Monitoring synaptic and neuronal activity in 3D with synthetic and genetic indicators using a compact acousto-optic lens two-photon microscope

Acousto-optic holography for pseudo-two-dimensional dynamic light patterning

Optical systems use acousto-optic deflectors (AODs) mostly for fast angular scanning and spectral filtering of laser beams. However, AODs may transform laser light in much broader ways. When time-locked to the pulsing of low repetition rate laser amplifiers, AODs permit the holographic reconstruction of 1D and pseudo-two-dimensional (ps2D) intensity objects of rectangular shape by controlling the amplitude and phase of the light field at high (20-200 kHz) rates for microscopic light patterning. Using iterative Fourier transformations (IFTs), we searched for AOD-compatible holograms to reconstruct the given ps2D target patterns through either phase-only or complex light field modulation. We previously showed that phase-only holograms can adequately render grid-like patterns of diffraction-limited points with non-overlapping diffraction orders, while side lobes to the target pattern can be cured with an apodization mask. Dense target patterns, in contrast, are typically encumbered by apodization-resistant speckle noise. Here, we show the denoised rendering of dense ps2D objects by complex acousto-optic holograms deriving from simultaneous optimization of the amplitude and phase of the light field. Target patterns lacking ps2D symmetry, although not translatable into single holograms, were accessed by serial holography based on a segregation into ps2D-compatible components. The holograms retrieved under different regularizations were experimentally validated in an AOD random-access microscope. IFT regularizations characterized in this work extend the versatility of acousto-optic holography for fast dynamic light patterning.

Multi-neuronal recording in unrestrained animals with all acousto-optic random-access line-scanning two-photon microscopy

To understand how neural activity encodes and coordinates behavior, it is desirable to record multi-neuronal activity in freely behaving animals. Imaging in unrestrained animals is challenging, especially for those, like larval Drosophila melanogaster, whose brains are deformed by body motion. A previously demonstrated two-photon tracking microscope recorded from individual neurons in freely crawling Drosophila larvae but faced limits in multi-neuronal recording. Here we demonstrate a new tracking microscope using acousto-optic deflectors (AODs) and an acoustic GRIN lens (TAG lens) to achieve axially resonant 2D random access scanning, sampling along arbitrarily located axial lines at a line rate of 70 kHz. With a tracking latency of 0.1 ms, this microscope recorded activities of various neurons in moving larval Drosophila CNS and VNC including premotor neurons, bilateral visual interneurons, and descending command neurons. This technique can be applied to the existing two-photon microscope to allow for fast 3D tracking and scanning.

Power-effective scanning with AODs for 3D optogenetic applications

Two-photon (2P) excitation is a cornerstone approach widely employed in neuroscience microscopy for deep optical access and sub-micrometric-resolution light targeting into the brain. However, besides structural and functional imaging, 2P optogenetic stimulations are less routinary, especially in 3D. This is because of the adopted scanning systems, often feebly effective, slow and mechanically constricted. Faster illumination can be achieved through acousto-optic deflectors (AODs) although their applicability to large volumes excitation has been limited by large efficiency drop along the optical axis. Here, we present a new AOD-based scheme for 2P 3D scanning that improves the power delivery between different illumination planes. We applied this approach to photostimulate an optogenetic actuator in zebrafish larvae, demonstrating the method efficiency observing increased activity responses and uniform activation probabilities from neuronal clusters addressed in the volume. This novel driving scheme can open to new AOD applications in neuroscience, allowing more effective 3D interrogation in large neuronal networks.

Fast optical recording of neuronal activity by three-dimensional custom-access serial holography

Optical recording of neuronal activity in three-dimensional (3D) brain circuits at cellular and millisecond resolution in vivo is essential for probing information flow in the brain. While random-access multiphoton microscopy permits fast optical access to neuronal targets in three dimensions, the method is challenged by motion artifacts when recording from behaving animals. Therefore, we developed three-dimensional custom-access serial holography (3D-CASH). Built on a fast acousto-optic light modulator, 3D-CASH performs serial sampling at 40 kHz from neurons at freely selectable 3D locations. Motion artifacts are eliminated by targeting each neuron with a size-optimized pattern of excitation light covering the cell body and its anticipated displacement field. Spike rates inferred from GCaMP6f recordings in visual cortex of awake mice tracked the phase of a moving bar stimulus with higher spike correlation between intra compared to interlaminar neuron pairs. 3D-CASH offers access to the millisecond correlation structure of in vivo neuronal activity in 3D microcircuits.

Neurophotonic tools for microscopic measurements and manipulation: status report

Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.

