Entropic Brain-computer Interfaces

Hincks, Samuel W.; Bratt, Sarah; Poudel, Sujit; Phoha, Vir V.; Jacob, Robert J. K.; Dennett, Daniel C.; Hirshfield, Leanne M.

doi:10.5220/0006383300230034

Cited by 5 publications

(3 citation statements)

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“…This latter example presents a sliding scale with respect to the primary purpose of each cursor movement. In a process later also described by Hincks et al (2017), the stimuli were initially selected a with no other purpose than to populate the user model. As information was gathered and a user model was formed, the stimuli became increasingly part of the task completion (target reaching) mechanism while still allowing for new information to be learned.…”

Section: Literature Reviewmentioning

confidence: 99%

“…towards the idea of cognitive probing presented here. While clearly sharing common methodologies, the used terminology is still disparate: authors referred to their methods, or parts thereof, as 'probing' (Kane et al 2000, 'brain reading' or 'embedded brain reading' (Kirchner et al 2019), 'exploration' (Iturrate et al 2015), 'active sampling' (Lorenz et al 2017), 'active inference' (Mladenovic et al 2019), or implied the method to be part of an 'entropic BCI' (Hincks et al 2017), of 'adaptive' systems (Schultheis andJameson 2004, Yuksel et al 2016), or of a system using 'brainput' (Solovey et al 2012). This is part of the reason why we now present a unified framework and terminology.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Other strategies can similarly be applied, notably expected model change (obtaining information that would most change the model) and expected error reduction (to reduce the error in the model, or in the system's behaviour). A system may initialise using random variables and based on these initial samples, move to specific strategies to find more suitable values (Hincks et al 2017).…”

Section: Learning Strategiesmentioning

confidence: 99%

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Cognitive and affective probing: a tutorial and review of active learning for neuroadaptive technology

Krol

Haselager

Zander³

2020

J. Neural Eng.

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Objective: The interpretation of neurophysiological measurements has a decadeslong history, culminating in current real-time brain-computer interfacing (BCI) applications for both patient and healthy populations. Over the course of this history, one focus has been on the investigation of cortical responses to specific stimuli. Such responses can be informative with respect to the human user's mental state at the time of presentation. An ability to decode neurophysiological responses to stimuli in real time becomes particularly powerful when combined with a simultaneous ability to autonomously produce such stimuli. This allows a computer to gather stimulus-response samples and iteratively produce new stimuli based on the information gathered from previous samples, thus acquiring more, and more specific, information. This information can even be obtained without the explicit, voluntary involvement of the user.Approach: We define cognitive and affective probing, referring to an application of active learning where repeated sampling is done by eliciting implicit brain responses. In this tutorial, we provide a definition of this method that unifies different past and current implementations based on common aspects. We then discuss a number of aspects that differentiate various possible implementations of cognitive probing.Main results: We argue that a key element is the user model, which serves as both information storage and basis for subsequent probes. Cognitive probing can be used to continuously and autonomously update this model, refining the probes, and obtaining increasingly detailed or accurate information from the resulting brain activity. In contrast to a number of potential advantages of the method, cognitive probing may also pose a threat to informed consent, our privacy of thought, and our ability to assign responsibility to actions mediated by the system.Significance: This tutorial provides guidelines to both implement, and critically discuss potential ethical implications of, novel cognitive probing applications and research endeavours.

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Section: Literature Reviewmentioning

confidence: 99%