Online correction of licking-induced brain motion during two-photon imaging with a tunable lens

Optical coherence tomography-based design for a real-time motion corrected scanning microscope

While two-photon fluorescence microscopy is a powerful platform for the study of functional dynamics in living cells and tissues, the bulk motion inherent to these applications causes distortions. We have designed a motion tracking module based on spectral domain optical coherence tomography which compliments a laser scanning two-photon microscope with real-time corrective feedback. The module can be added to fluorescent imaging microscopes using a single dichroic and without additional contrast agents. We demonstrate that the system can track lateral displacements as large as 10 μm at 5 Hz with latency under 14 ms and propose a scheme to extend the system to 3D correction with the addition of a remote focusing module. We also propose several ways to improve the module's performance by reducing the feedback latency. We anticipate that this design can be adapted to other imaging modalities, enabling the study of samples subject to motion artifacts at higher resolution.

Reliability of tunable lenses: feedback sensors and the influence of temperature, orientation, and vibrations

We compare different aspects of the robustness to environmental conditions of two different types of piezo-actuated fluid-membrane lenses: a silicone membrane lens, where the piezo actuator indirectly deforms the flexible membrane through fluid displacement, and a glass membrane lens, where the piezo actuator directly deforms the stiff membrane. While both lenses operated reliably over the temperature range of 0°-75°C, there was a significant effect on their actuation characteristics, which can be well described through a simple model. The silicone lens in particular showed a variation in focal power of up to 0.1m^{-1 ∘}C^-1. We demonstrated that integrated pressure and temperature sensors can provide feedback for focal power, however, limited by the response time of the elastomers in the lenses, with polyurethane in the support structures of the glass membrane lens being more critical than the silicone. Studying the mechanical effects, the silicone membrane lens showed a gravity-induced coma and tilt, and a reduced imaging quality with the Strehl ratio decreasing from 0.89 to 0.31 at a vibration frequency of 100 Hz and an acceleration of 3g. The glass membrane lens was unaffected by gravity, and the Strehl ratio decreased from 0.92 to 0.73 at a vibration of 100 Hz, 3g. Overall, the stiffer glass membrane lens is more robust against environmental influences.

A cranial implant for stabilizing whole-cell patch-clamp recordings in behaving rodents

BACKGROUND

In vivo patch-clamp recording techniques provide access to the sub- and suprathreshold membrane potential dynamics of individual neurons during behavior. However, maintaining recording stability throughout behavior is a significant challenge, and while methods for head restraint are commonly used to enhance stability, behaviorally related brain movement relative to the skull can severely impact the success rate and duration of whole-cell patch-clamp recordings.

NEW METHOD

We developed a low-cost, biocompatible, and 3D-printable cranial implant capable of locally stabilizing brain movement, while permitting equivalent access to the brain when compared to a conventional craniotomy.

RESULTS

Experiments in head-restrained behaving mice demonstrate that the cranial implant can reliably reduce the amplitude and speed of brain displacements, significantly improving the success rate of recordings across repeated bouts of motor behavior.

COMPARISON WITH EXISTING METHOD(S)

Our solution offers an improvement on currently available strategies for brain stabilization. Due to its small size, the implant can be retrofitted to most in vivo electrophysiology recording setups, providing a low cost, easily implementable solution for increasing intracellular recording stability in vivo.

CONCLUSIONS

By facilitating stable whole-cell patch-clamp recordings in vivo, biocompatible 3D printed implants should accelerate the investigation of single neuron computations underlying behavior.

Tunable doublets: piezoelectric glass membrane lenses with an achromatic and spherical aberration control

We present two versions of tunable achromatic doublets based on each two piezoelectrically actuated glass membranes that create the surface of fluid volumes with different dispersions: a straightforward back-to-back and a more intricate stack of the fluid volumes. In both cases, we can control the chromatic focal shift and focal power independently by a suitable combination of actuation voltages on both active membranes. The doublets have a large aperture of 12 mm at an outer diameter of the actuator of 18 mm, an overall thickness of 3 mm and a short response time of around 0.5 ms and, in addition, provide spherical aberration correction. The two designs have an achromatic focal power range of ±2.2 m^-1 and ±3.2 m^-1 or, for the purpose of actively correcting chromatic errors, a chromatic focal shift at vanishing combined focal power of up to ±0.08 m^-1 and ±0.12 m^-1.