Cerebellar granule cell axons support high-dimensional representations

In classical theories of cerebellar cortex, high-dimensional sensorimotor representations are used to separate neuronal activity patterns, improving associative learning and motor performance. Recent experimental studies suggest that cerebellar granule cell (GrC) population activity is low-dimensional. To examine sensorimotor representations from the point of view of downstream Purkinje cell 'decoders', we used three-dimensional acousto-optic lens two-photon microscopy to record from hundreds of GrC axons. Here we show that GrC axon population activity is high dimensional and distributed with little fine-scale spatial structure during spontaneous behaviors. Moreover, distinct behavioral states are represented along orthogonal dimensions in neuronal activity space. These results suggest that the cerebellar cortex supports high-dimensional representations and segregates behavioral state-dependent computations into orthogonal subspaces, as reported in the neocortex. Our findings match the predictions of cerebellar pattern separation theories and suggest that the cerebellum and neocortex use population codes with common features, despite their vastly different circuit structures.

Multidimensional population activity in an electrically coupled inhibitory circuit in the cerebellar cortex

Inhibitory neurons orchestrate the activity of excitatory neurons and play key roles in circuit function. Although individual interneurons have been studied extensively, little is known about their properties at the population level. Using random-access 3D two-photon microscopy, we imaged local populations of cerebellar Golgi cells (GoCs), which deliver inhibition to granule cells. We show that population activity is organized into multiple modes during spontaneous behaviors. A slow, network-wide common modulation of GoC activity correlates with the level of whisking and locomotion, while faster (<1 s) differential population activity, arising from spatially mixed heterogeneous GoC responses, encodes more precise information. A biologically detailed GoC circuit model reproduced the common population mode and the dimensionality observed experimentally, but these properties disappeared when electrical coupling was removed. Our results establish that local GoC circuits exhibit multidimensional activity patterns that could be used for inhibition-mediated adaptive gain control and spatiotemporal patterning of downstream granule cells.

Neuronal Activity at Synapse Resolution: Reporters and Effectors for Synaptic Neuroscience

The development of methods for the activity-dependent tagging of neurons enabled a new way to tackle the problem of engram identification at the cellular level, giving rise to groundbreaking findings in the field of memory studies. However, the resolution of activity-dependent tagging remains limited to the whole-cell level. Notably, events taking place at the synapse level play a critical role in the establishment of new memories, and strong experimental evidence shows that learning and synaptic plasticity are tightly linked. Here, we provide a comprehensive review of the currently available techniques that enable to identify and track the neuronal activity with synaptic spatial resolution. We also present recent technologies that allow to selectively interfere with specific subsets of synapses. Lastly, we discuss how these technologies can be applied to the study of learning and memory.

Real-time 3D movement correction for two-photon imaging in behaving animals

Two-photon microscopy is widely used to investigate brain function across multiple spatial scales. However, measurements of neural activity are compromised by brain movement in behaving animals. Brain motion-induced artifacts are typically corrected using post hoc processing of two-dimensional images, but this approach is slow and does not correct for axial movements. Moreover, the deleterious effects of brain movement on high-speed imaging of small regions of interest and photostimulation cannot be corrected post hoc. To address this problem, we combined random-access three-dimensional (3D) laser scanning using an acousto-optic lens and rapid closed-loop field programmable gate array processing to track 3D brain movement and correct motion artifacts in real time at up to 1 kHz. Our recordings from synapses, dendrites and large neuronal populations in behaving mice and zebrafish demonstrate real-time movement-corrected 3D two-photon imaging with submicrometer precision.

The temporal structure of the inner retina at a single glance

The retina decomposes visual stimuli into parallel channels that encode different features of the visual environment. Central to this computation is the synaptic processing in a dense layer of neuropil, the so-called inner plexiform layer (IPL). Here, different types of bipolar cells stratifying at distinct depths relay the excitatory feedforward drive from photoreceptors to amacrine and ganglion cells. Current experimental techniques for studying processing in the IPL do not allow imaging the entire IPL simultaneously in the intact tissue. Here, we extend a two-photon microscope with an electrically tunable lens allowing us to obtain optical vertical slices of the IPL, which provide a complete picture of the response diversity of bipolar cells at a "single glance". The nature of these axial recordings additionally allowed us to isolate and investigate batch effects, i.e. inter-experimental variations resulting in systematic differences in response speed. As a proof of principle, we developed a simple model that disentangles biological from experimental causes of variability and allowed us to recover the characteristic gradient of response speeds across the IPL with higher precision than before. Our new framework will make it possible to study the computations performed in the central synaptic layer of the retina more efficiently.

