The 3rd Neuroadaptive Technology Conference, NAT’22, will be held in Lübbenau, near Berlin, 9th – 12th of October, 2022.
NAT’22 will take place in Lübbenau, near Berlin, Germany.
The venue for the meeting is Schloss Lübbenau, a fully-preserved castle ensemble in the midst of the unique UNESCO Biosphere Reserve of the Spreewald.
Using public transport, this location is approximately 1,5 hours from Berlin Brandenburg Airport.
The castle will both provide the conference rooms and serve as conference hotel. Rooms at the castle have been reserved for conference participants. The booking of the individual rooms can be made independently via the booking portal of the castle.
You can plan your trip and book your ticket via the website of the Deutsche Bahn. The stop closest to the hotel is Schlossbezirk, Lübbenau (Spreewald).
When arriving by plane, the itinerary will look something like this:
- Take Train FEX, direction Berlin
- Change in Berlin Ostkreuz to train RE 2, direction Cottbus, or RB 24, direction Senftenberg
- Change in Lübbenau (Spreewald) to Bus 661, direction Busbahnhof, to get off at Schlossbezirk
The first leg may differ, as there are different options to connect to train RE 2 and RB 24. The last leg can be replaced by a 1.6 km walk, but including the bus stop in your ticket will not change the price.
Room descriptions can be accessed via the link at the room name, please use the booking tool above to book a room for the conference.
||Category||Total per night||Description|
(only 1 left)
|1||Standard||120€||Nice room in side building, Safe provided|
|Schlosszimmer superior||1||Comfort||150€||Comfortable room in main building, couch|
|1||Comfort||150€||Comfortable room in side building, couch, bathtub|
(only 1 left)
|1||Comfort||170€||Comfortable suite in main building, couch, bedroom|
|2||Comfort||200€||Comfortable suite in main building, couch, bedroom|
|2||Comfort||200€||Comfortable suite in side building, couch, bedroom, Safe provided|
Shared student appartment starting at 75,00 EUR per person (max. 2 people per room). To book the student option, please fill in this form instead of using the above portal.
The currently scheduled programme of the NAT’22 conference is listed below.
Sunday, October 9th
(All day: Arrival)
20:00 Hotel Garden Reception
Monday, October 10th
08:00 Registration & Welcome
09:00 Keynote: Fabien Lotte
09:40 Session: BCI & Applications I
11:00 Coffee break
11:20 Session: BCI & Applications II
14:00 Keynote: Marcello Ienca
14:40 Session: Ethics & Perspectives I
16:00 Coffee break
16:20 Session: Ethics & Perspectives II
18:00 Keynote: Caterina Cinel
20:00 Conference Dinner
Tuesday, October 11th
08:00 Registration & Coffee
09:00 Keynote: Mortiz Grosse-Wentrup
09:40 Session: AI & Machine Learning I
11:00 Session: Posters
12:20 Session: AI & Machine Learning II
15:00 Panel: Business
15:40 Keynote: Simon Vogt
16:20 Coffee break
16:40 Keynote: Matthew Richins
17:20 Panel: Cybersecurity
18:00 Goodbye Session
19:00 Open Discussions
Wednesday, October 12th
First Meeting BCI Network Germany
Sponsors: Cyberagentur, Brandenburg University of Technology
9:00 Overview BCI research landscape
in France, UK and Germany
– open for academics –
13:00 Workshop BCI Network
– closed network –
Call for Papers
We cordially invite you to submit contributions of research in the area of neuroadaptive technology, including artificial intelligence, fundamentals, and applied work. The call for papers (see below; also available as PDF) has a detailed list of relevant topics.
NAT’22 welcomes novel research results and ideas, but also explicitly invites already-published work to provide an overview of relevant research in the different domains to a new audience.
All accepted contributions will be published in the conference proceedings.
Please feel free to share the call for papers to your academic and industrial network.
Neuroadaptive technology (NAT) utilizes real-time measures of neurophysiological activity within a closed control loop to create intelligent software adaptation. Measures of electrocortical and neurovascular brain activity are quantified to provide a dynamic representation of the psychological state of the user, with respect to cognitions, emotions and motivation. As such, NAT can access unique aspects of human information processing, and human intelligence, which can subsequently be used to enable more versatile and more human-like forms of machine intelligence.