Review on data analysis methods for mesoscale neural imaging in vivo

Significance: Mesoscale neural imaging in vivo has gained extreme popularity in neuroscience for its capacity of recording large-scale neurons in action. Optical imaging with single-cell resolution and millimeter-level field of view in vivo has been providing an accumulated database of neuron-behavior correspondence. Meanwhile, optical detection of neuron signals is easily contaminated by noises, background, crosstalk, and motion artifacts, while neural-level signal processing and network-level coordinate are extremely complicated, leading to laborious and challenging signal processing demands. The existing data analysis procedure remains unstandardized, which could be daunting to neophytes or neuroscientists without computational background. Aim: We hope to provide a general data analysis pipeline of mesoscale neural imaging shared between imaging modalities and systems. Approach: We divide the pipeline into two main stages. The first stage focuses on extracting high-fidelity neural responses at single-cell level from raw images, including motion registration, image denoising, neuron segmentation, and signal extraction. The second stage focuses on data mining, including neural functional mapping, clustering, and brain-wide network deduction. Results: Here, we introduce the general pipeline of processing the mesoscale neural images. We explain the principles of these procedures and compare different approaches and their application scopes with detailed discussions about the shortcomings and remaining challenges. Conclusions: There are great challenges and opportunities brought by the large-scale mesoscale data, such as the balance between fidelity and efficiency, increasing computational load, and neural network interpretability. We believe that global circuits on single-neuron level will be more extensively explored in the future.

Review of data processing of functional optical microscopy for neuroscience

Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.

Two-photon calcium imaging of neuronal activity

In vivo two-photon calcium imaging (2PCI) is a technique used for recording neuronal activity in the intact brain. It is based on the principle that, when neurons fire action potentials, intracellular calcium levels rise, which can be detected using fluorescent molecules that bind to calcium. This Primer is designed for scientists who are considering embarking on experiments with 2PCI. We provide the reader with a background on the basic concepts behind calcium imaging and on the reasons why 2PCI is an increasingly powerful and versatile technique in neuroscience. The Primer explains the different steps involved in experiments with 2PCI, provides examples of what ideal preparations should look like and explains how data are analysed. We also discuss some of the current limitations of the technique, and the types of solutions to circumvent them. Finally, we conclude by anticipating what the future of 2PCI might look like, emphasizing some of the analysis pipelines that are being developed and international efforts for data sharing.

All-optical interrogation of neural circuits in behaving mice

Recent advances combining two-photon calcium imaging and two-photon optogenetics with computer-generated holography now allow us to read and write the activity of large populations of neurons in vivo at cellular resolution and with high temporal resolution. Such 'all-optical' techniques enable experimenters to probe the effects of functionally defined neurons on neural circuit function and behavioral output with new levels of precision. This greatly increases flexibility, resolution, targeting specificity and throughput compared with alternative approaches based on electrophysiology and/or one-photon optogenetics and can interrogate larger and more densely labeled populations of neurons than current voltage imaging-based implementations. This protocol describes the experimental workflow for all-optical interrogation experiments in awake, behaving head-fixed mice. We describe modular procedures for the setup and calibration of an all-optical system (~3 h), the preparation of an indicator and opsin-expressing and task-performing animal (~3-6 weeks), the characterization of functional and photostimulation responses (~2 h per field of view) and the design and implementation of an all-optical experiment (achievable within the timescale of a normal behavioral experiment; ~3-5 h per field of view). We discuss optimizations for efficiently selecting and targeting neuronal ensembles for photostimulation sequences, as well as generating photostimulation response maps from the imaging data that can be used to examine the impact of photostimulation on the local circuit. We demonstrate the utility of this strategy in three brain areas by using different experimental setups. This approach can in principle be adapted to any brain area to probe functional connectivity in neural circuits and investigate the relationship between neural circuit activity and behavior.

Assessing Local and Branch-specific Activity in Dendrites

Dendrites are elaborate neural processes which integrate inputs from various sources in space and time. While decades of work have suggested an independent role for dendrites in driving nonlinear computations for the cell, only recently have technological advances enabled us to capture the variety of activity in dendrites and their coupling dynamics with the soma. Under certain circumstances, activity generated in a given dendritic branch remains isolated, such that the soma or even sister dendrites are not privy to these localized signals. Such branch-specific activity could radically increase the capacity and flexibility of coding for the cell as a whole. Here, we discuss these forms of localized and branch-specific activity, their functional relevance in plasticity and behavior, and their supporting biophysical and circuit-level mechanisms. We conclude by showcasing electrical and optical approaches in hippocampal area CA3, using original experimental data to discuss experimental and analytical methodology and key considerations to take when investigating the functional relevance of independent dendritic activity.

