanics Research Group, Faculty of Psychology and Sports Science, Bielefeld University, Bielefeld, Germany
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Li L, Li Y, Li Z, Huang G, Liang Z, Zhang L, Wan F, Shen M, Han X, Zhang Z. Multimodal and hemispheric graph-theoretical brain network predictors of learning efficacy for frontal alpha asymmetry neurofeedback. Cogn Neurodyn 2024; 18:847-862. [PMID: 38826665 PMCID: PMC11143167 DOI: 10.1007/s11571-023-09939-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 12/29/2022] [Accepted: 01/31/2023] [Indexed: 02/23/2023] Open
Abstract
EEG neurofeedback using frontal alpha asymmetry (FAA) has been widely used for emotion regulation, but its effectiveness is controversial. Studies indicated that individual differences in neurofeedback training can be traced to neuroanatomical and neurofunctional features. However, they only focused on regional brain structure or function and overlooked possible neural correlates of the brain network. Besides, no neuroimaging predictors for FAA neurofeedback protocol have been reported so far. We designed a single-blind pseudo-controlled FAA neurofeedback experiment and collected multimodal neuroimaging data from healthy participants before training. We assessed the learning performance for evoked EEG modulations during training (L1) and at rest (L2), and investigated performance-related predictors based on a combined analysis of multimodal brain networks and graph-theoretical features. The main findings of this study are described below. First, both real and sham groups could increase their FAA during training, but only the real group showed a significant increase in FAA at rest. Second, the predictors during training blocks and at rests were different: L1 was correlated with the graph-theoretical metrics (clustering coefficient and local efficiency) of the right hemispheric gray matter and functional networks, while L2 was correlated with the graph-theoretical metrics (local and global efficiency) of the whole-brain and left the hemispheric functional network. Therefore, the individual differences in FAA neurofeedback learning could be explained by individual variations in structural/functional architecture, and the correlated graph-theoretical metrics of learning performance indices showed different laterality of hemispheric networks. These results provided insight into the neural correlates of inter-individual differences in neurofeedback learning. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-023-09939-x.
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Affiliation(s)
- Linling Li
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Yutong Li
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Zhaoxun Li
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Gan Huang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Zhen Liang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Li Zhang
- School of Biomedical Engineering, Medical School, Shenzhen University, Shenzhen 518060, China
- Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, China
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China
| | - Manjun Shen
- Department of Mental Health, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518060, China
| | - Xue Han
- Department of Mental Health, Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen 518060, China
| | - Zhiguo Zhang
- School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen 518060, China
- Peng Cheng Laboratory, Shenzhen 518060, China
- Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen 518060, China
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Etemadi N, Habibi R, Samadnezhad Z, Alishvandi M, Attaran A, Vazifehkhorani AK. Neurofeedback on Reward Processing among Children with Attention Deficit/Hyperactivity Disorder. IRANIAN JOURNAL OF PUBLIC HEALTH 2023; 52:2232-2233. [PMID: 37899920 PMCID: PMC10612549 DOI: 10.18502/ijph.v52i10.13864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Accepted: 12/14/2022] [Indexed: 10/31/2023]
Abstract
The Article Abstract is not available.
