Brain-Computer Interfaces and the quest to cyborgs.

_{George Henry Lewes (1817-78) English writer and critic, “Science is the systematic classification of experience.”}

BCI

In recent years, the appealing idea of a direct interface between the human brain and an artificial system, called Brain Computer Interface (BCI) or Brain Machine Interfaces (BMI), has proved the feasibility of a distinct non-biological communication channel to transmit information from the Central Nervous System (CNS) to a computer device. Its most important and straightforward application is for people affected by neuro-degenerative diseases.

A very remarkable aspect of this communication channel is the ability to transmit some general cognitive state, like alertness, drowsiness, boredom, and so on, which can very helpful particularly in rehabilitation procedures.

CNS’s biosignals, like EEG, have a high variability between different subjects and even between different moments for the same subject. This inherent complexity is a real challenge when it is required to feasily extract information from raw EEG signals.

Due to this inner complexity, it is often necessary to implement many distinct and specialized algorithmic methods, to filter the signal, classify it, and try to determine some meaning out of it.

Outstanding success has been achieved with invasive BCI, i.e. with surgically implanted electrodes, from the total reproduction of arm movement to the remote control of a manipulator by a macaque using brainwave information. However, Biocompatibilities issues and the pervasive complexity and risks of surgical procedures are the main drive to enhance current non-invasive technologies. Above all, Electroencephalography (EEG), is the most widespread method to gather information from the CNS in a non-invasive way. It measures the summed activity of post-synaptic potentials from electrodes positioned over the scalp. EEG has been used in various working prototypes, as assisting devices, mainly wheelchairs. In order to derive information out of the subject’s volition, different mental paradigms have been discovered and applied. There have been many algorithms developed so far for processing EEG signals, based on time, frequency, spatial domains or combinations. However, the exploration of alternative paths is ongoing, because non-invasive BCI still lacks the required performance to be used in real-time environments and to be ready for mainstream production.

Those devices that not only restrict themselves to use CNSs signals, but they also include any kind of biological signal (EMG, EKG, EOG, GSR, etc) combined with sensor fussion algorithms are often called Hybrid BCIs or the BCI term is generalized to BNCI: Brain Neuronal Computer Interaction. Additionally, when the controlling device is not restricted to a computer, the term BMI, Brain Machine Interface, could be also used.

BCI in the news and media

• Neuralink first person implanted
• Maureen Clerc
• Elon Musk Neuralink
• Wait But Why - Excellent BCI intro - Neurallink
• EE Times
• Turning Thoughs into Worlds, MIT Review
• BCI News Argentina
• Hacking the brain
• Make Magazine BCI(OpenBCI)

Electrodes info

• https://pressrelease.brainproducts.com/choosing-your-electrode-technology/

BCI Tour

BCI Guys

BCI solid sources

Neural Prosthetics Fabien Lotte’s Site SchalkLab BNCI Horizon 2020, The Europpean BCI project BNCI Horizon 2020, Roadmap Defunc! Springer The Neuro Network BCI MOOC Swartz Center for Computational Neuroscience BCI Society

Neuroscience Journals where BCI papers are published

This is an uncurated list of Journals were BCI research diaspora get published.

This is “the source”: https://sites.google.com/site/fabienlotte/conferences

Call for Paper’s Wiki Journal’s Evaluation

BCI Journal

Brain Computer Interfaces, Taylor and Francis BCI Journal

Most effective BCI Journals https://link.springer.com/article/10.1007/s10489-022-04226-4

• Journal of Neural Engineering
• IEEE Transactions on Neural Systems
• Rehabilitation Engineering

Machine Learning Journals

I/ECCV, CVPR, BMVC, PAMI, RSS, RAL, IJRR, TRO, NIPS

Teaching Material

University of Twentee’s Teaching Lectures g.Tec Webinars g.Tec White Papers BCI MOOC Swartz Center for Computational Neuroscience