Fast and Accurate Motion Correction for Two-Photon Ca2+ Imaging in Behaving Mice

Two-photon Ca2+ imaging is a widely used technique for investigating brain functions across multiple spatial scales. However, the recording of neuronal activities is affected by movement of the brain during tasks in which the animal is behaving normally. Although post-hoc image registration is the commonly used approach, the recent developments of online neuroscience experiments require real-time image processing with efficient motion correction performance, posing new challenges in neuroinformatics. We propose a fast and accurate image density feature-based motion correction method to address the problem of imaging animal during behaviors. This method is implemented by first robustly estimating and clustering the density features from two-photon images. Then, it takes advantage of the temporal correlation in imaging data to update features of consecutive imaging frames with efficient calculations. Thus, motion artifacts can be quickly and accurately corrected by matching the features and obtaining the transformation parameters for the raw images. Based on this efficient motion correction strategy, our algorithm yields promising computational efficiency on imaging datasets with scales ranging from dendritic spines to neuronal populations. Furthermore, we show that the proposed motion correction method outperforms other methods by evaluating not only computational speed but also the quality of the correction performance. Specifically, we provide a powerful tool to perform motion correction for two-photon Ca2+ imaging data, which may facilitate online imaging experiments in the future.

Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging

Two-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion-related intensity changes or motion artifacts can typically not be separated from neural activity-induced signals. While lateral motion, within the focal plane, can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected. Here, we developed an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using temporally multiplexed beams, recording simultaneously from at least two focal planes at different z positions, and recording a z-stack for each beam as a calibration step, the algorithm separates motion-related and neural activity-induced changes in fluorescence intensity. The algorithm is based on a maximum likelihood optimisation approach; it assumes (as a first order approximation) that no distortions of the sample occurs during axial motion and that neural activity increases uniformly along the optical axis in each region of interest. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.

High-resolution structural and functional deep brain imaging using adaptive optics three-photon microscopy

Multiphoton microscopy has become a powerful tool with which to visualize the morphology and function of neural cells and circuits in the intact mammalian brain. However, tissue scattering, optical aberrations and motion artifacts degrade the imaging performance at depth. Here we describe a minimally invasive intravital imaging methodology based on three-photon excitation, indirect adaptive optics (AO) and active electrocardiogram gating to advance deep-tissue imaging. Our modal-based, sensorless AO approach is robust to low signal-to-noise ratios as commonly encountered in deep scattering tissues such as the mouse brain, and permits AO correction over large axial fields of view. We demonstrate near-diffraction-limited imaging of deep cortical spines and (sub)cortical dendrites up to a depth of 1.4 mm (the edge of the mouse CA1 hippocampus). In addition, we show applications to deep-layer calcium imaging of astrocytes, including fibrous astrocytes that reside in the highly scattering corpus callosum.

Electrically tunable lenses - eliminating mechanical axial movements during high-speed 3D live imaging

The successful investigation of photosensitive and dynamic biological events, such as those in a proliferating tissue or a dividing cell, requires non-intervening high-speed imaging techniques. Electrically tunable lenses (ETLs) are liquid lenses possessing shape-changing capabilities that enable rapid axial shifts of the focal plane, in turn achieving acquisition speeds within the millisecond regime. These human-eye-inspired liquid lenses can enable fast focusing and have been applied in a variety of cell biology studies. Here, we review the history, opportunities and challenges underpinning the use of cost-effective high-speed ETLs. Although other, more expensive solutions for three-dimensional imaging in the millisecond regime are available, ETLs continue to be a powerful, yet inexpensive, contender for live-cell microscopy.

Eavesdropping wires: Recording activity in axons using genetically encoded calcium indicators

Neurons broadcast electrical signals to distal brain regions through extensive axonal arbors. Genetically encoded calcium sensors permit the direct observation of action potential activity at axonal terminals, providing unique insights on the organization and function of neural projections. Here, we consider what information can be gleaned from axonal recordings made at scales ranging from the summed activity extracted from multi-cell axon projections to single boutons. In particular, we discuss the application of different recently developed multi photon and fiber photometry methods for recording neural activity in axons of rodents. We define experimental difficulties associated with imaging approaches in the axonal compartment and highlight the latest methodological advances for addressing these issues. Finally, we reflect on ways in which new technologies can be used in conjunction with axon calcium imaging to address current questions in neurobiology.