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Affiliation(s)
- Niloofar Etemadi
- Department of Psychology and Educational Sciences, University of Tabriz, Tabriz, Iran
| | - Romina Habibi
- Department of Psychology and Educational Sciences, Allameh Tabataba’i University, Tehran, Iran
| | - Zahra Samadnezhad
- Department of Psychology and Educational Sciences, University of Tabriz, Tabriz, Iran
| | - Mohammad Alishvandi
- Department of Psychology and Educational Sciences, Central Gilan Branch, Islamic Azad University, Rasht, Iran
| | - Arina Attaran
- Department of Psychology and Educational Sciences, Central Tehran Branch, Islamic Azad University, Tehran, Iran
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Afrash S, Saemi E, Gong A, Doustan M. Neurofeedback training and motor learning: the enhanced sensorimotor rhythm protocol is better or the suppressed alpha or the suppressed mu? BMC Sports Sci Med Rehabil 2023; 15:93. [PMID: 37525277 PMCID: PMC10392010 DOI: 10.1186/s13102-023-00706-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 07/21/2023] [Indexed: 08/02/2023]
Abstract
A large number of previous studies have examined how different neurofeedback-based techniques may influence motor learning. However, only a few studies attempted to compare the effects of these different techniques on motor learning. Therefore, the present study attempts to examine the effects of neurofeedback training on motor learning in novice golfers, using three protocols, namely enhanced sensorimotor rhythm (SMR) at Cz, suppressed alpha waves at Fz, and suppressed mu waves at Cz. The participants were 64 adults (32 females; mean age = 22.31 ± 2.25 years). The study consisted of a pretest stage (day 1), intervention (6 sessions, over two weeks, 3 sessions per week), short-term retention (one day after intervention), and long-term retention (two weeks after intervention); in the pretest and short-term and long-term retention, motor performance for golf putting (12 trials) as well as amplitudes of SMR wave at Cz, alpha at Fz, and Mu at Cz were recorded. During each intervention session, the participants in three neurofeedback groups and a sham group first performed neurofeedback training (enhanced SMR at Cz, suppressed alpha at Fz, and suppressed Mu at Cz) for 20 min. Then, the participants in all groups performed three blocks of 12 trials consisting of golf putting training. The results indicated no difference between the sham and the experimental groups in the acquisition stage, as individuals in all groups experienced similar improvement in putting accuracy. However, in the short-term retention, all the three neurofeedback groups outperformed the sham group, although in the long-term retention, only the SMR group and the Alpha group showed a better performance than the sham group while the Mu group did not exhibit a notably better performance than the sham group. Our results also showed significant variations in the amplitudes of the SMR, alpha, and mu waves depending on the neurofeedback intervention provided, while no significant variation was observed in the sham group. Based on these results, it is recommended that coaches should make further use of enhanced SMR at Cz or suppressed alpha at Fz as their neurofeedback interventions to facilitate longer-term motor learning in golfers.
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Affiliation(s)
- Sana Afrash
- Department of Motor Behavior and Sport Psychology, Faculty of Sport Sciences, Shahid Chamran University of Ahvaz, Ahvaz, 6135783151, Iran
| | - Esmaeel Saemi
- Department of Motor Behavior and Sport Psychology, Faculty of Sport Sciences, Shahid Chamran University of Ahvaz, Ahvaz, 6135783151, Iran.
| | - Anmin Gong
- School of Information Engineering, Engineering University of People's Armed Police, Xi'an, 710086, China
| | - Mohammadreza Doustan
- Department of Motor Behavior and Sport Psychology, Faculty of Sport Sciences, Shahid Chamran University of Ahvaz, Ahvaz, 6135783151, Iran
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Both Sensorimotor Rhythm Neurofeedback and Self-Controlled Practice Enhance Motor Learning and Performance in Novice Golfers. Behav Sci (Basel) 2023; 13:bs13010065. [PMID: 36661637 PMCID: PMC9854920 DOI: 10.3390/bs13010065] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 01/09/2023] [Accepted: 01/09/2023] [Indexed: 01/12/2023] Open
Abstract
A major concern voiced by motor behavior scientists is to find useful practice techniques that can be effective in improving motor learning and performance. Neurofeedback and self-controlled practice are among the techniques that have recently drawn attention from specialists in this area. The present study examined the additive and individual effects of sensorimotor rhythm (SMR) neurofeedback as well as self-controlled practice on motor learning and performance in novice golfers. In this semi-empirical study, forty adults (20 females, Meanage = 26.10, SD = 5.56 years) were conveniently selected and randomly assigned to four groups: (1) neurofeedback/self-controlled practice, (2) neurofeedback/yoked practice, (3) sham/self-controlled practice, and (4) sham/yoked practice. The participants performed golf putting task in four stages, namely pretest (12 trials), intervention (one day after pretest; 6 sessions, 36 trails each), post-test (one day after intervention; 12 trials), and follow-up (two weeks after interventions; 12 trials). In addition, the participants had their EEG (SMR wave in Cz point) recorded during pretest, post-test, and follow-up. The results indicated that, although no additive effect was observed for the two practices during different stages of the experiment (p > 0.05), in acquisition and post-test stages, SMR neurofeedback and self-controlled practice independently facilitated golf putting (p ≤ 0.05). However, in the follow-up test, only the neurofeedback practice maintained its positive effects (p ≤ 0.05). The results also showed that participation in SMR neurofeedback practice can enhance the power of the SMR wave (p ≤ 0.05), regardless of the type of the self-controlled practice used. In sum, the two practice techniques seem to be independently effective in facilitating motor learning in instructional settings, particularly for golfers.
