Season 3, Episode 4: Listening to Neurons with Sumner Norman
First Author: Sumner Norman
Episode Summary: Brain machine interfaces untangle the complex web of neurons firing in our brains and relay the underlying meaning to a computer. These devices are being adapted to help patients regain motor control, monitor our mental well being, and may one day even make us more empathetic. State of the art methods to do this have massive trade-offs, either being high resolution yet requiring devices to be embedded in our heads, or low resolution but non-invasive. Finding a key middle ground, Sumner uses advances in ultrasound to monitor the brain activity of monkeys performing specific tasks. With this data, he can not only record the brain activity associated with performing the task itself but also the intention of doing it before the subject even has a chance to move.
About the Author
Sumner started his career in mechanical and aerospace engineering, performing research on haptics and mechatronics.
This developed in him the love for how humans and computers interact, leading him to earn a PhD developing exoskeleton robots for motor learning and control.
Through this, he realized that to translate these technologies, we need better methods to get information out of the brain.
Key Takeaways
Ultrasound technologies are leveraged to monitor brain activity.
The signal that is generated when these methods “listen” to the brain is extremely complex and entangled, akin to trying to make out a sentence from across a loud stadium.
Sumner taught monkeys how to perform a task, reading the brain with ultrasound and using machine learning to decode the message.
With it, they were able to read which way the monkey intended to move, when the movement would occur, which way the monkey actually moved, and whether it would move its hands or eyes.
Translation
This technology has massive potential to help those suffering from motor impairment and could one day connect us all on a deeper level.
To get there, the device will need to be optimized to find the best way to maximize signal-to-noise but minimize invasiveness.
Additionally, advances in miniaturization, wireless connections, lowered cost of goods, and finding the right balance between AI and BMI control are needed to get this extremely new technology into the hands of everyone.
Paper: Single-trial decoding of movement intentions using functional ultrasound neuroimaging