Decoding locomotion from population neural activity in moving C. elegans

We investigated the neural representation of locomotion in the nematode C. elegans by recording population calcium activity during movement. We report that population activity more accurately decodes locomotion than any single neuron. Relevant signals are distributed across neurons with diverse tunings to locomotion. Two largely distinct subpopulations are informative for decoding velocity and curvature, and different neurons’ activities contribute features relevant for different aspects of a behavior or different instances of a behavioral motif. To validate our measurements, we labeled neurons AVAL and AVAR and found that their activity exhibited expected transients during backward locomotion. Finally, we compared population activity during movement and immobilization. Immobilization alters the correlation structure of neural activity and its dynamics. Some neurons positively correlated with AVA during movement become negatively correlated during immobilization and vice versa. This work provides needed experimental measurements that inform and constrain ongoing efforts to understand population dynamics underlying locomotion in C. elegans.

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.

Dynamic perceptual feature selectivity in primary somatosensory cortex upon reversal learning

Neurons in primary sensory cortex encode a variety of stimulus features upon perceptual learning. However, it is unclear whether the acquired stimulus selectivity remains stable when the same input is perceived in a different context. Here, we monitor the activity of individual neurons in the mouse primary somatosensory cortex during reward-based texture discrimination. We track their stimulus selectivity before and after changing reward contingencies, which allows us to identify various classes of neurons. We find neurons that stably represented a texture or the upcoming behavioral choice, but the majority is dynamic. Among those, a subpopulation of neurons regains texture selectivity contingent on the associated reward value. These value-sensitive neurons forecast the onset of learning by displaying a distinct and transient increase in activity, depending on past behavioral experience. Thus, stimulus selectivity of excitatory neurons during perceptual learning is dynamic and largely relies on behavioral contingencies, even in primary sensory cortex.

Do cortical neurons stably represent stimulus features in different contexts? Here, using calcium imaging, the authors show that texture selectivity of individual neurons is dynamic during reversal learning. For a subclass this is contingent on the associated reward and forecasts the onset of learning.

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.

Somatic and Dendritic Encoding of Spatial Variables in Retrosplenial Cortex Differs during 2D Navigation

Active amplification of organized synaptic inputs in dendrites can endow individual neurons with the ability to perform complex computations. However, whether dendrites in behaving animals perform independent local computations is not known. Such activity may be particularly important for complex behavior, where neurons integrate multiple streams of information. Head-restrained imaging has yielded important insights into cellular and circuit function, but this approach limits behavior and the underlying computations. We describe a method for full-featured 2-photon imaging in awake mice during free locomotion with volitional head rotation. We examine head direction and position encoding in simultaneously imaged apical tuft dendrites and their respective cell bodies in retrosplenial cortex, an area that encodes multi-modal navigational information. Activity in dendrites was not determined solely by somatic activity but reflected distinct navigational variables, fulfilling the requirements for dendritic computation. Our approach provides a foundation for studying sub-cellular processes during complex behaviors.

Aberration-free multi-plane imaging of neural activity from the mammalian brain using a fast-switching liquid crystal spatial light modulator

We report a novel two-photon fluorescence microscope based on a fast-switching liquid crystal spatial light modulator and a pair of galvo-resonant scanners for large-scale recording of neural activity from the mammalian brain. The spatial light modulator is used to achieve fast switching between different imaging planes in multi-plane imaging and correct for intrinsic optical aberrations associated with this imaging scheme. The utilized imaging technique is capable of monitoring the neural activity from large populations of neurons with known coordinates spread across different layers of the neocortex in awake and behaving mice, regardless of the fluorescent labeling strategy. During each imaging session, all visual stimulus driven somatic activity could be recorded in the same behavior state. We observed heterogeneous response to different types of visual stimuli from ∼ 3,300 excitatory neurons reaching from layer II/III to V of the striate cortex.

