Brain machine interface (BMI) technology makes direct communication between the brain and a machine possible by means of electrodes. This paper reviews the existing and emerging technologies in this field and offers a systematic inquiry into the relevant ethical problems that are likely to emerge in the following decades.

This comment responds to Kevin Warwick’s article on predictability and responsibility with respect to brain-machine interfaces in action. It compares conventional responsibility for device use with the potential consequences of phenomenological human-machine integration which obscures the causal chain of an act. It explores two senses of “responsibility”: 1) when it is attributed to a person, suggesting the morally important way in which the person is a causal agent, and 2) when a person is accountable and, on the (...) basis of fairness about rewards and sanctions, has a duty to act responsibly and accept liability. The comment suggests that, in the absence of absolute knowledge and predictability, we continue to engage in practical forms of reasoning about the responsibility for BMI-use in ways which are inclusive of uncertainties about the liability of persons versus devices and those who create them. (shrink)

Physically enhancing brain–machine interfaces communicate elec­tronically with the patient’s mind in both directions. They present significant opportunities to improve a patient’s health and to restore his or her physical function, but they also present problems for the patient’s sense of agency and self. This is exacerbated by notions of extension and enhancement that are not grounded in an authentic human anthropology that describes the inherently dignified person as an integral union of body and soul.

The loss or absence of vision is probably one of the most incapacitating events that can befall a human being. The importance of vision for humans is also reflected in brain anatomy as approximately one third of the human brain is devoted to vision. It is therefore unsurprising that throughout history many attempts have been undertaken to develop devices aiming at substituting for a missing visual capacity. In this review, we present two concepts that have been prevalent over (...) the last two decades. The first concept is sensory substitution, which refers to the use of another sensory modality to perform a task that is normally primarily sub-served by the lost sense. The second concept is cross-modal plasticity, which occurs when loss of input in one sensory modality leads to reorganization in brain representation of other sensory modalities. Both phenomena are training-dependent. We also briefly describe the history of blindness from ancient times to modernity, and then proceed to address themeansthat have been used to help blind individuals, with an emphasis on modern technologies, invasive (various type of surgical implants) and non-invasive devices. With the advent of brain imaging, it has become possible to peer into the neural substrates of sensory substitution and highlight the magnitude of the plastic processes that lead to a rewired brain. Finally, we will address the important question of the value and practicality of the available technologies and future directions. (shrink)

The aim of this paper is to clarify specific aspects of the impact of the brain-machine interface on our understanding of subjectivity. The brain-machine interface is presented as a phase of cyborgization of humans. Some projects in the field of brain-machine interface are aimed at enabling consensual telepathy - communication without symbolic mediation. Consensual telepathy refers to one of potential ways of transmission of information within singularity. Therefore, consensual telepathy is an (...) important aspect of singularity. Singularity or human-machine symbiosis shows some similarities with child-mother unity. Therefore, the psychodynamic perspective might be considered useful in thinking about human-machine symbiosis. Knowledge from developmental psychodynamic psychology combined with insights by Slavoj Zizek and Jean Baudrillard provides an additional perspective looking at human-machine symbiosis. The paper claims that if consensual telepathy becomes another way of communication, it will have the potential to annihilate subjectivity making it schizophrenic. At the same time, we look at the possibility of an escape from our inner world through the prism of addictions. (shrink)

The ethical monitoring of brain-machine interfaces (BMIs) is discussed in connection with the potential impact of BMIs on distinguishing traits of persons, changes of personal identity, and threats to personal autonomy. It is pointed out that philosophical analyses of personhood are conducive to isolating an initial thematic framework for this ethical monitoring problem, but a contextual refinement of this initial framework depends on applied ethics analyses of current BMI models and empirical case-studies. The personal autonomy-monitoring problem is approached (...) by identifying various ways in which the inclusion of a robotic controller in the motor pathway of an output BMI may limit or jeopardize personal autonomy. (shrink)

We present a novel procedure to engage the public in ethical deliberations on the potential impacts of brain machine interface technology. We call this procedure a convergence seminar, a form of scenario-based group discussion that is founded on the idea of hypothetical retrospection. The theoretical background of this procedure and the results of five seminars are presented.

