Did I Do That? Brain–Computer Interfacing and the Sense of Agency

Neurotechnologies, Ethics, and the Limits of Free Will

This article delves into the implications of neurotechnologies for the philosophical debates surrounding free will and moral responsibility. Tracing the concept from ancient religious and philosophical roots, we discuss how recent neurotechnological advancements (e.g. optogenetics, fMRI and machine learning, predictive diagnostics, et al.) challenge traditional notions of autonomy. Although neurotechnologies aim to enhance autonomy in the strict sense - as self-determination - they risk reducing or changing the broader notion of autonomy, which involves personal authenticity. We also submit that, in a world with an altered or limited concept of free will, humans should still be held accountable for actions executed through their bodies. By examining the dynamic between choice and responsibility, we emphasize the shift in technology ethics, moral philosophy, and the broader legal landscape in response to the advancement of neurotechnologies. By bringing the neurotechnological innovations into the world, neuroscientists not only change the technological landscape but also partake in long-standing moral narratives about freedom, justice, and responsibility.

Intentional binding for noninvasive BCI control

Objective. Noninvasive brain-computer interfaces (BCIs) allow to interact with the external environment by naturally bypassing the musculoskeletal system. Making BCIs efficient and accurate is paramount to improve the reliability of real-life and clinical applications, from open-loop device control to closed-loop neurorehabilitation.Approach. By promoting sense of agency and embodiment, realistic setups including multimodal channels of communication, such as eye-gaze, and robotic prostheses aim to improve BCI performance. However, how the mental imagery command should be integrated in those hybrid systems so as to ensure the best interaction is still poorly understood. To address this question, we performed a hybrid EEG-based BCI training involving healthy volunteers enrolled in a reach-and-grasp action operated by a robotic arm.Main results. Showed that the hand grasping motor imagery timing significantly affects the BCI accuracy evolution as well as the spatiotemporal brain dynamics. Larger accuracy improvement was obtained when motor imagery is performed just after the robot reaching, as compared to before or during the movement. The proximity with the subsequent robot grasping favored intentional binding, led to stronger motor-related brain activity, and primed the ability of sensorimotor areas to integrate information from regions implicated in higher-order cognitive functions.Significance. Taken together, these findings provided fresh evidence about the effects of intentional binding on human behavior and cortical network dynamics that can be exploited to design a new generation of efficient brain-machine interfaces.

Good scientific practice in EEG and MEG research: Progress and perspectives

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

Strictly Human: Limitations of Autonomous Systems

Can autonomous systems replace humans in the performance of their activities? How does the answer to this question inform the design of autonomous systems?  The study of technical systems and their features should be preceded by the study of the activities in which they play roles. Each activity can be described by its overall goals, governing norms and the intermediate steps which are taken to achieve the goals and to follow the norms. This paper uses the activity realist approach to conceptualize autonomous systems in the context of human activities. By doing so, it first argues for epistemic and logical conditions that illustrate the limitations of autonomous systems in tasks which they can and cannot perform, and then, it discusses the ramifications of the limitations of system autonomy on the design of autonomous systems.

Sense of agency for mental actions: Insights from a belief-based action-effect paradigm

A substantial body of research has converged on the idea that the sense of agency arises from the integration of multiple sources of information. In this study, we investigated whether a measurable sense of agency can be detected for mental actions, without the contribution of motor components. We used a fake action-effect paradigm, where participants were led to think that a motor action or a particular thought could trigger a sound. Results showed that the sense of agency, when measured through explicit reports, was of comparable strength for motor and mental actions. The intentional binding effect, a phenomenon typically associated with the experience of agency, was also observed for both motor and mental actions. Taken together, our results provide novel insights into the specific role of intentional cues in instantiating a sense of agency, even in the absence of motor signals.

Recommendations for Responsible Development and Application of Neurotechnologies

Advancements in novel neurotechnologies, such as brain computer interfaces (BCI) and neuromodulatory devices such as deep brain stimulators (DBS), will have profound implications for society and human rights. While these technologies are improving the diagnosis and treatment of mental and neurological diseases, they can also alter individual agency and estrange those using neurotechnologies from their sense of self, challenging basic notions of what it means to be human. As an international coalition of interdisciplinary scholars and practitioners, we examine these challenges and make recommendations to mitigate negative consequences that could arise from the unregulated development or application of novel neurotechnologies. We explore potential ethical challenges in four key areas: identity and agency, privacy, bias, and enhancement. To address them, we propose (1) democratic and inclusive summits to establish globally-coordinated ethical and societal guidelines for neurotechnology development and application, (2) new measures, including “Neurorights,” for data privacy, security, and consent to empower neurotechnology users’ control over their data, (3) new methods of identifying and preventing bias, and (4) the adoption of public guidelines for safe and equitable distribution of neurotechnological devices.

