Director, Department of Neuroengineering
Fatronik-Tecnalia Foundation, San Sebastian, Spain
Co-founder, Neural Engineering Coroporation, MA
Randal DoT A DoT Koene_AT_gmail DoT com
tel: +1-617-418-3045, fax: +1-928-543-5112

“Competition is an inescapable occurrence in the animate and even in the inanimate universe. To give our minds the flexibility to transfer and to operate in different substrates bestows upon our species the most important competitive advantage.”

I am director of the Department of Neuroengineering at Tecnalia, third largest private research organization in Europe, and I am co-founder of the Neural Engineering Corporation of Massachusetts. Prior to this, I was a Prof. at the Center for Memory and Brain of Boston University. My research objective is whole brain emulation, creating the large-scale high-resolution representations and emulations of activity in neuronal circuitry that are needed in patient-specific neuroprostheses.

My professional background includes computational neuroscience, psychology, information theory, electrical engineering and physics. Presently:

• I am organizing neural engineering efforts to obtain and replicate function and structure information that resides in the neural substrate for use in neuroprostheses and neural interfaces.
• The Department of Neuroengineering of the Fatronik-Tecnalia Foundation focuses on research in neuro-adaptive control, with robotics applications, and research in neural recording, interfaces and feedback.
  
• The Neural Engineering Corporation and partners are creating a Virtual Brain Laboratory (VBL) based on NETMORPH (netmorph.org), the computational framework for the simulated morphological development of neuronal circuitry. The VBL will give neuroscientists, neuroengineers and clinicians large-scale high-resolution quantitative tools analogous to the computational tools that have become essential in fields such as genomics, chemistry or the aero-space industry.

These efforts bridge scales and will help determine how significant functions are encoded robustly in neural ensembles, and how those functions can nevertheless depend in specific ways on the detailed biophysics of particular component physiology.