High efficiency two-photon uncaging coupled by the correction of spontaneous hydrolysis

Two-photon (TP) uncaging of neurotransmitter molecules is the method of choice to mimic and study the subtleties of neuronal communication either in the intact brain or in slice preparations. However, the currently available caged materials are just at the limit of their usability and have several drawbacks. The local and focal nature of their use may for example be jeopardized by a high spontaneous hydrolysis rate of the commercially available compounds with increased photochemical release rate. Here, using quantum chemical modelling we show the mechanisms of hydrolysis and two-photon activation, and synthesized more effective caged compounds. Furthermore, we have developed a new enzymatic elimination method removing neurotransmitters inadvertently escaping from their compound during experiment. This method, usable both in one and two-photon experiments, allows for the use of materials with an increased rate of photochemical release. The efficiency of the new compound and the enzymatic method and of the new compound are demonstrated in neurophysiological experiments.

Line excitation array detection fluorescence microscopy at 0.8 million frames per second

Three-dimensional, fluorescence imaging methods with ~1 MHz frame rates are needed for high-speed, blur-free flow cytometry and capturing volumetric neuronal activity. The frame rates of current imaging methods are limited to kHz by the photon budget, slow camera readout, and/or slow laser beam scanners. Here, we present line excitation array detection (LEAD) fluorescence microscopy, a high-speed imaging method capable of providing 0.8 million frames per second. The method performs 0.8 MHz line-scanning of an excitation laser beam using a chirped signal-driven longitudinal acousto-optic deflector to create a virtual light-sheet, and images the field-of-view with a linear photomultiplier tube array to generate a 66 × 14 pixel frame each scan cycle. We implement LEAD microscopy as a blur-free flow cytometer for Caenorhabditis elegans moving at 1 m s-1 with 3.5-µm resolution and signal-to-background ratios >200. Signal-to-noise measurements indicate future LEAD fluorescence microscopes can reach higher resolutions and pixels per frame without compromising frame rates.

Simultaneous two-plane, two-photon imaging based on spatial multiplexing

The two-photon microscope is a powerful tool in life science. Conventional two-photon microscopy can image only a plane of a particular axial position at a time. Axial scanning can get the volumetric information, but it gets signals from different axial positions serially, which means that the exposure time at every plane is limited. Here we demonstrate a novel method, to the best of our knowledge, that can simultaneously record images from two planes at different xyz positions. The demultiplexing of the signal is realized using a confocal strategy. The experimental results show that it can be used for simultaneous two-photon imaging at two focal planes with little cross talk.

A Guide to Emerging Technologies for Large-Scale and Whole-Brain Optical Imaging of Neuronal Activity

The mammalian brain is a densely interconnected network that consists of millions to billions of neurons. Decoding how information is represented and processed by this neural circuitry requires the ability to capture and manipulate the dynamics of large populations at high speed and high resolution over a large area of the brain. Although the use of optical approaches by the neuroscience community has rapidly increased over the past two decades, most microscopy approaches are unable to record the activity of all neurons comprising a functional network across the mammalian brain at relevant temporal and spatial resolutions. In this review, we survey the recent development in optical technologies for Ca2+ imaging in this regard and provide an overview of the strengths and limitations of each modality and its potential for scalability. We provide guidance from the perspective of a biological user driven by the typical biological applications and sample conditions. We also discuss the potential for future advances and synergies that could be obtained through hybrid approaches or other modalities.

Studying Axon-Astrocyte Functional Interactions by 3D Two-Photon Ca2+ Imaging: A Practical Guide to Experiments and "Big Data" Analysis

Recent advances in fast volumetric imaging have enabled rapid generation of large amounts of multi-dimensional functional data. While many computer frameworks exist for data storage and analysis of the multi-gigabyte Ca²⁺ imaging experiments in neurons, they are less useful for analyzing Ca²⁺ dynamics in astrocytes, where transients do not follow a predictable spatio-temporal distribution pattern. In this manuscript, we provide a detailed protocol and commentary for recording and analyzing three-dimensional (3D) Ca²⁺ transients through time in GCaMP6f-expressing astrocytes of adult brain slices in response to axonal stimulation, using our recently developed tools to perform interactive exploration, filtering, and time-correlation analysis of the transients. In addition to the protocol, we release our in-house software tools and discuss parameters pertinent to conducting axonal stimulation/response experiments across various brain regions and conditions. Our software tools are available from the Volterra Lab webpage at https://wwwfbm.unil.ch/dnf/group/glia-an-active-synaptic-partner/member/volterra-andrea-volterra in the form of software plugins for Image J (NIH)—a de facto standard in scientific image analysis. Three programs are available: MultiROI_TZ_profiler for interactive graphing of several movable ROIs simultaneously, Gaussian_Filter5D for Gaussian filtering in several dimensions, and Correlation_Calculator for computing various cross-correlation parameters on voxel collections through time.

