Using SEEG Data to Decode Brain Activity for Decision-Making: Alexander C. Whiting, MD

WATCH TIME: 4 minutes

“For patients with seizures, we can implant a device called a responsive neurostimulator. We place an electrode in a specific part of the brain, and it listens constantly. When it detects the beginning of a seizure, it can stop it before it starts. Why couldn’t we do something similar for other diseases?”

Stereoelectroencephalography (SEEG) is a cutting-edge technique that has revolutionized the treatment and understanding of neurological conditions such as epilepsy. At Allegheny Health Network’s Neuroscience Institute, neurosurgeon Alexander Whiting, MD, and colleagues typically use robotic SEEG to implant electrodes in the brains of patients with drug-resistant epilepsy to identify the precise areas responsible for seizures. This innovative approach not only guides surgical interventions but also opens doors to exploring the brain's intricate risk-reward and decision-making circuits, offering profound insights into the neural underpinnings of human behavior.

Recently, Whiting has expanded his SEEG research to investigate decision-making and impulse control through structured neuropsychological tests conducted in the epilepsy monitoring unit. By mapping brain activity during tasks, the researchers can possibly uncover correlations between behavior and neural communication. In collaboration with Pulkit Grover, PhD, professor of electrical and computer engineering at Carnegie Mellon University, both experts aim to use advanced machine learning to analyze vast data sets that may reveal complex networks of brain circuits involved in risk-reward decision-making. The clinical implications of this research could offer potential pathways to develop interventions for other conditions involving the brain, not just epilepsy.

To delve deeper into the groundbreaking potential of SEEG and its broader implications, NeurologyLive® spoke with Whiting, the director of epilepsy surgery at Allegheny Health Network, in a recent interview. In the conversation, he shed light on how integrating machine learning can possibly transform the analysis of brain activity, the ethical challenges of expanding neurostimulation treatments beyond epilepsy, and how advancements in brain signal mapping could revolutionize care for conditions like addiction, obsessive-compulsive disorder, and treatment-resistant depression. Overall, Whiting’s clinical insights from his experience using SEEG offer a compelling glimpse into the future of neuroscience and personalized medicine.

REFERENCES
1. Can you hear the sounds of the brain’s risk-reward circuitry?. Nature Research. Published October 16, 2024. Accessed December 12, 2024. https://www.nature.com/articles/d42473-024-00212-1