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Guest Editorial: Advanced Machine-Learning Methods for Brain-Machine Interfacing or Brain-Computer Interfacing

Kaijian Xia, Yizhang Jiang, Yudong Zhang, Wen Si
2021 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
In the article "Advanced Machine-Learning Methods for Brain-Computer Interfacing," Zhihan Lv, Liang Qiao, Kaijian Xia is with the School  ...  This special section focuses primarily on novel theories and methods using transfer learning and deep learning proposed for Brain-Machine Interfacing (BMI) or Brain-Computer Interfacing (BCI).  ...  This special section focuses primarily on novel theories and methods using transfer learning and deep learning proposed for Brain-Machine Interfacing (BMI) or Brain-Computer Interfacing (BCI).  ... 
doi:10.1109/tcbb.2021.3078145 fatcat:hojaokclpjhgpcqob5jbwrlktm

Machine Learning and Computational Neuroscience: A Widespread Move towards Brain Computer Interface

Alpana Upadhyay
2018 Biomedical Journal of Scientific & Technical Research  
Artificial neural network in machine learning, on the other hand has a propensity to disdain for designing codes, designing of circuits and dynamics to support optimization of brute force by means of consistent  ...  Neuroscience is more centered on study of neural codes and computations using advance data analytics.  ...  Machine Learning and Brain Computer Interfaces Machine learning methods for Brain Computer Interface pursues architecture of two functions a) Training function and b) Prediction function.  ... 
doi:10.26717/bjstr.2018.03.000846 fatcat:z6qs4wdl5bhkdbftu3v3es6wju

To Root Artificial Intelligence Deeply in Basic Science for a New Generation of AI [article]

Jingan Yang, Yang Peng
2020 arXiv   pre-print
(iii)~to root brain-computer interface~(BCI) and brain-muscle interface~(BMI) technologies deeply in science on human behaviour; (iv)~making research on knowledge-driven visual commonsense reasoning~(VCR  ...  This paper presents the grand challenges of artificial intelligence research for the next 20 years which include:~(i) to explore the working mechanism of the human brain on the basis of understanding brain  ...  Methods and all data are present in the main text and supplementary materials. Correspondence should be addressed to yja431008@gmail.com.  ... 
arXiv:2009.05678v1 fatcat:vn4pdl3k7jdwrmx4dygsyyfxvy

Brain Computer Interface Systems for Neurorobotics: Methods and Applications

Victor Hugo C. de Albuquerque, Robertas Damaševičius, Nuno M. Garcia, Plácido Rogério Pinheiro, Pedro P. Rebouças Filho
2017 BioMed Research International  
Brain computer interface (BCI) systems establish a direct communication between the brain and an external device.  ...  With the advancement of a better understanding of how our brain works, new realistic computational algorithms are being considered, making it possible to simulate and model specific brain functions for  ...  Acknowledgments The (lead) guest editors wish to thank all the authors and reviewers for helping to improve the works published. Victor Hugo C. de Albuquerque Robertas Damaševičius Nuno M.  ... 
doi:10.1155/2017/2505493 pmid:29214161 pmcid:PMC5682896 fatcat:2ig4chnxgrfudbt5ccfthxw7kq

A New Frontier: The Convergence of Nanotechnology, Brain Machine Interfaces, and Artificial Intelligence

Gabriel A. Silva
2018 Frontiers in Neuroscience  
A confluence of technological capabilities is creating an opportunity for machine learning and artificial intelligence (AI) to enable "smart" nanoengineered brain machine interfaces (BMI).  ...  Advances in computation, hardware, and algorithms that learn and adapt in a contextually dependent way will be able to leverage the capabilities that nanoengineering offers the design and functionality  ...  CONCLUDING COMMENTS The integration of machine learning and AI with nanoengineered brain machine and brain computer interfaces offers the potential for significant advances in neurotechnology.  ... 
doi:10.3389/fnins.2018.00843 pmid:30505265 pmcid:PMC6250836 fatcat:pizb7osvyzdnhiuqn7ok2ujmwy

Recent advances in brain–machine interfaces

Tadashi Isa, Eberhard E. Fetz, Klaus-Robert Müller
2009 Neural Networks  
Brain-machine interfaces (BMIs) and braincomputer interfaces (BCIs) will allow humans to operate computers, robotic arms, wheelchairs, prosthetic devices and other instruments by using only the signals  ...  Historically, the term BCI has been used to designate noninvasive recording methods whereby subjects learn to control their brain activity for manipulation of cursor on a computer display.  ... 
doi:10.1016/j.neunet.2009.10.003 pmid:19840893 pmcid:PMC4015971 fatcat:h4ht7o45ara7fpisyr3rdli43a

Recent Advances in Statistical Data and Signal Analysis: Application to Real World Diagnostics from Medical and Biological Signals

Dwarikanath Mahapatra, Krishna Agarwal, Reza Khosrowabadi, Dilip K. Prasad
2016 Computational and Mathematical Methods in Medicine  
Computational approaches that have been hugely popular and found important applications include computational modeling, Bayesian and graphical models, machine learning, deep-learning, pattern recognition  ...  interface in medicine.  ...  Computational approaches that have been hugely popular and found important applications include computational modeling, Bayesian and graphical models, machine learning, deep-learning, pattern recognition  ... 
doi:10.1155/2016/1643687 pmid:27563342 pmcid:PMC4985579 fatcat:crlkjdgcdjhrljbm6njy7ia6a4

