Grant: Discovery Grants Program - Individual
Dalhousie University
$48,000.00
Can The Analysis Of Large Open-Access Neuroimaging Data Inform The Development Of More Effective Neurofeedback Training Systems?
FY 2022-23
Summary
My research program develops new technology (hardware and software) to aid people to train their brain more effectively. We have developed innovative technology that guides people when they are thinking about a task. The technology provides feedback about how their brain is working. The feedback - provided on an electronic device - gives a second-by-second report about brain activity, called neurofeedback. Neurofeedback might help people to use their brain in a way that will help them learn more effectively. Neurofeedback is particularly important when we are thinking about a task during the learning process because we don't usually get feedback, which is key to learning. Our technology provides that feedback, and helps users to change their brain activity for the better.The problem is that our neurofeedback technology is not as effective as it could be. Our technology assumes that the brain activity that a user generates matches to the pattern that you see if you average a lot of people's brain activity together. This doesn't always work because there is a lot of variability in how different people use their brains. My research program will develop new software to provide personalized neurofeedback that accounts for the variability between users. I will test to see if personalized neurofeedback helps people change their brain activity for the better.My research will also, for the first time, use big data to better understand the signals that we will use when we personalize neurofeedback. This will combine the software that we develop for analyzing brain imaging data with big data using a set of algorithms called machine learning (borrowed from Computer Science). This novel combination has the potential to improve neurofeedback systems by accounting for individual variability, as well as demographic factors like age and gender.A neurofeedback system is only effective if it targets the right signals from a person's brain. My research is focused on making sure that we target the right signals every time. If neurofeedback is more effective, then it will be used by more researchers and companies to help people improve their brains. This has the potential to help people learn better, and to help patients recover better after a stroke or brain injury. I have collaborators that are interested in these applications for my technology. My Discovery Grant research will help them to help people.
Program
Discovery Grants Program - Individual
Recipient
Location
Nova Scotia, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
RGPIN-2018-05470
Name nom
Bardouille, Timothy
Department département
Physics and Atmospheric Science - Physics and Atmospheric Science
Organization id
79
Institution établissement
Dalhousie University
Province en
Nova Scotia
Province fr
Nouvelle-Écosse
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2018
Award amount
48000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1505
Committee name en
Physics
Committee name fr
Physique
Area of application code
1201
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Life sciences (including biotechnology)
Area of application fr
Sciences de la vie (y compris biotechnologie)
Research subject code
3100
Research subject group en
Physics
Research subject group fr
Physique
Research subject en
Physics
Research subject fr
Physique
Installment
inst:5;6
Partie
2
Nb partie
6
Application title
Can The Analysis Of Large Open-Access Neuroimaging Data Inform The Development Of More Effective Neurofeedback Training Systems?
Application summary
My research program develops new technology (hardware and software) to aid people to train their brain more effectively. We have developed innovative technology that guides people when they are thinking about a task. The technology provides feedback about how their brain is working. The feedback - provided on an electronic device - gives a second-by-second report about brain activity, called neurofeedback. Neurofeedback might help people to use their brain in a way that will help them learn more effectively. Neurofeedback is particularly important when we are thinking about a task during the learning process because we don't usually get feedback, which is key to learning. Our technology provides that feedback, and helps users to change their brain activity for the better.The problem is that our neurofeedback technology is not as effective as it could be. Our technology assumes that the brain activity that a user generates matches to the pattern that you see if you average a lot of people's brain activity together. This doesn't always work because there is a lot of variability in how different people use their brains. My research program will develop new software to provide personalized neurofeedback that accounts for the variability between users. I will test to see if personalized neurofeedback helps people change their brain activity for the better.My research will also, for the first time, use big data to better understand the signals that we will use when we personalize neurofeedback. This will combine the software that we develop for analyzing brain imaging data with big data using a set of algorithms called machine learning (borrowed from Computer Science). This novel combination has the potential to improve neurofeedback systems by accounting for individual variability, as well as demographic factors like age and gender.A neurofeedback system is only effective if it targets the right signals from a person's brain. My research is focused on making sure that we target the right signals every time. If neurofeedback is more effective, then it will be used by more researchers and companies to help people improve their brains. This has the potential to help people learn better, and to help patients recover better after a stroke or brain injury. I have collaborators that are interested in these applications for my technology. My Discovery Grant research will help them to help people.