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Gu F, Gong A, Qu Y, Bao A, Wu J, Jiang C, Fu Y. From Expert to Elite? — Research on Top Archer’s EEG Network Topology. Front Hum Neurosci 2022; 16:759330. [PMID: 35280210 PMCID: PMC8916709 DOI: 10.3389/fnhum.2022.759330] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 01/14/2022] [Indexed: 12/17/2022] Open
Abstract
It is not only difficult to be a sports expert but also difficult to grow from a sports expert to a sports elite. Professional athletes are often concerned about the differences between an expert and an elite and how to eventually become an elite athlete. To explore the differences in brain neural mechanism between experts and elites in the process of motor behavior and reveal the internal connection between motor performance and brain activity, we collected and analyzed the electroencephalography (EEG) findings of 14 national archers and 14 provincial archers during aiming and resting states and constructed the EEG brain network of the two archer groups based on weighted phase lag index; the graph theory was used to analyze and compare the network characteristics via local network and global network topologies. The results showed that compared with the expert archers, the elite archers had stronger functional coupling in beta1 and beta2 bands, and the difference was evident in the frontal and central regions; in terms of global characteristics of brain network topology, the average clustering coefficient and global efficiency of elite archers were significantly higher than that of expert archers, and the eigenvector centrality of expert archers was higher; for local characteristics, elite archers had higher local efficient; and the brain network characteristics of expert archers showed a strong correlation with archery performance. This suggests that compared with expert archers, elite archers showed stronger functional coupling, higher integration efficiency of global and local information, and more independent performance in the archery process. These findings reveal the differences in brain electrical network topologies between elite and expert archers in the archery preparation stage, which is expected to provide theoretical reference for further training and promotion of professional athletes.
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Affiliation(s)
- Feng Gu
- School of Information Engineering, Engineering University of People’s Armed Police, Xi’an, China
| | - Anmin Gong
- School of Information Engineering, Engineering University of People’s Armed Police, Xi’an, China
- *Correspondence: Anmin Gong,
| | - Yi Qu
- School of Information Engineering, Engineering University of People’s Armed Police, Xi’an, China
| | - Aiyong Bao
- School of Military Basic Education, Engineering University of People’s Armed Police, Xi’an, China
| | - Jin Wu
- Department of Physical Education, Beijing City University, Beijing, China
| | - Changhao Jiang
- Key Laboratory of Sports Performance Evaluation and Technical Analysis, Capital Institute of Physical Education, Beijing, China
| | - Yunfa Fu
- School of Automation and Information Engineering, Kunming University of Science and Technology, Kunming, China
- Yunfa Fu,
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Gong A, Gu F, Nan W, Qu Y, Jiang C, Fu Y. A Review of Neurofeedback Training for Improving Sport Performance From the Perspective of User Experience. Front Neurosci 2021; 15:638369. [PMID: 34127921 PMCID: PMC8195869 DOI: 10.3389/fnins.2021.638369] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Accepted: 04/14/2021] [Indexed: 11/13/2022] Open
Abstract
Neurofeedback training (NFT) is a non-invasive, safe, and effective method of regulating the nerve state of the brain. Presently, NFT is widely used to prevent and rehabilitate brain diseases and improve an individual's external performance. Among the various NFT methods, NFT to improve sport performance (SP-NFT) has become an important research and application focus worldwide. Several studies have shown that the method is effective in improving brain function and motor control performance. However, appropriate reviews and prospective directions for this technology are lacking. This paper proposes an SP-NFT classification method based on user experience, classifies and discusses various SP-NFT research schemes reported in the existing literature, and reviews the technical principles, application scenarios, and usage characteristics of different SP-NFT schemes. Several key issues in SP-NFT development, including the factors involved in neural mechanisms, scheme selection, learning basis, and experimental implementation, are discussed. Finally, directions for the future development of SP-NFT, including SP-NFT based on other electroencephalograph characteristics, SP-NFT integrated with other technologies, and SP-NFT commercialization, are suggested. These discussions are expected to provide some valuable ideas to researchers in related fields.
