Grants and Contributions:

Title:
Elucidating the principles behind neural processing with application to neuromodulation and implant design
Agreement Number:
RGPIN
Agreement Value:
$120,000.00
Agreement Date:
May 10, 2017 -
Organization:
Natural Sciences and Engineering Research Council of Canada
Location:
Ontario, CA
Reference Number:
GC-2017-Q1-03417
Agreement Type:
Grant
Report Type:
Grants and Contributions
Additional Information:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

Recipient's Legal Name:
Wong, Willy (University of Toronto)
Program:
Discovery Grants Program - Individual
Program Purpose:

With current imaging technology and instrumentation, there is a wealth of information that can be obtained from the human brain. But how do we best interpret this data to obtain a better understanding of the functioning of the brain both for scientific exploration and for the improvement of human health? A challenge with understanding the language of the brain, or its neural code, is that it is complex in nature. We attempt to tackle this problem by developing new theoretical ideas and applying these approaches to understand and classify brain states in a manner not previously possible. One area of our work has been to better characterize brain electrophysiological signals, where we have been developing new techniques to characterize the state of the human brain. Currently there are no known cures for neurological diseases like Parkinsonism. However through the study of the motor system, we will explore strategies that can improve brain implants and neuromodulation. Support for this research will not only allow better understanding of disease but allow a clearer picture of how the motor system functions. Parallel to this, fundamental work on modelling brain pathway is undergoing. A new technique based on the information transmission of peripheral sensory neurons allows us to understand, perhaps for the very first time, the generic principles by which the brain interprets the world around us. This method uses information theory and complexity theory to provide a quantitative understanding of the sensory system. By investigating sensory information processing, our model may help in the design of visual prosthetic devices which restore eyesight to those with vision loss.