Books

• Brain–Computer Interfaces Handbook: Technological and Theoretical Advances, Nam; Nijholt; Lotte
• Brain Computer Interfaces Research: State of the Art (I, II, III, IV), Allison
• Signal processing for neuroscientists: an introduction to the analysis of physiological signals
• Springer.BCI.Applying.Our.Mind.To.Human.Computer.Interaction.2010
• Brain Computer Interfaces International Assesment, 2010
• Brain Computer Interfaces - Current Trends And Applications, 2015, Aboul Ella
• Brain-Computer Interfaces: applying our minds to human-computer interaction, Nijholt, 2010
• Brain-Computer Interfaces in Their Ethical Social and Cultural Contexts, Springer Gubler 2014
• Brain Computer Interfaces for Assistive Robotics, Gandhi, Elsevier 2015
• Toward Practical Brain Computer Interfaces, 2012, Allison
• Statistical Signal Processing for Neuroscience and Neurotechnology, Oweiss.
• Brain Computer Interfaces for Communication and Control, Wolpaw and Wolpaw.
• Brain Computer Interfacing: An Introduction, Rajesh Rao (http://bci.cs.washington.edu/)
• Beyond Boundaries: The New Neuroscience of Conneting Brains with Machines and Hot it will change our lives, Miguel Nicolelis.

Relevant Papers

• Wolpaw J, Birbaumer N, McFarland D , Clinical Neurophysiology, Brain-computer interfaces for communication and control,2002 (most cited paper in BCI).
• Lotte et al, A review of classification algorithms for EEG-based brain-computer interfaces: a 10 year update.,2018
• Lotte et al, A review of classification algorithms for EEG-based brain-computer interfaces.2007
• Lebedev A, Nicolelis MA,Trends in Neurosciences, Brain-machine interfaces: past, present and future,2006
• Nijboer, Femke and Broermann, Ursula, Brain Computer Interfaces for Communication and Control in Locked-in Patients
• Donoghue JP , Nature Neuroscience, Connecting cortex to machines: recent advances in brain interfaces,2002
• Heetderks WJ, McFarland DJ, et al , IEEE Transactions on Rehabilitation Engineering, Brain-computer interface technology: a review of the first international meeting,2000
• Cohen, Where Does EEG Come From and What Does It Mean?, Trends in Neurosciences,2017.
• McCall, Owning Ethical Innovation: Claims about Commercial Wearable Brain Technologies, Neuron 2019
• Deep Learning-Based Electroencephalography Analysis: A systematic Review, Roy, Banville,..,Gramfort, 2019
• Baseline Correction done right https://onlinelibrary.wiley.com/doi/abs/10.1111/psyp.13451
• https://www.nature.com/articles/s41591-019-0548-6
• Second opinion needed, communicating uncertainty in medical machine learning https://www.nature.com/articles/s41746-020-00367-3: This paper discuss very compelling the ideas of uncertainty within the field of ML applied to medical applications.

Getting-Started Papers…

• Evolving Signal Processing for Brain–Computer Interfaces, Makeig, 2012
• Information Systems Opportunities in Brain–Machine Interface Decoders, Kao, 2014
• Non-Invasive Brain-to-Brain Interface (BBI): Establishing Functional Links between Two Brains, Seung-Schik, 2013
• Highly comparative time-series analysis: the empirical structure of time series and their methods, Fulcher, 2013
• Minimally invasive endovascular stent-electrode array for high-fidelity, chronic recordings of cortical neural activity, Oxley, 2016
• Brain-to-text: decoding spoken phrases from phone representations in the brain, Herff, 2015

Handy papers

• General Principles of machine learning for brain computer interfacing, Iturrate et al, 2020
• Chronically Implanted Intracranial Electrodes: Tissue Reaction and Electrical Changes, Campbel 2018, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6187588/
• What Makes Clinical Research Ethical, Ezekiel, 2000
• Mind the traps! Design Guidelines for Rigorous BCI Experiments, Jeunet, 2017
• Generating Artificial EEG Signals to Reduce BCI Calibration Time, Lotte, 2011
• Heading for new shores! Overcoming pitfalls in BCI desing, Chavarriaga, 2017
• Committee report: Publication guidelines and recommendations for studies using EEG and MEG, Keil, 2014
• Evaluation Criteria for BCI Research, Schlogl, 2007
• The neurophysiological bases of EEG and EEG measurement: A review for the rest of us, Jackson, 2014
• Digital filter design for electrophysiological data - A Practical Approach, Widmann, 2014
• How inappropriate high‐pass filters can produce artifactual effects and incorrect conclusions in ERP studies of language and cognition, Tanner, 2015
• An introduction to ROC Analysis, Fawcett, 2005
• Billinger, Is it Significant? Guidelines for Reporting BCI Performance, 2012
• http://www.cnrs.fr/en/similar-information-rates-across-languages-despite-divergent-speech-rates ITR of speech
• https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086733 Synchronization procedure and stimulations frequencies check.
• The origin of extracellular fields and currents-EEG, ECoG, LFP and spikes, buzsaki
• Methodological Considerations for Studying Neural Oscillations, Donoghue, Voytek

