Passive brain–computer interfaces : A perspective on increased interactivity

Passive brain–computer interfaces (passive BCI; pBCI) have been introduced and formally defined almost a decade ago and have gained considerable attention since then. In this chapter, we clarify some points of confusion and provide a perspective on the past, present, and future of the field of passive BCI. This perspective concerns a key aspect with regard to which various pBCI-based systems differ from each other: interactivity. The more interactive a system is, the more responsive it is, the more autonomous, and the better capable of adaptation. Along these lines, we identify and describe four relevant categories of systems with varying levels of interactivity: mental state assessment, open-loop adaptation, closed-loop adaptation, and automated adaptation. We give examples of past and current research for each of these categories. The latter three are collectively introduced as neuroadaptive systems. This perspective and formal categorisation helps to highlight human–computer interaction aspects that are relevant for the design of pBCI-based systems and points to possibilities for future research and development into passive BCI, implicit interaction, and neuroadaptive technology

Salience versus valence in implicit cursor control: First indications of separate cortical processes

It has previously been shown that passive brain-computer interfacing enables implicit control over a cursor: participants were able to guide a cursor towards a target without being aware of doing so. The control was based on their brain's automatic responses to the cursor's autonomous movements. This raises questions with respect to informed consent and privacy of thought. The extent to which these ethical issues are truly relevant depends on the type of cognitive processes targeted by implicit control paradigms: did the cursor indeed have access to the participants' subjective preferences? It has been argued that the relevant neurophysiological processes may be based on visual salience rather than on the participants' personal interpretations. We now present a paradigm that aims to differentiate between salience and valence. Based on data from eight initial participants, we present findings that indicate both processes play a role, meaning that valence is not solely responsible, but indeed reflected in the signal

Supporting "what-if" in touch-screen web applications

Surface computing encourages exploratory interaction, and many applications are designed to work this way. In essence, the fluid interaction causes the user to ask "What if?" We suggest this requires support for recording the history of such explorations and allowing reversion to earlier states. There are currently a variety of related mechanisms, but they are either underpowered for the sort of interaction history management we suggest is needed, or are restricted to very specific domains. We present a prototype implementation of an interaction history manager: Ra is a JavaScript library for supporting this exploration and version tracking in web applications. We illustrate the interface for end users seen in augmenting simple web applications; we describe the underlying technical architecture, which uses ES6 Proxy objects to maintain access to the application's model; and we present the API, which allows an existing application to include Ra with minimal code change