LANGUAGE NOTE | Document text in English; abstract also in Chinese. 腦機介面 (BCIs) 是大腦和電腦無需人工交互即可直接交流的一系列技術。隨著人工智能 (AI) 時代的到來，我們需要更多地關注腦機介面和人工智能的融合所帶來的倫理問題。那麼，與機器一起思考會帶來什麼樣的倫理問題？在本文中，圍繞這一主題，我們將重點關注以下問題：自主性、完整性、身分認同、隱私，以及 作為一種增強的方式，該技術在兒科領域的應用會帶來怎樣的風險和潛在收益。我們的結論是，雖然該技術存在多種令人擔憂的問題，同時也有可能帶來好處，但仍存在很大的不確定性。如果生命倫理學家想在這一領域有所建樹 ，他們就應該做好準備來迎接我們對醫學和醫療保健領域中一些我們視為核心價值的理解的重大轉變。 Brain-Computer Interfaces – BCIs – are a set of technologies with which brains and computers can communicate directly, without the need for manual interaction. As we are witnessing the dawn of an era in which Artificial Intelligence (AI) quite possibly will come to dominate the technological innovation landscape, we are compelled to ask questions about the ethical issues which the convergence of BCIs and (...) AI is poised to bring about. What are the ethics of thinking with machines? In this paper, we explore this question, focusing on some of the main arenas of ethical debate and contention, ranging from autonomy and integrity to identity and privacy, and discuss the risks and potential benefits of the technology in the domains of paediatric populations, and as a means of human enhancement. We conclude that, while there are multiple concerns as well as possibilities for the technology to do good, there are great uncertainties at play. If bioethicists want to stay relevant in this field, they ought to prepare themselves for seismic shift in how we conceptualise much of what we take to be core values in medicine and healthcare. (shrink)

This Master’s thesis explores the relationship between Brain-Computer Interfaces (BCIs) and their human users from a functional, epistemological and phenomenological perspective. The analysis has four steps. I start out with a technical description of BCI systems in which I conceptually analyze different types of BCI applications. This results in the development of a taxonomy of applications which is the point of departure for further philosophical analysis. Thereafter, I explore the functional relationship between BCI applications and their users. That is (...) to say, I analyze functions of BCI applications, relate them to abilities of their users and explore how they extend these abilities. After that, the epistemological relation between BCI systems and their users is conceptualized by analyzing how they contribute to cognitive processes of their users, which is done by using the distributed cognition framework. And lastly, a postphenomenological framework is adapted to investigate how BCIs mediate the experiences of their users. This thesis ends with a reflection in which (1) possible developments in BCI research are placed in a broader historical-anthropological perspective, and (2) a moral consideration is given on the desirability of BCIs. (shrink)

Brain-machine interfaces are a growing field of research and application. The increasing possibilities to connect the human brain to electronic devices and computer software can be put to use in medicine, the military, and entertainment. Concrete technologies include cochlear implants, Deep Brain Stimulation, neurofeedback and neuroprosthesis. The expectations for the near and further future are high, though it is difficult to separate hope from hype. The focus in this paper is on the effects that these new (...) technologies may have on our ‘symbolic order’—on the ways in which popular categories and concepts may change or be reinterpreted. First, the blurring distinction between man and machine and the idea of the cyborg are discussed. It is argued that the morally relevant difference is that between persons and non-persons, which does not necessarily coincide with the distinction between man and machine. The concept of the person remains useful. It may, however, become more difficult to assess the limits of the human body. Next, the distinction between body and mind is discussed. The mind is increasingly seen as a function of the brain, and thus understood in bodily and mechanical terms. This raises questions concerning concepts of free will and moral responsibility that may have far reaching consequences in the field of law, where some have argued for a revision of our criminal justice system, from retributivist to consequentialist. Even without such a (unlikely and unwarranted) revision occurring, brain-machine interactions raise many interesting questions regarding distribution and attribution of responsibility. (shrink)