Datasets

• MEG Archive
• Dream Nights
• TUH EEG Corpus
• BIDS Standard for Brain Dataset Sharing
• Open IO Data Repository
• EEG MI
• EEG Motor Imaginary
• EEGLAB Datasets @ Columbia University
• BCIs Competitions
• P300 Datasets @EPFL
• ERP ERD fMRI Datasets
• BNCI Datasets
• UCSD Datasets
• EEG Time Series 2001
• The Neural Prediction Challenge
• Kaggle Competitions
• Kaggle EEG Analysis for Confusion

# Toolbox

• PsychoPy
• https://openmeeg.github.io/
• https://github.com/BciPy/BciPy
• http://asi.insa-rouen.fr/enseignants/~arakoto/code/bciindex.html

BCI on the Web

• BCI origins: Vidal’s seminal work presented by Allison
• Allison’s BNCI
• Zaragoza’s BitBrain
• WTEC Foreign BCI Research Program
• BioScience Argentina
• Javier Minguez’s Pubs
• More References
• Emotiv Blog
• Neurogadget Web Site
• BCI Over EEG
• BCI Blog
• BCI Blog
• Brainpedia
• Sapiens Lab

BCI Tweeters

• https://twitter.com/FemkeNijboer
• https://twitter.com/TanTTLe
• https://twitter.com/cybathlon
• https://twitter.com/sapien_labs
• https://twitter.com/konigpeter
• https://twitter.com/ana_maiques
• https://twitter.com/GrazBCI
• https://twitter.com/mlopezBCI
• https://twitter.com/fieldtriptoolbx
• https://twitter.com/mne_python
• https://twitter.com/chavarriagaBCI
• https://twitter.com/tactileBCI
• https://twitter.com/bci_lab_info
• https://twitter.com/eegrapher
• https://twitter.com/BrainAnalyser
• https://twitter.com/SafeForRobots
• https://twitter.com/HacktheBrain_UK
• https://twitter.com/IsraelBrainTech
• https://twitter.com/bncih2020
• https://twitter.com/jminguezBCI
• https://twitter.com/anijholt
• https://twitter.com/BCIJournal
• https://twitter.com/MuSAELab
• https://twitter.com/openvibebci
• https://twitter.com/ChristophGuger
• https://twitter.com/russomanno15
• https://twitter.com/gtec_BCI
• https://twitter.com/OpenBCI

BCI from a perspective of neuroscience and neuroeconomics (Gmuden Retreat 2009)

1. Neuroeconomics: The consilience of brain and decision [Science, 2004]
2. Neuroeconomics: How neuroscience can inform economics [Journal of Economic Literature, 2005]
3. Neuroeconomics: An overview from an economic perspective [Brain Research Bulletin, 2005]
4. Neuroeconomics: Cross-currents in research on decision-making [Trends in Cognitive Sciences, 2006]
5. Decision Neuroscience [Marketing Letters, 2005]
6. What is ―neuromarketing‖? A discussion and agenda for future research [International Journal ofPsychophysiology, 2007]
7. Multilevel integrative analysis of human behavior: Social neuroscience and the complementing nature of social and biological approaches [Psychological Bulletin, 2000]
8. What are the brain mechanisms on which psychological processes are based? [Perspectives on Psychological Science, 2009]
9. Brain-computer communication: Unlocking the locked in [Psychological Bulletin, 2001]
10. Brain-computer interfaces for communication and control [Clinical Neurophysiology, 2002]

ITBA BCI Tour

• Brain Computer Interfaces
• EPOC Emotiv EEG Basics
• Drowsiness Detection
• The Sound of your Brain
• Embodiment
• Hybrid Brain Waves
• Monostuff Blog

Side Projects

• EPOC EEG Visual C++ Data Logger Library
• Brain Waving
• SPo2 Data Logger Library

