NeuroNex: Enabling Identification and Impact of Synaptic Weight in Functional Networks

University Of Texas At Austin, Austin TX

Investigators

Abstract

Trillions of synapses connect billions of neurons in neural circuits that allow sensation, thought, action, learning, and memory. This NeuroNex Network involves the development of new approaches to determine the strength of connections between neurons—synaptic weight--in the brain. Understanding synaptic weight is crucial, yet even a clear definition remains elusive, despite more than a century of searching. This NeuroNex Network assembles world experts to study synapses from molecules to behavior, to answer this fundamental and ambitious question: What constitutes synaptic weight, and what role does it play in shaping neural circuits? Synaptic weight is hypothesized to involve the differential composition and co-occurrence of key proteins and subcellular resources. Multidisciplinary approaches are used to assess these features in well-defined states of neural circuits involving multiple cell types, brain regions, and diverse behaviors. Consistent predictors of synaptic state are mapped onto neural connectomes to enhance understanding of how synaptic weight influences circuit organization and function. New electron microscopy technologies developed and used in this project bridge gaps in image size and resolution needed to achieve deeper understanding of brain function and regulation from nanoscale to circuit levels. A long-lasting, far-reaching impact involves leveraging work from this NeuroNex Network with other BRAIN Initiative projects to enable acquisition and sharing of the new knowledge. Future applications, even beyond the brain, of the knowledge and tools developed here will give rise to data that address fundamental and novel principles of complex self-organizing systems. The NeuroNex Network also involves training the next generation, including through inter-laboratory and fellow exchanges. What constitutes synaptic weight, what role does it play in shaping neural circuits, and how does it change during growth and plasticity? Answers require a shift away from thinking about synapses as isolated entities. Synapses are not simply on or off one-bit machines; instead the information content stored in synapse size, as a proxy for weight, is much higher. Synaptic weight is controlled over broad temporal and spatial scales dynamically regulated by neural activity. New evidence points to subcellular resources (endoplasmic reticulum, mitochondria, endosomes, ribosomes) as brokers that drive synaptic efficacy and plasticity. This project seeks to understand how synapse composition and structure predict synaptic weight and function at a scale that reveals biological mechanisms at the subcellular level. A new 3D electron microscopy (EM) approach is developed using conical tilt tomography on the scanning EM operating in the transmission mode (tomoSEM). TomoSEM fills the current resolution-to-volume gap between methods of structural biology (high resolution, small volumes) and connectomics (relatively low resolution, larger volumes). TomoSEM eliminates major artifacts of other EM methods while reducing human effort and cost. The investigators comprise world experts in protein chemistry, cell biology, connectomics, and behavior. Experts in EM implement, validate, and deploy tomoSEM. Experts in image analysis, geometry, statistics, machine learning, and multilevel modeling create platforms to search data for hidden order. These strategies share international resources to overcome limits of accumulating data locally one synapse at a time. This project is co-funded by Emerging Frontiers in the Directorate for Biological Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.