Prosthetic devices that replace a lost limb have become increasingly performant in recent years. Recent advances in both software and hardware allow for the decoding of electroencephalogram signals to improve the control of active prostheses with brain-computer interfaces. Most BCI research is focused on the upper body. Although BCI research for the lower extremities has increased in recent years, there are still gaps in our knowledge of the neural patterns associated with lower limb movement. Therefore, the main objective of (...) this study is to show the feasibility of decoding lower limb movements from EEG data recordings. The second aim is to investigate whether well-known neuroplastic adaptations in individuals with an amputation have an influence on decoding performance. To address this, we collected data from multiple individuals with lower limb amputation and a matched able-bodied control group. Using these data, we trained and evaluated common BCI methods that have already been proven effective for upper limb BCI. With an average test decoding accuracy of 84% for both groups, our results show that it is possible to discriminate different lower extremity movements using EEG data with good accuracy. There are no significant differences in the decoding performance of these movements between healthy subjects and subjects with lower extremity amputation. These results show the feasibility of using BCI for lower limb prosthesis control and indicate that decoding performance is not influenced by neuroplasticity-induced differences between the two groups. (shrink)

Prosthetic devices that replace a lost limb have become increasingly performant in recent years. Recent advances in both software and hardware allow for the decoding of electroencephalogram signals to improve the control of active prostheses with brain-computer interfaces. Most BCI research is focused on the upper body. Although BCI research for the lower extremities has increased in recent years, there are still gaps in our knowledge of the neural patterns associated with lower limb movement. Therefore, the main objective of (...) this study is to show the feasibility of decoding lower limb movements from EEG data recordings. The second aim is to investigate whether well-known neuroplastic adaptations in individuals with an amputation have an influence on decoding performance. To address this, we collected data from multiple individuals with lower limb amputation and a matched able-bodied control group. Using these data, we trained and evaluated common BCI methods that have already been proven effective for upper limb BCI. With an average test decoding accuracy of 84% for both groups, our results show that it is possible to discriminate different lower extremity movements using EEG data with good accuracy. There are no significant differences in the decoding performance of these movements between healthy subjects and subjects with lower extremity amputation. These results show the feasibility of using BCI for lower limb prosthesis control and indicate that decoding performance is not influenced by neuroplasticity-induced differences between the two groups. (shrink)

The rapid expansion of research on Brain-Computer Interfaces is not only due to the promising solutions offered for persons with physical impairments. There is also a heightened need for understanding BCIs due to the challenges regarding ethics presented by new technology, especially in its impact on the relationship between man and machine. Here we endeavor to present a scoping review of current studies in the field to gain insight into the complexity of BCI use. By examining studies related (...) to BCIs that employ social research methods, we seek to demonstrate the multitude of approaches and concerns from various angles in considering the social and human impact of BCI technology. For this scoping review of research on BCIs’ social and ethical implications, we systematically analyzed six databases, encompassing the fields of medicine, psychology, and the social sciences, in order to identify empirical studies on BCIs. The search yielded 73 publications that employ quantitative, qualitative, or mixed methods. Of the 73 publications, 71 studies address the user perspective. Some studies extend to consideration of other BCI stakeholders such as medical technology experts, caregivers, or health care professionals. The majority of the studies employ quantitative methods. Recurring themes across the studies examined were general user opinion towards BCI, central technical or social issues reported, requests/demands made by users of the technology, the potential/future of BCIs, and ethical aspects of BCIs. Our findings indicate that while technical aspects of BCIs such as usability or feasibility are being studied extensively, comparatively little in-depth research has been done on the self-image and self-experience of the BCI user. In general there is also a lack of focus or examination of the caregiver’s perspective. (shrink)

Brain–computer interfacing (BCI) aims at directly capturing brain activity in order to enable a user to drive an application such as a wheelchair without using peripheral neural or motor systems. Low signal to noise ratio’s, low processing speed, and huge intra- and inter-subject variability currently call for the addition of intelligence to the applications, in order to compensate for errors in the production and/or the decoding of brain signals. However, the combination of minds and machines through BCI’s (...) and intelligent devices (IDs) can affect a user’s sense of agency. Particularly confusing cases can arise when the behavioral control switches implicitly from user to ID. I will suggest that in such situations users may be insecure about the extent to which the resulting behavior, whether successful or unsuccessful, is genuinely their own. Hence, while performing an action, a user of a BCI–ID may be uncertain about being the agent of the act. Several cases will be examined and some implications for (legal) responsibility (e.g. establishing the presence of a ‘guilty mind’) are discussed. (shrink)

