Workshops are a defining feature of the BCI Meeting Series. BCI Meeting workshops have a distinctive emphasis on interaction and contribution from all members. They help to shape the field of BCI research, producing consensus and collaborations.

There are 3 workshop sessions.  At the time of registration, you will have the option to select one workshop per session.  Please note that some workshops have a limited seating capacity, so please register early to ensure you can attend the workshop of your choice.


Session 1- Tuesday, June 9, 9:00am – 12:00pm

W1- Riemannian Geometry Methods for EEG preprocessing, analysis and classification

Marco Congedo, Gipsa-lab/CNRS, Univ. Grenoble Alpes
Sylvain Chevallier, UVSQ, Université de Versailles Saint-Quentin-en-Yvelines
Louis Korczowski, Independent Scientist
Florian Yger, Université Paris-Dauphine
Pierre Clisson, Independent Scientist

Riemannian Geometry (RG) is currently the object of growing interest within the BCI community. Machine learning methods based on RG have demonstrated robustness, accuracy and transfert learning capabilities for the classification of Motor Imagery, Event-Related Potential, Steady-State Visual Evoke Potentials, Sleep stages, as well as other mental states. This workshop will provide an overview of RG, emphasizing the characteristics that make RG compelling for BCI and its practical use for signal pre-processing, data analysis, mental state classification and regression. The workshop will be an opportunity for new users to solve real BCI problems (artifact removal, classification, transfert learning) with existing RG code resources and discuss the results.

Intended audience
BCI reasearchers/Neuroscientist working with EEG/MEG that are interested by Riemannian Geometry but haven’t used it already or who want a deeper understanding of the underlying properties (going beyong CSP)

Learning objectives
1. Understanding Riemannian Geometry, its history of application in BCI
2. Understanding the mathematical properties of Riemannian Geometry methods and the drawback
3. Being able to find a use a specific method/toolbox using RG for a given need (preprocessing/analysis/classification/regression)

W2- On the need of good practices and standards for Benchmarking Brain-Machine Interfaces

Ricardo Chavarriaga, IEEE Industry Connections group on neurotechnologies for brain-machine interface
Ander Ramos-Murguialday, University of Tübingen
José Contreras-Vidal, University of Houston
Paul Sajda, Columbia University
Zach McKinney, Scuola Sant’Anna
Carole Carey, IEEE EMB Standard Committee

Translating Brain-Machine Interfacing (BMI) systems outside research laboratories onto real applications requires reliable measurement of their performance. However, there are no accepted, well-defined criteria to assess their effectiveness, usability or safety. Few attempts of benchmarking have mainly focused on off-line comparison of decoding accuracy, neglecting the effects of closed loop interaction, as well as other elements of the BMI loop (e.g. shared-control or hybrid BMI systems). This workshop will work on the identification of specific challenges related to assessing performance of closed-loop BMI systems, and propose specific action points that can lead toward good practices and standards on benchmarking BMI systems. This workshop is supported by the IEEE EMB standards committee, the IEEE Brain Initiative, and the IEEE Standards Association working group on neurotechnologies (

Intended audience
The workshop is aimed at all individuals interested in the development and translation of neurotechnologies from research prototypes onto clinical and consumer applications. These include novice and experienced researchers, potential innovators and entrepreneurs, as well as representatives of the industry and regulatory bodies among others

Learning objectives
1. Participants will improve their knowledge about the current situation and practices regarding performance evaluation and standards relevant to neurotechnologies and brain-machine interfaces
2. Participants will acknowledge the importance agreed metrics and benchmarking have in the successful translation of research onto clinical and consumer applications
3. Participants will be able to identify current scenario and initiatives that can help the definition of common metrics and standards for BMI performance evaluation

W3- Brain-computer interfaces for the assessment of patients with disorders of consciousness

Christoph Guger, g.tec medical engineering
Damien Coyle, Ulster University
Kyousuke Kamada, Hokashin Group Megumino Hospital
Rossella Spataro, University of Palermo
Jing Jin, East China University
Donatella Mattia, FSL

Some patients diagnosed as vegetative are reclassified as (at least) minimally conscious when assessed by expert teams. A further subset of potentially communicative non-responsive patients might be undetectable through standard clinical testing. Other patients might have transient periods of relative wakefulness, but remain unaware of their surroundings. The workshop will provide an overview over groups that aim to use BCI technology to identify non-responsive patients or locked-in patients that might be able to communicate and use the technology as an assessment tool. In the workshop recent experiments, analysis methods and results with EEG, fNIRS and fMRI will be shown and discussed. The goal of the workshop is to identify the most important trends of the last years and to facilitate interaction between participants.