Some Videos

• https://www.youtube.com/watch?v=JrbZ6I7d0gE
• https://www.youtube.com/watch?v=L4NtUgb-OEQ
• https://www.youtube.com/watch?v=EI1LCVYd23w
• https://www.youtube.com/watch?v=SbIlOemnSkw
• https://www.youtube.com/watch?v=uLd-BW4ov7U
• https://www.youtube.com/watch?v=Xk8dWdHnrnM
• https://www.youtube.com/watch?v=SGKXJZVHONo
• https://www.youtube.com/watch?v=c8vJ5QAIc1I

Laboratories

Woldwide Laboratories

• Pakistan list
• Awesome list of neuroscientists
• Wolpaw’s Wardworth Center
• SchalkLab
• Inria Lab BCI
• RIKEN
• Cichocki Lab@RIKEN
• Graz BCI
• Essex BCI-NE
• Twentee Human Media Interaction
• Twentee BSS Lab

## USA Labs

• Boston University: http://www.bu.edu/npl/
• BrainGate: http://braingate2.org/
• Colorado State University: http://www.cs.colostate.edu/eeg/main/about
• Duke University: http://sspaciss.ee.duke.edu/bci.php
• East Tennessee State University: http://www.etsu.edu/cas/bcilab/
• Georgia Tech: http://www.cc.gatech.edu/brainlab/kg/
• Northeastern University: http://www.ece.neu.edu/groups/csl/
• Oregon Health & Science University/Northeastern University: http://www.ohsu.edu/xd/research/centers-institutes/institute-on-development-and-disability/reknew/locked-in-syndrome.cfm
• University of California, Berkeley: http://www.eecs.berkeley.edu/~carmena/
• University of California, San Diego: http://sccn.ucsd.edu/
• University of Michigan: http://www.umich.edu/~umdbi/
• University of Minnesota: http://www.tc.umn.edu/~binhe/bci.htm
• University of Pittsburgh: http://clinicaltrials.upmcphysicianresources.com/bci/
• University of Rhode Island: http://web.uri.edu/inp/meet/walter-besio/
• University of Washington: http://neural.cs.washington.edu/
• Wadsworth Center: http://www.wadsworth.org/bci/
• Washington University in St. Louis: http://labs.seas.wustl.edu/bme/dmoran/

http://braincomputerinterface.weebly.com/other-bci-researchers-and-labs.html http://about.bci-lab.info/ Great List »> https://bmi.neuroinf.jp/interest/t-b-emgeeg.html (datasets are also here) http://www.alsa.org/als-care/resources/publications-videos/factsheets/brain-computer-interface.html?referrer=https://www.google.com.ar/

Worldwide People

• Wolpaw - NY Wadsworth
• Maureen Clerc - Inria
• Klaus Robert Muller - TU Berlin
• Benjamin Blankertz - TU Berlin
• José del R. Millan - EPFL
• Femke Nijboer - Leiden University
• Lotte Fabien - INRIA
• Brendan Allison - g.Tec
• Gert Pfurtscheller
• Donchin and Farwell
• Andrea Kubler
• Christoph Guger - G.Tec
• Anton Nijholt
• Javier Minguez
• Donatella Mattia - Foundazione Santa Lucia
• Cichocki Nonnegative matrix factorization
• Izhikevich Dynamical Systems
• Buzsaki Rythms of the Brain
• Riccardo Poli
• Reza Fazel-Rezai - Tiene un libro buenísimo.

Worldwide companies

• Neuralink
• Neurable
• Braingate
• Neuroelectric https://interestingengineering.com/neuroelectrics
• https://www.astrocyte.me/notesarticles/startups-that-hack-the-brain-a-review-of-67-european-neurotech-startups

