My laboratory studies the structural properties of dendrites that allow them to implement computational functions to process information and store memories. The influence of dendritic structure on the electrical properties of neurons has been intensely studied over 50 years; however, the question of how dendritic structure affects biochemical computation remains a very open topic of research. For example, from my work as well as the work of others in the field, it is now clear that not only the physical structure of dendrites, but also their cytosolic structure and organization affect computation. My research therefore addresses dendritic structure over a wide range of spatial scales, from nanoscopic to the whole dendrite.

At present, our work is specifically focused on understanding how dendritic structure controls the reliability and specificity of the biochemical signals that underlie synaptic activity and plasticity. This is an important problem because it is not yet understood how the relatively low numbers of molecules in a synapse can support reliable memory storage especially given the inherently noisy nature of biochemical cascades. Our recent work has specifically shown that the complexity of dendritic structure, quantified by the diversity and density of dendritic spines, modifies the diffusional environment of dendrites by breaking down the classical laws of diffusion, a phenomenon known as anomalous diffusion. We have predicted and experimentally corroborated how spine density maps to the level of anomalous diffusion in Purkinje and hippocampal pyramidal cells. The biological implications of this break-down are that the reaction rates that were assumed to be noisy at low concentrations may actually be much more efficient than previously expected, resulting in more reliable synapses.

Each of our efforts has been undertaken using combined and interacting computational, theoretical, and experimental approaches in order to develop a unified framework to understand how dendritic structure affects biochemical processing. We believe that this framework can be applied at multiple scales, from glutamate receptors moving in and out of the synapse, to large scale heterogeneous networks of spiking neurons