Grant: Research Tools and Instruments

Five PIs of the Polaris Brain Dynamics Group at the Canadian Centre for Behavioural Neuroscience (CCBN) at the University of Lethbridge will develop a next-generation, high-throughput, neural recording and behavioral analysis platform that will support experiments now and into the future. These investigators are at the forefront of decoding information from ensembles of neurons recorded in the brain using hand-made devices containing 48-68 wires. However, the yield of neurons is often insufficient for accurate decoding using modern data analytic techniques. Recent manufacturing advances now allow probes to have thousands of recording sites on a silicon shank, which significantly increases neuron yield to enable data-science approaches. The first part of this project will allow us to modernize our infrastructure in order to use these probes. This is necessary for us to adopt machine learning and other modern statistical techniques in order to continue to be leaders in understanding how the brain forms and uses neural representations to process information. Decoding information from neural ensembles requires that we have good control over sensory inputs. We have made important advances in the use of virtual reality (VR) to (1) mimic real-life conditions, (2) introduce manipulations not possible in real-life and (3) exert control over multimodal sensory inputs. This second part of this project will allow us to expand the capacity of our VR apparatus to present visual, auditory, tactile, and olfactory cues, as well as food rewards and air puff punishments, while recording neural activity. This new technology will allow us to record more neurons and better track stimuli and outputs, which are necessary to extract deeper knowledge about how the brain processes information to form memories and make decisions. Furthermore, advances in automated data preprocessing and analysis enabled by the probes will allow experiments to be completed much faster. To accomplish this, the Polaris Brain Dynamics Group will leverage three important competencies: 1) our experience in high-density electrophysiology; 2) our strong background in computational neuroscience and data analysis; and 3) our team of skilled trainees. The proposed RTI grant will enable studies to make discoveries about the mechanisms of learning and memory, decision making, movements, epilepsy, drug addiction, depression, and Alzheimer's disease. This will also give trainees the tools they need to develop successful careers in computational neuroscience, machine learning, and data science.