Project summary: Modern electron-microscopy (EM) imaging and analysis methods permit the comprehensive reconstruction of all neurons and synapses in large volumes of brain tissue or the entire brains of individual organisms. However, relating this structure to function is difficult because of the many biophysical processes that remain unmeasured in EM images. This proposal describes a combined theory and data analysis approach that is informed by large- scale EM datasets in tandem with functional and behavioral recordings collected by our experimental collaborators. These efforts are aimed at developing principled ways to build and benchmark connectome-constrained models. The methods we will develop extend the state of the art by integrating both connectivity data and functional or behavioral recordings. They also offer a principled way of handling uncertainty in the dynamics of individual neurons, which are not constrained by EM data. Our aim is both to develop general and scalable techniques to be used on the latest generation of datasets, as well as apply these techniques to specific scientific questions about the organization of sensory and decision-making pathways in the Drosophila brain. Scalability will ensure the ability to generalize the techniques to future datasets in larger organisms, such as mice. Specific aims of the project include a number of subgoals, starting with the development of techniques to inte- grate recordings of the activity of subsets of neurons, or of behavior driven by this activity, to constrain models beyond what can be done with knowledge solely of connectivity. They also include the development of theoretical approaches for understanding how connectivity information constrains network dynamics, and how uncertainty in such dynamics can be reduced most effectively through neural recordings. Finally, they include techniques targeted specifically toward identifying the encoding of specific variables of interest. The proposed methods will be of interest for researchers working across model organisms for which EM recon- struction efforts have been completed or are currently underway, and for which functional and behavioral data is also available. They provide both a template for integrating these diverse data modalities and benchmarks for assessing the effectiveness of this integration.

Project narrative: Modern electron-microscopy imaging and analysis methods permit the comprehensive reconstruction of all neu- rons and synapses in large volumes of brain tissue or the entire brains of individual organisms. This data is now being paired with functional and behavioral measurements, but how to integrate these new data modalities is not clear. Litwin-Kumar’s group is developing analysis methods to translate the rich anatomical information identified in electron microscopy data into insights about how neural circuits give rise to behavior.