NeuroMatic: An Integrated Open-Source Software Toolkit for Acquisition, Analysis and Simulation of Electrophysiological Data

Acquisition, analysis and simulation of electrophysiological properties of the nervous system require multiple software packages. This makes it difficult to conserve experimental metadata and track the analysis performed. It also complicates certain experimental approaches such as online analysis. To address this, we developed NeuroMatic, an open-source software toolkit that performs data acquisition (episodic, continuous and triggered recordings), data analysis (spike rasters, spontaneous event detection, curve fitting, stationarity) and simulations (stochastic synaptic transmission, synaptic short-term plasticity, integrate-and-fire and Hodgkin-Huxley-like single-compartment models). The merging of a wide range of tools into a single package facilitates a more integrated style of research, from the development of online analysis functions during data acquisition, to the simulation of synaptic conductance trains during dynamic-clamp experiments. Moreover, NeuroMatic has the advantage of working within Igor Pro, a platform-independent environment that includes an extensive library of built-in functions, a history window for reviewing the user's workflow and the ability to produce publication-quality graphics. Since its original release, NeuroMatic has been used in a wide range of scientific studies and its user base has grown considerably. NeuroMatic version 3.0 can be found at http://www.neuromatic.thinkrandom.com and https://github.com/SilverLabUCL/NeuroMatic.

Simultaneous high-speed imaging and optogenetic inhibition in the intact mouse brain

Genetically encoded calcium indicators and optogenetic actuators can report and manipulate the activity of specific neuronal populations. However, applying imaging and optogenetics simultaneously has been difficult to establish in the mammalian brain, even though combining the techniques would provide a powerful approach to reveal the functional organization of neural circuits. Here, we developed a technique based on patterned two-photon illumination to allow fast scanless imaging of GCaMP6 signals in the intact mouse brain at the same time as single-photon optogenetic inhibition with Archaerhodopsin. Using combined imaging and electrophysiological recording, we demonstrate that single and short bursts of action potentials in pyramidal neurons can be detected in the scanless modality at acquisition frequencies up to 1 kHz. Moreover, we demonstrate that our system strongly reduces the artifacts in the fluorescence detection that are induced by single-photon optogenetic illumination. Finally, we validated our technique investigating the role of parvalbumin-positive (PV) interneurons in the control of spontaneous cortical dynamics. Monitoring the activity of cellular populations on a precise spatiotemporal scale while manipulating neuronal activity with optogenetics provides a powerful tool to causally elucidate the cellular mechanisms underlying circuit function in the intact mammalian brain.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.

Design and mechanistic insight into ultrafast calcium indicators for monitoring intracellular calcium dynamics

Calmodulin-based genetically encoded fluorescent calcium indicators (GCaMP-s) are powerful tools of imaging calcium dynamics from cells to freely moving animals. High affinity indicators with slow kinetics however distort the temporal profile of calcium transients. Here we report the development of reduced affinity ultrafast variants of GCaMP6s and GCaMP6f. We hypothesized that GCaMP-s have a common kinetic mechanism with a rate-limiting process in the interaction of the RS20 peptide and calcium-calmodulin. Therefore we targeted specific residues in the binding interface by rational design generating improved indicators with GCaMP6f_u displaying fluorescence rise and decay times (t_1/2) of 1 and 3 ms (37 °C) in vitro, 9 and 22-fold faster than GCaMP6f respectively. In HEK293T cells, GCaMP6f_u revealed a 4-fold faster decay of ATP-evoked intracellular calcium transients than GCaMP6f. Stimulation of hippocampal CA1 pyramidal neurons with five action potentials fired at 100 Hz resulted in a single dendritic calcium transient with a 2-fold faster rise and 7-fold faster decay time (t_1/2 of 40 ms) than GCaMP6f, indicating that tracking high frequency action potentials may be limited by calcium dynamics. We propose that the design strategy used for generating GCaMP6f_u is applicable for the acceleration of the response kinetics of GCaMP-type calcium indicators.

Fast volumetric calcium imaging across multiple cortical layers using sculpted light

Although whole-organism calcium imaging in small and semi-transparent animals has been demonstrated, capturing the functional dynamics of large-scale neuronal circuits in awake behaving mammals at high speed and resolution has remained one of the main frontiers in systems neuroscience. Here we present a method based on light sculpting that enables unbiased single- and dual-plane high-speed (up to 160 Hz) calcium imaging as well as in vivo volumetric calcium imaging of a mouse cortical column (0.5 mm × 0.5 mm × 0.5 mm) at single-cell resolution and fast volume rates (3-6 Hz). We achieved this by tailoring the point-spread function of our microscope to the structures of interest while maximizing the signal-to-noise ratio using a home-built fiber laser amplifier with pulses that are synchronized to the imaging voxel speed. This enabled in vivo recording of calcium dynamics of several thousand neurons across cortical layers and in the hippocampus of awake behaving mice.

