About the headliner speaker: Dr. Colin McNamara is a Senior Research Scientist at the University of Cork. Before that, he was a Sir Henry Wellcome Postdoctoral Fellow at the University of Oxford, completing his research as a part of the Sharott lab. Colin is currently working on developing systems to directly monitor and in real time manipulate specific brain activities using closed-loop systems.

Title of headliner talk: “Manipulation of brain activity through closed-loop interaction”

Abstract: Much research focuses on measuring brain activity to understand function. This has highlighted the importance of timing relationships in neuronal activity. Equally, delivering carefully designed perturbations to the brain has delivered significant insight. However, such perturbations are mostly delivered independent of ongoing brain activity. I posit that precisely aligning perturbations to the structure of ongoing activity can be a powerful tool for understanding brain function and providing interventions to ameliorate pathological activity. I will discuss this philosophy and an approach we developed along with experiments we conducted to achieve this. OscillTrack responds on a cycle-by-cycle basis to deliver stimulation aligned to a user specified phase of a fluctuating neuronal oscillation within a user specified frequency band. We used OscillTrack to stimulate basal ganglia nuclei at predetermined phases of successive cortical beta cycles in parkinsonian rats. We showed it was possible to maintain oscillatory brain activity in a desired state by delivering stimulation accurately aligned with the timing of each cycle. An equilibrium emerged in the feedback-loop between the modified brain signal and resulting stimulation pattern, leading to sustained amplification or suppression of the oscillation depending on the phase targeted. Additionally, beta amplification slowed movement speed by biassing the animal’s mode of locomotion. Our work has demonstrated the feasibility of achieving a stable brain-machine interaction that produces robust modulation of ongoing behaviour. Designing fast feedback interactions to manipulate different aspects of ongoing neuronal activity – to continuously push a brain network toward a desired state – has wide ranging potential in understanding the function and dysfunction of memory, sleep, and other fundamental brain operations.