Bionic systems, connecting biological tissues with computer or robotic devices through brain–machine interfaces, can be used in various ways to discover biological mechanisms. In this article I outline and discuss a “stimulation-connection” bionics-supported methodology for the study of the brain, and compare it with other epistemic uses of bionic systems described in the literature. This methododology differs from the “synthetic”, simulative method often followed in theoretically driven Artificial Intelligence and cognitive science, even though it involves machine (...) models of biological systems. I also bring the previous analysis to bear on some claims on the epistemic value of bionic technologies made in the recent philosophical literature. I believe that the methodological reflections proposed here may contribute to the piecewise understanding of the many ways bionic technologies can be deployed not only to restore lost sensory-motor functions, but also to discover brain mechanisms. (shrink)

Connecting human minds to various technological devices and applications through brain-computer interfaces (BCIs) affords intriguingly novel ways for humans to engage and interact with the world. Not only do BCIs play an important role in restorative medicine, they are also increasingly used outside of medical or therapeutic contexts (e.g., gaming or mental state monitoring). A striking peculiarity of BCI technology is that the kind of actions it enables seems to differ from paradigmatic human actions, because, effects in the world (...) are brought about by devices such as robotic arms, prosthesis, or other machines, and their execution runs through a computer directed by brain signals. In contrast to usual forms of action, the sequence does not need to involve bodily or muscle movements at all. A motionless body, the epitome of inaction, might be acting. How do theories of action relate to such BCI-mediated forms of changing the world? We wish to explore this question through the lenses of three perspectives on agency: subjective experience of agency, philosophical action theory, and legal concepts of action. Our analysis pursues three aims: First, we shall discuss whether and which BCI-mediated events qualify as actions, according to the main concepts of action in philosophy and law. Secondly, en passant, we wish to highlight the ten most interesting novelties or peculiarities of BCI-mediated movements. Thirdly, we seek to explore whether these novel forms of movement may have consequences for concepts of agency. More concretely, we think that convincing assessments of BCI-movements require more fine-grained accounts of agency and a distinction between various forms of control during movements. In addition, we show that the disembodied nature of BCI-mediated events causes troubles for the standard legal account of actions as bodily movements. In an exchange with views from philosophy, we wish to propose that the law ought to reform its concept of action to include some, but not all, BCI-mediated events and sketch some of the wider implications this may have, especially for the venerable legal idea of the right to freedom of thought. In this regard, BCIs are an example of the way in which technological access to yet largely sealed-off domains of the person may necessitate adjusting normative boundaries between the personal and the social sphere. (shrink)

Brain-Computer Interface (BCI) research and (future) applications raise important ethical issues that need to be addressed to promote societal acceptance and adequate policies. Here we report on a survey we conducted among 145 BCI researchers at the 4th International BCI conference, which took place in May–June 2010 in Asilomar, California. We assessed respondents’ opinions about a number of topics. First, we investigated preferences for terminology and definitions relating to BCIs. Second, we assessed respondents’ expectations on the marketability of (...) different BCI applications (BCIs for healthy people, BCIs for assistive technology, BCIs-controlled neuroprostheses and BCIs as therapy tools). Third, we investigated opinions about ethical issues related to BCI research for the development of assistive technology: informed consent process with locked-in patients, risk-benefit analyses, team responsibility, consequences of BCI on patients’ and families’ lives, liability and personal identity and interaction with the media. Finally, we asked respondents which issues are urgent in BCI research. (shrink)

Brain–computer interfaces (BCIs) utilizing machine learning techniques are an emerging technology that enables a communication pathway between a user and an external system, such as a computer. Owing to its practicality, electroencephalography (EEG) is one of the most widely used measurements for BCI. However, EEG has complex patterns and EEG-based BCIs mostly involve a cost/time-consuming calibration phase; thus, acquiring sufficient EEG data is rarely possible. Recently, deep learning (DL) has had a theoretical/practical impact on BCI research because of (...) its use in learning representations of complex patterns inherent in EEG. Moreover, algorithmic advances in DL facilitate short/zero-calibration in BCI, thereby suppressing the data acquisition phase. Those advancements include data augmentation (DA), increasing the number of training samples without acquiring additional data, and transfer learning (TL), taking advantage of representative knowledge obtained from one dataset to address the so-called data insufficiency problem in other datasets. In this study, we review DL-based short/zero-calibration methods for BCI. Further, we elaborate methodological/algorithmic trends, highlight intriguing approaches in the literature, and discuss directions for further research. In particular, we search forgenerative model-based andgeometric manipulation-based DA methods. Additionally, we categorize TL techniques in DL-based BCIs intoexplicitandimplicitmethods. Our systematization reveals advances in the DA and TL methods. Among the studies reviewed herein, ~45% of DA studies used generative model-based techniques, whereas ~45% of TL studies used explicit knowledge transferring strategy. Moreover, based on our literature review, we recommend an appropriate DA strategy for DL-based BCIs and discuss trends of TLs used in DL-based BCIs. (shrink)