Intended audience
Neurologists and scientists working with DOC patients

Learning objectives
1. How can BCI technology be used to assess brain functions of DOC patients
2. How can BCI technology be used by DOC patients to answer questions
3. Which rehabilitation BCI techniques are used for DOC patients

W4- Adaptation in closed-loop BCIs

Tetiana Akenova, University Grenoble Alpes, CEA, LETI, CLINATEC
Andrey Eliseyev, Columbia University in the City of New York
Amy L. Orsborn, University of Washington
Martin Bogdan, Universität Leipzig
José del R. Millán, University of Texas at Austin
Jean Faber, Federal University of São Paulo

Significant drop in decoding performance is a crucial drawback of BCI decoders calibrated in the frame of the offline open-loop paradigm and then applied in the online closed-loop experiments. Adaptive algorithms allow substantial decreasing of this shortcoming by taking into account patient’s performance and adjusting the BCI parameters to new incoming data. In this way, adaptive decoders can enhance the quality of the BCI control, which is of great importance for the real-world BCI applications. This workshop will be devoted to the adaptive / incremental real-time BCI decoders and their applications. Design of adaptive BCI systems will be explained. Adaptive / incremental decoding algorithm and closed-loop calibration procedure will be addressed. Examples and evidence of efficiency of closed-loop adaptive BCI in clinical and preclinical studies, with various recording systems (EEG, ECoG, multi-unit activity) and different applications will be provided. The aspects of patient adaptation and patient/algorithm adaptation will be specially discussed. Workshop will include a round table/discussion, with invited person (possibly by conf. call) – a user of ECoG-based BCI, participant of clinical trial ‘BCI and tetraplegia’ at CLINATEC, Grenoble.

Intended audience
Engineers responsible for algorithm design; Persons responsible for BCI experiment design and patients training Computer; Scientists responsible for data processing

Learning objectives
1. Participants will learn the design of adaptive BCI session
2. Participants will learn the adaptive / incremental BCI decoding algorithms
3. Participants will discuss patient training using adaptive BCI

W5- Artificial intelligence in Brain-Computer Interfacing

Moritz Grosse-Wentrup, University of Vienna
Aldo Faisal, Imperial College London
Tonio Ball, University of Freiburg
Gernot Müller-Putz, TU Graz

The introduction of machine learning into the field of BCI, which began almost two decades ago, enabled unprecedented performance. Today, machine learning algorithms have become an indispensable component of a BCI. Machine learning, however, has undergone a radical transformation in the past two decades, resulting in artificial intelligence (AI) systems that surpass human performance in many real-world tasks. The motivation for this workshop is to evaluate and present the current state-of-the-art in AI to the BCI community, and then discuss how future BCI systems can benefit from AI technologies.

Intended audience
The workshop targets all BCI researchers interested in decoding methods, with a particular focus on young Ph.D. students in neuro-engineering, engineering, and computer science who are about to develop the next generation of decoding methods for BCI.

Learning objectives
1. Learn the current state-of-the-art in AI technologies, including deep neural networks, deep reinforcement learning, and toolboxes to implement and deploy AI systems.
2. Get to know the most successful network topologies in BCI decoding for widely used BCI paradigms (motor imagery & P300 speller systems).
3. Understand the challenges in translating AI technologies into novel BCI decoding methods, including computational complexity, scarcity of training data, and network topology design.

W6- The design of effective BCIs for children

Disha Gupta, New York University School of Medicine
James J. S. Norton, National Center for Adaptive Neurotechnologies
Kim Adams, University of Alberta
Tom Chau, University of Toronto
Sarah House, University of Toronto
Eli Kinney-Lang, University of Calgary
Adam Kirton, University of Calgary
Corinne Tuck, Glenrose Rehabilitation Hospital-I CAN Centre

BCIs have the potential to enhance, restore, or replace function in children with neurodevelopmental disorders, neurodegenerative disorders, and severe motor disabilities caused by stroke, spinal cord injury, or other acquired injuries. At present, however, very few studies have investigated the design of BCIs for children. Even within this limited literature, there are conflicts; for instance, it remains unclear whether children–especially those with neurological disabilities–can effectively use BCIs. In this workshop, we will explore the design of effective BCIs for children. Inspired by the experiences of researchers, we will first examine how BCIs can potentially improve children’s quality-of-life. We will then discuss some of the unique physiological, interfacing, and signal-processing challenges encountered during the design of BCIs for kids, and the strategies that can be used to mitigate these challenges. We will continue by considering the use of BCIs for children as augmentative and alternative communication devices and for rehabilitation in clinical settings. Finally, we will conclude with a data blitz–a fast-paced session that will provide participants with an overview of the exciting, ongoing work on the design of BCIs for children.

Intended audience
This workshop will be useful for student researchers, neuroscientists, clinicians, rehabilitation professionals, engineers, computer programmers, therapists, caregivers, biosignal acquisition equipment manufacturers, eye-tracker manufacturers, and video game developers/hobbyists who are working with, or would like to pursue, EEG- and BCI-based research and rehabilitation in children. Participants should be familiar with the basics of EEG and BCI, but the workshop will endeavor to be accessible to all conference attendees.

Learning objectives
1. Participants will learn about more than five populations of children who may benefit from BCIs and how each of these populations will benefit from these systems.
2. Participants will be able to describe at least three challenges encountered during the design of BCIs for children.
3. Participants will know at least three strategies for overcoming the challenges encountered during the design of BCIs for kids.

