Connectionists: Frontiers in Neurorobotics: 2 open research topics

[Florian Roehrbein]

Topic Title 1: Peripheral Nervous System-Machine Interfaces
Editors: Michael Wininger, Panagiotis Artemiadis, Claudio Castellini, Patrick Pilarski

Abstract: There is an ever-increasing interest in emergent approaches for extracting signatures of neuromuscular volition for high-fidelity operation of prosthetic devices and assistive technologies. In a recent position paper [Castellini 2015], the Peripheral Nervous System-Machine Interface (PNS-MI) workgroup has taken on focal topics driving the field of prosthetic detection and control: Limitations of surface electromyography (sEMG), Opportunities for improvement of sEMG, Alternative prosthetic sensing technologies, and Shared control strategies. One particularly critical barrier to development is the need for greater integration of the clinician and the patient into the work of laboratory-based developers: technology that isn’t conceived, designed, fitted, and instructed to the patients, stands a high risk of disuse and abandonment. In particular, areas of need include: provision of real-time feedback, improved reliability in the face of inherently unstable control signals, expansion of the number of controllable degrees of freedom, and increased sense of embodiment.  
This Research Topic welcomes all types of articles related to novel technologies for control of prosthetic or assistive devices, and places high priority on those articles addressing the areas of need as described above. All types of articles are welcome among those permitted in the Frontiers in Neurorobotics platform.

For submission details see http://journal.frontiersin.org/researchtopic/4614/peripheral-nervous-system-machine-interfaces-pns-mi <http://journal.frontiersin.org/researchtopic/4614/peripheral-nervous-system-machine-interfaces-pns-mi>

Topic Title 2: Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology
Editors: Poramate Manoonpong, Christian Tetzlaff

Abstract: The brain of biological systems is a highly complex and very efficient computing unit. It can deal with a multitude of tasks from low-level sensorimotor coordination to high-level cognition. Specifically, it can process high-dimensional sensory information and, dependent on this, generate coordinated motor commands in real time, resulting in actions (like, locomotion and manipulation). Simultaneously, it can also perform cognitive functions (such as navigation, goal-oriented behavior, reasoning and decision making, interaction, communication). This amazing performance is achieved by using the full capacity of its neural dynamics, learning, memory, and adaptation as well as by interacting with the environment through its body (i.e., sensory-motor system). Thus, actions and cognition require dynamical brain-body-environment interactions and thereby cannot be disembodied. A number of researchers have tried to investigate biological systems to understand principles underlying these complex behaviors and to imitate such performance with artificial systems by using different types of neural computation models in open-loop and closed-loop contexts. However, achieving the level of performance of living creatures remains a grand challenge. According to this, the Research topic welcomes articles that recent neural mechanisms for the generation of complex behavior in embodied closed-loop systems from biological investigations to technical implementations. 

For submission details see http://journal.frontiersin.org/researchtopic/4674/neural-computation-in-embodied-closed-loop-systems-for-the-generation-of-complex-behavior-from-biolo <http://journal.frontiersin.org/researchtopic/4674/neural-computation-in-embodied-closed-loop-systems-for-the-generation-of-complex-behavior-from-biolo>
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