Intentional binding enhances hybrid BCI control

Mental imagery-based 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. 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 experiment 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 as well as the spatiotemporal brain dynamics. Higher control accuracy 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. 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.Comment: 18 pages, 5 figures, 7 supplementary material

Did I do that? Brain-computer interfacing and the sense of agency

Contains fulltext : 116450.pdf (publisher's version ) (Closed access)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.14 p

Intelligent technologies for the aging brain: opportunities and challenges

Intelligent computing is rapidly reshaping healthcare. In light of the global burden of population aging and neurological disorders, dementia and elderly care are among the healthcare sectors that are most likely to benefit from this technological revolution. Trends in artificial intelligence, robotics, ubiquitous computing, neurotechnology and other branches of biomedical engineering are progressively enabling novel opportunities for technology-enhanced care. These Intelligent Assistive Technologies (IATs) open the prospects of supporting older adults with neurocognitive disabilities, maintain their independence, reduce the burden on caregivers and delay the need for long-term care (1, 2). While technology develops fast, yet little knowledge is available to patients and health professionals about the current availability, applicability, and capability of existing IATs. This thesis proposes a state-of-the-art analysis of IATs in dementia and elderly care. Our findings indicate that advances in intelligent technology are resulting in a rapidly expanding number and variety of assistive solutions for older adults and people with neurocognitive disabilities. However, our analysis identifies a number of challenges that negatively affect the optimal deployment and uptake of IATs among target users and care institutions. These include design issues, sub-optimal approaches to product development, translational barriers between lab and clinics, lack of adequate validation and implementation, as well as data security and cyber-risk weaknesses. Additionally, in virtue of their technological novelty, intelligent technologies raise a number of Ethical, Legal and Social Implications (ELSI). Therefore, a significant portion of this thesis is devoted to providing an early ethical Technology Assessment (eTA) of intelligent technology, hence contributing to preparing the terrain for its safe and ethically responsible adoption. This assessment is primarily focused on intelligent technologies at the human-machine interface, as these applications enable an unprecedented exposure of the intimate dimension of individuals to the digital infosphere. Issues of privacy, integrity, equality, and dual-use were addressed at the level of stakeholder analysis, normative ethics and human-rights law. Finally, this thesis is aimed at providing evidence-based recommendations for guiding participatory and responsible development in intelligent technology, and delineating governance strategies that maximize the clinical benefits of IATs for the aging world, while minimizing unintended risks