Common spatial pattern is an effective algorithm for extracting electroencephalogram features of motor imagery ; however, CSP mainly aims at multichannel EEG signals, and its effect in extracting EEG features with fewer channels is poor—even worse than before using CSP. To solve the above problem, a new combined feature extraction method has been proposed in this study. For EEG signals from fewer channels, wavelet packet transform, fast ensemble empirical mode decomposition, and local mean decomposition were used to decompose the band-pass (...) filtered EEG into multiple time–frequency components, and the corresponding components were selected according to the frequency characteristics of MI or the correlation coefficient between its time–frequency components and the original EEG signal. Furthermore, phase space reconstruction was performed on the selected components after the three time-frequency decompositions, the maximum Lyapunov index was calculated, and the features were reconstructed; then, CSP projection mapping was used for the reconstructed features. The support vector machine probability output model was trained by the obtained three mappings. Probability outputs by three different support vector machines were then obtained. Finally, the classification of test samples was determined by the fusion of the Dempster–Shafer evidence theory at the decision level. The results showed that the accuracy of the proposed method was 95.71% on data set III of BCI competition II, which was 2.88% higher than the existing methods. On data set IIb of BCI competition IV, the average accuracy was 86.60%, which was 2.3% higher than the existing methods. This study verified the effectiveness of the proposed method and provided an approach for the research and development of the MI-BCI system based on fewer channels. (shrink)

A brain-computer interface is a rapidly evolving neurotechnology connecting the human brain with a computer. In its classic form, brain activity is recorded and used to control external devices like protheses or wheelchairs. Thus, BCI users act with the power of their thoughts. While the initial development has focused on medical uses of BCIs, non-medical applications have recently been gaining more attention, for example in automobiles, airplanes, and the entertainment context. However, the attitudes of the general (...) public towards BCIs have hardly been explored. Among the general population in Germany aged 18–65 years, a representative online survey with 20 items was conducted in summer 2018 and analysed by descriptive statistics. The survey assessed: affinity for technology; previous knowledge and experience concerning BCIs; the attitude towards ethical, social and legal implications of BCI use and demographic information. Our results indicate that BCIs are a unique and puzzling way of human–machine interaction. The findings reveal a positive view and high level of trust in BCIs on the one hand but on the other hand a wide range of ethical and anthropological concerns. Agency and responsibility were clearly attributed to the BCI user. The participants’ opinions were divided regarding the impact BCIs have on humankind. In summary, a high level of ambivalence regarding BCIs was found. We suggest better information of the public and the promotion of public deliberation about BCIs in order to ensure responsible development and application of this potentially disruptive technology. (shrink)

Technologies like passive brain-computer interfaces can enhance human-machine interaction. Anyhow, there are still shortcomings in terms of easiness of use, reliability, and generalizability that prevent passive-BCI from entering real-life situations. The current work aimed to technologically and methodologically design a new gel-free passive-BCI system for out-of-the-lab employment. The choice of the water-based electrodes and the design of a new lightweight headset met the need for easy-to-wear, comfortable, and highly acceptable technology. The proposed system showed high reliability in both (...) laboratory and realistic settings, performing not significantly different from the gold standard based on gel electrodes. In both cases, the proposed system allowed effective discrimination between low and high levels of workload, vigilance, and stress even for high temporal resolution. Finally, the generalizability of the proposed system has been tested through a cross-task calibration. The system calibrated with the data recorded during the laboratory tasks was able to discriminate the targeted human factors during the realistic task reaching AUC values higher than 0.8 at 40 s of temporal resolution in case of vigilance and workload, and 20 s of temporal resolution for the stress monitoring. These results pave the way for ecologic use of the system, where calibration data of the realistic task are difficult to obtain. (shrink)

