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Deep Pinsker and James-Stein Neural Networks for Decoding Motor Intentions from Limited Data

Marko Angjelichinoski, Mohammadreza Soltani, John Choi, Bijan Pesaran, Vahid Tarokh
2021 IEEE transactions on neural systems and rehabilitation engineering  
Yet, in many instances, brain-computer interfaces (BCIs) rely on simple classification methods, circumventing deep neural networks (DNNs) due to limited training data.  ...  We consider a solution that combines Pinsker's theorem as well as its adaptively optimal counterpart due to James-Stein for feature extraction from LFPs, followed by a DNN for classifying motor intentions  ...  connected MLP and referred to as deep James-Stein neural network (DJSNN).  ... 
doi:10.1109/tnsre.2021.3083755 pmid:34038363 fatcat:fhxzwr32v5dcbhwxreu423rtfu

Front Matter

2020 2020 International Joint Conference on Neural Networks (IJCNN)  
Lan, Wei Liu and Bao-Liang Lu Center for Brain-like Computing and Machine Intelligence, Shanghai Jiao Tong University, China; Center for Brain-like Computing and Machine Intelligence, Department of Computer  ...  Neural Computation and Adaptation, RIKEN Centre for Brain Science, Japan 4:30PM Neural H2 Control Using Reinforcement Learning for Unknown Nonlinear Systems [#21468] Perrusquia Adolfo and Yu Wen CINVESTAV-IPN  ...  Special Session I-SS52: Methods and Applications of Deep Reinforcement Learning to Autonomous Systems Friday, July 24, 5:00PM-7:00PM, Room: IJCNN Room 3, Chair: Thanh Thi Nguyen 5:00PM Beyond-Visual-Range  ... 
doi:10.1109/ijcnn48605.2020.9207579 fatcat:hptkppolhbfn7nz3yangesetpi

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Network for EEG-Based Brain-Computer Interface Applications Avinash Kumar Singh and Xiao Tao .......... 582 EDAC1I: Neural Network Learning Models/Dimensionality Reduction and Analysis of Large and Complex  ...  Recovery of Silent Data Corruption in Convolutional Neural Network Data Storage Mohammadreza Ramzanpour and Simone Ludwig .......... 3057 Auto-tuned Deep Recurrent Neural Networks for Application in Wind  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

Brain-Controlled Interfaces: Movement Restoration with Neural Prosthetics

Andrew B. Schwartz, X. Tracy Cui, Douglas J. Weber, Daniel W. Moran
2006 Neuron  
Brain-controlled interfaces are devices that capture brain transmissions involved in a subject's intention to act, with the potential to restore communication and movement to those who are immobilized.  ...  From the rapid growth in biotechnology, neural engineering has emerged as a new field.  ...  Sensory Input Interfaces The function of a somatosensory neural input interface is to transmit the physical state of the prosthetic limb to the neural networks supporting perception and feedback control  ... 
doi:10.1016/j.neuron.2006.09.019 pmid:17015237 fatcat:4hpdr5fhgbdrbc62lxk4mgiuky

Adaptive Extreme Edge Computing for Wearable Devices

Erika Covi, Elisa Donati, Xiangpeng Liang, David Kappel, Hadi Heidari, Melika Payvand, Wei Wang
2021 Frontiers in Neuroscience  
We propose various solutions for biologically plausible models for continual learning in neuromorphic computing technologies for wearable sensors.  ...  Furthermore, we evaluate the requirements for edge computing within wearable devices in terms of footprint, power consumption, latency, and data size.  ...  Stefan Slesazeck for useful discussion on ferroelectric and memristive devices.  ... 
doi:10.3389/fnins.2021.611300 pmid:34045939 pmcid:PMC8144334 fatcat:5by77im5crcslgt7zj3wulzd5e

CloudBrain: Online neural computation in the cloud [article]

Leon Bonde Larsen, Rasmus Stagsted, Beck Strohmer, Anders Lyhne Christensen
2021 bioRxiv   pre-print
Neuromorphic computing currently relies heavily on complicated hardware design to implement asynchronous, parallel and very large-scale brain simulations.  ...  We explain principles for how neuron, synapse and network models can be implemented and we demonstrate that our implementation can be used to control a physical robot in real-time.  ...  We thank Cao Danh Do and Emil Bonde Larsen for help preparing the robot and its environment. Finally we thank SDU-Biorobotics and The Centre for BioRobotics for funding the project. References  ... 
doi:10.1101/2021.01.21.427662 fatcat:ypn6ed425vandlptxnqpdgikxq

Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs

Cristian Rotaru, Octav Brudaru
2012 2012 IEEE Congress on Evolutionary Computation  
This paper presents a cellular genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The evolution process is inspired by a basic genetic algorithm.  ...  285, Rifai Chai, Sai Ho Ling, Gregory P Hunter and Hung T Nguyen, Mental Non-motor Imagery Tasks Classifications of Brain Computer Interface for Wheelchair Commands Using Genetic Algorithm-Based Neural  ...  neural prosthetic applications 773, Li-ning Xing, Ying-wu Chen and Jian Xiong, Dynamic Structure-based Neural Network Determination for Simulation Optimization 774, James Schwaber, Systems and Computational  ... 
doi:10.1109/cec.2012.6256590 dblp:conf/cec/RotaruB12 fatcat:4ly3nrktw5habc6lf5err7d5py

Connectome analysis with diffusion MRI in idiopathic Parkinson's disease: Evaluation using multi-shell, multi-tissue, constrained spherical deconvolution