Argie Labs

• UNER, Faculta de Ingeniería, LIRINS,(Oro Verde) Bioingeniería / Dr. Gerardo Gentilleti :
  • Organizadores de las JAICC de 2006 y 2009.
  • http://cortex.loria.fr/Projects/STIC-AmSud-BCI,
  • http://www.bioingenieria.edu.ar/postgrado/index.php?option=com_content&view=category&id=72&Itemid=61
  • Interactive Dynamics ,https://www.infobae.com/2016/03/17/1797779-pyme-argentina-creo-una-silla-ruedas-que-se-maneja-la-mente/
  • +Investigadores: Guerenstein, Pablo; Carolina B. Tabernig (BCI-FES system for neuro-rehabilitation of stroke patients)
• UNL, Centro de I+D en Señales, Sistemas e Inteligencia Computacional; Facultad de Ingeniería y Ciencias Hídricas.
  • IMAL Matemáicas Ruben Spies, Victoria Peterson https://scholar.google.com/citations?user=vCuSUEIAAAAJ&hl=en
• UBA, Facultad de Ingeniería, Laboratorio de Sergio Lew (http://www.fi.uba.ar/es/node/1442) , “Instituto de Ingeniería Biomédicas” / Dr. Sergio Lew
  • BCI Invasivo principalmente.
• UBA, Facultad de Ingeniería, Laboratorio de Sistemas Inteligentes Dr. Jorge Ierache
  • http://laboratorios.fi.uba.ar/lsi/: control de robots por bioseñales, detecció de emociones.
• UBA, Exactas
  • https://liaa.dc.uba.ar/ Applied Artificial Intelligence Lab Dr. Agustín Gravano / Dr. Diego Fernandez Slezak
  • Tesis de grado del labo de Mindlin de Dinámica del Canto de Aves, (Tesis de Ezequiel Arneodo).
  • +Investigadores: Alejandro Sabatini
• UNSJ GATEME Laboratorio de Neurorehabilitación
  • Directora: Dra. Bioing. Natalia Lopez: http://www.suplementos.unsj.edu.ar/octubre73/?p=1856
  • Diez Pablo Federico
• INAUT, Instituto Nacional de Automática, San Juan, / Dr. Carlos Soria, Dr. Eugenio Orosco
  • Enrique Avila Perona,
  • BCI Robótica (BCI híbridos, robótica asistiva)
  • Trabajan con Teodiano Freire Bastos en Brasil
  • +Investigadores: Mst. Ing. Fernando Auat Cheeín
  • E-mail: fauat@inaut.unsj.edu.ar
• IAM Instituto Argentino de Matemáticas Alberto Calderon / Bioing. Sergio Liberczuk, Dr. Bruno Cernuschi Frías
  • Matemáticas y modelado del problema inverso.
• ITBA, / CiC del Dr Juan Santos, http://www.itba.edu.ar/es/id/centros/cic-centro-de-inteligencia-computacional
  • Proyecto Doctorado Robótica Asistiva BCI Neurorehabilitación, Rodrigo Ramele
  • http://www.unsam.edu.ar/tss/controlar-maquinas-con-el-pensamiento/
  • EEG Waveforms basado en métodos de Computer Vision: estabilidad
• UNC, Universidad Nacional de Cordoba
  • Trabajo Final de Ingeniería: http://www.electronicosonline.com/2013/07/08/crean-jovenes-argentinos-interface-cerebral-para-discapacitados/
  • Carrera de Ingeniería Biomédica: Ing. Diego Beltramone
  • Florencia Garro: https://ieeexplore.ieee.org/abstract/document/8914572
• UNLP, LEICI / Dr. Enrique Spinelli (http://www.ing.unlp.edu.ar/leici/esp/pspinelli.html)
  • Electrónica.
  • Tesis de Grado de García Pablo: http://sedici.unlp.edu.ar/handle/10915/3800631605
  • Tesis de Maestría de Andrea Noelia Bermudez Cicchino
• UNT Universidad Nacional de Tucuman, Instituto Superior de Investigaciones Biológicas (INSIBIO)
  • www.lamein.org
  • Investigación sobre alternativas de codificación neural de los sistemas sensoriales.
  • Investigadores responsables: Dr. Carmelo Felice, Mst. Ing. Fernando Farfán
  • E-mail: cfelice@herrera.unt.edu.ar, ffarfan@herrera.unt.edu.ar
• ANSES Laboratorio de Investigación y Desarrollo en Nuevas Tecnologías (LIDeNTec)
  • Desarrollo de BCI
  • Investigadores responsables: Dr. Mario Mastriani
  • E-mail: mmastri@gmail.com
• Cesar Caiafa http://ccaiafa.wixsite.com/cesar
  • Cesar fue parte del equipo que desarrollo diversas técnicas de Blind Source Separation basadas en factorización de matrices no negativas (Cichocki en RIKEN en Japón)
• UNS, HCI
  • Martín Larrea (desde UX).
• Diego Ervin, Alejandro Hadad, Omar Chiotti (Biosignals, ICU)
  • http://iopscience.iop.org/article/10.1088/1742-6596/90/1/012074/meta

Startups

• Interactive Dynamics (OpenHacks)
• OTTAA Project: Florencia Garro (Cordoba)
• https://es.viewmind.ai/