Current trends in different scientific fields indicate an increased interest in integrating context-sensitive information from the human brain into Artificial Intelligence. NAT’22 is intended to bring scientists interested in Physiological Computing, Applied Neurosciences and Passive Brain-Computer Interfaces together with experts from the fields of Artificial Intelligence, Machine Learning and Intelligent Systems. The main goals of the conference are an exchange of research questions and findings from both fields and the identification of common goals and joint ventures in the domain of Neuroadaptive Technology, including: real-time signal processing, unsupervised vs. supervised ML, designing neuroadaptive interaction, explainable AI (XAI), neuroadaptive applications, hybrid AI systems (DL + symbolic AI) for applied neurosciences, ethics of neurotechnology in real world (responsibility for action, security), cloud-based solutions for data management and more.
We are pleased to announce that the Third Neuroadaptive Technology Conference (NAT’22) will be held in Lübbenau, near Berlin, Germany, from October 9th to 11th, 2022. The venue for NAT’22 is the Lübbenau Castle, a fully-preserved castle ensemble in the middle of the UNESCO Biosphere Reserve of the Spree Forest, approximately an hour drive from Berlin-Brandenburg Airport.
In addition to scientists from different areas of research, representatives from companies are invited to attend NAT’22 and add their perspective from a market viewpoint. Furthermore, NAT’22 invites representatives of national governments to discuss the legal and societal impacts of NAT and how we can prepare our work and our societies accordingly.
Participants of NAT’22 are invited to submit a short abstract describing their research results and/or perspectives on the combination of NAT and Artificial Intelligence and will have the opportunity to present this work at the conference. NAT’22 welcomes novel research results and ideas, but also explicitly invites work that has been already published to provide an overview of relevant research in the different domains. This is intended to support the main idea of the conference to bring scientists from different fields together and inspire cooperative work. Furthermore, Participants of NAT’22 will have the opportunity to jointly work on publications describing the main outcomes of the conference, including concepts of roadmaps, theoretical concepts and ethical/societal considerations.
Registration fees. All inclusive (conference, lunch included) + 50,- for the social evening
Early Bird Standard (before 9th of Augst 2022, CEST)
Early Bird Industry / Exhibitors (before 9th of August 2022, CEST)
Industry / Exhibitors
Thorsten O. Zander, Brandenburg University of Technology, Germany
Stephen H. Fairclough, Liverpool John Moores University, UK
Contact Information email@example.com
Use this form to submit your contributions to the NAT’22 conference. Please use the provided template in a compatible format.
Please use the attached Word template to structure and style your submission.
The maximum length of the submission is 2 pages, including at most 1 figure. References do not count towards the maximum page length. Please also include at least 2 keywords. Further details are given or described in the template document itself;.
To ensure a blind review, please do not include your names and affiliations in the template. Instead, you will be asked to provide them during the submission process. Also try to not provide other obvious clues to your own identities, e.g. by referring to own past work: “We (Zander et al., 2022) showed that…”
When your submission is finished, please use the submission page on this website to submit it for consideration.
Prof. Dr. Fabien Lotte
Inria Bordeaux (National Institute for Research in Digital Science and Technology), Research Director, Potioc project team (Novel Multimodal Interactions for a stimulating User Experience).
Artificial Intelligence for passive BCI design: the good, the bad and the maybe
Passive Brain-Computer Interfaces (pBCIs) hold great promises for Human-Computer Interaction (HCI), notably to monitor users’ sensory, cognitive, affective or conative states during interaction, and adapt this interaction accordingly. Artifical Intelligence (AI) methods, notably machine learning classifiers, have always played a key role in pBCI designs. This role is currently increasing even further by now encompasing methods not only to classify brain signals but also to model the users’ behaviour, intentions and needs as well as to design intelligent adaptations, based on such models. While numerous publications on AI methods for (p)BCIs are released every month, such publication landscape may sometimes appear like the “far west”, with a lack of research rules and standards, and an apparent difficulty in identifying solid works from the rest. Therefore, in this talk, I will discuss on the pros and promises of various recent AI algorithms for pBCI designs (the good), but also on the flaws and common pitfalls of AI use for (p)BCIs (the bad), as well as related perspectives for the future of the pBCI field (the maybe). More precisely, I will first start by the bright side (the good), by presenting recent and promising advances in Riemannian geometry and deep learning classifiers for mental state monitoring, and discuss of their respective merits when compared with each other. I will then move to more concerning issues (the bad), by identifying various pitfalls in AI studies for (p)BCIs, including lack of reproducibility, biaised evaluations and comparisons, ignorance of common confounding factors or lack of usability in practice, among others. Finally, I will end on a more optimistic note, by presenting some perspectives on AI for pBCIs (the maybe). I will notably cover future promising applications of AI for pBCIs, such as pBCI-based personalized and adaptive medical rehabilitation or artistic experience, as well as open challenges such as the need for models of variability in (p)BCIs and for considering pBCI users in all stages of their design, including in AI algorithms.
