Calcium imaging with fluorescent protein sensors is widely used to record activity in neuronal populations. The transform between neural activity and calcium-related fluorescence involves nonlinearities and low-pass filtering, but the effects of the transformation on analyses of neural populations are not well understood. We compared neuronal spikes and fluorescence in matched neural populations in behaving mice. We report multiple discrepancies between analyses performed on the two types of data, including changes in single-neuron selectivity and population decoding. These were only partially resolved by spike inference algorithms applied to fluorescence. To model the relation between spiking and fluorescence we simultaneously recorded spikes and fluorescence from individual neurons. Using these recordings we developed a model transforming spike trains to synthetic-imaging data. The model recapitulated the differences in analyses. Our analysis highlights challenges in relating electrophysiology and imaging data, and suggests forward modeling as an effective way to understand differences between these data.

Most cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing pattern completion and other computations. Cortical circuits contain subnetworks that consist of neurons with similar receptive fields and increased connectivity relative to the network average. Cortical neurons that encode different types of information are spatially intermingled and distributed over large brain volumes, and this complexity has hindered attempts to probe the function of these subnetworks by perturbing them individually. Here we use computational modelling, optical recordings and manipulations to probe the function of recurrent coupling in layer 2/3 of the mouse vibrissal somatosensory cortex during active tactile discrimination. A neural circuit model of layer 2/3 revealed that recurrent excitation enhances sensory signals by amplification, but only for subnetworks with increased connectivity. Model networks with high amplification were sensitive to damage: loss of a few members of the subnetwork degraded stimulus encoding. We tested this prediction by mapping neuronal selectivity and photoablating neurons with specific selectivity. Ablation of a small proportion of layer 2/3 neurons (10-20, less than 5% of the total) representing touch markedly reduced responses in the spared touch representation, but not in other representations. Ablations most strongly affected neurons with stimulus responses that were similar to those of the ablated population, which is also consistent with network models. Recurrence among cortical neurons with similar selectivity therefore drives input-specific amplification during behaviour.

Imaging neurons and neural circuits over large volumes at high speed and subcellular resolution is a difficult task. Incorporating a Bessel focus module into a two-photon fluorescence mesoscope, we achieved rapid volumetric imaging of neural activity over the mesoscale with synaptic resolution. We applied the technology to calcium imaging of entire dendritic spans of neurons as well as neural ensembles within multiple cortical regions over two hemispheres of the awake mouse brain.

The active properties of dendrites can support local nonlinear operations, but previous imaging and electrophysiological measurements have produced conflicting views regarding the prevalence and selectivity of local nonlinearities in vivo. We imaged calcium signals in pyramidal cell dendrites in the motor cortex of mice performing a tactile decision task. A custom microscope allowed us to image the soma and up to 300 μm of contiguous dendrite at 15 Hz, while resolving individual spines. New analysis methods were used to estimate the frequency and spatial scales of activity in dendritic branches and spines. The majority of dendritic calcium transients were coincident with global events. However, task-associated calcium signals in dendrites and spines were compartmentalized by dendritic branching and clustered within branches over approximately 10 μm. Diverse behavior-related signals were intermingled and distributed throughout the dendritic arbor, potentially supporting a large learning capacity in individual neurons.

Neural computation involves diverse types of GABAergic inhibitory interneurons that are integrated with excitatory (E) neurons into precisely structured circuits. To understand how each neuron type shapes sensory representations, we measured firing patterns of defined types of neurons in the barrel cortex while mice performed an active, whisker-dependent object localization task. Touch excited fast-spiking (FS) interneurons at short latency, followed by activation of E neurons and somatostatin-expressing (SST) interneurons. Touch only weakly modulated vasoactive intestinal polypeptide-expressing (VIP) interneurons. Voluntary whisker movement activated FS neurons in the ventral posteromedial nucleus (VPM) target layers, a subset of SST neurons and a majority of VIP neurons. Together, FS neurons track thalamic input, mediating feedforward inhibition. SST neurons monitor local excitation, providing feedback inhibition. VIP neurons are activated by non-sensory inputs, disinhibiting E and FS neurons. Our data reveal rules of recruitment for interneuron types during behavior, providing foundations for understanding computation in cortical microcircuits.