Opposing Influence of Sensory and Motor Cortical Input on Striatal Circuitry and Choice Behavior

The striatum is the main input nucleus of the basal ganglia and is a key site of sensorimotor integration. While the striatum receives extensive excitatory afferents from the cerebral cortex, the influence of different cortical areas on striatal circuitry and behavior is unknown. Here, we find that corticostriatal inputs from whisker-related primary somatosensory (S1) and motor (M1) cortex differentially innervate projection neurons and interneurons in the dorsal striatum and exert opposing effects on sensory-guided behavior. Optogenetic stimulation of S1-corticostriatal afferents in ex vivo recordings produced larger postsynaptic potentials in striatal parvalbumin (PV)-expressing interneurons than D1- or D2-expressing spiny projection neurons (SPNs), an effect not observed for M1-corticostriatal afferents. Critically, in vivo optogenetic stimulation of S1-corticostriatal afferents produced task-specific behavioral inhibition, which was bidirectionally modulated by striatal PV interneurons. Optogenetic stimulation of M1 afferents produced the opposite behavioral effect. Thus, our results suggest opposing roles for sensory and motor cortex in behavioral choice via distinct influences on striatal circuitry.

A novel device for real-time measurement and manipulation of licking behavior in head-fixed mice

The mouse has become an influential model system for investigating the mammalian nervous system. Technologies in mice enable recording and manipulation of neural circuits during tasks where they respond to sensory stimuli by licking for liquid rewards. Precise monitoring of licking during these tasks provides an accessible metric of sensory-motor processing, particularly when combined with simultaneous neural recordings. There are several challenges in designing and implementing lick detectors during head-fixed neurophysiological experiments in mice. First, mice are small, and licking behaviors are easily perturbed or biased by large sensors. Second, neural recordings during licking are highly sensitive to electrical contact artifacts. Third, submillisecond lick detection latencies are required to generate control signals that manipulate neural activity at appropriate time scales. Here we designed, characterized, and implemented a contactless dual-port device that precisely measures directional licking in head-fixed mice performing visual behavior. We first determined the optimal characteristics of our detector through design iteration and then quantified device performance under ideal conditions. We then tested performance during head-fixed mouse behavior with simultaneous neural recordings in vivo. We finally demonstrate our device's ability to detect directional licks and generate appropriate control signals in real time to rapidly suppress licking behavior via closed-loop inhibition of neural activity. Our dual-port detector is cost effective and easily replicable, and it should enable a wide variety of applications probing the neural circuit basis of sensory perception, motor action, and learning in normal and transgenic mouse models. NEW & NOTEWORTHY Mice readily learn tasks in which they respond to sensory cues by licking for liquid rewards; tasks that involve multiple licking responses allow study of neural circuits underlying decision making and sensory-motor integration. Here we design, characterize, and implement a novel dual-port lick detector that precisely measures directional licking in head-fixed mice performing visual behavior, enabling simultaneous neural recording and closed-loop manipulation of licking.

Technologies for imaging neural activity in large volumes

Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Conventional microscopy collects data from individual planes and cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point-spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for processing and analyzing volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics and helping elucidate how brain regions work in concert to support behavior.

Automated Remote Focusing, Drift Correction, and Photostimulation to Evaluate Structural Plasticity in Dendritic Spines

Long-term structural plasticity of dendritic spines plays a key role in synaptic plasticity, the cellular basis for learning and memory. The biochemical step is mediated by a complex network of signaling proteins in spines. Two-photon imaging techniques combined with two-photon glutamate uncaging allows researchers to induce and quantify structural plasticity in single dendritic spines. However, this method is laborious and slow, making it unsuitable for high throughput screening of factors necessary for structural plasticity. Here we introduce a MATLAB-based module built for Scanimage to automatically track, image, and stimulate multiple dendritic spines. We implemented an electrically tunable lens in combination with a drift correction algorithm to rapidly and continuously track targeted spines and correct sample movements. With a straightforward user interface to design custom multi-position experiments, we were able to adequately image and produce targeted plasticity in multiple dendritic spines using glutamate uncaging. Our methods are inexpensive, open source, and provides up to a five-fold increase in throughput for quantifying structural plasticity of dendritic spines.

