Minds, Motherboards, and Money: Futurism and Realism in the Neuroethics of BCI Technologies

From the Introduction: Brain computer interfaces (BCIs) are systems that enable the brain to send and receive information to and from a computer, bypassing the body\u27s own efferent and afferent pathways. BCIs have been used in experimental animal models to augment perception, motor control and even memory (Velliste et al., 2008; Berger et al., 2011; Torab et al., 2011). Human BCIs include cochlear implants and a host of experimental devices including retinal implants (Niparko et al., 2010; Klauke et al., 2011). BCI technology holds the potential to benefit humanity greatly, but also the potential to do harm, and its ethical implications have therefore been addressed by a number of commentators

Neuro-electronic technology in medicine and beyond

This dissertation looks at the technology and social issues involved with interfacing electronics directly to the human nervous system, in particular the methods for both reading and stimulating nerves. The development and use of cochlea implants is discussed, and is compared with recent developments in artificial vision. The final sections consider a future for non-medicinal applications of neuro-electronic technology. Social attitudes towards use for both medicinal and non-medicinal purposes are discussed, and the viability of use in the latter case assessed

Developer perspectives on the ethics of AI-driven neural implants:a qualitative study

Convergence of neural implants with artificial intelligence (AI) presents opportunities for the development of novel neural implants and improvement of existing neurotechnologies. While such technological innovation carries great promise for the restoration of neurological functions, they also raise ethical challenges. Developers of AI-driven neural implants possess valuable knowledge on the possibilities, limitations and challenges raised by these innovations; yet their perspectives are underrepresented in academic literature. This study aims to explore perspectives of developers of neurotechnology to outline ethical implications of three AI-driven neural implants: a cochlear implant, a visual neural implant, and a motor intention decoding speech-brain-computer-interface. We conducted semi-structured focus groups with developers (n = 19) of AI-driven neural implants. Respondents shared ethically relevant considerations about AI-driven neural implants that we clustered into three themes: (1) design aspects; (2) challenges in clinical trials; (3) impact on users and society. Developers considered accuracy and reliability of AI-driven neural implants conditional for users’ safety, authenticity, and mental privacy. These needs were magnified by the convergence with AI. Yet, the need for accuracy and reliability may also conflict with potential benefits of AI in terms of efficiency and complex data interpretation. We discuss strategies to mitigate these challenges.</p

Developer perspectives on the ethics of AI-driven neural implants:a qualitative study

Convergence of neural implants with artificial intelligence (AI) presents opportunities for the development of novel neural implants and improvement of existing neurotechnologies. While such technological innovation carries great promise for the restoration of neurological functions, they also raise ethical challenges. Developers of AI-driven neural implants possess valuable knowledge on the possibilities, limitations and challenges raised by these innovations; yet their perspectives are underrepresented in academic literature. This study aims to explore perspectives of developers of neurotechnology to outline ethical implications of three AI-driven neural implants: a cochlear implant, a visual neural implant, and a motor intention decoding speech-brain-computer-interface. We conducted semi-structured focus groups with developers (n = 19) of AI-driven neural implants. Respondents shared ethically relevant considerations about AI-driven neural implants that we clustered into three themes: (1) design aspects; (2) challenges in clinical trials; (3) impact on users and society. Developers considered accuracy and reliability of AI-driven neural implants conditional for users’ safety, authenticity, and mental privacy. These needs were magnified by the convergence with AI. Yet, the need for accuracy and reliability may also conflict with potential benefits of AI in terms of efficiency and complex data interpretation. We discuss strategies to mitigate these challenges.</p

Utilizing Brain-computer Interfacing to Control Neuroprosthetic Devices

Advances in neuroprosthetics in recent years have made an enormous impact on the quality of life for many people with disabilities, helping them regain the functionality of damaged or impaired abilities. One of the main hurdles to regaining full functionality regarding neuroprosthetics is the integration between the neural prosthetic device and the method in which the neural prosthetic device is controlled or manipulated to function correctly and efficiently. One of the most promising methods for integrating neural prosthetics to an efficient method of control is through Brian-computer Interfacing (BCI). With this method, the neuroprosthetic device is integrated into the human brain through the use of a specialized computer, which allows for users of neuroprosthetic devices to control the devices in the same way that they would control a normally working human function- with their mind. There are both invasive and non-invasive methods to implement Brain-computer Interfacing, both of which involve the process of acquiring a brain signal, processing the signal, and finally providing a usable device output. There are several examples of integration between Brain-computer Interfacing and neural prosthetics that are currently being researched. Many challenges must be overcome before a widespread clinical application of integration between Brain-computer Interfaces and neural prosthetics becomes a reality, but current research continues to provide promising advancement toward making this technology available as a means for people to regain lost functionality

Human Sensation of Transcranial Electric Stimulation.

Noninvasive transcranial electric stimulation is increasingly being used as an advantageous therapy alternative that may activate deep tissues while avoiding drug side-effects. However, not only is there limited evidence for activation of deep tissues by transcranial electric stimulation, its evoked human sensation is understudied and often dismissed as a placebo or secondary effect. By systematically characterizing the human sensation evoked by transcranial alternating-current stimulation, we observed not only stimulus frequency and electrode position dependencies specific for auditory and visual sensation but also a broader presence of somatic sensation ranging from touch and vibration to pain and pressure. We found generally monotonic input-output functions at suprathreshold levels, and often multiple types of sensation occurring simultaneously in response to the same electric stimulation. We further used a recording circuit embedded in a cochlear implant to directly and objectively measure the amount of transcranial electric stimulation reaching the auditory nerve, a deep intercranial target located in the densest bone of the skull. We found an optimal configuration using an ear canal electrode and low-frequency (&lt;300 Hz) sinusoids that delivered maximally ~1% of the transcranial current to the auditory nerve, which was sufficient to produce sound sensation even in deafened ears. Our results suggest that frequency resonance due to neuronal intrinsic electric properties need to be explored for targeted deep brain stimulation and novel brain-computer interfaces

Neuroengineering Tools/Applications for Bidirectional Interfaces, Brain–Computer Interfaces, and Neuroprosthetic Implants – A Review of Recent Progress

The main focus of this review is to provide a holistic amalgamated overview of the most recent human in vivo techniques for implementing brain–computer interfaces (BCIs), bidirectional interfaces, and neuroprosthetics. Neuroengineering is providing new methods for tackling current difficulties; however neuroprosthetics have been studied for decades. Recent progresses are permitting the design of better systems with higher accuracies, repeatability, and system robustness. Bidirectional interfaces integrate recording and the relaying of information from and to the brain for the development of BCIs. The concepts of non-invasive and invasive recording of brain activity are introduced. This includes classical and innovative techniques like electroencephalography and near-infrared spectroscopy. Then the problem of gliosis and solutions for (semi-) permanent implant biocompatibility such as innovative implant coatings, materials, and shapes are discussed. Implant power and the transmission of their data through implanted pulse generators and wireless telemetry are taken into account. How sensation can be relayed back to the brain to increase integration of the neuroengineered systems with the body by methods such as micro-stimulation and transcranial magnetic stimulation are then addressed. The neuroprosthetic section discusses some of the various types and how they operate. Visual prosthetics are discussed and the three types, dependant on implant location, are examined. Auditory prosthetics, being cochlear or cortical, are then addressed. Replacement hand and limb prosthetics are then considered. These are followed by sections concentrating on the control of wheelchairs, computers and robotics directly from brain activity as recorded by non-invasive and invasive techniques