Our brains contain billions of neurons, each with thousands of synapses. Together, they form a functional neural network with trillions of connections. Its scale and complexity is daunting, but from this complexity emerges perception and behavior. How do we understand the organization of such an immense and complex network? A key path forward is investigating the relationship between structure and function in neuronal circuits. The function of a neuron is fundamentally dependent on how it is connected. Therefore, understanding the relationship between circuit structure - connectivity - and cellular function will help us understand how neurons and networks process information. Unfortunately, detailed connectivity mapping remains difficult. One critical barrier is data throughput. Recently, high-throughput transmission electron microscopy (TEM) has increased the speed of imaging, but continues to rely on humans for laborious manual sample collection and handling. Current methods of automated sectioning can collect thousands of electron microscopy (EM) samples on a tape substrate, but are incompatible with fast TEM imaging because the tape prevents transmission of an electron beam. Serial sections collected in this manner are currently imaged using scanning EM, which is typically slower. This proposal aims to develop novel technologies that synergistically bridge automated sample collection and high-speed TEM imaging to transcend the throughput barrier. We will generate a novel tape substrate for sample collection that is compatible with TEM imaging and use it to collect thousands of serial thin sections. Additionally, we will engineer and build a sample stage for continuous TEM imaging of tape-collected samples. These methods would allow high-quality EM imaging of local mammalian cortical circuits to be completed in ~1 year compared to more than 100 years with conventional approaches. We expect that the routine generation of larger, high-quality datasets using these novel techniques will also accelerate advances in their analyses. We will immediately use this approach to increase our understanding of the fundamental principles underlying cortical processing and organization. Furthermore, with higher- throughput EM imaging, we will finally be poised to compare diseased and healthy brains to assess how circuit connectivity is altered, thereby directing intelligent treatment strategies.

Public Health Relevance

The goal of this proposal is to develop novel technology to break the throughput barrier of electron microscopy data acquisition. With these new methods and instrumentation, we aim to discover rules underlying connectivity between neurons and neuronal networks in the brain. Understanding the basic principles of neuronal connectivity and their relationship to function will help reveal how the brain is altered in neurodegenerative disorders such as schizophrenia, autism, and Alzheimer's disease and point toward strategies remedy them.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Exploratory/Developmental Grants (R21)
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Talley, Edmund M
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Harvard Medical School
Schools of Medicine
United States
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Hildebrand, David Grant Colburn; Cicconet, Marcelo; Torres, Russel Miguel et al. (2017) Whole-brain serial-section electron microscopy in larval zebrafish. Nature 545:345-349
Lee, Wei-Chung Allen; Bonin, Vincent; Reed, Michael et al. (2016) Anatomy and function of an excitatory network in the visual cortex. Nature 532:370-4