Electron microscopy (EM) allows for the reconstruction of dense neuronal connectomes but suffers from low throughput, limiting its application to small numbers of reference specimens. We developed a protocol and analysis pipeline using tissue expansion and lattice light-sheet microscopy (ExLLSM) to rapidly reconstruct selected circuits across many samples with single synapse resolution and molecular contrast. We validate this approach in Drosophila, demonstrating that it yields synaptic counts similar to those obtained by EM, can be used to compare counts across sex and experience, and to correlate structural connectivity with functional connectivity. This approach fills a critical methodological gap in studying variability in the structure and function of neural circuits across individuals within and between species.

To successfully perform goal-directed navigation, animals must know where they are and what they are doing—e.g., looking for water, bringing food back to the nest, or escaping from a predator. Hippocampal neurons code for these critical variables conjunctively, but little is known about how this where/what code is formed or flexibly routed to other brain regions. To address these questions, we performed intracellular whole-cell recordings in mouse CA1 during a cued, two-choice virtual navigation task. We demonstrate that plateau potentials in CA1 pyramidal neurons rapidly strengthen synaptic inputs carrying conjunctive information about position and choice. Plasticity-induced response fields were modulated by cues only in animals previously trained to collect rewards based on these cues. Thus, we reveal that gradual learning is required for the formation of a conjunctive population code, upstream of CA1, while plateau-potential-induced synaptic plasticity in CA1 enables flexible routing of the code to downstream brain regions.

To successfully perform goal-directed navigation, animals must know where they are and what they are doing-e.g., looking for water, bringing food back to the nest, or escaping from a predator. Hippocampal neurons code for these critical variables conjunctively, but little is known about how this "where/what" code is formed or flexibly routed to other brain regions. To address these questions, we performed intracellular whole-cell recordings in mouse CA1 during a cued, two-choice virtual navigation task. We demonstrate that plateau potentials in CA1 pyramidal neurons rapidly strengthen synaptic inputs carrying conjunctive information about position and choice. Plasticity-induced response fields were modulated by cues only in animals previously trained to collect rewards based on available cues. Thus, we reveal that gradual learning is required for the formation of a conjunctive population code, upstream of CA1, while plateau-potential-induced synaptic plasticity in CA1 enables flexible routing of the code to downstream brain regions.

A key challenge when imaging living cells is how to noninvasively extract the most spatiotemporal information possible. Unlike popular wide-field and confocal methods, plane-illumination microscopy limits excitation to the information-rich vicinity of the focal plane, providing effective optical sectioning and high speed while minimizing out-of-focus background and premature photobleaching. Here we used scanned Bessel beams in conjunction with structured illumination and/or two-photon excitation to create thinner light sheets (<0.5 μm) better suited to three-dimensional (3D) subcellular imaging. As demonstrated by imaging the dynamics of mitochondria, filopodia, membrane ruffles, intracellular vesicles and mitotic chromosomes in live cells, the microscope currently offers 3D isotropic resolution down to \~{}0.3 μm, speeds up to nearly 200 image planes per second and the ability to noninvasively acquire hundreds of 3D data volumes from single living cells encompassing tens of thousands of image frames.

A key challenge when imaging living cells is how to noninvasively extract the most spatiotemporal information possible. Unlike popular wide-field and confocal methods, plane-illumination microscopy limits excitation to the information-rich vicinity of the focal plane, providing effective optical sectioning and high speed while minimizing out-of-focus background and premature photobleaching. Here we used scanned Bessel beams in conjunction with structured illumination and/or two-photon excitation to create thinner light sheets (<0.5 μm) better suited to three-dimensional (3D) subcellular imaging. As demonstrated by imaging the dynamics of mitochondria, filopodia, membrane ruffles, intracellular vesicles and mitotic chromosomes in live cells, the microscope currently offers 3D isotropic resolution down to \~{}0.3 μm, speeds up to nearly 200 image planes per second and the ability to noninvasively acquire hundreds of 3D data volumes from single living cells encompassing tens of thousands of image frames.