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Affiliation(s)
- Anmin Gong
- School of Information Engineering, Engineering University of People's Armed Police, Xi'an, China
| | - Feng Gu
- School of Information Engineering, Engineering University of People's Armed Police, Xi'an, China
| | - Wenya Nan
- Department of Psychology, College of Education, Shanghai Normal University, Shanghai, China
| | - Yi Qu
- School of Information Engineering, Engineering University of People's Armed Police, Xi'an, China
| | - Changhao Jiang
- Key Laboratory of Sports Performance Evaluation and Technical Analysis, Capital Institute of Physical Education, Beijing, China
| | - Yunfa Fu
- School of Automation and Information Engineering, Kunming University of Science and Technology, Kunming, China
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Rocha K, Marinho V, Magalhães F, Carvalho V, Fernandes T, Ayres M, Crespo E, Velasques B, Ribeiro P, Cagy M, Bastos VH, Gupta DS, Teixeira S. Unskilled shooters improve both accuracy and grouping shot having as reference skilled shooters cortical area: An EEG and tDCS study. Physiol Behav 2020; 224:113036. [PMID: 32598941 DOI: 10.1016/j.physbeh.2020.113036] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 06/24/2020] [Accepted: 06/25/2020] [Indexed: 12/18/2022]
Abstract
Transcranial direct current stimulation (tDCS) has been used as a non-invasive method for enhanced motor and cognitive abilities. However, no previous study has investigated if the tDCS application in unskilled shooters on cortical sites, selected based on the cortical activity of skilled shooters, improves the accuracy and shot grouping. Sixty participants were selected, which included 10 skilled shooters and 50 unskilled shooters. After we identified the right dorsolateral prefrontal cortex (DLPFC) as the area with the highest activity in skilled shooters, we applied anodal tDCS over the right DLPFC in the unskilled shooters under two conditions: sham-tDCS (placebo) and real-tDCS (anodal tDCS). We also analyzed electroencephalography. Our results indicated that anodal tDCS application enhanced the shot accuracy (p = 0.001). Furthermore, the beta power in the EEG recording was higher in the left DLPFC, left and right parietal cortex (p = 0,001) after applying anodal tDCS, while the low-gamma power was higher in the right DLPFC in sham-tDCS (p = 0.001) and right parietal cortex after anodal-tDCS (p = 0.001). Our findings indicate that anodal tDCS can improve accuracy and shot grouping when applied over the unskilled shooters' right DLPFC. Furthermore, beta and low-gamma bands are influenced by anodal tDCS over the right DLPFC, which may be predictive of skill improvement.
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Affiliation(s)
- Kaline Rocha
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil; The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil.
| | - Victor Marinho
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil; The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil
| | - Francisco Magalhães
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil; The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil
| | - Valécia Carvalho
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil; The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil
| | - Thayaná Fernandes
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil
| | - Marcos Ayres
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil; The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil
| | - Eric Crespo
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil
| | - Bruna Velasques
- Brain Mapping and Sensory Motor Integration Laboratory, Institute of Psychiatry of Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Pedro Ribeiro
- Brain Mapping and Sensory Motor Integration Laboratory, Institute of Psychiatry of Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Mauricio Cagy
- Biomedical Engineering Program, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Victor Hugo Bastos
- The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil; Brain Mapping and Functionality Laboratory, Federal University of Delta do Parnaíba, Parnaíba, Brazil
| | - Daya S Gupta
- Department of Biology, Camden County College, Blackwood, NJ, United States
| | - Silmar Teixeira
- Neuro-innovation Technology & Brain Mapping Laboratory, Federal University of Delta of Parnaíba, Parnaíba, Brazil; The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil
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