Analysis of the dynamics of temporal relationships of neural activities using optical imaging data

The temporal relationship between the activities of neurons in biological neural systems is critically important for the correct delivery of the functionality of these systems. Fine measurement of temporal relationships of neural activities using micro-electrodes is possible but this approach is very limited due to spatial constraints in the context of physiologically valid settings of neural systems. Optical imaging with voltage-sensitive dyes or calcium dyes can provide data about the activity patterns of many neurons in physiologically valid settings, but the data is relatively noisy. Here we propose a numerical methodology for the analysis of optical neuro-imaging data that allows robust analysis of the dynamics of temporal relationships of neural activities. We provide a detailed description of the methodology and we also assess its robustness. The proposed methodology is applied to analyse the relationship between the activity patterns of PY neurons in the crab stomatogastric ganglion. We show for the first time in a physiologically valid setting that as expected on the basis of earlier results of single neuron recordings exposure to dopamine de-synchronises the activity of these neurons. We also discuss the wider implications and application of the proposed methodology.

Fast 3D Imaging of Spine, Dendritic, and Neuronal Assemblies in Behaving Animals

Understanding neural computation requires methods such as 3D acousto-optical (AO) scanning that can simultaneously read out neural activity on both the somatic and dendritic scales. AO point scanning can increase measurement speed and signal-to-noise ratio (SNR) by several orders of magnitude, but high optical resolution requires long point-to-point switching time, which limits imaging capability. Here we present a novel technology, 3D DRIFT AO scanning, which can extend each scanning point to small 3D lines, surfaces, or volume elements for flexible and fast imaging of complex structures simultaneously in multiple locations. Our method was demonstrated by fast 3D recording of over 150 dendritic spines with 3D lines, over 100 somata with squares and cubes, or multiple spiny dendritic segments with surface and volume elements, including in behaving animals. Finally, a 4-fold improvement in total excitation efficiency resulted in about 500 × 500 × 650 μm scanning volume with genetically encoded calcium indicators (GECIs).

Random-access scanning microscopy for 3D imaging in awake behaving animals

Understanding how neural circuits process information requires rapid measurements of activity from identified neurons distributed in 3D space. Here we describe an acousto-optic lens two-photon microscope that performs high-speed focusing and line scanning within a volume spanning hundreds of micrometers. We demonstrate its random-access functionality by selectively imaging cerebellar interneurons sparsely distributed in 3D space and by simultaneously recording from the soma, proximal and distal dendrites of neocortical pyramidal cells in awake behaving mice.

Dynamic wavefront shaping with an acousto-optic lens for laser scanning microscopy

Acousto-optic deflectors (AODs) arranged in series and driven with linearly chirped frequencies can rapidly focus and tilt optical wavefronts, enabling high-speed 3D random access microscopy. Non-linearly chirped acoustic drive frequencies can also be used to shape the optical wavefront allowing a range of higher-order aberrations to be generated. However, to date, wavefront shaping with AODs has been achieved by using single laser pulses for strobed illumination to 'freeze' the moving acoustic wavefront, limiting voxel acquisition rates. Here we show that dynamic wavefront shaping can be achieved by applying non-linear drive frequencies to a pair of AODs with counter-propagating acoustic waves, which comprise a cylindrical acousto-optic lens (AOL). Using a cylindrical AOL we demonstrate high-speed continuous axial line scanning and the first experimental AOL-based correction of a cylindrical lens aberration at 30 kHz, accurate to 1/35^th of a wave at 800 nm. Furthermore, we develop a model to show how spherical aberration, which is the major aberration in AOL-based remote-focusing systems, can be partially or fully corrected with AOLs consisting of four or six AODs, respectively.

Extracting quantal properties of transmission at central synapses

Chemical synapses enable neurons to communicate rapidly, process and filter signals and to store information. However, studying their functional properties is difficult because synaptic connections typically consist of multiple synaptic contacts that release vesicles stochastically and exhibit time-dependent behavior. Moreover, most central synapses are small and inaccessible to direct measurements. Estimation of synaptic properties from responses recorded at the soma is complicated by the presence of nonuniform release probability and nonuniform quantal properties. The presence of multivesicular release and postsynaptic receptor saturation at some synapses can also complicate the interpretation of quantal parameters. Multiple-probability fluctuation analysis (MPFA; also known as variance-mean analysis) is a method that has been developed for estimating synaptic parameters from the variance and mean amplitude of synaptic responses recorded at different release probabilities. This statistical approach, which incorporates nonuniform synaptic properties, has become widely used for studying synaptic transmission. In this chapter, we describe the statistical models used to extract quantal parameters and discuss their interpretation when applying MPFA.

