Co-Evolution of Human and Machine: Neuroprosthetics in the 21st Century (original) (raw)
Related papers
The Evolution of Neuroprosthetic Interfaces
Critical Reviews in Biomedical Engineering, 2016
The ideal neuroprosthetic interface permits high-quality neural recording and stimulation of the nervous system while reliably providing clinical benefits over chronic periods. Although current technologies have made notable strides in this direction, significant improvements must be made to better achieve these design goals and satisfy clinical needs. This article provides an overview of the state of neuroprosthetic interfaces, starting with the design and placement of these interfaces before exploring the stimulation and recording platforms yielded from contemporary research. Finally, we outline emerging research trends in an effort to explore the potential next generation of neuroprosthetic interfaces.
Neuroprosthetic Supersystems Architecture, 2017
In this text, we develop an ontology that envisions, captures, and describes the full range of ways in which a neuroprosthesis may participate in the sensory, cognitive, and motor processes of its human host. By considering anticipated future developments in neuroprosthetics and adopting a generic biocybernetic approach, the ontology is able to account for therapeutic neuroprostheses already in use as well as future types of neuroprostheses expected to be deployed for purposes of human enhancement. The ontology encompasses three areas. First, a neuroprosthesis may participate in its host’s processes of sensation by (a) detecting stimuli such as photons, sound waves, or chemicals; (b) fabricating sense data, as in the case of virtual reality systems; (c) storing sense data; (d) transmitting sense data within a neural pathway; (e) enabling its host to experience sense data through a sensory modality such as vision, hearing, taste, smell, touch, balance, heat, or pain; or (f) creating mappings of sensory routes – e.g., in order to allow sensory substitution. Second, a neuroprosthesis may participate in processes of cognition by (a) creating a basic interface between the device and the host’s conscious awareness or affecting the host’s (b) perception, (c) creativity, (d) memory and identity, or (e) reasoning and decision-making. Third, a neuroprosthesis may participate in processes of motion by (a) detecting motor instructions generated by the host’s brain; (b) fabricating motor instructions, as in the case of a medical device controlled by software algorithms rather than its host’s volitions; (c) storing motor instructions; (d) transmitting motor instructions, as within a neural pathway; (e) effectuating physical action within effectors such as natural biological muscles and glands, synthetic muscles, robotic actuators, video screens, audio speakers, or wireless transmitters; (f) allowing the expression of volitions through motor modalities such as language, paralanguage, and locomotion; or (g) creating mappings of motor routes. The use of such an ontology allows easier, more systematic, and more robust analysis of the biocybernetic role of a neuroprosthesis within its host-device system.
An Introduction to Advanced Neuroprosthetics
The Handbook of Information Security for Advanced Neuroprosthetics, 2017
This text presents an introduction to neuroprosthetic devices and systems that explores both the state of the art of sensory, motor, and cognitive neuroprostheses that are currently in use as well as more sophisticated kinds of neuroprosthetic technologies that are being actively pursued or that are expected to be developed in the future. This overview takes us from the contemporary world of neuroprostheses that have been designed primarily for purposes of therapeutic treatment of medical disorders and the restoration of natural human abilities lost due to illness or injury to an emerging future world in which neuroprosthetic devices offer the possibility of augmenting and transforming the capacities of their users in such a way that they can perhaps best be described as ‘posthumanizing’ technologies.
Being Machine: Two Competing Models for Neuroprosthesis
(Springer) In: Medicine and Society, New Perspectives in Continental Philosophy (Edited by Darian Meacham), 2015
Some posthumanists see the potential in forthcoming enhancement technologies to alter human beings so much that we would no longer recognize them as members of our species. One sort of enhancement technology are prosthetic devices that would replace or increase normal human functioning, for example computer chips implanted in the brain or robotic arms controlled with our minds. On account of neuroplasticity, our brains would gradually reconfigure themselves so that we may use the prosthesis as though it were biologically a part of us. And, if our bodily organs can be replaced by mechanical counterparts, then piece-by-piece, as our body ages and its malfunctioning parts are replaced, one might gradually become less a human and more a machine, and one with extraordinary non-human abilities. There are even developments in brain simulation that could allow a computer to handle the functioning of large parts of one’s brain, opening the possibility that one’s whole brain might be “uploaded” to continue performing its functions on a computer connected to a robotic body. If the process of body-part replacement were slow and gradual enough that our minds and bodies always have ample opportunity to adjust to the new prosthetic devices, is it not conceivable that we could make a complete and continuous transition from human to machine using these technologies? Andy Clark’s and David Chalmers’ “extended mind hypothesis” provides a theoretical account for our bodily and cognitive extension into external technologies, and Clark as well as therapeutic prosthetic researchers draw from Merleau-Ponty’s philosophy of the body to explain how such devices become a part of our body schemas. But, is Merleau-Ponty’s “organic” view of the body really the best theoretical framework to explain how our bodies are becoming more and more robotic? I will argue instead that Deleuze’s and Guattari’s “machinic” model is a more promising theoretical basis for the notion of posthuman enhancement and also for successful therapeutic prosthesis usage.