Commentary: Plane illumination microscopy has proven to be a powerful tool for studying multicellular organisms and their development at single cell resolution. However, the light sheets employed are usually too thick to provide much benefit for imaging organelles within single cultured cells. Here we introduce the use of scanned Bessel beams to create much thinner light sheets better suited to long-term dynamic live cell imaging. Such light sheets not only minimize photobleaching and phototoxicity at the sub-cellular level, but also provide axial resolution enhancement, yielding isotropic three dimensional spatial resolution. Numerous movies are provided to demonstrate the wealth of 4D information (x,y,x,t) that can be obtained from single living cells by the method. Besides providing an attractive alternative to spinning disk, AOD-driven, or line scan confocal microscopes for high speed live cell imaging, the Bessel microscope might serve as a valuable platform for superresolution microscopy (PALM, structured Illumination, or RESOLFT), since confinement of the excitation to the focal plane makes far better use of the limited fluorescence photon budget than does the traditional epi-illumination configuration.

Inducible and reversible perturbation of the activity of selected neurons in vivo is critical to understanding the dynamics of brain circuits. Several genetically encoded systems for rapid inducible neuronal silencing have been developed in the past few years offering an arsenal of tools for in vivo experiments. Some systems are based on ion-channels or pumps, others on G protein coupled receptors, and yet others on modified presynaptic proteins. Inducers range from light to small molecules to peptides. This diversity results in differences in the various parameters that may determine the applicability of each tool to a particular biological question. Although further development would be beneficial, the current silencing tool kit already provides the ability to make specific perturbations of circuit function in behaving animals.

We have conducted a genetic screen for mutations that decrease the effectiveness of signaling by a protein tyrosine kinase, the product of the Drosophila melanogaster sevenless gene. These mutations define seven genes whose wild-type products may be required for signaling by sevenless. Four of the seven genes also appear to be essential for signaling by a second protein tyrosine kinase, the product of the Ellipse gene. The putative products of two of these seven genes have been identified. One encodes a ras protein. The other locus encodes a protein that is homologous to the S. cerevisiae CDC25 protein, an activator of guanine nucleotide exchange by ras proteins. These results suggest that the stimulation of ras protein activity is a key element in the signaling by sevenless and Ellipse and that this stimulation may be achieved by activating the exchange of GTP for bound GDP by the ras protein.

Neurophysiology has long progressed through exploratory experiments and chance discoveries. Anecdotes abound of researchers setting up experiments while listening to spikes in real time and observing a pattern of consistent firing when certain stimuli or behaviors happened. With the advent of large-scale recordings, such close observation of data has become harder because high-dimensional spaces are impenetrable to our pattern-finding intuitions. To help ourselves find patterns in neural data, our lab has been openly developing a visualization framework known as “Rastermap” over the past five years. Rastermap takes advantage of a new global optimization algorithm for sorting neural responses along a one-dimensional manifold. Displayed as a raster plot, the sorted neurons show a variety of activity patterns, which can be more easily identified and interpreted. We first benchmark Rastermap on realistic simulations with multiplexed cognitive variables. Then we demonstrate it on recordings of tens of thousands of neurons from mouse visual and sensorimotor cortex during spontaneous, stimulus-evoked and task-evoked epochs, as well as on whole-brain zebrafish recordings, widefield calcium imaging data, population recordings from rat hippocampus and artificial neural networks. Finally, we illustrate high-dimensional scenarios where Rastermap and similar algorithms cannot be used effectively.

We investigate a practical approach to solving one instantiation of a distributed hypothesis testing problem under severe rate constraints that shows up in a wide variety of applications such as camera calibration, biometric authentication and video hashing: given two distributed continuous-valued random sources, determine if they satisfy a certain Euclidean distance criterion. We show a way to convert the problem from continuous-valued to binary-valued using binarized random projections and obtain rate savings by applying a linear syndrome code. In finding visual correspondences, our approach uses just 49% of the rate of scalar quantization to achieve the same level of retrieval performance. To perform video hashing, our approach requires only a hash rate of 0.0142 bpp to identify corresponding groups of pictures correctly.

We investigate a practical approach to solving one instantiation of a distributed hypothesis testing problem under severe rate constraints that shows up in a wide variety of applications such as camera calibration, biometric authentication and video hashing: given two distributed continuous-valued random sources, determine if they satisfy a certain Euclidean distance criterion. We show a way to convert the problem from continuous-valued to binary-valued using binarized random projections and obtain rate savings by applying a linear syndrome code. In finding visual correspondences, our approach uses just 49% of the rate of scalar quantization to achieve the same level of retrieval performance. To perform video hashing, our approach requires only a hash rate of 0.0142 bpp to identify corresponding groups of pictures correctly.