Neuronal cell types are the nodes of neural circuits that determine the flow of information within the brain. Neuronal morphology, especially the shape of the axonal arbor, provides an essential descriptor of cell type and reveals how individual neurons route their output across the brain. Despite the importance of morphology, few projection neurons in the mouse brain have been reconstructed in their entirety. Here we present a robust and efficient platform for imaging and reconstructing complete neuronal morphologies, including axonal arbors that span substantial portions of the brain. We used this platform to reconstruct more than 1,000 projection neurons in the motor cortex, thalamus, subiculum, and hypothalamus. Together, the reconstructed neurons constitute more than 85 meters of axonal length and are available in a searchable online database. Axonal shapes revealed previously unknown subtypes of projection neurons and suggest organizational principles of long-range connectivity.

Imaging changes in membrane potential using genetically encoded fluorescent voltage indicators (GEVIs) has great potential for monitoring neuronal activity with high spatial and temporal resolution. Brightness and photostability of fluorescent proteins and rhodopsins have limited the utility of existing GEVIs. We engineered a novel GEVI, "Voltron", that utilizes bright and photostable synthetic dyes instead of protein-based fluorophores, extending the combined duration of imaging and number of neurons imaged simultaneously by more than tenfold relative to existing GEVIs. We used Voltron for in vivo voltage imaging in mice, zebrafish, and fruit flies. In mouse cortex, Voltron allowed single-trial recording of spikes and subthreshold voltage signals from dozens of neurons simultaneously, over 15 min of continuous imaging. In larval zebrafish, Voltron enabled the precise correlation of spike timing with behavior.

In a recent Editorial, De Schutter commented on our recent study on the roles of a cortico-cerebellar loop in motor planning in mice (De Schutter 2019, Neuroinformatics, 17, 181-183, Gao et al. 2018, Nature, 563, 113-116). Two issues were raised. First, De Schutter questions the involvement of the fastigial nucleus in motor planning, rather than the dentate nucleus, given previous anatomical studies in non-human primates. Second, De Schutter suggests that our study design did not delineate different components of the behavior and the fastigial nucleus might play roles in sensory discrimination rather than motor planning. These comments are based on anatomical studies in other species and homology-based arguments and ignore key anatomical data and neurophysiological experiments from our study. Here we outline our interpretation of existing data and point out gaps in knowledge where future studies are needed.

Point-scanning two-photon microscopy enables high-resolution imaging within scattering specimens such as the mammalian brain, but sequential acquisition of voxels fundamentally limits imaging speed. We developed a two-photon imaging technique that scans lines of excitation across a focal plane at multiple angles and uses prior information to recover high-resolution images at over 1.4 billion voxels per second. Using a structural image as a prior for recording neural activity, we imaged visually-evoked and spontaneous glutamate release across hundreds of dendritic spines in mice at depths over 250 microns and frame-rates over 1 kHz. Dendritic glutamate transients in anaesthetized mice are synchronized within spatially-contiguous domains spanning tens of microns at frequencies ranging from 1-100 Hz. We demonstrate high-speed recording of acetylcholine and calcium sensors, 3D single-particle tracking, and imaging in densely-labeled cortex. Our method surpasses limits on the speed of raster-scanned imaging imposed by fluorescence lifetime.

Physiological measurements in neuroscience experiments often involve complex stimulus paradigms and multiple data channels. Ephus (http://www.ephus.org) is an open-source software package designed for general-purpose data acquisition and instrument control. Ephus operates as a collection of modular programs, including an ephys program for standard whole-cell recording with single or multiple electrodes in typical electrophysiological experiments, and a mapper program for synaptic circuit mapping experiments involving laser scanning photostimulation based on glutamate uncaging or channelrhodopsin-2 excitation. Custom user functions allow user-extensibility at multiple levels, including on-line analysis and closed-loop experiments, where experimental parameters can be changed based on recently acquired data, such as during in vivo behavioral experiments. Ephus is compatible with a variety of data acquisition and imaging hardware. This paper describes the main features and modules of Ephus and their use in representative experimental applications.