Connectionists: CNS 2007 : Workshop

[Mini P Kurian]

Call for Participation:

Workshop on *Neuro-Machine Interfaces: Integrating Biology and Technology to
Develop Functionally Relevant Devices

CNS 2007
Toronto, Canada
July 12,  2007
**http://www.cnsorg.org/cns_meeting_workshops.htm

*

*Description:*
A half-day* *workshop.
Website: http://www.public.asu.edu/~mputhaya/CNS2007Workshop/<http://www.public.asu.edu/%7Emputhaya/CNS2007Workshop/>
**
Neuroprosthetics are artificial extensions that replace or improve the
function of an impaired nervous system.  Some examples of neuroprosthetics
include: cochlear implants, retinal implants, cortical implants, and
functional neuromuscular stimulation (FNS) electrodes.  Neuro-machine
interfaces (NMI) use neuroprosthetics to read signals from neurons and then
computers and algorithms are used to translate those signals into desired
actions.

Successful development of functional neuroprosthetics requires an
interdisciplinary approach, involving experimentalists to understand the
physiology and behavior of the nervous system, engineers to develop adaptive
biocompatible devices, clinicians to implement and study the interaction
between the device and the patient, and computational modelers to integrate
the diverse approaches.

There are still many important issues that must be addressed for NMI
development, such as a need for fully-implantable biocompatible devices,
real-time computational algorithms, efficient neural signal acquisition and
processing, and improved sensory feedback with links to motor output.
Perhaps the most important issue in NMI development is optimizing the
behavior of the combined system (biological and technological) by fully
utilizing the plasticity of the nervous system.

How can computational neuroscience help address these issues?  This workshop
will explore some of the major challenges in interfacing biological adaptive
systems with adaptive NMI devices:

   - Given that the human nervous system is more complex than *in
vitro*preparations and different from
   *in vivo* animal models how do we transform an experimental device
   from a laboratory setting to a clinically relevant device?


   - How can computational neuroscientists help in improving the design
   of experimental devices?  How biologically accurate do models have to be,
   and on what scales, in order to positively contribute to technological
   development?


   - There is a problem in NMI of both too little and too much data.  The
   number of channels available to interact with the nervous system is limited,
   while the amount of raw *voltage vs. time* data acquired from probes
   can be overwhelming.  How can computational neuroscientists help to maximize
   use of limited channel data, while extracting only useful information?


   - How do we incorporate and take advantage of the properties of the
   musculoskeletal system in order to maximize the utility and effectiveness of
   NMI devices?


   - The nervous system is adaptive, so NMI control algorithms have to be
   versatile enough to accommodate this plasticity.  How can we design NMI
   control algorithms that promote adaptive plasticity in the nervous system
   throughout the time course of that adaptation?

* **Structure:*

This will be a half-day workshop, consisting of two or three invited talks,
additional short presentations, and a panel discussion.  Attendance is open
to all CNS attendees.

Those interested in presenting are invited to contact the workshop
organizer.
*Contact*: kurian at mathpost.la.asu.edu
*Organizers:*
Mini Kurian1, 4, Joe Graham 2, 4, Sharon Crook1, 3, 4, Ranu Jung2, 4
1Department of Mathematics and Statistics
2Harrington Department of Bioengineering
3School of Life Science
4Center for Adaptive Neural Systems at the Biodesign Institute
Arizona State University