W7- Lessons from successfully implanted neurotechnology

Erik Aarnoutse, University Medical Center Utrecht
Aysegul Gunduz, University of Florida
Leigh R. Hochberg, Brown University
Guillaume Charvet, CEA-LETI/Clinatec Grenoble

Implantable neurotechnology has demonstrated successful applications. Users are able to move arms, walk, communicate again; disease symptoms are alleviated. This is despite the fact that setting up a clinical neurotechnology study is a tremendous effort, involving expertise in many fields. This workshop will bring insight in how successful research teams have brought implant neurotechnology into the lab and are able to change the lives of users. It is intended to bring new perspectives to the audience on clearly visible aspects and focus attention on sometimes overlooked aspects of clinical trials with implants. Two speakers will discuss their clinical studies, conducted with different technologies (ECoG, exoskeleton, micro electrode arrays, robotics) and in different continents (North America and Europe). The talks will be focused not only on technology and results, but also on know-how and lessons learned. After the coffee break a neurotechnology study is discussed as an example to bring a perspective on design of implantable smart closed-loop neurotechnology with user needs and risk management in mind. The fourth talk discusses the experience of bringing a fully implantable system for communication into the life of a user. This talk is structured as a tutorial. After the talks the speakers will share experiences and recommendations for future projects in a panel discussion, where the workshop participants will be able to ask questions and is invited to share experiences with clinical implant studies. This workshop is designed to bring together engineers, clinicians and neuroscientists. Experienced implant neurotechnology researchers may enjoy hearing and sharing experiences, aspiring researchers will gain insight in the many aspects needed to successfully conduct an implant neurotechnology clinical trial.

Intended audience
Neuroscientists, engineers, clinicians. Anyone who is conducting or plans to conduct an implantable neurotechnology project.

Learning objectives
1. Participants will be able to list 4 crucial expertises for a clinical neurotechnology study
2. Participants will be able to list 8 essential requirements for a clinical neurotechnology study
3. Participants will be able to list 4 lessons learned from successful clinical neurotechnology studies

W8- Next steps for practically useful BCI ethics

Brendan Z. Allison, UC San Diego
Pim Haselager, Donders Institute
Andrea Kübler, University of Wüersburg University
Donatella Mattia, Santa Lucia Foundation

Numerous meetings, conferences, workshops, publications, posters, talks, etc. have raised concerns about ethical issues involving BCIs. As BCIs become more prevalent – especially with the rapid growth in the size and number of companies seeking to profit from BCIs – these concerns have gained urgency. Hence, this workshop will address future directions of BCI ethics. Topics include:

1) How can we separate hype from hope? What can we reasonably expect of near-future or longer-term BCI applications?
2) What do BCI practitioners need regarding ethical recommendations? To what extent are recently published ethical papers and existing guidelines useful? When are more or differently formulated recommendations needed, or superfluous?
3) Are generally upheld ethical codes, regulations or certifications useful? Which partners, from both within the BCI community and outside (e.g. policy makers) should be involved, and how?

The workshop aims to collect suggestions toward a clear, readable set of recommendations to raise awareness of the issues involved and inspire discussions of potential further steps. We hope these guidelines will be adopted by the BCI Society to catalyze broader adoption. This workshop is meant to complement the ethical discussion and debate that Professor Wolpaw and colleagues plan for the Eighth International BCI Meeting.

Intended audience
This workshop does not require any specific skills or knowledge. This workshop should be of interest to anyone involved with BCIs and related fields, especially persons with strong interests or concerns regarding ethics, large-scale BCI commercialization, regulatory issues, and the future of BCIs. Examples include: Users; Patients and patient groups; Caregivers; Researchers; Scientific experts/organizations; Regulatory entities and other policy makers (governmental); Legal institutions; Nongovernmental organizations; Companies in neurotech; Companies using neurotech (e.g. neuromarketing); Insurance companies; Journalists; and the Public at Large.

Learning objectives
1. Different ethical issues in both invasive and noninvasive BCI research
2. How to best involve different players in academia, medicine, industry and the non-profit sector
3. Which near- and longer- term BCI applications may reasonably require ethical guidelines?

Session 2- Wednesday, June 10, 9:00am – 12:00pm

W9- Open-source Python tools for BCIs

Pierre Clisson, Mindify
Sylvain Chevallier, LISV, University of Versailles
Marco Congedo, GIPSA-lab, CNRS, University of Grenoble Alpes
Raphaëlle Bertrand-Lalo, Open Mind Neurotechnologies

The field of Brain-Computer Interfaces is currently experiencing a momentum, attracting both researchers and hackers. At the same time, more and more people rely on the thriving Python data science and machine learning ecosystem. Over the past few years, a number of tools have emerged, such as MNE for offline EEG analysis, MOABB for algorithm benchmarking, and PyRiemann for state-of-the-art biosignal classification. Yet, until recently, there was no fully open-source Python solution for actually building BCIs. Timeflux, a framework for the acquisition and real-time processing of signal streams, aims to fill this gap. During the first half of this workshop, participants will get an overview of the Python BCI landscape and will receive hands-on instructions on how to perform offline pre-processing and how to evaluate ERP classification methods. A clear explanation of the theory and practice of Riemannian geometry will also be given. The second half will focus on online BCIs: attendees will learn the core concepts driving Timeflux, how to describe processing pipelines, how to create interfaces available from a web browser, and how to easily develop their own plugins. They will also discover how MNE and Timeflux can be used together.

Intended audience
Anyone interested in practical BCIs: neuroscientists, research engineers, developers. A basic knowledge of the Python programming language is required.