Fabien Lotte obtained a M.Sc., a M.Eng. (2005), and a PhD (2008) from INSA Rennes, and a Habilitation (HDR, 2016) from Univ. Bordeaux, all in computer science. His research focuses on the design, study and application of Brain-Computer Interfaces (BCI). In 2009 and 2010, Fabien Lotte was a research fellow at the Institute for Infocomm Research in Singapore. From 2011 to 2019, he was a Research Scientist at Inria Bordeaux Sud-Ouest, France. Between October 2016 and January 2018, he was a visiting scientist at the RIKEN Brain Science Institute, Japan, and then in 2019 a visiting associate professor at the Tokyo University of Agriculture and Technologies (TUAT), still in Japan. Since October 2019, he is a Research Director (DR2) at Inria Bordeaux Sud-Ouest. He is on the editorial boards of the journals Brain-Computer Interfaces (since 2016), Journal of Neural Engineering (since 2016) and IEEE Transactions on Biomedical Engineering (since 2021). He is also “co-specialty chief editor” of the section “Neurotechnologies and System Neuroergonomics” of the journal “Frontiers in Neuroergonomics”. He co-edited the books ”Brain-Computer Interfaces 1: foundations and methods” and ”Brain-Computer Interfaces 2: technology and applications” (2016) and the ”Brain-Computer Interfaces Handbook: Technological and Theoretical Advance” (2018). In 2016, he was the recipient of an ERC Starting Grant to develop his research on BCI.
Prof. Dr. Moritz Grosse-Wentrup
Universität Wien, Head of Research Group Neuroinformatics, Deputy Head of Research Group Security and Privacy, Member of Research Network Data Science
Brain-Artificial Intelligence Interfaces (BAIs)
Brain-Computer Interfaces (BCIs) provide alternative communication channels to users with impaired peripheral nervous systems. They are of limited utility, however, if users lack the cognitive abilities to operate a BCI. For instance, a BCI that decodes intended movements of vocal tract muscles to synthesize speech would be of limited use to a stroke patient with Broca’s aphasia. To overcome this limitation and expand the group of people that could benefit from neural interfaces, I introduce a new class of systems, which I term Brain-Artificial Intelligence (BAI) interfaces. BAIs aim to connect the brain with an AI system that replaces a lost cognitive function. Speech BAIs, for instance, would decode high-level cognitive states that enable a conversational AI to generate sentences congruent with their users’ communication intents. I review recent advances in AI that render BAIs feasible, discuss how to adapt our decoding pipelines from BCIs to BAIs, and outline the challenges that we need to address to turn BAIs from a vision into a reality.
Moritz Grosse-Wentrup is full professor and head of the Research Group Neuroinformatics at the University of Vienna, Austria. He develops machine learning algorithms that provide insights into how large-scale neural activity gives rise to (disorders of) cognition, and applies these algorithms in the domain of cognitive neural engineering, e.g., to build brain-computer interfaces for communication with severely paralyzed patients, design closed-loop neural interfaces for stroke rehabilitation, and develop personalized brain stimulation paradigms. He has received numerous awards for his work, including the 2011 Annual Brain-Computer Interface Research Award, the 2014 Teaching Award of the Graduate School of Neural Information Processing at the University of Tübingen, and the 2016 IEEE Brain Initiative Best Paper Award.
Dr. Caterina Cinel
Essex Brain-Computer Interfaces and Neural Engineering (BCI-NE) Lab, University of Essex, United Kingdom
Brain-Computer Interfaces for Group Decision-making
Making decisions—either individually or in group—is an important aspect at all levels of everyday life. Decisions (for example made by government, military or hospital management) can be highly critical in nature, with mistakes possibly resulting in extremely adverse outcomes, including loss of lives. Often, decisions must be made with limited amounts of information, or indeed too much information for any single person to process in a meaningful manner, hence involving a high degree of uncertainty. In such difficult conditions, groups usually make better decisions than individuals, who tend to make suboptimal decisions. Groups have inherent error correction capabilities, but, unfortunately, they also suffer from many biases and flaws, such as difficulties in coordination and interaction between group members, reduced member effort within a group, strong leadership, group judgement biases, and so on.
