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Multiterabyte electron microscopy image volumes containing the neuronal circuits of interest are generated using high-throughput electron microscopy of serial thin sections. The arbors of selected neurons and the synaptic connections between them are then mapped, and the resulting 'wiring diagram' is analyzed in the context of circuit function.

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Connectivity between neurons is established by tracing the axons, dendrites, and synapses through the imaged volume, and patterns of connectivity are compared with the functional properties of the neurons in the circuit. In this way, the relationship between how neuronal circuits process information and how their constituent neurons are connected to one another can be explored.

We currently use large-scale, high-throughput transmission electron microscopy (EM) of serial thin (<50 nm) sections of brain tissue, followed by reconstruction of the neurons within the EM-imaged volume, to map the anatomical connectivity of a set of neurons.

The advantage of EM is that it can resolve both the "wires" between neurons—their axons, dendrites, and dendritic spines—and the connections between the wires, which are composed of chemical synapses and gap junctions. The method used to prepare neural tissue for EM labels cellular membrane in a complete and unbiased fashion. This means that, in principle, we can start at a given "seed" neuron in an EM-imaged volume and trace out its complete dendritic and axonal arbors and, in the process, note all sites of input and output to the cell (chemical and electrical synapses).

The tracing process can be continued iteratively. The pre- or postsynaptic partners of the seed neuron can be reconstructed, and then their partners, and so on, until the connectivity underlying a given circuit has been mapped out. (This mapping strategy is similar to how Web crawlers deployed by search engine companies chart the connectivity of the World Wide Web, by traversing from one Web page to the next.) A key output of the tracing effort is a graph, in the mathematical sense, with neurons represented by vertices and connections represented as edges. Pairwise and higher order connectivity patterns can be extracted from the graph and related to cell type, neural geometry, and most importantly, function: the physiological properties of the neurons in the graph, and information processing at the level of the circuit.

The method for obtaining functional information about the neurons in a given circuit depends on the species and the specific physiological parameters of interest. My past work in Clay Reid's lab at Harvard Medical School (now at the Allen Brain Institute), in collaboration with other members of the lab and researchers in the Center for Brain Science at Harvard and the Pittsburgh Supercomputing Center, provides an early proof-of-principle of combined network anatomy and function in mouse primary visual cortex. We used in vivo two-photon calcium imaging to characterize the preferred stimulus orientations of a group of neurons in layer 2/3 of visual cortex. We then prepared the tissue for EM and cut serial thin sections through the cluster of physiologically characterized cells.

We imaged the thin sections using a custom high-throughput transmission electron microscope camera array (TEMCA1). This resulted in a 10-terabyte EM-imaged volume, with each section represented by a 120,000 × 80,000 pixel composite image (4 nm/pixel), encompassing about 450 × 350 × 50 micrometers of brain tissue. This volume was sufficiently large that we could construct the proximal portions of the axonal and dendritic arbors of the physiologically characterized neurons. We then traced all the dendrites postsynaptic to the physiologically characterized cells' axons, and examined the patterns of convergence by similarly and differently tuned cells onto their post-synaptic targets. In this way we were able to explore whether a relationship existed between the structure of this partial connectivity graph of visual cortex and the orientation tunings of the cells within it.
Our prototype effort revealed a number of technical limitations.

Foremost was the size of the EM-imaged volume. Although it was unusually large by historical standards, it was just barely big enough to contain some interesting cortical circuitry. Currently, the lab has three dedicated FEI T12 electron microscopes. Two host next-generation camera arrays, which acquire data at ~6x the rate of TEMCA1; the third hosts a prototype 'autoloader' allowing for 24-7 unattended fast imaging and sample exchange. The goal of this infrastructure development is to allow significantly larger volumes of neural tissue (large enough, for example, to span all the cortical laminae, or the complete brain of the fruit fly or zebrafish), to be imaged in a few months' time. We also continue to collaborate for the development of tools for efficient manual and semi-automated tracing of subsets of neural circuitry contained in our multi-terabyte EM image volumes.

Overall, our goal is to explore the extent to which anatomical connectivity can be related to the functional properties of a circuit. Although it is unlikely that an anatomical correlate can be found to all of a circuit's physiological properties, knowing the structure of a circuit's connectivity will likely constrain hypotheses about how the circuit processes information, generate new hypotheses, and help guide new experimental work.