Learning objectives
1. Participants will learn how to use two Python tools for offline analysis, one library for classification based on Riemannian geometry and one framework for online BCIs.
2. They will discover two ways of using MNE and Timeflux together.
3. At the end of the workshop, they will be able to implement two typical BCI pipelines from scratch: a P300 speller and a neurofeedback application.

W10- The treasure of BCI research “lost forever” How to convert existing into available knowledge

Andrea Kübler, University of Würzburg
Ricardo Chavarriaga, IEEE Standards Association
Camille Jeunet, Centre national de la recherche scientifique
Fabien Lotte, Université de Bordeaux
Donatella Mattia, Fondazione Santa Lucia
Fabrizio de Vico Fallani, Brain and Spine Institute (ICM)

In the past 30 years there has been an almost exponentially growing publication activity on brain-computer interfaces leading to a treasure of knowledge. While in the mid-90ies of the last century it was still possible to overview all published papers, this has become impossible by 2020. Even the number of papers in a circumscribed area of BCI, such as “visual P300”, is immense. This leads, for example, to unnecessary repetition of experiments while urgent questions may be left unanswered or may not even be asked. Even more dramatic, existing knowledge and insight may be lost. This workshop sets out to formulate a roadmap on how to preserve, merge, and consolidate knowledge and achievements in the BCI field and how to convert existing into available knowledge. From such a gathering of information, recommendations toward important questions and desirable achievements in BCI research and development may be derived and major conclusions about the current state-of-the-art of the field may be drawn. Further, we will discuss recommendations and means for systematically gathering and updating information.

Intended audience
All BCI researchers who are willing to discuss the issue of existing vs. available knowledge and who would potentially be willing to contribute to searching, gathering, and summarizing BCI knowledge.

Learning objectives
1. Getting ideas and structure on how such an endeavour of gathering and condensing knowledge could be realised with a joint effort and an overview of relevant topics to be included

W11- Towards the decoding of neural information for motor control: present and future approaches

Gernot  Müller-Putz, Graz University of Technology
Andreea Sburlea, Graz University of Technology
Valeria Mondini, Graz University of Technology
Tonio Ball, Universityclinics of Freiburg
Damien Coyle, Ulster University
Cuntai Guan, NTU Singapore

With this workshop we aim to address state-of-the-art approaches in neural control of movement and discuss future perspectives. First, we plan to give an overview on the clinical applications of BCI control. Next, we will discuss novel approaches for natural motor control. Further, we plan to present our findings in leveraging the low-frequency amplitude neural information for online control of a robotic arm, neuroprosthesis or exoskeleton. We will then highlight how higher-frequency oscillatory activity carries information about the trajectory of the movement also during movement imagination. Moreover, we will touch upon the relevance of reasons and goals when initiating a movement. Finally, we want to bring to the discussion the contribution of deep learning in motor decoding and its potential for reliable invasive and non-invasive control.

Intended audience
Researchers with an interest in motor control, with a background in neuroscience, neural engineering, biomedical engineering, and clinicians. Although research is quite in basic sciences, we invite people with an application background to discuss further directions and limitations.

Learning objectives
1. Participants will be informed about novel paradigms for closed-loop BCI control and clincal applications
2. Participants will learn about the invasive and non-invasive neural correlates of motor control
3. Participants will appraise the role of machine learning for motor decoding based on EEG and EcoG

W12- Optimising BCI performance by integrating information on the user's internal state

Sebastian Halder, University of Essex
Elia Valentini, University of Essex
Johan F. Storm, University of Oslo
Ana-Matran Fernandez, University of Essex
Angela Riccio, Fondazione Santa Lucia
Philipp Ziebell, University of Würzburg
Roberto Hornero, University of Valladolid
Eduardo Santamaría-Vázquez, University of Valladolid

Brain-computer interface (BCI) performance is known to be sensitive to the internal state of the user, e.g. consciousness, somatosensory state, attention and internal mental processes. For this reason, it is important to quantify the physical and mental state of the user while recording brain activity with the electroencephalogram (EEG). Such information may be beneficial not only to implement a BCI for communication, but also when using EEG technology with healthy users. In this workshop we will discuss the use of biomarkers extracted from the EEG to make inferences about internal states in combination with state-of-the-art active, reactive or passive BCIs. We will also discuss psychological perspectives following the User-Centered Design approach as well as novel machine learning techniques aiming at increasing the benefits of BCI technology for healthy as well as users with disabilities. Participants will learn details about the neurophysiological background of these signals, how improvements of user experience may be quantified and how detection of changes in the state of the user can be implemented technically.

Intended audience
Neuroscientists, engineers and clinicians are welcome. Participants should have an interest in designing, developing, deploying and evaluating a brain-computer interface in a real world scenario.

Learning objectives
1. Learn about biosignals for the detection of consciousness and the detection of pain.
2. Learn about three scenarios in which BCIs might offer an advantage to the user and be able to reason why these groups of users might benefit from BCIs
3. Learn how to thoroughly quantify user experience according to the User-Centered Design and it?s three BCI usability criteria effectiveness, efficiency and satisfaction. This will be illustrated in detail with examples from clinical environments.

