Why cognitive effects such as memory loss and ageing go hand in hand is only recently beginning to be understood.
‘Thinkers And Innovators’: What It Will Take To Figure Out The Brain, From A Neuroscience And AI Pioneer
Terrence Sejnowski is a professor at the Salk Institute and a pioneer in computational neuroscience and artificial neural networks.
What does nanotechnology offer the study of the brain and neuroscience? The answer, in fact, is quite a lot.
Sscientists need to better understand how the physiology of the body will be affected by the travel conditions of space over prolonged periods.
We will never be able to understand how the brain works without the use of mathematics and related applied fields of physics and engineering.
With the integration of machine learning, BMIs may one day be able to anticipate the contextual needs of situations a patient finds themselves in.
The link between mathematics, engineering, and neuroscience will only continue to become ever more stronger. It has to.
The physical constraints imposed on the brain guide the construction of mathematical models for insights about how the brain works.
Machine learning and AI can provide opportunities to create “smart” BMI that contextually learn and adapt to changing functional requirements.
AI and neuroscience share can advance research, achieving new levels of ability for computers and understanding of natural brains.