Mapping the Dimensions of Agency

Neural devices have the capacity to enable users to regain abilities lost due to disease or injury - for instance, a deep brain stimulator (DBS) that allows a person with Parkinson's disease to regain the ability to fluently perform movements or a Brain Computer Interface (BCI) that enables a person with spinal cord injury to control a robotic arm. While users recognize and appreciate the technologies' capacity to maintain or restore their capabilities, the neuroethics literature is replete with examples of concerns expressed about agentive capacities: A perceived lack of control over the movement of a robotic arm might result in an altered sense of feeling responsible for that movement. Clinicians or researchers being able to record and access detailed information of a person's brain might raise privacy concerns. A disconnect between previous, current, and future understandings of the self might result in a sense of alienation. The ability to receive and interpret sensory feedback might change whether someone trusts the implanted device or themselves. Inquiries into the nature of these concerns and how to mitigate them has produced scholarship that often emphasizes one issue - responsibility, privacy, authenticity, or trust - selectively. However, we believe that examining these ethical dimensions separately fails to capture a key aspect of the experience of living with a neural device. In exploring their interrelations, we argue that their mutual significance for neuroethical research can be adequately captured if they are described under a unified heading of agency. On these grounds, we propose an "Agency Map" which brings together the diverse neuroethical dimensions and their interrelations into a comprehensive framework. With this, we offer a theoretically-grounded approach to understanding how these various dimensions are interwoven in an individual's experience of agency.

How using brain-machine interfaces influences the human sense of agency

Brain-machine interfaces (BMI) allows individuals to control an external device by controlling their own brain activity, without requiring bodily or muscle movements. Performing voluntary movements is associated with the experience of agency ("sense of agency") over those movements and their outcomes. When people voluntarily control a BMI, they should likewise experience a sense of agency. However, using a BMI to act presents several differences compared to normal movements. In particular, BMIs lack sensorimotor feedback, afford lower controllability and are associated with increased cognitive fatigue. Here, we explored how these different factors influence the sense of agency across two studies in which participants learned to control a robotic hand through motor imagery decoded online through electroencephalography. We observed that the lack of sensorimotor information when using a BMI did not appear to influence the sense of agency. We further observed that experiencing lower control over the BMI reduced the sense of agency. Finally, we observed that the better participants controlled the BMI, the greater was the appropriation of the robotic hand, as measured by body-ownership and agency scores. Results are discussed based on existing theories on the sense of agency in light of the importance of BMI technology for patients using prosthetic limbs.

Brain-Machine Interfaces as Commodities: Exchanging Mind for Matter

Brain-machine interfaces (BMIs), which enable a two-way flow of signals, information, and directions between human neurons and computerized machines, offer spectacular opportunities for therapeutic and consumer applications, but they also present unique dangers to the safety, privacy, psychological health, and spiritual well-being of their users. The sale of these devices as commodities for profit exacerbates such issues and may subject the user to an unequal exchange with corporations. Catholic healthcare professionals and bioethicists should be especially concerned about the implications for the essential dignity of the persons using the new BMIs.

Summary

The commercial sale of brain-machine interfaces (BMIs) generates and exacerbates problems for end-users' safety, psychological health, and spiritual well-being.

Ethics and the emergence of brain-computer interface medicine

Brain-computer interface (BCI) technology will usher in profound changes to the practice of medicine. BCI devices, broadly defined as those capable of reading brain activity and translating this into operation of a device, will offer patients and clinicians new ways to address impairments of communication, movement, sensation, and mental health. These new capabilities will bring new responsibilities and raise a diverse set of ethical challenges. One way to understand and begin to address these challenges is to view them in terms of the goals of medicine. In this chapter, different ways in which BCI technology may subserve the goals of medicine is explored. This is followed by articulation of additional goals particularly relevant to BCI technology: neural diversity, neural privacy, agency, and authenticity. The goals of medicine provide a useful ethical framework for the introduction of BCI devices into medicine.

Brain–Computer Interfaces: Lessons to Be Learned from the Ethics of Algorithms

Brain–computer interfaces (BCIs) are driven essentially by algorithms; however, the ethical role of such algorithms has so far been neglected in the ethical assessment of BCIs. The goal of this article is therefore twofold: First, it aims to offer insights into whether (and how) the problems related to the ethics of BCIs (e.g., responsibility) can be better grasped with the help of already existing work on the ethics of algorithms. As a second goal, the article explores what kinds of solutions are available in that body of scholarship, and how these solutions relate to some of the ethical questions around BCIs. In short, the article asks what lessons can be learned about the ethics of BCIs from looking at the ethics of algorithms. To achieve these goals, the article proceeds as follows. First, a brief introduction into the algorithmic background of BCIs is given. Second, the debate about epistemic concerns and the ethics of algorithms is sketched. Finally, this debate is transferred to the ethics of BCIs.

On the Necessity of Ethical Guidelines for Novel Neurotechnologies

Because novel neurotechnologies may alter human identity and society in profound ways, we advocate for the early integration of ethics into neurotechnology. We recommend developing and adopting a set of guidelines, like the Belmont Report on human subject research, as a framework for development and use of brain-related technologies.