Brain-Computer Interfaces (BCIs) have traditionally been used as assistive devices for restoring capabilities in people with disabilities. However, an important and exciting line of research has turned them into tools for augmenting cognitive functions in healthy people.
For nearly a decade, this has been a major strand of research within the Essex BCI-NE lab, where we pioneered the idea of combining brain signals (and other physiological and behavioural data) across multiple people to achieve a form of emergent group augmentation particularly for decision-making.
Over this period, with significant support from the UK Ministry of Defence, we have developed a collaborative BCI (cBCI) technology that has delivered significant improvements over the group performance achieved by more traditional methods of integrating individual decisions, for progressively more and more realistic environments.
In this presentation, I will give an overview of the work done in our lab with cBCIs, from their precursors to the range of techniques and results obtained in nearly a decade, in decision tasks, including: identification of visual targets in cluttered environments, comprehension of military radio communication, face recognition, military simulations of outposts and strategic decision making in a pandemic. I will touch upon our recent results with decision making systems where BCI-assisted humans make decisions together with AI agents treated as peers.
Dr. Marcello Ienca
École Polytechnique Fédérale de Lausanne (EPFL), Principal Investigator at College of Humanities, Leader Intelligent Systems Ethics research unit (ERA-NET funded)
The ethics and philosophy of Neurotechnologies
In recent years, the debate on the ethical implications of advances in neuroscience and neurotechnology has resonated widely not only in academia but also at the political level of governmental and intergovernmental organizations. Various governance proposals have been made in order to ensure the responsible development of neurotechnologies, promote fair access to them and prevent their misuse. Among these approaches, the most foundational one is that of the so-called ‘neurorights’, i.e. the fundamental human rights linked to the sphere of the human brain and mind. From the perspective of neurorights, the human brain and the cognitive and affective processes it enables, represents a domain of fundamental ethical-normative salience. Therefore, it must be protected through regulatory reforms concerning either the evolutionary reinterpretation of existing rights or the introduction of new rights. Among the rights that have been proposed are the right to cognitive liberty, mental privacy, mental integrity and psychological continuity. The neurorights approach serves to identify certain unauthorized forms of intrusion into a person’s brain function (especially if they result in damage to the cognitive, affective or behavioral sphere) and banish or limit them as violations of the aforementioned rights. International organizations such as the UN, UNESCO, the Council of Europe, the OECD as well as national parliaments such as that of Chile are working on the advancement of neurorights through various forms of regulatory instruments. This presentation will provide an overview of the ethics and policy challenges of neurotechnologies from a neurorights perspective, inform the audience about ongoing regulatory efforts by governmental and intergovernmental agencies, and propose a novel interdisciplinary approach to the assessment of ethical considerations in neuroscience called “experimental neuroethics”.
Dr. Simon Vogt
Agentur für Innovation in der Cybersicherheit (Cyberagentur), Vice President Strategy/Secure Society
The Unhackable Brain – Why Brain Computer Interfaces will become a Matter of Cybersecurity
Brain-Computer Interfaces (BCI) are undergoing a rapidly accelerating pace of research and development. Today, emerging applications and use-cases outside of controlled laboratories are still at an early technological stage. Nevertheless, it is clear to see that the future applications of BCI span new domains, especially in the context of consumer products for interaction with robots, autonomous vehicles, computer games or metaverse/Web 3 scenarios. In parallel to those new communication channels between machines on the one side and the human brain on the other side, privacy and security concerns must be taken into account as early as possible.
The Cyberagentur as a federal German organization has the mission to find and foster breakthrough research in technology fields that are relevant to the security of every citizen, company, authority or the infrastructure with a scope of 10-15 years into the future. For us, BCI are a focal topic of interest. We aim to escort and guide technology development in this domain based on a privacy and security by design approach and have thus commissioned the development of a “Framework for Preserving Privacy and Cybersecurity in Brain-Computer Interfacing Applications” that has just been finished and will be presented during this conference.
For us, the human brain represents the highest resort for privacy and security of information – and we aim to make sure that this will never change.
Dr. Matthew Richins
Defence Science & Technology Laboratory (DSTL), UK
Topic: Neuro-tech in Defence and Security