Recording activity from identified populations of neurons is a central goal of neuroscience. Changes in membrane depolarization, particularly action potentials, are the most important features of neural physiology to extract, although ions, neurotransmitters, neuromodulators, second messengers, and the activation state of specific proteins are also crucial. Modern fluorescence microscopy provides the basis for such activity mapping, through multi-photon imaging and other optical schemes. Probes remain the rate-limiting step for progress in this field: they should be bright and photostable, and ideally come in multiple colors. Only protein-based reagents permit chronic imaging from genetically specified cells. Here we review recent progress in the design, optimization and deployment of genetically encoded indicators for calcium ions (a proxy for action potentials), membrane potential, and neurotransmitters. We highlight seminal experiments, and present an outlook for future progress.

Electrophysiological recordings from behaving animals provide an unparalleled view into the functional role of individual neurons. Intracellular approaches can be especially revealing as they provide information about a neuron's inputs and intrinsic cellular properties, which together determine its spiking output. Recent technical developments have made intracellular recording possible during an ever-increasing range of behaviors in both head-fixed and freely moving animals. These recordings have yielded fundamental insights into the cellular and circuit mechanisms underlying neural activity during natural behaviors in such areas as sensory perception, motor sequence generation, and spatial navigation, forging a direct link between cellular and systems neuroscience.

Light sheet microscopy is a versatile imaging technique with a unique combination of capabilities. It provides high imaging speed, high signal-to-noise ratio and low levels of photobleaching and phototoxic effects. These properties are crucial in a wide range of applications in the life sciences, from live imaging of fast dynamic processes in single cells to long-term observation of developmental dynamics in entire large organisms. When combined with tissue clearing methods, light sheet microscopy furthermore allows rapid imaging of large specimens with excellent coverage and high spatial resolution. Even samples up to the size of entire mammalian brains can be efficiently recorded and quantitatively analyzed. Here, we provide an overview of the history of light sheet microscopy, review the development of tissue clearing methods, and discuss recent technical breakthroughs that have the potential to influence the future direction of the field.

Virtual reality (VR) holds great promise as a tool to study the neural circuitry underlying animal behaviors. Here, we discuss the advantages of VR and the experimental paradigms and technologies that enable closed loop behavioral experiments. We review recent results from VR research in genetic model organisms where the potential combination of rich behaviors, genetic tools and cutting edge neural recording techniques are leading to breakthroughs in our understanding of the neural basis of behavior. We also discuss several key issues to consider when performing VR experiments and provide an outlook for the future of this exciting experimental toolkit.

The last decade has seen a rapid increase in the number of tools to acquire volume electron microscopy (EM) data. Several new scanning EM (SEM) imaging methods have emerged, and classical transmission EM (TEM) methods are being scaled up and automated. Here we summarize the new methods for acquiring large EM volumes, and discuss the tradeoffs in terms of resolution, acquisition speed, and reliability. We then assess each method’s applicability to the problem of reconstructing anatomical connectivity between neurons, considering both the current capabilities and future prospects of the method. Finally, we argue that neuronal ’wiring diagrams’ are likely necessary, but not sufficient, to understand the operation of most neuronal circuits: volume EM imaging will likely find its best application in combination with other methods in neuroscience, such as molecular biology, optogenetics, and physiology.

Most functional plasticity studies in the cortex have focused on layers (L) II/III and IV, whereas relatively little is known of LV. Structural measurements of dendritic spines in vivo suggest some specialization among LV cell subtypes. We therefore studied experience-dependent plasticity in the barrel cortex using intracellular recordings to distinguish regular spiking (RS) and intrinsic bursting (IB) subtypes. Postsynaptic potentials and suprathreshold responses in vivo revealed a remarkable dichotomy in RS and IB cell plasticity; spared whisker potentiation occurred in IB but not RS cells while deprived whisker depression occurred in RS but not IB cells. Similar RS/IB differences were found in the LII/III to V connections in brain slices. Modeling studies showed that subthreshold changes predicted the suprathreshold changes. These studies demonstrate the major functional partition of plasticity within a single cortical layer and reveal the LII/III to LV connection as a major excitatory locus of cortical plasticity.

Using ultralow light intensities that are well suited for investigating biological samples, we demonstrate whole-cell superresolution imaging by nonlinear structured-illumination microscopy. Structured-illumination microscopy can increase the spatial resolution of a wide-field light microscope by a factor of two, with greater resolution extension possible if the emission rate of the sample responds nonlinearly to the illumination intensity. Saturating the fluorophore excited state is one such nonlinear response, and a realization of this idea, saturated structured-illumination microscopy, has achieved approximately 50-nm resolution on dye-filled polystyrene beads. Unfortunately, because saturation requires extremely high light intensities that are likely to accelerate photobleaching and damage even fixed tissue, this implementation is of limited use for studying biological samples. Here, reversible photoswitching of a fluorescent protein provides the required nonlinearity at light intensities six orders of magnitude lower than those needed for saturation. We experimentally demonstrate approximately 40-nm resolution on purified microtubules labeled with the fluorescent photoswitchable protein Dronpa, and we visualize cellular structures by imaging the mammalian nuclear pore and actin cytoskeleton. As a result, nonlinear structured-illumination microscopy is now a biologically compatible superresolution imaging method.

Transforming synaptic input into action potential output is a fundamental function of neurons. The pattern of action potential output from principal cells of the mammalian hippocampus encodes spatial and nonspatial information, but the cellular and circuit mechanisms by which neurons transform their synaptic input into a given output are unknown. Using a combination of optical activation and cell type-specific pharmacogenetic silencing in vitro, we found that dendritic inhibition is the primary regulator of input-output transformations in mouse hippocampal CA1 pyramidal cells, and acts by gating the dendritic electrogenesis driving burst spiking. Dendrite-targeting interneurons are themselves modulated by interneurons targeting pyramidal cell somata, providing a synaptic substrate for tuning pyramidal cell output through interactions in the local inhibitory network. These results provide evidence for a division of labor in cortical circuits, where distinct computational functions are implemented by subtypes of local inhibitory neurons.

The signal and resolution during in vivo imaging of the mouse brain is limited by sample-induced optical aberrations. We find that, although the optical aberrations can vary across the sample and increase in magnitude with depth, they remain stable for hours. As a result, two-photon adaptive optics can recover diffraction-limited performance to depths of 450 μm and improve imaging quality over fields of view of hundreds of microns. Adaptive optical correction yielded fivefold signal enhancement for small neuronal structures and a threefold increase in axial resolution. The corrections allowed us to detect smaller neuronal structures at greater contrast and also improve the signal-to-noise ratio during functional Ca(2+) imaging in single neurons.

Early stages of visual processing are thought to decorrelate, or whiten, the incoming temporally varying signals. Because the typical correlation time of natural stimuli, as well as the extent of temporal receptive fields of lateral geniculate nucleus (LGN) neurons, is much greater than neuronal time constants, such decorrelation must be done in stages combining contributions of multiple neurons. We propose to model temporal decorrelation in the visual pathway with the lattice filter, a signal processing device for stage-wise decorrelation of temporal signals. The stage-wise architecture of the lattice filter maps naturally onto the visual pathway (photoreceptors -> bipolar cells -> retinal ganglion cells -> LGN) and its filter weights can be learned using Hebbian rules in a stage-wise sequential manner. Moreover, predictions of neural activity from the lattice filter model are consistent with physiological measurements in LGN neurons and fruit fly second-order visual neurons. Therefore, the lattice filter model is a useful abstraction that may help unravel visual system function.