Any given neuron is continuously bombarded with thousands of synaptic inputs and responds by firing patterns of action potentials. This input-output transformation is the basis for neuronal feature selectivity, including the spatial tuning of hippocampal place cells. We would like to understand how learning impacts the input-output-transformations of neurons, changes their feature selectivity, and, ultimately, shapes neuronal ensemble activity. As a result, we are particularly interested in the activity of dendrites, these intricate structures where neurons receive the majority of their synaptic inputs.

Internal representations of the external world are produced throughout the mammalian brain by the activity of many thousands of neurons, each responding to diverse environmental features. During learning representations in the hippocampus are thought to form a cellular memory, which can be recruited in the future to guide behavior. However, the nature of the neuronal code remains unsolved; How are representations embedded within hippocampal circuits used by the brain to produce learned behaviors? What are the cellular and circuit-level computations used to create and maintain these representations?

Alzheimer’s disease is a disorder identified by the abnormal accumulation of amyloid-ß and tau protein in the brain. There is increasing evidence that functional circuit disruptions are among the early effects of Alzheimer’s and occur prior to the large-scale death of neurons that accompanies late-stage dementia. We are interested in understanding how early-stage Alzheimer’s impacts neuronal representations in the entirhinal-hippocampal circuit.