A passive brain–computer interface based upon functional near-infrared spectroscopy brain signals is used for earlier detection of human drowsiness during driving tasks. This BCI modality acquired hemodynamic signals of 13 healthy subjects from the right dorsolateral prefrontal cortex of the brain. Drowsiness activity is recorded using a continuous-wave fNIRS system and eight channels over the right DPFC. During the experiment, sleep-deprived subjects drove a vehicle in a driving simulator while their cerebral oxygen regulation state was continuously (...) measured. Vector phase analysis was used as a classifier to detect drowsiness state along with sleep stage-based threshold criteria. Extensive training and testing with various feature sets and classifiers are done to justify the adaptation of threshold criteria for any subject without requiring recalibration. Three statistical features along with six VPA features were used. The average accuracies for the five classifiers are 90.9% for discriminant analysis, 92.5% for support vector machines, 92.3% for nearest neighbors, 92.4% for both decision trees, and ensembles over all subjects’ data. Trajectory slopes of CORE vector magnitude and angle: m and m are the best-performing features, along with ensemble classifier with the highest accuracy of 95.3% and minimum computation time of 40 ms. The statistical significance of the results is validated with a p-value of less than 0.05. The proposed passive BCI scheme demonstrates a promising technique for online drowsiness detection using VPA along with sleep stage classification. (shrink)

Electroencephalography and functional near-infrared spectroscopy have potentially complementary characteristics that reflect the electrical and hemodynamic characteristics of neural responses, so EEG-fNIRS-based hybrid brain-computer interface is the research hotspots in recent years. However, current studies lack a comprehensive systematic approach to properly fuse EEG and fNIRS data and exploit their complementary potential, which is critical for improving BCI performance. To address this issue, this study proposes a novel multimodal fusion framework based on multi-level progressive learning with multi-domain features. The (...) framework consists of a multi-domain feature extraction process for EEG and fNIRS, a feature selection process based on atomic search optimization, and a multi-domain feature fusion process based on multi-level progressive machine learning. The proposed method was validated on EEG-fNIRS-based motor imagery and mental arithmetic tasks involving 29 subjects, and the experimental results show that multi-domain features provide better classification performance than single-domain features, and multi-modality provides better classification performance than single-modality. Furthermore, the experimental results and comparison with other methods demonstrated the effectiveness and superiority of the proposed method in EEG and fNIRS information fusion, it can achieve an average classification accuracy of 96.74% in the MI task and 98.42% in the MA task. Our proposed method may provide a general framework for future fusion processing of multimodal brain signals based on EEG-fNIRS. (shrink)

I use a hypothetical case study of a woman who replaces here biological arms with prostheses controlled through a brain–computer interface the explore how a BCI might interpret and misinterpret intentions. I define pre-veto intentions and post-veto intentions and argue that a failure of a BCI to differentiate between the two could lead to some troubling legal and ethical problems.

This study evaluated the feasibility of using occipitoparietal alpha activity to drive target/non-target classification in a brain-computer interface for communication. EEG data were collected from 12 participants who completed BCI Rapid Serial Visual Presentation calibrations at two different presentation rates: 1 and 4 Hz. Attention-related changes in posterior alpha activity were compared to two event-related potentials : N200 and P300. Machine learning approaches evaluated target/non-target classification accuracy using alpha activity. Results indicated significant alpha attenuation following target letters (...) at both 1 and 4 Hz presentation rates, though this effect was significantly reduced in the 4 Hz condition. Target-related alpha attenuation was not correlated with coincident N200 or P300 target effects. Classification using posterior alpha activity was above chance and benefitted from individualized tuning procedures. These findings suggest that target-related posterior alpha attenuation is detectable in a BCI RSVP calibration and that this signal could be leveraged in machine learning algorithms used for RSVP or comparable attention-based BCI paradigms. (shrink)