W13- Brain-Computer Interfaces for human enhancement

Davide Valeriani, Massachusetts Eye and Ear, Harvard Medical School
Riccardo Poli, University of Essex
Maryam Shanechi, USC
Hasan Ayaz, Drexel University
Nataliya Kosmyna, MIT Media Lab
Yannick Roy, NeuroTechX
Marcello Ienca, ETH Zurich

BCIs have traditionally been used for restoring capabilities in people with disabilities. However, an emerging line of research has extended their scope from assistive devices to tools for augmenting human functions in healthy people. BCIs have been developed for improving decision-making in realistic scenarios, augment working memory and visual perception, control emotions while driving to enhance our attention, or to speedup task learning. This workshop will bring together neuroscientists, engineers, ethicists, and researchers working at the cutting-edge of development of BCIs for human augmentation to discuss current trends and future prospects. Several research areas are related to the workshop, including neuroergonomics, passive BCIs, collaborative BCIs, neuroethics, and hyperscanning.

Intended audience
This workshop is intended for BCI researchers, including neuroscientists, engineers, computer scientists, clinicians, and entrepreneurs, with a particular interest on developing BCIs for human augmentation. Attendees should be familiar with modalities to record brain signals (e.g., EEG, fNIRS) and/or stimulate the brain (e.g., tDCS).

Learning objectives
1. Participants will be able to differentiate between assistive BCIs and BCIs for human augmentation
2. Participants will be able to list three application domains for BCIs for human augmentation
3. Participants will be able to identify three novel areas where BCIs could be applied to enhance human performance

W14- Non-invasive BCIs for people with cerebral palsy

Jane Huggins, University of Michigan
Katya Hill, University of Pittsburgh
Petra Karlsson, Cerebral Palsy Alliance, University of Sydney
Reinhold Scherer, University of Essex

Many people with cerebral palsy have complex communication needs. Non-invasive BCIs offer an immediate opportunity for communication and control of technology, despite the remarkable possibilities that invasive BCIs may eventually offer for people with cerebral palsy. These complex communication issues include motor impairment, involuntary movements, lack of educational opportunities, lack of access to technology, difficulty understanding expectations, and difficulties with electrode setup and stability. Together, these issues pose unique demands on the BCI system that may not necessarily be present in other user populations. This workshop will present case studies and discuss challenges to BCI use for people with cerebral palsy, both those who have never established communication and access to augmentative and alternative (AAC) technologies as well as those who are losing access to AAC technologies as they age. The workshop will seek to pool the resources of multiple BCI and AAC labs with experience using non-invasive BCI for people with cerebral palsy and define challenges and potential solutions for BCI use for those with the most severe symptoms from cerebral palsy.

Intended audience
Clinicians, researchers, people with cerebral palsy and their support people who are interested in non-invasive BCIs for communication. This workshop has been developed from a combination of clinical experience and research using P300 and SSVEP, SMR signal sources with people with cerebral palsy.

Learning objectives
1. Describe three key factors important to evaluate when considering non-invasive brain-computer interface for people with cerebral palsy with and without a history of AAC use.
2. Identify three possible ideas for engaging attention or modelling BCI skills for people with cerebral palsy.
3. Identify challenges and possibilities using SSVEP, SMR and P300 signal sources for people with cerebral palsy.

W15- From speech decoding to speech neuroprostheses

Christian Herff, Maastricht University
Jon Brumberg, Kansas University
Phil Kennedy, Neural Signals Inc.
Miguel Angrick, University of Bremen
Sergey Stavisky, Stanford University
Julia Berezutskaya, Utrecht Medical Center
Qinwan Rabbani, Johns Hopkins University

Speech provides a natural and efficient means of communication, and its loss is devastating to patients. Directly tapping into the neural correlates of speaking is mostly unharnessed in current Brain-Computer Interfaces. Recent advances in the decoding and synthesis of speech from intracranial recordings have highlighted the exciting potential of speech as a paradigm for Brain-Computer Interfacing. However, to translate these decoding results into a viable, closed-loop speech neuroprosthesis for patients who are unable to speak, a number of challenges still need to be tackled. In this workshop, we will present recent progress in decoding speech using intracranially measured brain activity (iEEG and intracortical recording) and will openly discuss ongoing challenges. The workshop will begin with short presentations that will each touch on at least two of these challenges. The subsequent panel discussion among all presenting experts will focus on the following three open questions: 1. Which brain area(s) to target for recording speech- or language-related activity? 2. What representation(s) (articulatory, auditory, semantic, etc.) might we want to work with for implementing a BCI? 3. How do we do this for patients who cannot speak?

Intended audience
This workshop is intended for students, researchers and clinicians interested in Brain-Computer Interfaces based on speech. While all talks present results from intracranial electrodes, the workshop will also be of interest for researchers working with non-invasive measures, since results might be transferable to non-invasive measures and many open challenges are independent of the measurement modality.

Learning objectives
1. Participants will be able to discriminate between speech decoding and “thought-reading”.
2. Participants will be able to define four milestones towards clinical use of speech prostheses.
3. Participants will be able to identify multiple promising cortical areas for speech decoding.

