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Enabling Identification and Impact of Synaptic Weight in Functional Networks

Subject Area Molecular Biology and Physiology of Neurons and Glial Cells
Cognitive, Systems and Behavioural Neurobiology
Term since 2020
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 436260754
 
Synapses form trillions of connections between billions of neurons in the brain to establish neural circuits that allow us to sense, think, act, learn, and remember. Synaptic weight is a crucial concept to understand the nervous system, yet its clear definition remains elusive, despite more than a century of searching. This NeuroNex Network assembles world experts to study synapses from molecules to behavior, in order to answer this fundamental and ambitious question: What constitutes synaptic weight and what role does it play in shaping neural circuits? Answering this question requires a major shift away from thinking about synapses as isolated entities. Traditionally, synapses have been treated as on or off switches, that is, one-bit machines. Recent models, based on synapse size as a proxy for synaptic weight, show that this assumption is wrong. In fact, the information content can be much higher, for example, being >4 bits at hippocampal synapses. Synaptic weight is controlled over broad temporal and spatial scales that are dynamically regulated by activity in neural circuits. New evidence points to subcellular resources (endoplasmic reticulum, mitochondria, endosomes, ribosomes) that broker and drive synaptic efficacy and plasticity through mechanisms that regulate local protein synthesis. Thus, an understanding of synaptic weights needs to be addressed at both subcellular and circuit levels. We hypothesize that synaptic weight is defined by the differential composition and co-occurrence of key proteins and subcellular resources. We will use multidisciplinary approaches to assess these features in well-defined states. Comparisons will be made across neural circuits involving multiple cell types, brain regions, and diverse behaviors in several species. Mapping consistent predictors of synaptic state arising from these analyses onto neural connectomes will enhance tremendously our understanding of the roles of synaptic weight in circuit organization and function. To achieve these goals, new technologies are needed to bridge multiple scales in image resolution and to collect sufficiently large tissue volumes to perform circuit level analyses. Our work lays the foundation to propel deeper understanding of brain function and regulation from nanoscale to circuit levels. We envision that future application, beyond the brain, of the knowledge and tools developed here will give rise to data that will address fundamental and potentially novel principles of complex self-organizing systems.
DFG Programme Research Grants
International Connection Canada, United Kingdom, USA
 
 

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