Neuro

• Laboratorio del Sueño Dr. Cecilia Forcato https://www.labsuenoymemoria.com/
• INECO
  • Eugenia Hesse https://neuro.org.ar/sites/neuro.org.ar/files/Hesse-2015-Early%20detection%20of%20intentional%20harm.pdf
  • Agustín Ibañez (capo de INECO)
• UBA FMED Dra. Valeria Della Magiore
  • http://www.physiologyofactionlab.info/es/el-lab/
• IBCN Silvia Kochen
  • http://www.ibcn.fmed.uba.ar/200_grupos-lab-epilepsia-kochen.html

Argie Conferences

RPIC CLAIB

Argie Organizations

SAN Sociedad Argentina de Neurociencias

Devices and Components

• CTRL Labs
• Next Mind
• BTS Bioengineering
• Open BCI
• Biometrics EMG sensors
• Intendix
• Emotiv EPOC EEG, Insight
• [NeuroSky] Mindwave Mobile
• FlexCTRL Brain
• Melon Headband monosensor EEG
• Interaxon Muse
• HaloNeuro tDCS
• focUS tDCS
• Quantum 6
• Olimex OpenEEG
• DIY Electrodes and Tetrodes
• Enobio EEG
• Wireless EEG sensors
• NeuroOne EEG
• Bitalino, body signals
• MBrainTrain
• Walnut Wearables
• Neuroelectric Emobio
• Wearable Sensing
• DCS Corporation
• National Chiao Tung University Brain Research Center
• Nice (but old) review of devices: Science For the Masses
• Low’s iBrain
• https://backyardbrains.com/experiments/
• https://www.cooking-hacks.com/documentation/tutorials/ehealth-biometric-sensor-platform-arduino-raspberry-pi-medical

fUnctional Near Infrared Spectroscopy

• fNIR by BioPac, Optical Brain Imaging
• fNIR
• fNIR100A
• (OXYMON MKIII, Artinis).
• ETG 4000 (Hitachi Medical Systems), the
• ImagentTM (ISS, Champaign, Illinois), the
• NIRO 200 (Hamamatsu Photonics),
• DYNOT-232 (NIRx Medical Technologies, LLC.),
• spectratech OEG-16, http://spectratech.co.jp/En/indexEn.html
• FOIRE-3000 (Shimadzu OMM),
• fNIR (BIOPAC Systems, Inc.), and
• CW6 (Techen Inc.).
• http://nirx.net/nirsport
• http://www.biocompresearch.org/
• http://www.golem.de/1109/86514.html

Software

• http://www.comp-engine.org/timeseries/
• Python emotiv, this is the hack to Emotiv. You do not need the Emotiv Driver.
• FieldTrip, Matlab Plugin
• BCI2000
• OpenVibe
• OpenBMI
• http://sapienlabs.co/emotiv-epoc-signal-quality-good-enough-research/
• bbci
• pyff
• mne
• EEGLAB
• BCILAB
• https://github.com/NOCIONS/letswave6
• https://github.com/VisLab/EEG-Annotate

### Python BCI

https://logdown.com/account/posts/737354-python-brain-computer-interface

Epistemology

• Neuro Terms
• How to Write papers
• Research Tools
• Reinforcement Learning Tool
• IEEE Latex guidelines
• Russian Sci HUB!
• Preparing Manuscript in Latex
• Guidelines for writing research proposals
• Times higher education guide
• Graduate students guide for computer science
• Computer Science Research Guide
• How to give a talk by Microsoft
• Call to end p-values statistical significance

Other stuff

Computational Neuro Web Intelligence requires a body MazoUZBCI.NET BCIer Direct BCI Blog BCI Over EEG Great Blog Emotiv Experimenter Robert Burke, MIT Media Lab Limitations of Emotiv MindReading with RaspBerry PI Application of BCI to detect commit-and-runs Bill Gate’s Scientific Crowfunding Site Neurogadget Site Student Dave’s Tutorials BCI is used in the IARPA Challenge to predict truesworthyness BCI on Google+

Matlab

• Matlab CheatSheet
• Matlab Tutorial for Engineers
• Matlab GraphToolBox
• Pandas Cheetsheet
• Signal Similarities

R

Using R http://www.cookbook-r.com/Strings/Creating_strings_from_variables/

Algorithms

Fast ICA