Trends in BCIs for us - UCSD Cognitive Sciencedesa/Brendanslides.pdfBrain-Computer-Interface (BCI)...

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Trends in BCIs for us Brendan Allison, PhD University of California, San Diego COGS 189 January 8, 2019

Transcript of Trends in BCIs for us - UCSD Cognitive Sciencedesa/Brendanslides.pdfBrain-Computer-Interface (BCI)...

  • Trends in BCIs for us

    Brendan Allison, PhD

    University of California, San Diego

    COGS 189

    January 8, 2019

  • Brain-Computer-Interface (BCI) components

    BCI components (Allison, 2011)

  • Applications: RISER model

    From Wolpaw and Wolpaw (2012); since widely adopted

    This broadens the applications of BCIs from the

    definitions in the 2010 “Gentle Introduction” chapter

    and 2011 “Trends in BCI Research”.

  • Video courtesy of G. Schalk.

    Work is from Schalk et al., 2017.

  • Common view

    BCI/AN is for users with disabilities

  • Sci-fi view

    BCI and AN is from, and for, evil

    Star Trek (1966)

    This is still among the mostrealistic and altruistic

    portrayals of BCIs.

  • Widespread BCI adoption requires replacing

    conventional interfaces for conventional

    users in conventional settings.

    Common view

    TU Graz,

    2010

  • Replacing or supplementing conventional

    interfaces for conventional users in

    specific settings.

    → Any user may be like a disabled user due

    to situational disability and laziness.

    People might enjoy a BCI in some settings

    just for fun.

    Emerging view

  • When a healthy person cannot use some natural means of communication and control in a certain situation.

  • Leeb et al (2007), Faller et al (2010, 2017), Aloise et al (2011) – virtual navigation

    Middendorf et al (2000), Trejo et al (2006), Menon al (2011) – pilots or astronauts

    Pineda et al (2003), Nijholt et al (2008, 2011,2016), Navarro et al (2011) – gamers

    Allison (2008, 2010, 2011), Millan et al (2010), Zander and Kothe (2011) – other examples

    Also cellphone users, mechanics, surgeons, soldiers, drivers aka Tesla seatwarmers

    And (sadly) disability by laziness: remote control or cellphone users

    Trejo et al (2006) Scherer et al (2008)

    Sit. Disability

  • Widespread BCI adoption requires

    dramatically new capabilities, such that gel-

    based wired “ugly” systems are appealing.

    Common view

  • Disruptive TechnologiesPractical electrodesWireless systems

    Emerging view

  • Cosmesis

  • PERCEIVED Cosmesis

  • Common view

    Schalk (2008)

    Moderately disabled

    Eager healthy

    Mainstream healthy

    Speed = critical for broader adoption

  • Emerging view

    Ease, design, utility = key for broader adoption

  • • Improved hardware (esp. wireless, dry electrodes)

    • Easy, available software (BCI2000 and others)

    • Easy, available systems and classes (Hack-a-thons, majors)

    • Improved math and signal processing

    • Improved knowledge of EEGs and cognitive correlates

    • Wearable computing ubiquity

    • Perceived cosmesis

    • Positive media coverage of AN and related systems

    Catalysts

    Catalysts of Broader Adoption

  • Why not use something else?• Faster than an unavailable interface

    – That requires impractical hardware

    – That cannot be easily used

    – That would take longer to provide the same information (if at all)

    • Easier to use than other interfaces– More portable, accessible, or convenient in real world settings

    – Induced disability is major, even from laziness (TV remote control)

    – More natural and intuitive

    – Less training?

    • The only interface capable of total privacy?

    • May seem novel or fun

  • How much useful additional information would remain in the output of the brain-, other body-organ- , or behavior-based workload gauges after regressing out variation directly measurable [from photodiodes, a software agent counting mouse clicks, and a microphone]?

    Commentary on DARPA AugCog report by Gevins and Smith, 2003.

    **Note: They referred to workload monitoring here.

    Why not use something else?

  • • “Enhance” = User experience in games

    • “Supplement” = Google Glass (this was 2015)

    • “Improve” = Upper Limb therapy after stroke

    • “Research tool” = Cognitive neuroscience research

    Case Scenarios

  • Image Triaging• Images shown to a user 10x per second

    – EEG can identify a minority of images that are of interest

    – Could reduce time for photo analysis work

    From Paul Sajda’s group

  • Neurofeedback• Has a “bad rep” due largely to unethical claims

    – Done properly, NF is good for (at least) relaxation and attention

    – Many, many companies offer NF.

    – How can people identify the best ones?

    From company websites

  • “Lie” detection• P300 and related signals can detect image familiarity

    – Does the accused have “guilty knowledge”?

    From Farwell and colleagues

  • NeuromarketingCan detect how focus groups react to sounds/images

  • Error detection• ERN = Error-related negativity

    – Real-time error correction requires good single-trial performance. Most systems are integrated with BCIs – not other interfaces

    – Non-real-time HCI, usability testing

    – Still a popular topic at the BCI Meeting 2018

    From Schalk et al. (2000)

  • Alertness monitoring• Based on only 2 EEG channels, 20 years ago

    – Red = missed targets; green = hit targets

    – Blue = actual error rate; red = predicted error rate

    From Scott Makeig and T-P Jung

  • Task adaptation

    From Alan Pope’s group

  • EEG-controlled World of Warcraft (g.tec)

    4 controls:

    Turn left, right, move forward, perform actions like grasping

    objects, attacking other objects

    60 Hz LCD display with 15, 12, 10 and 8.75 Hz.

    BCI overlay based on OpenGL –

    can be used with any graphics application

  • Game adaptation

    From Ewing et al. (2016)

  • Necomimi

  • Brainball

  • Star Wars Force Trainer

  • Cockroach racing

  • Towards “Big BCI”

    BCI Meeting

    2018

    Sponsors

  • Emerging “Big BCI”

    Galvani

    NeuralinkFacebook

  • Emerging “Big BCI”• Facebook

    – Announced a noninvasive 100 word-per-minute BCI.

    – They announced at our 2018 BCI Meeting that it will be in 10 years.

    – What’s new: BCI? Optical imaging? Natural language processing?

    • Neuralink– New effort popularized by Elon Musk

    – Focuses on invasive approaches, including patients

  • Good progress on BCI training and infrastructure, but we need more:

    • Classes, majors, degrees focused on BCI, neurotech

    • Many classes on BCIs; NCAN summer schools

    • Publicly available training videos, websites, exercises, lectures

    • Quite a lot available online

    • Open Access software for BCIs

    • BCI2000, OpenVibe, OpenEEG, BF++, others

    • Official conferences and societies

    • BCI Conferences, BCI Meetings, BCI Society!!!

    • Official journals and special issues

    • BCI Journal, Special Issues in Frontiers

    • Make BCIs fun and available

    • Museums, hackathons

  • Public activities for students and enthusiasts to make their own BCI applications!

  • Wolpaw et al., 2002

  • Thanks to Prof. De Sa, and to all of you for coming!

    For questions, including image credts, please email me: [email protected]