W16- Brain-Computer Interfaces for art, entertainment, and domestic applications

Anton Nijholt, University of Twente, Netherlands
Erika Mondria, Art University, Linz, Austria
Tim Mullen, Intheon, San Diego, USA
Aleksander Valjamae, Tallinn University
Chang S. Nam, North Carolina State University, USA
Marvin Andujar, University of South Florida, Tampa, USA
Christoph Guger, g.tec medical engineering, Graz, Austria
Doron Friedman, Advanced Reality Lab, Herzliya, Israel
Stephanie Scott, Colorado State University, Fort Collins, USA

In this decade BCI technology has entered mainstream human-computer interaction (HCI) research for non-clinical applications. BCI has become part of multimodal interaction research as an additional interaction modality for a user of a technological system. BCI has also become part of research in which neurophysiological data provides a system with information about a user’s affective and mental state, making it possible to adapt system, task, and interaction to a particular user, online. Currently, there is a market for inexpensive EEG devices and software kits that capture voluntarily and involuntarily evoked brain activity and allow this activity to be translated into control and communication commands for environments and devices. Although EEG-based BCIs are limited in robustness and bandwidth, they are still, by far, the most accessible type of BCI to explore its potential use in domains such as games, entertainment, education, and art. HCI researchers’ interest in BCI is increasing because the technology industry is expanding into application areas where efficiency is not the main goal of concern. Domestic or public space use of information and communication technology raise awareness of the importance of affect, comfort, family, community, and playfulness, rather than efficiency. Therefore, in addition to non-clinical BCI applications that require efficiency and precision, this workshop also addresses the use of BCI for various types of domestic, entertainment, educational, health, and artistic applications. Topics that will be addressed: – BCI control of instruments and tools for domestic, entertainment, and artistic applications – Affective BCI in domestic, art and entertainment environments – BCI for Augmented and Virtual Reality, for Serious Games, and for rehabilitation; – Multi-brain and multimodal interaction in game and artistic environments; – BCI environments for self-reflection, empathizing, and therapy; – Agency in interactive BCI applications

Intended audience
This workshop is dedicated to BCI researchers, developers, artists, and users. It can also interest social neuroscientists, researchers in socio-affective computing, and game designers.

Learning objectives
1. Participants will be able to identify key benefits of engaging the arts and sciences to promote beneficial applications of BCI systems.
2. Participants will participate in, and gain insight from, discussions about how BCI and neurofeedback systems can extend a rehabilitative reach into different populations of users through less-explored integrative applications.
3. Participants will be able to differentiate passive and active BCI for domestic, entertainment, and artistic applications and become aware of their design problems.

Session 3- Thursday, June 11, 9:00am- 12:00pm

W17- Focal bi-directional Brain Computer Interfacing with concentric electrode technology

Chuck Anderson, Colorado State University
Walter Besio, University of Rhode Island and CREMedical
Barry Oken, Oregon Health & Science University
Myles McLaughlin, KU Leuven

Conventional non-invasive EEG electrodes limit the quality of recorded EEG and BCI applications. Recently developed concentric ring electrode sensing technologies may lead to breakthroughs that are necessary for practical BCI. Further, there are applications where once a feature has been sensed that focal electrical stimulation may be appropriate for altering brain states, or for applying a peripheral stimulus. This workshop will discuss the use, signal quality, bandwidth, spatial resolution, and applications of tripolar concentric ring electrode sensing technologies. Some of the applications include: imagined single finger movement classification and imagined movement robot arm control. We will also discuss applications for focal concentric ring electrode electrical stimulation such as: transcranial focal stimulation (TFS) for motor prosthesis, seizure control, and neurodegenerative diseases, as well as peripheral focal stimulation generating pain and sensation for feedback.

Intended audience
Persons interested in new EEG sensing technologies that provide high-fidelity, high-spatial resolution, high-signal-to-noise ratio, high-frequency EEG. Persons who are interested in bi-directional brain computer interfacing.

Learning objectives
1. Understand at least three of the four metrics in which concentric ring electrodes exceed the performance of conventional electrodes.
2. Be able to describe how multiple conventional electrodes and single concentric ring electrodes can be used to obtain increased spatial resolution.
3. Have an understanding of the possible applications of focused concentric ring electrode stimulation.

W18- Competitive BCI Activities

Brendan Z. Allison, UC San Diego
Gernot Müller-Putz, Graz Institute of Technology
Christoph Guger, g.tec medical engineering
Jing Jin, East China University of Science and Technology
Yannick Roy, NeurotechX
Aleksander Semyonov, Neuronet Industry Union

Over the past several years, competitive activities involving BCIs have been gaining attention. Examples include BCI Hackathons, the annual BCI Research Awards, Cybathlons and other online BCI competitions, BCI Trivia Nights, and different types of offline BCI competitions. Interestingly, offline BCI data analysis competitions seem to have become less prominent since the first such competition in 2002. BCI competitions can be very effective ways to engage new people in BCI R&D, teach students about BCIs, encourage new ideas, provide positive publicity for our field, and assess trends in BCI research. This workshop will discuss different BCI competitions and how we make them more prevalent and effective, including communication and collaboration among different groups that host them.