Koji Kamagata, Andrew Zalesky, Taku Hatano, Maria Angelique Di Biase, Omar El Samad, Shinji Saiki, Keigo Shimoji, Kanako K. Kumamaru, Kouhei Kamiya, Masaaki Hori, Nobutaka Hattori, Shigeki Aoki (+1 others)
2018 NeuroImage: Clinical  
network.  ...  Mapping was also performed by deterministic single-shell, single tissue (SSST)-CSD tracking and probabilistic SSST-CSD tracking for comparison.  ...  Acknowledgments This work was supported by the program for Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) from Japan Agency for Medical Research and development (AMED);  ... 
doi:10.1016/j.nicl.2017.11.007 pmid:29201640 pmcid:PMC5700829 fatcat:edm2wodokbgpziuvicymvbp5ca

Proceedings of the Sixth Deep Brain Stimulation Think Tank Modulation of Brain Networks and Application of Advanced Neuroimaging, Neurophysiology, and Optogenetics

Adolfo Ramirez-Zamora, James Giordano, Edward S. Boyden, Viviana Gradinaru, Aysegul Gunduz, Philip A. Starr, Sameer A. Sheth, Cameron C. McIntyre, Michael D. Fox, Jerrold Vitek, Vinata Vedam-Mai, Umer Akbar (+22 others)
2019 Frontiers in Neuroscience  
The proceedings also offer insights into the new era of brain network neuromodulation and connectomic DBS to define and target dysfunctional brain networks.  ...  The annual deep brain stimulation (DBS) Think Tank aims to create an opportunity for a multidisciplinary discussion in the field of neuromodulation to examine developments, opportunities and challenges  ...  ACKNOWLEDGMENTS MO acknowledges the support of Tyler's Hope for a Dystonia Cure and the Parkinson's Foundation Center of Excellence.  ... 
doi:10.3389/fnins.2019.00936 pmid:31572109 pmcid:PMC6751331 fatcat:hqoewqybk5gopp4a4vyovhpbkq

27th Annual Computational Neuroscience Meeting (CNS*2018): Part Two

2018 BMC Neuroscience  
for various neural and neural network models.  ...  To test this, we built a deep convolutional neural network that receives reverberated waveform inputs.  ...  Our results suggest that MLMC may offer significant speed-up for collecting statistics from spiking network models, particularly for predominantly feed-forward networks and for recurrent networks operating  ... 
doi:10.1186/s12868-018-0451-y fatcat:afgrjlnjgjarldkuwo3e2pt5sm

Possibilities and limits of mind-reading: A neurophilosophical perspective

Kathinka Evers, Mariano Sigman
2013 Consciousness and Cognition  
In this article we inspect technical and theoretical limits on brain-machine interface access to other minds.  ...  Today, several methods have been developed which can measure brain states relevant for assessments of mental states without 1st person overt external behavior or speech.  ...  Mariano Sigman is sponsored by the James McDonnell Foundation 21st Century Science Initiative in Understanding Human Cognition -Scholar Award.  ... 
doi:10.1016/j.concog.2013.05.011 pmid:23807515 fatcat:g3r5uciyvba5tndupi2mgkpuxq

Big Data and Neuroimaging

Yenny Webb-Vargas, Shaojie Chen, Aaron Fisher, Amanda Mejia, Yuting Xu, Ciprian Crainiceanu, Brian Caffo, Martin A. Lindquist
2017 Statistics in Biosciences  
We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big  ...  There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas.  ...  Shrinkage estimators, such as empirical Bayes and James-Stein estimators, borrow strength from the larger population to produce more accurate subjectlevel estimates [52, 53] .  ... 
doi:10.1007/s12561-017-9195-y pmid:29335670 pmcid:PMC5766007 fatcat:b6wwfdd735cybdsmnbvaf63mha

Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review

Mahyar Hamedi, Sh-Hussain Salleh, Alias Mohd Noor
2016 Neural Computation  
Recent research has reached a consensus on the feasibility of motor imagery brain-computer interface (MI-BCI) for different applications, especially in stroke rehabilitation.  ...  Brain connectivity analysis, particularly functional and effective, has been described as one of the most promising approaches for improving MI-BCI performance.  ...  Introduction Brain-computer interface (BCI) is a state-of-the-art technology that translates neuronal activities into user commands.  ... 
doi:10.1162/neco_a_00838 pmid:27137671 fatcat:eyz64y3vmneplmgdlapn5whp7m

Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

Michael A. Arbib, James J. Bonaiuto, Ina Bornkessel-Schlesewsky, David Kemmerer, Brian MacWhinney, Finn Årup Nielsen, Erhan Oztop
2013 Neuroinformatics  
of databases for encoding -separately or together -neurocomputational models and empirical data that serve systems and cognitive neuroscience.  ...  Keywords Linking models and experiments; Models, neurocomputational; Action and the brain; Language and the brain; Mirror systems; Multi-level data; Multi-level models; Databasing empirical data; Federation  ...  How can modelers begin to build systems that span the layers between information processing in brain circuits -the typical domain of neural processing models -and genes, gene products, and regulatory networks  ... 
doi:10.1007/s12021-013-9210-5 pmid:24234916 pmcid:PMC4101894 fatcat:j5ddog5unbf6tlbgn6mt4oj334

The Cognitive NeurosciencesEdited by M. S. Gazzaniga, Cambridge, MA: The MIT Press, 1994, Hardbound, 1447 pages, $95.00. ISBN 0-262-07157-6

James M. Sprague
1995 Journal of Cognitive Neuroscience  
The reason for defective orienting may be very different in each case. The neural mechanisms for visual attentional orienting constitute a distributed network that may include all of these regions.  ...  Neural Mechanisms Mediating Attention and Orientation to Multisensory Cues (B. E. Stein, M. Wallace, and A.  ... 
doi:10.1162/jocn.1995.7.4.514 pmid:23961910 fatcat:fhyditswmrb3lm74uau5bq7une
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