Method to quantify accuracy of position feedback signals of a three-dimensional two-photon laser-scanning microscope

Two-photon laser-scanning microscopy enables to record neuronal network activity in three-dimensional space while maintaining single-cellular resolution. One of the proposed approaches combines galvanometric x-y scanning with piezo-driven objective movements and employs hardware feedback signals for position monitoring. However, readily applicable methods to quantify the accuracy of those feedback signals are currently lacking. Here we provide techniques based on contact-free laser reflection and laser triangulation for the quantification of positioning accuracy of each spatial axis. We found that the lateral feedback signals are sufficiently accurate (defined as <2.5 µm) for a wide range of scan trajectories and frequencies. We further show that axial positioning accuracy does not only depend on objective acceleration and mass but also its geometry. We conclude that the introduced methods allow a reliable quantification of position feedback signals in a cost-efficient, easy-to-install manner and should be applicable for a wide range of two-photon laser scanning microscopes.

Development and application of a ray-based model of light propagation through a spherical acousto-optic lens

A spherical acousto-optic lens (AOL) consists of four acousto-optic deflectors (AODs) that can rapidly and precisely control the focal position of an optical beam in 3D space. Development and application of AOLs has increased the speed at which 3D random access point measurements can be performed with a two-photon microscope. This has been particularly useful for measuring brain activity with fluorescent reporter dyes because neuronal signalling is rapid and sparsely distributed in 3D space. However, a theoretical description of light propagation through AOLs has lagged behind their development, resulting in only a handful of simplified principles to guide AOL design and optimization. To address this we have developed a ray-based computer model of an AOL incorporating acousto-optic diffraction and refraction by anisotropic media. We extended an existing model of a single AOD with constant drive frequency to model a spherical AOL: four AODs in series driven with linear chirps. AOL model predictions of the relationship between optical transmission efficiency and acoustic drive frequency including second order diffraction effects closely matched experimental measurements from a 3D two-photon AOL microscope. Moreover, exploration of different AOL drive configurations identified a new simple rule for maximizing the field of view of our compact AOL design. By providing a theoretical basis for understanding optical transmission through spherical AOLs, our open source model is likely to be useful for comparing and improving different AOL designs, as well as identifying the acoustic drive configurations that provide the best transmission performance over the 3D focal region.

Closed-loop and activity-guided optogenetic control

Advances in optical manipulation and observation of neural activity have set the stage for widespread implementation of closed-loop and activity-guided optical control of neural circuit dynamics. Closing the loop optogenetically (i.e., basing optogenetic stimulation on simultaneously observed dynamics in a principled way) is a powerful strategy for causal investigation of neural circuitry. In particular, observing and feeding back the effects of circuit interventions on physiologically relevant timescales is valuable for directly testing whether inferred models of dynamics, connectivity, and causation are accurate in vivo. Here we highlight technical and theoretical foundations as well as recent advances and opportunities in this area, and we review in detail the known caveats and limitations of optogenetic experimentation in the context of addressing these challenges with closed-loop optogenetic control in behaving animals.

Contribution of sublinear and supralinear dendritic integration to neuronal computations

Nonlinear dendritic integration is thought to increase the computational ability of neurons. Most studies focus on how supralinear summation of excitatory synaptic responses arising from clustered inputs within single dendrites result in the enhancement of neuronal firing, enabling simple computations such as feature detection. Recent reports have shown that sublinear summation is also a prominent dendritic operation, extending the range of subthreshold input-output (sI/O) transformations conferred by dendrites. Like supralinear operations, sublinear dendritic operations also increase the repertoire of neuronal computations, but feature extraction requires different synaptic connectivity strategies for each of these operations. In this article we will review the experimental and theoretical findings describing the biophysical determinants of the three primary classes of dendritic operations: linear, sublinear, and supralinear. We then review a Boolean algebra-based analysis of simplified neuron models, which provides insight into how dendritic operations influence neuronal computations. We highlight how neuronal computations are critically dependent on the interplay of dendritic properties (morphology and voltage-gated channel expression), spiking threshold and distribution of synaptic inputs carrying particular sensory features. Finally, we describe how global (scattered) and local (clustered) integration strategies permit the implementation of similar classes of computations, one example being the object feature binding problem.