Pupil Dynamics Reflect Behavioral Choice and Learning in a Go/NoGo Tactile Decision-Making Task in Mice

The eye’s pupil undergoes dynamic changes in diameter associated with cognitive effort, motor activity and emotional state, and can be used to index brain state across mammalian species. Recent studies in head-fixed mice have linked arousal-related pupil dynamics with global neural activity as well as the activity of specific neuronal populations. However, it has remained unclear how pupil dynamics in mice report trial-by-trial performance of behavioral tasks, and change on a longer time scale with learning. We measured pupil dynamics longitudinally as mice learned to perform a Go/NoGo tactile decision-making task. Mice learned to discriminate between two textures presented to the whiskers by licking in response to the Go texture (Hit trial) or withholding licking in response to the NoGo texture (Correct Reject trial, CR). Characteristic pupil dynamics were associated with behavioral choices: large-amplitude pupil dilation prior to and during licking accompanied Hit and False Alarm (FA) responses, while smaller amplitude dilation followed by constriction accompanied CR responses. With learning, the choice-dependent pupil dynamics became more pronounced, including larger amplitude dilations in both Hit and FA trials and earlier onset dilations in Hit and CR trials. A more pronounced constriction was also present in CR trials. Furthermore, pupil dynamics predicted behavioral choice increasingly with learning to greater than 80% accuracy. Our results indicate that pupil dynamics reflect behavioral choice and learning in head-fixed mice, and have implications for understanding decision- and learning-related neuronal activity in pupil-linked neural circuits.

Parallel processing by cortical inhibition enables context-dependent behavior

Physical features of sensory stimuli are fixed, but sensory perception is context-dependent. The precise mechanisms that govern contextual modulation remain unknown. Here, we trained mice to switch between two contexts: passively listening to pure tones vs. performing a recognition task for the same stimuli. Two-photon imaging showed that many excitatory neurons in auditory cortex were suppressed, while some cells became more active during behavior. Whole-cell recordings showed that excitatory inputs were only modestly affected by context, but inhibition was more sensitive, with PV, SOM+, and VIP+ interneurons balancing inhibition/disinhibition within the network. Cholinergic modulation was involved in context-switching, with cholinergic axons increasing activity during behavior and directly depolarizing inhibitory cells. Network modeling captured these findings, but only when modulation coincidently drove all three interneuron subtypes, ruling out either inhibition or disinhibition alone as sole mechanism for active engagement. Parallel processing of cholinergic modulation by cortical interneurons therefore enables context-dependent behavior.

Motion quantification during multi-photon functional imaging in behaving animals

Functional imaging in behaving animals is essential to understanding brain function. However, artifacts resulting from animal motion, including locomotion, can severely corrupt functional measurements. To dampen tissue motion, we designed a new optical window with minimal optical aberrations. Using the newly developed high-speed continuous volumetric imaging system based on an optical phase-locked ultrasound lens, we quantified motion of the cerebral cortex and hippocampal surface during two-photon functional imaging in behaving mice. We find that the out-of-plane motion is generally greater than the axial dimension of the point-spread-function during mouse locomotion, which indicates that high-speed continuous volumetric imaging is necessary to minimize motion artifacts.

Improving data quality in neuronal population recordings

Understanding how the brain operates requires understanding how large sets of neurons function together. Modern recording technology makes it possible to simultaneously record the activity of hundreds of neurons, and technological developments will soon allow recording of thousands or tens of thousands. As with all experimental techniques, these methods are subject to confounds that complicate the interpretation of such recordings, and could lead to erroneous scientific conclusions. Here we discuss methods for assessing and improving the quality of data from these techniques and outline likely future directions in this field.

Compact multi-band fluorescent microscope with an electrically tunable lens for autofocusing

Autofocusing is a routine technique in redressing focus drift that occurs in time-lapse microscopic image acquisition. To date, most automatic microscopes are designed on the distance detection scheme to fulfill the autofocusing operation, which may suffer from the low contrast of the reflected signal due to the refractive index mismatch at the water/glass interface. To achieve high autofocusing speed with minimal motion artifacts, we developed a compact multi-band fluorescent microscope with an electrically tunable lens (ETL) device for autofocusing. A modified searching algorithm based on equidistant scanning and curve fitting is proposed, which no longer requires a single-peak focus curve and then efficiently restrains the impact of external disturbance. This technique enables us to achieve an autofocusing time of down to 170 ms and the reproductivity of over 97%. The imaging head of the microscope has dimensions of 12 cm × 12 cm × 6 cm. This portable instrument can easily fit inside standard incubators for real-time imaging of living specimens.

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.

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.

Optical neural interfaces

Genetically encoded optical actuators and indicators have changed the landscape of neuroscience, enabling targetable control and readout of specific components of intact neural circuits in behaving animals. Here, we review the development of optical neural interfaces, focusing on hardware designed for optical control of neural activity, integrated optical control and electrical readout, and optical readout of population and single-cell neural activity in freely moving mammals.

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.