Developments in neurotechnology took a leap forward with the demonstration of the first Brain to Brain Interface (BBI). BBIs enable direct communication between two brains via a Brain Computer Interface (BCI) and bypasses the peripheral nervous system. This discovery promises new possibilities for future battlefield technology. As battlefield technology evolves, it is more likely to place greater demands on future soldiers. Future soldiers are more likely to process large amounts of data derived from an extensive (...) networks of humans and machines. This raises several ethical and philosophical concerns. This paper will look at BBI technology in current stages of research, future BBI applications in the military and how the potential use of BBIs in military operations challenges the way we understand the concept of responsibility. In this paper, I propose that an individual connected to a BBI ought not to be held fully responsible for her actions. The justification for this proposition is based on three key points such as an individual connected to a BBI does not have the ability to act freely, has a diminished sense of self-agency and may not be able to demonstrate authenticity of the thoughts and memories generated when connected to the interface. (shrink)

Novel neurotechnologies like deep brain stimulation and brain-computer interfaces promise clinical benefits for severely suffering patients. Nevertheless, such electroceuticals raise several ethical issues on different levels: while on the level of clinical neuroethics issues with direct relevance for diagnosis and treatment have to be discussed, on the level of research neuroethics questions regarding research and development of these technological devices like investigating new targets and different diseases as well as thorough inclusion criteria are dealt with. On the level (...) of theoretical neuroethics more general questions are examined including anthropological considerations on “normal” human functioning as well as implications on personality, personal identity and authenticity. This paper presents a brief review on ethical issues of deep brain stimulation and brain computer interfacing and simultaneously introduces to this themed issue with thirteen contributions dealing from different perspectives with ethical implications of electroceuticals for the human brain. (shrink)

Brain Computer Interfaces (BCIs) enable one to control peripheral ICT and robotic devices by processing brain activity on-line. The potential usefulness of BCI systems, initially demonstrated in rehabilitation medicine, is now being explored in education, entertainment, intensive workflow monitoring, security, and training. Ethical issues arising in connection with these investigations are triaged taking into account technological imminence and pervasiveness of BCI technologies. By focussing on imminent technological developments, ethical reflection is informatively grounded into realistic protocols of brain-to-computer (...) communication. In particular, it is argued that human-machine adaptation and shared control distinctively shape autonomy and responsibility issues in current BCI interaction environments. Novel personhood issues are identified and analyzed too. These notably concern (i) the “sub-personal” use of human beings in BCI-enabled cooperative problem solving, and (ii) the pro-active protection of personal identity which BCI rehabilitation therapies may afford, in the light of so-called motor theories of thinking, for the benefit of patients affected by severe motor disabilities. (shrink)

The paper develops two related thought experiments exploring variations on an ‘animat’ theme. Animats are hybrid devices with both artificial and biological components. Traditionally, ‘components’ have been construed in concrete terms, as physical parts or constituent material structures. Many fascinating issues arise within this context of hybrid physical organization. However, within the context of functional/computational theories of mentality, demarcations based purely on material structure are unduly narrow. It is abstract functional structure which does the key work in characterizing the respective (...) ‘components’ of thinking systems, while the ‘stuff’ of material implementation is of secondary importance. Thus the paper extends the received animat paradigm, and investigates some intriguing consequences of expanding the conception of bio-machine hybrids to include abstract functional and semantic structure. In particular, the thought experiments consider cases of mind-machine merger where there is no physical Brain-Machine Interface: indeed, the material human body and brain have been removed from the picture altogether. The first experiment illustrates some intrinsic theoretical difficulties in attempting to replicate the human mind in an alternative material medium, while the second reveals some deep conceptual problems in attempting to create a form of truly Artificial General Intelligence. (shrink)

This article examines the emerging possibility of “brain-state transitioning,” in which one brain state is prompted through manipulating the dynamics of the active brain. The technique, still in its infancy, is intended to provide the basis for novel treatments for brain-based disorders. Although a detailed literature exists covering topics around brain-machine interfaces, where targets of brain-based activity include artificial limbs, hardware, and software, there is less concentration on the brain itself as a (...) target for instrumental intervention. This article examines some of the science behind brain-state transitioning, before extending beyond current possibilities in order to explore philosophical and ethical questions about how transitions could be seen to impact on assessment of responsibility and personal identity. It concludes with some thoughts on how best to pursue this nascent approach while accounting for the philosophical and ethical issues. (shrink)