Large-scale imaging in small brains

The dense connectivity in the brain means that one neuron's activity can influence many others. To observe this interconnected system comprehensively, an aspiration within neuroscience is to record from as many neurons as possible at the same time. There are two useful routes toward this goal: one is to expand the spatial extent of functional imaging techniques, and the second is to use animals with small brains. Here we review recent progress toward imaging many neurons and complete populations of identified neurons in small vertebrates and invertebrates.

High-throughput spatial light modulation two-photon microscopy for fast functional imaging

The optical monitoring of multiple single neuron activities requires high-throughput parallel acquisition of signals at millisecond temporal resolution. To this aim, holographic two-photon microscopy (2PM) based on spatial light modulators (SLMs) has been developed in combination with standard laser scanning microscopes. This requires complex coordinate transformations for the generation of holographic patterns illuminating the points of interest. We present a simpler and fully digital setup (SLM-2PM) which collects three-dimensional two-photon images by only exploiting the SLM. This configuration leads to an accurate placement of laser beamlets over small focal volumes, eliminating mechanically moving parts and making the system stable over long acquisition times. Fluorescence signals are diffraction limited and are acquired through a pixelated detector, setting the actual limit to the acquisition rate. High-resolution structural images were acquired by raster-scanning the sample with a regular grid of excitation focal volumes. These images allowed the selection of the structures to be further investigated through an interactive operator-guided selection process. Functional signals were collected by illuminating all the preselected points with a single hologram. This process is exemplified for high-speed (up to 1 kHz) two-photon calcium imaging on acute cerebellar slices.

Monitoring activity in neural circuits with genetically encoded indicators

Recent developments in genetically encoded indicators of neural activity (GINAs) have greatly advanced the field of systems neuroscience. As they are encoded by DNA, GINAs can be targeted to genetically defined cellular populations. Combined with fluorescence microscopy, most notably multi-photon imaging, GINAs allow chronic simultaneous optical recordings from large populations of neurons or glial cells in awake, behaving mammals, particularly rodents. This large-scale recording of neural activity at multiple temporal and spatial scales has greatly advanced our understanding of the dynamics of neural circuitry underlying behavior—a critical first step toward understanding the complexities of brain function, such as sensorimotor integration and learning. Here, we summarize the recent development and applications of the major classes of GINAs. In particular, we take an in-depth look at the design of available GINA families with a particular focus on genetically encoded calcium indicators (GCaMPs), sensors probing synaptic activity, and genetically encoded voltage indicators. Using the family of the GCaMP as an example, we review established sensor optimization pipelines. We also discuss practical considerations for end users of GINAs about experimental methods including approaches for gene delivery, imaging system requirements, and data analysis techniques. With the growing toolbox of GINAs and with new microscopy techniques pushing beyond their current limits, the age of light can finally achieve the goal of broad and dense sampling of neuronal activity across time and brain structures to obtain a dynamic picture of brain function.

Network structure within the cerebellar input layer enables lossless sparse encoding

The synaptic connectivity within neuronal networks is thought to determine the information processing they perform, yet network structure-function relationships remain poorly understood. By combining quantitative anatomy of the cerebellar input layer and information theoretic analysis of network models, we investigated how synaptic connectivity affects information transmission and processing. Simplified binary models revealed that the synaptic connectivity within feedforward networks determines the trade-off between information transmission and sparse encoding. Networks with few synaptic connections per neuron and network-activity-dependent threshold were optimal for lossless sparse encoding over the widest range of input activities. Biologically detailed spiking network models with experimentally constrained synaptic conductances and inhibition confirmed our analytical predictions. Our results establish that the synaptic connectivity within the cerebellar input layer enables efficient lossless sparse encoding. Moreover, they provide a functional explanation for why granule cells have approximately four dendrites, a feature that has been evolutionarily conserved since the appearance of fish.