Informed Consent in Implantable BCI Research: Identifying Risks and Exploring Meaning

Implantable brain-computer interface (BCI) technology is an expanding area of engineering research now moving into clinical application. Ensuring meaningful informed consent in implantable BCI research is an ethical imperative. The emerging and rapidly evolving nature of implantable BCI research makes identification of risks, a critical component of informed consent, a challenge. In this paper, 6 core risk domains relevant to implantable BCI research are identified-short and long term safety, cognitive and communicative impairment, inappropriate expectations, involuntariness, affective impairment, and privacy and security. Work in deep brain stimulation provides a useful starting point for understanding this core set of risks in implantable BCI. Three further risk domains-risks pertaining to identity, agency, and stigma-are identified. These risks are not typically part of formalized consent processes. It is important as informed consent practices are further developed for implantable BCI research that attention be paid not just to disclosing core research risks but exploring the meaning of BCI research with potential participants.

Advances in user-training for mental-imagery-based BCI control: Psychological and cognitive factors and their neural correlates

While being very promising for a wide range of applications, mental-imagery-based brain-computer interfaces (MI-BCIs) remain barely used outside laboratories, notably due to the difficulties users encounter when attempting to control them. Indeed, 10-30% of users are unable to control MI-BCIs (so-called BCI illiteracy) while only a small proportion reach acceptable control abilities. This huge interuser variability has led the community to investigate potential predictors of performance related to users' personality and cognitive profile. Based on a literature review, we propose a classification of these MI-BCI performance predictors into three categories representing high-level cognitive concepts: (1) users' relationship with the technology (including the notions of computer anxiety and sense of agency), (2) attention, and (3) spatial abilities. We detail these concepts and their neural correlates in order to better understand their relationship with MI-BCI user-training. Consequently, we propose, by way of future prospects, some guidelines to improve MI-BCI user-training.

New frontiers in the rubber hand experiment: when a robotic hand becomes one's own

The rubber hand illusion is an experimental paradigm in which participants consider a fake hand to be part of their body. This paradigm has been used in many domains of psychology (i.e., research on pain, body ownership, agency) and is of clinical importance. The classic rubber hand paradigm nevertheless suffers from limitations, such as the absence of active motion or the reliance on approximate measurements, which makes strict experimental conditions difficult to obtain. Here, we report on the development of a novel technology-a robotic, user- and computer-controllable hand-that addresses many of the limitations associated with the classic rubber hand paradigm. Because participants can actively control the robotic hand, the device affords higher realism and authenticity. Our robotic hand has a comparatively low cost and opens up novel and innovative methods. In order to validate the robotic hand, we have carried out three experiments. The first two studies were based on previous research using the rubber hand, while the third was specific to the robotic hand. We measured both sense of agency and ownership. Overall, results show that participants experienced a "robotic hand illusion" in the baseline conditions. Furthermore, we also replicated previous results about agency and ownership.

Brain-computer interfaces and disability: extending embodiment, reducing stigma?

Brain-Computer Interfaces (BCIs) now enable an individual without limb function to "move" a detached mechanical arm to perform simple actions, such as feeding herself. This technology may eventually offer almost everyone a way to move objects at a distance, by exercising cognitive control of a mechanical device. At that point, BCIs may be seen less as an assistive technology for disabled people, and more as a tool, like the internet, which can benefit all users. We will argue that BCIs will have a significant but uncertain impact on attitudes toward disabilities and on norms of bodily form and function. It may be liberating, oppressive, or both. Its impact, we argue, will depend - though not in any simple way - on whether BCIs come to be seen as parts of the body itself or as external tools.

What limits the performance of current invasive brain machine interfaces?

The concept of a brain-machine interface (BMI) or a computer-brain interface is simple: BMI creates a communication pathway for a direct control by brain of an external device. In reality BMIs are very complex devices and only recently the increase in computing power of microprocessors enabled a boom in BMI research that continues almost unabated to this date, the high point being the insertion of electrode arrays into the brains of 5 human patients in a clinical trial run by Cyberkinetics with few other clinical tests still in progress. Meanwhile several EEG-based BMI devices (non-invasive BMIs) were launched commercially. Modern electronics and dry electrode technology made possible to drive the cost of some of these devices below few hundred dollars. However, the initial excitement of the direct control by brain waves of a computer or other equipment is dampened by large efforts required for learning, high error rates and slow response speed. All these problems are directly related to low information transfer rates typical for such EEG-based BMIs. In invasive BMIs employing multiple electrodes inserted into the brain one may expect much higher information transfer rates than in EEG-based BMIs because, in theory, each electrode provides an independent information channel. However, although invasive BMIs require more expensive equipment and have ethical problems related to the need to insert electrodes in the live brain, such financial and ethical costs are often not offset by a dramatic improvement in the information transfer rate. Thus the main topic of this review is why in invasive BMIs an apparently much larger information content obtained with multiple extracellular electrodes does not translate into much higher rates of information transfer? This paper explores possible answers to this question by concluding that more research on what movement parameters are encoded by neurons in motor cortex is needed before we can enjoy the next generation BMIs.