Cellular-based Mechanisms Underlying Oscillatory Brain Dynamics

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How does the brain work? Rhythmic brain activities are a common feature in brain recordings and there is now much evidence indicating that the generation of these rhythms in our brain circuits is a way in which our brains work to organize information. However, it is far from clear how these rhythms are generated. The complex networks of the brain are a challenge to appreciate because of the multi-scale nature of the brain along with its myriad of biological details. Mathematical models are strongly needed to help us tackle this complexity, but experimental interactions with our models need to be clear if we are to achieve an understanding of the biological system, and not only the mathematical model system. The long-term goal of my lab is to determine cellular-based mechanisms underlying oscillatory network dynamics, and we do this by combining theory, experiment and modeling at initial stages of the research. It is important to note that determining a cellular-based understanding is critical as we know that cell specifics matter. In this proposal I focus on particular rhythms in particular brain structures to allow us to include biological details and to closely interface with experimental studies. Theta (3-12 Hz) and gamma (25-140 Hz) rhythms and combinations of them in a region of the brain called the hippocampus are our focus. This is because these rhythms in the hippocampus are not only known to be essential in memory processing and spatial navigation, but have also been shown to be components of the brain's coding scheme. To understand the generation of these rhythms, we will build computational models of neurons and networks of neurons that are centered on inhibitory cell types since they express a wide diversity and are controllers of these rhythms in specific ways. Our general approach is to closely align our neuronal and neuronal network model development and analyses with data in well-defined experimental contexts. In this way, predictions and hypotheses that arise from our models can be tested. We collaborate with both experimentalists and mathematicians allowing us to have access to experimental data and to be able to harness in depth theory. Given the importance of these rhythms to brain workings, any understanding achieved by our work would be of fundamental interest to the Neuroscience community. As well, it would provide a basis to understand neurological disease when brain circuits go awry and are reflected in modulation of these rhythms.