Spatial navigation is often used as a behavioral task in studies of the neuronal circuits that underlie cognition, learning and memory in rodents. The combination of in vivo microscopy with genetically encoded indicators has provided an important new tool for studying neuronal circuits, but has been technically difficult to apply during navigation. Here we describe methods for imaging the activity of neurons in the CA1 region of the hippocampus with subcellular resolution in behaving mice. Neurons that expressed the genetically encoded calcium indicator GCaMP3 were imaged through a chronic hippocampal window. Head-restrained mice performed spatial behaviors in a setup combining a virtual reality system and a custom-built two-photon microscope. We optically identified populations of place cells and determined the correlation between the location of their place fields in the virtual environment and their anatomical location in the local circuit. The combination of virtual reality and high-resolution functional imaging should allow a new generation of studies to investigate neuronal circuit dynamics during behavior.

Understanding the principles of information processing in neural circuits requires systematic characterization of the participating cell types and their connections, and the ability to measure and perturb their activity. Genetic approaches promise to bring experimental access to complex neural systems, including genetic stalwarts such as the fly and mouse, but also to nongenetic systems such as primates. Together with anatomical and physiological methods, cell-type-specific expression of protein markers and sensors and transducers will be critical to construct circuit diagrams and to measure the activity of genetically defined neurons. Inactivation and activation of genetically defined cell types will establish causal relationships between activity in specific groups of neurons, circuit function, and animal behavior. Genetic analysis thus promises to reveal the logic of the neural circuits in complex brains that guide behaviors. Here we review progress in the genetic analysis of neural circuits and discuss directions for future research and development.

Tremendous progress has been made since Neuron published our Primer on genetic dissection of neural circuits 10 years ago. Since then, cell-type-specific anatomical, neurophysiological, and perturbation studies have been carried out in a multitude of invertebrate and vertebrate organisms, linking neurons and circuits to behavioral functions. New methods allow systematic classification of cell types and provide genetic access to diverse neuronal types for studies of connectivity and neural coding during behavior. Here we evaluate key advances over the past decade and discuss future directions.

Can neuronal morphology predict functional synaptic circuits? In the rat barrel cortex, ’barrels’ and ’septa’ delineate an orderly matrix of cortical columns. Using quantitative laser scanning photostimulation we measured the strength of excitatory projections from layer 4 (L4) and L5A to L2/3 pyramidal cells in barrel- and septum-related columns. From morphological reconstructions of excitatory neurons we computed the geometric circuit predicted by axodendritic overlap. Within most individual projections, functional inputs were predicted by geometry and a single scale factor, the synaptic strength per potential synapse. This factor, however, varied between projections and, in one case, even within a projection, up to 20-fold. Relationships between geometric overlap and synaptic strength thus depend on the laminar and columnar locations of both the pre- and postsynaptic neurons, even for neurons of the same type. A large plasticity potential appears to be incorporated into these circuits, allowing for functional ’tuning’ with fixed axonal and dendritic arbor geometry.

Neuroscience research is becoming increasingly more collaborative and interdisciplinary with partnerships between industry and academia and insights from fields beyond neuroscience. In the age of institutional initiatives and multi-investigator collaborations, scientists from around the world shared their perspectives on the effectiveness of large-scale collaborations versus single-lab, hypothesis-driven science.

Two-photon microscopy together with fluorescent proteins and fluorescent protein-based biosensors are commonly used tools in neuroscience. To enhance their experimental scope, it is important to optimize fluorescent proteins for two-photon excitation. Directed evolution of fluorescent proteins under one-photon excitation is common, but many one-photon properties do not correlate with two-photon properties. A simple system for expressing fluorescent protein mutants is colonies on an agar plate. The small focal volume of two-photon excitation makes creating a high throughput screen in this system a challenge for a conventional point-scanning approach. We present an instrument and accompanying software that solves this challenge by selectively scanning each colony based on a colony map captured under one-photon excitation. This instrument, called the GIZMO, can measure the two-photon excited fluorescence of 10,000 colonies in 7 hours. We show that the GIZMO can be used to evolve a fluorescent protein under two-photon excitation.

The ability to probe the membrane potential of multiple genetically defined neurons simultaneously would have a profound impact on neuroscience research. Genetically encoded voltage indicators are a promising tool for this purpose, and recent developments have achieved a high signal-to-noise ratio in vivo with 1-photon fluorescence imaging. However, these recordings exhibit several sources of noise and signal extraction remains a challenge. We present an improved signal extraction pipeline, spike-guided penalized matrix decomposition-nonnegative matrix factorization (SGPMD-NMF), which resolves supra- and subthreshold voltages in vivo. The method incorporates biophysical and optical constraints. We validate the pipeline with simultaneous patch-clamp and optical recordings from mouse layer 1 in vivo and with simulated and composite datasets with realistic noise. We demonstrate applications to mouse hippocampus expressing paQuasAr3-s or SomArchon1, mouse cortex expressing SomArchon1 or Voltron, and zebrafish spines expressing zArchon1.

Calcium imaging with genetically encoded calcium indicators (GECIs) is routinely used to measure neural activity in intact nervous systems. GECIs are frequently used in one of two different modes: to track activity in large populations of neuronal cell bodies, or to follow dynamics in subcellular compartments such as axons, dendrites and individual synaptic compartments. Despite major advances, calcium imaging is still limited by the biophysical properties of existing GECIs, including affinity, signal-to-noise ratio, rise and decay kinetics and dynamic range. Using structure-guided mutagenesis and neuron-based screening, we optimized the green fluorescent protein-based GECI GCaMP6 for different modes of in vivo imaging. The resulting jGCaMP7 sensors provide improved detection of individual spikes (jGCaMP7s,f), imaging in neurites and neuropil (jGCaMP7b), and may allow tracking larger populations of neurons using two-photon (jGCaMP7s,f) or wide-field (jGCaMP7c) imaging.

Genetically encoded calcium indicators (GECIs) can be used to image activity in defined neuronal populations. However, current GECIs produce inferior signals compared to synthetic indicators and recording electrodes, precluding detection of low firing rates. We developed a single-wavelength GCaMP2-based GECI (GCaMP3), with increased baseline fluorescence (3-fold), increased dynamic range (3-fold) and higher affinity for calcium (1.3-fold). We detected GCaMP3 fluorescence changes triggered by single action potentials in pyramidal cell dendrites, with signal-to-noise ratio and photostability substantially better than those of GCaMP2, D3cpVenus and TN-XXL. In Caenorhabditis elegans chemosensory neurons and the Drosophila melanogaster antennal lobe, sensory stimulation-evoked fluorescence responses were significantly enhanced with GCaMP3 (4-6-fold). In somatosensory and motor cortical neurons in the intact mouse, GCaMP3 detected calcium transients with amplitudes linearly dependent on action potential number. Long-term imaging in the motor cortex of behaving mice revealed large fluorescence changes in imaged neurons over months.