How can we better understand the human brain and use that knowledge to improve cognition, wellbeing and human potential? These are the questions driving the work of Dr Avinash Singh, whose research sits at the intersection of neuroscience, technology and artificial intelligence.
Decoding, augmenting and extending the human brain
At UTS's Human Augmentation Lab, Avinash investigates how the brain responds in natural cognition. By studying these responses, his team aims to map and decode brain activity to develop brain-computer interface technologies that can adapt to our cognitive needs.
“We continuously sense, perceive, plan and make decisions. Now the question is: why does the brain behave in the way it does? That's essentially what I ask in my research at the Human Augmentation Lab. We are trying to understand how we can map and decode the brain activity when there is a mismatch between expectations, actions and outcomes, and how we can use these insights to develop brain-computer interface technologies to adapt and augment,” he explained.
Avinash’s research is structured around three key areas: decode, augment and extend.
The first, decode, focuses on understanding the brain through cognitive neuroscience. Using technologies such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI) and emerging neural interface approaches, Avinash collects and analyses brain data to better understand how the brain processes information and makes decisions.
The second area, augment, explores how these insights might be used to create adaptive technologies that respond to an individual's cognitive state. These systems could help to manage cognitive workload, improve cognitive performance and potentially support people with conditions such as Alzheimer’s disease or ADHD.
The third and most ambitious area, extend, looks beyond restoring or improving existing abilities. Avinash is investigating whether technology can extend human capabilities through innovations such as memory augmentation systems, additional sensory inputs or extra limb and biohybrid neural interfaces that combine neural tissues with silicon-based systems.
“Together, three directions of decode, augment and extend could help to solve some of the biggest challenges in brain science as well as AI. They may provide new approach in advancing brain-computer interface technologies, tackling cognitive decline but also growing issues in AI such as human-AI alignment problem and ultimately, contribute to the development of more capable forms of intelligence.”
Avinash recently published a book, Neural Interface – Bridging Cognitive Neuroscience and Artificial Intelligence, which explores many of these emerging developments and the future of brain-computer interface technologies.
We are trying to understand how we can map and decode the brain activity when there is a mismatch between expectations, actions and outcomes, and how we can use these insights to develop brain-computer interface technologies to adapt and augment.
Looking ahead, Avinash believes this research could play an important role in addressing challenges in both brain science and artificial intelligence. By strengthening the connection between humans and intelligent technologies, he hopes to contribute to a future where human and AI systems can work together more effectively.