Neuroprosthetics: from sensorimotor to cognitive disorders
Communications Biology
Neuroprosthetics is a multidisciplinary field at the interface between neurosciences and biomedical engineering, which aims at replacing or modulating parts of the nervous system that get disrupted in neurological disorders or after injury. Although neuroprostheses have steadily evolved over the past 60 years in the field of sensory and motor disorders, their application to higher-order cognitive functions is still at a relatively preliminary stage. Nevertheless, a recent series of proof-of-concept studies suggest that electrical neuromodulation strategies might also be useful in alleviating some cognitive and memory deficits, in particular in the context of dementia. Here, we review the evolution of neuroprosthetics from sensorimotor to cognitive disorders, highlighting important common principles such as the need for neuroprosthetic systems that enable multisite bidirectional interactions with the nervous system.
Neuroprostheses for increasing disabled patients' mobility and control
PubMed, 2012
Neuroprostheses are electronic devices using electrophysiological signals to stimulate muscles, electronic/ mechanical devices such as substitutes for limbs or parts of limbs, or computers. The development of neuroprostheses was possible thanks to advances in understanding of the physiology of the human brain and in the capabilities of hardware and software. Recent progress in the area of neuroprosthetics may offer important breakthroughs in therapy and rehabilitation. New dedicated solutions for disabled people can lead to their increased participation in social, educational and professional areas. It is worth focussing particular attention on new solutions for people with paralysis, people with communication disorders and amputees. This article aims at investigating the extent to which the available opportunities are being exploited, including current and potential future applications of brain-computer interfaces.
Neuroprosthesis: A Step Towards Complete Control Over Prosthetic Limbs
2017
The paper proposes an alternative to Bionic Prosthetics, which can be advancement in the field of Neuroprosthetics, using the user’s brain wave. It uses WBCI and organic opto-electronic muscle contracting sensor to interface the brain with the basic bionic arm making the mobility of amputees easier. This paper also proposes the usage and importance of “phantom limb syndrome” for replicating sensations and for creating an interface between both brain and technology.[4]
Neuroprosthetics and the science of patient input
Experimental Neurology, 2017
Safe and effective neuroprosthetic systems are of great interest to both DARPA and CDRH, due to their innovative nature and their potential to aid severely disabled populations. By expanding what is possible in human-device interaction, these devices introduce new potential benefits and risks. Therefore patient input, which is increasingly important in weighing benefits and risks, is particularly relevant for this class of devices. FDA has been a significant contributor to an ongoing stakeholder conversation about the inclusion of the patient voice, working collaboratively to create a new framework for a patient-centered approach to medical device development. This framework is evolving through open dialogue with researcher and patient communities, investment in the science of patient input, and policymaking that is responsive to patient-centered data throughout the total product life cycle. In this commentary, we will discuss recent developments in patientcentered benefit-risk assessment and their relevance to the development of neural prosthetic systems.
Exploiting co-adaptation for the design of symbiotic neuroprosthetic assistants
Neural Networks, 2009
The success of brain-machine interfaces (BMI) is enabled by the remarkable ability of the brain to incorporate the artificial neuroprosthetic 'tool' into its own cognitive space and use it as an extension of the user's body. Unlike other tools, neuroprosthetics create a shared space that seamlessly spans the user's internal goal representation of the world and the external physical environment enabling a much deeper human-tool symbiosis. A key factor in the transformation of 'simple tools' into 'intelligent tools' is the concept of co-adaptation where the tool becomes functionally involved in the extraction and definition of the user's goals. Recent advancements in the neuroscience and engineering of neuroprosthetics are providing a blueprint for how new co-adaptive designs based on reinforcement learning change the nature of a user's ability to accomplish tasks that were not possible using conventional methodologies. By designing adaptive controls and artificial intelligence into the neural interface, tools can become active assistants in goal-directed behavior and further enhance human performance in particular for the disabled population. This paper presents recent advances in computational and neural systems supporting the development of symbiotic neuroprosthetic assistants.