WONOEP appraisal: new genetic approaches to study epilepsy

New genetic investigation techniques, including next-generation sequencing, epigenetic profiling, cell lineage mapping, targeted genetic manipulation of specific neuronal cell types, stem cell reprogramming, and optogenetic manipulations within epileptic networks are progressively unraveling the mysteries of epileptogenesis and ictogenesis. These techniques have opened new avenues to discover the molecular basis of epileptogenesis and to study the physiologic effects of mutations in epilepsy-associated genes on a multilayer level, from cells to circuits. This manuscript reviews recently published applications of these new genetic technologies in the study of epilepsy, as well as work presented by the authors at the genetic session of the XII Workshop on the Neurobiology of Epilepsy (WONOEP 2013) in Quebec, Canada. Next-generation sequencing is providing investigators with an unbiased means to assess the molecular causes of sporadic forms of epilepsy and has revealed the complexity and genetic heterogeneity of sporadic epilepsy disorders. To assess the functional impact of mutations in these newly identified genes on specific neuronal cell types during brain development, new modeling strategies in animals, including conditional genetics in mice and in utero knock-down approaches, are enabling functional validation with exquisite cell-type and temporal specificity. In addition, optogenetics, using cell-type-specific Cre recombinase driver lines, is enabling investigators to dissect networks involved in epilepsy. In addition, genetically encoded cell-type labeling is providing new means to assess the role of the nonneuronal components of epileptic networks such as glial cells. Furthermore, beyond its role in revealing coding variants involved in epileptogenesis, next-generation sequencing can be used to assess the epigenetic modifications that lead to sustained network hyperexcitability in epilepsy, including methylation changes in gene promoters and noncoding ribonucleic acid (RNA) involved in modifying gene expression following seizures. In addition, genetically based bioluminescent reporters are providing new opportunities to assess neuronal activity and neurotransmitter levels both in vitro and in vivo in the context of epilepsy. Finally, genetically rederived neurons generated from patient induced pluripotent stem cells and genetically modified zebrafish have become high-throughput means to investigate disease mechanisms and potential new therapies. Genetics has changed the field of epilepsy research considerably, and is paving the way for better diagnosis and therapies for patients with epilepsy.

The spatiotemporal organization of cerebellar network activity resolved by two-photon imaging of multiple single neurons

In order to investigate the spatiotemporal organization of neuronal activity in local microcircuits, techniques allowing the simultaneous recording from multiple single neurons are required. To this end, we implemented an advanced spatial-light modulator two-photon microscope (SLM-2PM). A critical issue for cerebellar theory is the organization of granular layer activity in the cerebellum, which has been predicted by single-cell recordings and computational models. With SLM-2PM, calcium signals could be recorded from different network elements in acute cerebellar slices including granule cells (GrCs), Purkinje cells (PCs) and molecular layer interneurons. By combining WCRs with SLM-2PM, the spike/calcium relationship in GrCs and PCs could be extrapolated toward the detection of single spikes. The SLM-2PM technique made it possible to monitor activity of over tens to hundreds neurons simultaneously. GrC activity depended on the number of spikes in the input mossy fiber bursts. PC and molecular layer interneuron activity paralleled that in the underlying GrC population revealing the spread of activity through the cerebellar cortical network. Moreover, circuit activity was increased by the GABA-A receptor blocker, gabazine, and reduced by the AMPA and NMDA receptor blockers, NBQX and APV. The SLM-2PM analysis of spatiotemporal patterns lent experimental support to the time-window and center-surround organizing principles of the granular layer.

Sensory-evoked synaptic integration in cerebellar and cerebral cortical neurons

Neurons integrate synaptic inputs across time and space, a process that determines the transformation of input signals into action potential output. This article explores how synaptic integration contributes to the richness of sensory signalling in the cerebellar and cerebral cortices. Whether a neuron receives a few or a few thousand discrete inputs, most evoked synaptic activity generates only subthreshold membrane potential fluctuations. Sensory tuning of synaptic inputs is typically broad, but short-term dynamics and the interplay between excitation and inhibition restrict action potential firing to narrow windows of opportunity. We highlight the challenges and limitations of the use of somatic recordings in the study of synaptic integration and the importance of active dendritic mechanisms in sensory processing.

Inference of neuronal network spike dynamics and topology from calcium imaging data

Two-photon calcium imaging enables functional analysis of neuronal circuits by inferring action potential (AP) occurrence ("spike trains") from cellular fluorescence signals. It remains unclear how experimental parameters such as signal-to-noise ratio (SNR) and acquisition rate affect spike inference and whether additional information about network structure can be extracted. Here we present a simulation framework for quantitatively assessing how well spike dynamics and network topology can be inferred from noisy calcium imaging data. For simulated AP-evoked calcium transients in neocortical pyramidal cells, we analyzed the quality of spike inference as a function of SNR and data acquisition rate using a recently introduced peeling algorithm. Given experimentally attainable values of SNR and acquisition rate, neural spike trains could be reconstructed accurately and with up to millisecond precision. We then applied statistical neuronal network models to explore how remaining uncertainties in spike inference affect estimates of network connectivity and topological features of network organization. We define the experimental conditions suitable for inferring whether the network has a scale-free structure and determine how well hub neurons can be identified. Our findings provide a benchmark for future calcium imaging studies that aim to reliably infer neuronal network properties.