SMC 2020 Author Information Page

2020 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)  
Human- Machine Interface: Machine Learning Human- Computer Interaction in Military Applicatio ns Mental Models User Interface Design for Mixed Modalities Virtual and Augmente  ...  brain-computer interface (BCI) applications together in teams.  ... 
doi:10.1109/smc42975.2020.9283192 fatcat:pqulbwjesjdl5cabec6hd2bgpe

Return of cybernetics

2019 Nature Machine Intelligence  
The opportunities for enhancing human capabilities and restoring functions are now quickly expanding with a combination of advances in machine learning, smart materials and robotics.  ...  Brain-machine interfaces were envisioned already in the 1940s by Norbert Wiener, the father of cybernetics.  ...  Decoding the recorded signals into useful real-time information is challenging, but advances in materials engineering and machine learning in the past decade are showing promise.  ... 
doi:10.1038/s42256-019-0100-x fatcat:lrspnn4x7rgr7dggtqaepx7yw4

Guest Editorial for the Special Section on Brain Computer Interface (BCI)

Dongrui Wu, Brent J. Lance, Vernon J. Lawhern
2017 IEEE transactions on fuzzy systems  
The paper entitled "Brain Machine Interface and Visual Compressive Sensing based Teleoperation Control of an Exokeleton Robot," by Qiu et al., presents a brain-machine interface and vision feedback based  ...  A BRAIN computer interface (BCI) enables direct communication between the brain and a computer. It can be used to research, repair, or enhance human cognitive or sensorymotor functions.  ...  He is currently interested in machine learning, statistical signal processing, and data mining of large neurophysiological data collections for the development of improved brain-computer interfaces.  ... 
doi:10.1109/tfuzz.2017.2652799 fatcat:hqxvoefwdbc2hl4ioiss6tqc6q

Advances in Recent Nature-Inspired Algorithms for Neural Engineering

Ricardo Soto, Juan A. Gómez-Pulido, Eduardo Rodriguez-Tello, Pedro Isasi
2020 Computational Intelligence and Neuroscience  
interface, machine learning, and optimization algorithms. e first article in this special issue is entitled "Double-Criteria Active Learning for Multiclass Brain-Computer Interfaces" and focuses on improving  ...  the data collection process for developing brain-computer interface (BCI) systems.  ...  Acknowledgments e guest editors thank all authors who have submitted their manuscripts to this special issue and the reviewers for their hard work with the reviewing process. Ricardo Soto Juan A.  ... 
doi:10.1155/2020/7836239 pmid:33178257 pmcid:PMC7644309 fatcat:vnrmvyl26nd3njwqwt3qfvmxyy

Active Learning Pipeline for Brain Mapping in a High Performance Computing Environment [article]

Adam Michaleas, Lars A. Gjesteby, Michael Snyder, David Chavez, Meagan Ash, Matthew A. Melton, Damon G. Lamb, Sara N. Burke, Kevin J. Otto, Lee Kamentsky, Webster Guan, Kwanghun Chung (+1 others)
2020 arXiv   pre-print
This paper describes a scalable active learning pipeline prototype for large-scale brain mapping that leverages high performance computing power.  ...  It enables high-throughput evaluation of algorithm results, which, after human review, are used for iterative machine learning model training.  ...  The authors also wish to thank Kevin Brady and Pooya Khorrami at MIT Lincoln Laboratory for their input on the active learning framework at the start of the project.  ... 
arXiv:2006.14684v1 fatcat:cpiqekn2pbf55iqv5pjqa6hy6y

Brain–machine interfaces: computational demands and clinical needs meet basic neuroscience

F Mussa-Ivaldi
2003 Trends in Neurosciences  
Meeting these challenges is the key to extending the impact of the brain-machine interface.  ...  As long as 150 years ago, when Fritz and Hitzig demonstrated the electrical excitability of the motor cortex, scientists and fiction writers were considering the possibility of interfacing a machine with  ...  Feedback is needed for learning and for control Real-time feedback can dramatically improve the performance of a brain-machine interface.  ... 
doi:10.1016/s0166-2236(03)00121-8 pmid:12798603 fatcat:g2h7mcscbffqvepnuu5dvse3jq

In the spotlight: Neuroengineering

N. Thakor
2008 IEEE Reviews in Biomedical Engineering  
The "hot" areas, at least as measured by popularity and visibility, continue to be the fields of brain-computer interface (BCI) or brain-machine interface (BMI), the application of BMI to neural prosthesis  ...  Jose Principe from University of Florida gave a keynote talk on "Toward cognitive neuroprosthesis" that reviewed his team's recent work on a new "co-adaptive" close loop paradigm for brain machine interfaces  ...  Thaut [3] also gives an indication of community interest in developing advanced EEG signal processing methods, particularly for the application to brain computer interface applications.  ... 
doi:10.1109/rbme.2008.2008231 pmid:22274896 fatcat:7wwhsnlqefbjrmo2ylzd5lgyy4

In the Spotlight: Neuroengineering

Nitish V. Thakor
2013 IEEE Reviews in Biomedical Engineering  
The "hot" areas, at least as measured by popularity and visibility, continue to be the fields of brain-computer interface (BCI) or brain-machine interface (BMI), the application of BMI to neural prosthesis  ...  Jose Principe from University of Florida gave a keynote talk on "Toward cognitive neuroprosthesis" that reviewed his team's recent work on a new "co-adaptive" close loop paradigm for brain machine interfaces  ...  Thaut [3] also gives an indication of community interest in developing advanced EEG signal processing methods, particularly for the application to brain computer interface applications.  ... 
doi:10.1109/rbme.2012.2228515 pmid:23193468 fatcat:6neq4ti3ojg67ehsm65inwivrm
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