How do we study visual memory?

To understand the neural basis of visual memory, our lab employs a number of different approaches. These include investigations of human and animal visual memory behaviors, measurements and manipulations of neural activity, and computational modeling. Our overarching goal is to understand how our brain stores visual memories at multiple levels of explanation.

Information processing: We are interested in algorithmic (or mathematical) descriptions of the brain's learning rules as well as descriptions of how populations of neurons signal visual memory percepts. To arrive at these descriptions, we execute thoughtfully designed behavioral and neural experiments, and use that data to constrain computational models. To account for the rich visual detail with which visual memories are stored, our modeling approaches extend contemporary models of visual processing (which describe how your brain determines what you are looking at) to also account for memory. Our modeling approaches are designed to both capture the rich, high-dimensional nature of visual memory as well as produce intuitive descriptions about how visual memory works.

Biophysical implementation: One intriguing thing that distinguishes visual memory is the fact that the locus at which visual memories are stored is unlikely to be the same location where the brain signals the percept "I've seen this before". As such, you can't simply point to the patterns of spiking activity across a population and infer that you've found the locus for memory. A non-trivial understanding of where and how visual memories are stored requires targeting the circuit and synaptic mechanisms responsible for memory storage. One important emphasis of our work is linking these biophysical descriptions to behavior via computational models.