Information and communication technologies , with their increasing and widespread utilization in daily life, may exert an important impact on brain performances. The development of their use for improving several cerebral processes, by abolishing the brain/machine interface, is envisaged and is subject to debate. The scientific research on brain implants and brain gene transfer aiming to restore central nervous system functions, altered by disease or trauma, may contribute to this debate. Indeed, the advances that (...) are enabling non drug-mediated approaches for direct interventions on the brain are raising the possibility not only of restoring neural functions for therapeutic purposes, but also of monitoring, controlling and ultimately modifying from the outside these functions for enhancement. This paper gives an overview of the state of the art of brain implants and brain gene transfer for neurological diseases with a particular emphasis on Parkinson’s disease and a forecast on their possible application for other conditions. In doing so, the authors, who are neuroscientists working in the field of gene transfer for neuropsychiatric diseases, aim to establish a scientifically, medically and technically realistic framework to open up discussion on relevant ethical issues in this domain. (shrink)

The aim here is to implement intelligence in an engineered processing substrate – a machine mind, as it were. This solution is clearly related to work in artificial intelligence (AI) and shares many of its analytical requirements and synthesis goals, but the objective is unambiguously to make individual human minds independent of a single substrate. Brain–machine interfaces require adaptations for communication to be possible, emphasizing either the machine or the brain. Brain emulation on general‐purpose (...) computers is convenient, because model functions can be modified easily. Ultimately, a mature emulation demands a suitable computing substrate. Theoretical debates occasionally focus on the question of determinism and computation in the Von Neumann sense. ARPANET (the Advanced Research Projects Agency Network) useful for university projects and for the military, but it was not immediately obvious what sort of civilian applications would thrive on such a computer network. (shrink)

The paper reports our research aiming at utilization of human interactive communication modeling principles in application to a novel interaction paradigm designed for brain–computer/machine-interfacing (BCI/BMI) technologies as well as for socially aware intelligent environments or communication support systems. Automatic procedures for human affective responses or emotional states estimation are still a hot topic of contemporary research. We propose to utilize human brain and bodily physiological responses for affective/emotional as well as communicative interactivity estimation, which potentially could be (...) used in the future for human–machine/environment interaction design. As a test platform for such an intelligent human–machine communication application, an emotional stimuli paradigm was chosen to evaluate brain responses to various affective stimuli in an emotional empathy mode. Videos with moving faces expressing various emotional displays as well as speech stimuli with similarly emotionally articulated sentences are presented to the subjects in order to further analyze different affective responses. From information processing point of view, several challenges with multimodal signal conditioning and stimuli dynamic response extraction in time frequency domain are addressed. Emotions play an important role in human daily life and human-to-human communication. This is why involvement of affective stimuli principles to human–machine communication or machine-mediated communication with utilization of multichannel neurophysiological and periphery physiological signals monitoring techniques, allowing real-time subjective brain responses evaluation, is discussed. We present our preliminary results and discuss potential applications of brain/body affective responses estimation for future interactive/smart environments. (shrink)

An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural (...) plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design. (shrink)

In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I (...) argue that MVPA does not inherently provide a new answer to classical worries about reverse inference, and that the method faces pervasive interpretive problems of its own. Further, the epistemic setting of MVPA and other decoding methods contributes to a potentially worrisome shift towards prediction and away from explanation in fundamental neuroscience. (shrink)

The typical approach to decoding speech from the brain (using brain-machine interfaces) is to decode low-level linguistic units (e.g. phonemes, syllables) from motor articulation areas (e.g. Premotor cortex) with the aim of assembling these low-level units into higher-level discourse. We propose that brain-to-speech decoding may benefit from adopting a functional view of language, which conceives of language as an instrumental tool for interacting with others' intentions in order to fulfil one's own intentions. This functional view of (...) language motivates adopting usability (i.e. the decoder's usefulness as a tool for achieving goals), in addition to decoding accuracy, as a criterion for assessing decoder performance. Decoders may achieve gains in usability by incorporating data about communicative situations and speaker intentions in order to generate and fill in speech act templates. We suggest that this intention-oriented, template-based, and functionally inspired view of brain-to-speech decoding may facilitate efforts to achieve naturalistic speech decoding. (shrink)