Intended audience
This workshop does not require any specific skills or knowledge. This workshop should be of interest to anyone involved with BCIs and related fields, especially persons interested in teaching and new directions in BCI research. Examples include: Users; Students; Professors and other teachers; Patients and patient groups; Researchers; Scientific experts/organisations; Policy makers (governmental); Nongovernmental organizations; Companies in neurotech; Companies using neurotech (e.g. neuromarketing); Journalists; and the Public at large.

Learning objectives
1. Types of competitive BCI activities
2. Different people and groups that organize and execute BCI competitions
3. How to better organize and execute different BCI competitions

W19- Biomimetic approaches to restore somatosensation

Robert Gaunt, University of Pittsburgh
Sliman Bensmaia, University of Chicago
Warren Grill, Duke University
Silvestro Micera, Scuola Superiore SantAnna, EPFL
Emily Graczyk, Case Western Reserve University
Luke Bashford, California Institute of Technology
Christopher Hughes, University of Pittsburgh

When people lose the ability to move and interact with the world because of a spinal cord injury or amputation, the rehabilitation focus is often on restoring movement. However, without somatosensory feedback from the hand, achieving natural and intuitive interactions will likely prove difficult. In recent years, there has been a surge of interest to address this issue and restore somatosensory feedback through electrical stimulation of the somatosensory cortex and peripheral nerves using invasive electrodes. While several labs have promising results, creating sensations that feel natural or that substantially improve function remains a challenge. To improve upon these simple stimulus trains, biomimetic stimulus trains could be used, in which stimulation is designed to mimic normal neural responses. However, there is currently no consensus on what biomimetic features should be used, how to map stimulus parameters to these biomimetic features, and whether there is evidence that biomimetic stimulation is useful. This workshop will bring together experts in somatosensory neuroscience and computational modeling, as well as human peripheral nerve and cortical stimulation to discuss the principles of biomimetic stimulation, how it may be useful, how to measure success, what the current limitations are, and how it can be improved moving forward.

Intended audience
This workshop is intended for anyone interested in learning about how to generate useful somatosensory percepts using neural interfaces, including engineers, scientists and clinicians. There will be a variety of speakers with backgrounds in neuroscience, neural engineering, clinical trials, and computational modeling. The talks will provide sufficient background for those less familiar with somatosensory neural interfaces to follow along.

Learning objectives
1. Participants will be able to define what the term ?biomimetic? means in the context of somatosensory neural interfaces
2. Participants will learn how basic neuroscience and computational approaches directly inform electrical stimulation parameter design
3. Participants will learn how biomimetic stimulation trains differ from standard stimulus trains and what the effects on sensation and function are

W20- Toward an international consensus on user characterization and BCI outcomes in settings of daily living

Nataliya Kosmyna, MIT Media Lab
Peter Desain, Radboud University
Theresa Vaughan, Wadsworth Center, New York State Department of Health
Andrew Geronimo, Penn State College of Medicine
Mariska J Vansteensel, UMC Utrecht
Melanie Fried-Oken, Oregon Health & Science University
Jane Huggins, University of Michigan

BCI research is growing at a fast pace, and implantable and non-invasive BCIs are being introduced to people with significant motor disability for independent use in daily living situations, allowing end-users to participate in R&D experiments and provide critical input into user-centered iterative design. While the number of studies that include target users continues to grow, most laboratories use disparate methodology and run studies in a limited number of participants. Descriptions of users are inconsistent, and we lack agreed on measures of device usefulness, speed and reliability. As a result, interpreting and replicating results is difficult, limiting collaborative scientific discussion and the identification of environmental and participant characteristics affecting BCI performance and user satisfaction. These factors all impede actual translation to practical use. This workshop is designed to gather clinical BCI researchers to discuss the assessment and reporting of these intrinsic and extrinsic characteristics as well as successes and challenges of BCI use for communication by people with severe disabilities. Presentations and discussions will explore practical means for curating and sharing precious results that would drive further research and facilitate consensus among clinical BCI researchers and are expected to lead to a common database with agreed-upon fields. These efforts should enhance clinical BCI adoption, and allow end-users to provide critical input to iterative user-centered design.

Intended audience
The proposed workshop is aimed at a multidisciplinary audience including, but not limited to, clinicians, engineers, and neuroscientists. A multidisciplinary team is crucial to help ensure a range of perspectives/experiences are considered in establishing a consensus of database content and data acquisition/user feedback methods.

Learning objectives
1. Participants will be able to identify environmental and participant characteristics that can affect communication-BCI performance in daily living situations.
2. Participants will be able to identify BCI performance and outcome measures (in addition to accuracy and speed) from the user?s and from a clinical/behavioral perspective that are important to take into account when implementing communication-BCIs in daily
3. Participants will be able to identify available tools to assess environmental and participant characteristics, as well as BCI performance and outcome measures.

