A fundamental but unsolved question in neuroscience is how specific connections between neurons underlie information processing in the cortical circuits. Local circuits in the cerebral cortex consist of tens of thousands of neurons, each making thousands of connections. Perhaps the biggest reason we don't understand these circuits is that we have never been able to reconstruct their actual wiring diagrams. But if we had a partial or even complete wiring diagram, we would also need to know what each neuron in a circuit is doing: its physiology. In this proposal we plan to develop and apply new approaches for large-scale electron microscopy, towards the goal of mapping wiring diagrams of cortical circuits in a functional context. We will use two-photon calcium imaging to see the activity of neurons in a functioning local circuit. We will then use large-scale serial-section electron microscopy to trace circuits in the same piece of cortex. Recent advances in functional imaging and serial-section electron microscopy (EM) allow us to study this difficult problem, but before we can reap the benefits of these approaches, considerable technical work is necessary. Functional imaging with two-photon microscopy is a technically mature field, but approaches for large-scale serial-section EM are still in their infancy. We propose to apply the dual approach of functional imaging followed by high-resolution anatomical imaging-which we have already performed once in a large pilot project-with the goal of improving the technologies specifically for large-scale EM, correlated with functional studies. Our four-year goal is to create a high-throughput system for generating correlated structure/function data sets from the cortex. In particular, we will build a new EM imaging system, a second-generation Transmission EM Camera Array (TEMCA), that will allow us to capture very large three-dimensional data sets (300 to 500 micrometers on a side) in a week, rather than months. We propose to address one class of question: are there subnetworks within each local cortical circuit that process distinct information? But the approach is general and can be applied to a wide range of questions, including clinically relevant ones. Are neural connections disrupted near plaques in Alzheimer's disease? When stem cells incorporate into a circuit, do they form connections that play a functional role? For the first time, these questions should be within our reach. By developing high-throughput methods for large-scale imaging, we will begin to study neural circuits on their own terms: in all of their complexity and with data sets that are in many senses complete.

Public Health Relevance

Many of the neurological and psychiatric diseases with the largest impact on public health-Alzheimer's disease, stroke, epilepsy, and autism-are functional disorders that likely have correlates in disordered brain connections. The proposed studies will characterize the functional connectivity of brain circuits with unprecedented resolution and completeness. In models of functional brain disorders, the approaches we develop will greatly improve our ability to study the relationship between altered connections and functional deficits. NOTE: The purpose of the EUREKA initiative is to foster exceptionally innovative research that, if successful, will have an unusually high impact on the areas of science that are germane to the mission of one or more of the participating NIH Institutes. EUREKA is for new projects. EUREKA is not for the continuation of existing projects. EUREKA is not for support of pilot projects (i.e., projects of limited scope that are designed primarily to generate data that will enable the PI to seek other funding opportunities). Rather, it is anticipated that EUREKA projects will begin and be completed during the funding period. Please provide an overall impact/priority score to reflect your assessment of the likelihood the project will exert a sustained, powerful influence on the research field(s) involved, Significance and Innovation should be the major determinants of your overall impact score. The approach should be evaluated for general feasibility. An application should score poorly if it is clear to the reviewers that the proposed methodology has no probability at all of being successful, either because it is inherently illogical or because the same approach has already been attempted and shown not to be feasible. Remember that unavoidable risk, which is intrinsic to novel and innovative approaches, is expected for these applications and reviewers are instructed that the presence or absence of preliminary data should not be taken into account when determining the score. Disclaimer: Please note that the following critiques were prepared by the reviewers prior to the Study Section meeting and are provided in an essentially unedited form. While there is opportunity for the reviewers to update or revise their written evaluation, based upon the group's discussion, there is no guarantee that individual critiques have been updated subsequent to the discussion at the meeting. Therefore, the critiques may not fully reflect the final opinions of the individual reviewers at the close of group discussion or the final majority opinion of the group. Thus the Resume and Summary of Discussion is the final word on what the reviewers actually considered critical at the meeting.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS075436-03
Application #
8452709
Study Section
Special Emphasis Panel (ZNS1-SRB-B (26))
Program Officer
Gnadt, James W
Project Start
2011-07-15
Project End
2013-06-30
Budget Start
2013-05-01
Budget End
2013-06-30
Support Year
3
Fiscal Year
2013
Total Cost
$269,343
Indirect Cost
$110,468
Name
Harvard University
Department
Biology
Type
Schools of Medicine
DUNS #
047006379
City
Boston
State
MA
Country
United States
Zip Code
02115
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
Reid, R Clay (2012) From functional architecture to functional connectomics. Neuron 75:209-17