MEMORIES are encoded as enduring physical changes in the brain, and several studies in murine models have identified specific subpopulations of neurons throughout various brain regions whose activity encodes specific features of experiences and correlates to memory formation. According to the Hebbian postulate - often paraphrased as “fire together, wire together” - connections between neurons with highly correlated activity patterns are strengthened while connections between neurons whose activity patterns are weakly correlated are depressed or even lost. In this framework, increased synaptic strength between co-active neurons increases the likelihood for the same spatial-temporal pattern of neural activity that occurred during memory encoding to occur again during retrieval. This hypothesis suggests that synaptic strengthening between coactivated neurons forms the NEURAL SUBSTRATE OF MEMORY. However, the relationship between structural synaptic connectivity and the formation of activity patterns functional to learning and recall is still largely qualitative, which precludes the generation of quantitative mathematical models of memory that would have far reaching implications – for instance - for neuromorphic computing or machine learning.
The goal of my scientific program is to establish quantitative relationships between the changes in synaptic connectivity patterns and the emergence of activity patterns underlying encoding and recall of information. To this aim, my laboratory employs OPTICAL IMAGING TECHNIQUES to probe from the single synapse to the network-level, and combines this with opto- and chemogenetic methods to control the activity of defined neuronal subpopulations. Moreover, we use BEHAVIORAL TASKS to investigate to what extent the neuronal dynamics of structural plasticity or of activity can predict the behavioral outcome at the level of single individuals.