W21- The promise of BCI-driven functional recovery after stroke: leveraging current evidence to define next steps

Aliceson Nicole Dusang, Brown University
Donatella Mattia, Fondazione Santa Lucia, IRCCS
Febo Cincotti, Sapienza University of Rome, Italy
George F. Wittenberg, VA Pittsburgh HS, Univ. of Pittsburgh
Christoph Guger, g.tec
Murat Akcakaya, University of Pittsburgh
Cuntai Guan, Nanyang Technological University (NTU), Singapore
José del R. Millán, The University of Texas at Austin
David Lin, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital
Vivek Prabhakaran, University of Wisconsin-Madison Radiology WIMR
Kyousake Kamada

BCIs have the potential to promote functional motor recovery after stroke but sufficient evidence regarding effectiveness to provide guidelines for clinicians is still lacking. Furthermore, there is still much to be understood about the mechanisms underlying stroke recovery and rehabilitation. Large, multicentric, randomized controlled trials (RCTs) are warranted to produce further evidence about administration, effectiveness and which stroke populations might most benefit from BCI interventions. Various studies with EEG-based BCIs have demonstrated functional improvements for stroke patients when compared to control groups using sham BCI or standard therapy. However, rehabilitative BCIs are still not widely available as a therapeutic option for stroke patients. This workshop will review current stroke rehabilitation programs from different research labs and will provide insight into technology (EEG, MEG, fMRI), experimental setups (VR, FES, BCI), results and outcomes of patient studies in the acute, sub-acute or chronic state. These will include approaches directed at motor, sensory, and cognitive recovery. The goal will be to collaboratively define the pathway to effectively design large, registered RCT to translate BCI based interventions.

Intended audience
Neuroscientists, engineers, clinicians, physiotherapists, patient representatives, policy makers, funding agencies, companies in BCI/neurotechnology, and insurance companies interested in rehabilitative brain-computer interfaces for stroke.

Learning objectives
1. Participants will learn about state-of-the art in BCI stroke rehabilitation to reduce a number of disabilities
2. Participants will be able to understand the target patient group populations (i.e. lesion locations and time post-stroke)
3. Participants will be able to articulate how non-invasive BCI technologies fit into stroke recovery, how to adequately engage and meet the needs of stakeholders, and what are overarching parameters and priorities for designing RCTs

W22- Invasive Brain Computer Interface technology: Open loop and closed loop decoding applications

Christoph Kapeller, g.tec medical engineering GmbH
Peter Brunner, National Center for Adaptive Neurotechnologies, Albany Medical College
Aysegul Gunduz, University of Florida
Kyousuke Kamada, Megumino Hospital

Invasive electroencephalographic (iEEG) signals, such as electrocorticography (ECoG) or stereo EEG, contain information with high spatial and temporal resolution, including very localized high-gamma activity. Hence, ECoG can be used for closed loop control of prosthetic limbs, avatars or cursors, but can also be used in open loop decoding to identify the eloquent cortex of a patient in preparation for resective brain surgeries. The concept of open loop electrical brain stimulation for neuromodulation has been widely used in clinical applications such as functional brain mapping. Closed loop stimulation based on iEEG signals opens a variety of clinical applications, including treatment of movement and neuropsychiatric disorders. The workshop will show state-of-the art experiments of open and closed loop decoding and neuromodulation, and describes how the data acquisition, device synchronization, signal processing and experimental setup is done based on practical examples with a guidance through important processing and design steps in MATLAB/Simulink.

Intended audience
People interested in invasive open and closed loop decoding applications; People interested in clinical studies with brain stimulation and high-gamma mapping; People interested in the practical realization of BCI experiments

Learning objectives
1. Participants will learn about state-of-the art in ECoG based mapping and neuromodulation through electrical stimulation
2. Participants will be able to understand the target patient group who benefits from invasive BCI technology
3. Participants will learn to establish iEEG based open or closed loop system applications in MATLAB/Simulink

W23- Brain-Computer Interfaces for outside the lab: Neuroergonomics for human-computer interaction, education and sport

Camille Jeunet, Université Toulouse Jean Jaurès
Fabien Lotte, Inria Bordeaux Sud-Ouest
Martijn Schreuder, ANT Neuro Bv
Frédéric Dehais, Institut des Sciences du Cerveau, de la Cognition et du Comportement de Toulouse
Antonia Thelen, ANT NeuroGmbH

General aim of this workshop is to present and discuss advances of the application of EEG based BCI to real-world situations. Specifically, we would like to discuss application possibilities outside of a laboratory and/or clinical setting. The here proposed panel comprises experts from different application fields, who conjointly want to promote BCI techniques to the greater public (i.e. outside of purely scientific and/or clinical settings). Generally, the efforts undertaken towards the instrumentalization of EEG and specifically BCI techniques within the field of neuroergonomics will be at the center of the proposed presentations and subsequent discussion/debates. Importantly, we will focus on advances made in the field and describe the challenges encountered. Subsequently, we aim at collectively debating and brainstorming about possible strategies to tackle them. Specifically, we will discuss Human-Computer Interaction in virtual environments, as well as the application of BCI techniques in Sport Sciences. The challenges arising when applying BCI to real-world and potentially mobile settings in such application fields will be discussed. Ultimately, we will explore how experimental setups, multi-modal signal integration and advances in hard- and software development can pave the way for future endeavors. The workshop is aimed at neuroscientists and developers interested in the application of EEG-based BCI in the field of neuroergonomics. We foresee a lively discussion, which will ultimately provide the starting points for an Opinion Paper-like publication.

Intended audience
Neuroscientists and Developers

Learning objectives
1. Neuroergonomics
2. Mobile EEG
3. Hardware challenges

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