Imaging in vivo: watching the brain in action

Application of machine learning in the study of development, behavior, nerve, and genotoxicity of zebrafish

Machine learning (ML) as a novel model-based approach has been used in studying aquatic toxicology in the environmental field. Zebrafish, as an ideal model organism in aquatic toxicology research, has been widely used to study the toxic effects of various pollutants. However, toxicity testing on organisms may cause significant harm, consume considerable time and resources, and raise ethical concerns. Therefore, ML is used in related research to reduce animal experiments and assist researchers in conducting toxicological research. Although ML techniques have matured in various fields, research on ML-based aquatic toxicology is still in its infancy due to the lack of comprehensive large-scale toxicity databases for environmental pollutants and model organisms. Therefore, to better understand the recent research progress of ML in studying the development, behavior, nerve, and genotoxicity of zebrafish, this review mainly focuses on using ML modeling to assess and predict the toxic effects of zebrafish exposure to different toxic chemicals. Meanwhile, the opportunities and challenges faced by ML in the field of toxicology were analyzed. Finally, suggestions and perspectives were proposed for the toxicity studies of ML on zebrafish in future applications.

CalciSeg: A versatile approach for unsupervised segmentation of calcium imaging data

Recent advances in calcium imaging, including the development of fast and sensitive genetically encoded indicators, high-resolution camera chips for wide-field imaging, and resonant scanning mirrors in laser scanning microscopy, have notably improved the temporal and spatial resolution of functional imaging analysis. Nonetheless, the variability of imaging approaches and brain structures challenges the development of versatile and reliable segmentation methods. Standard techniques, such as manual selection of regions of interest or machine learning solutions, often fall short due to either user bias, non-transferability among systems, or computational demand. To overcome these issues, we developed CalciSeg, a data-driven and reproducible approach for unsupervised functional calcium imaging data segmentation. CalciSeg addresses the challenges associated with brain structure variability and user bias by offering a computationally efficient solution for automatic image segmentation based on two parameters: regions' size limits and number of refinement iterations. We evaluated CalciSeg efficacy on datasets of varied complexity, different insect species (locusts, bees, and cockroaches), and imaging systems (wide-field, confocal, and multiphoton), showing the robustness and generality of our approach. Finally, the user-friendly nature and open-source availability of CalciSeg facilitate the integration of this algorithm into existing analysis pipelines.

A low dimensional embedding of brain dynamics enhances diagnostic accuracy and behavioral prediction in stroke

Large-scale brain networks reveal structural connections as well as functional synchronization between distinct regions of the brain. The latter, referred to as functional connectivity (FC), can be derived from neuroimaging techniques such as functional magnetic resonance imaging (fMRI). FC studies have shown that brain networks are severely disrupted by stroke. However, since FC data are usually large and high-dimensional, extracting clinically useful information from this vast amount of data is still a great challenge, and our understanding of the functional consequences of stroke remains limited. Here, we propose a dimensionality reduction approach to simplify the analysis of this complex neural data. By using autoencoders, we find a low-dimensional representation encoding the fMRI data which preserves the typical FC anomalies known to be present in stroke patients. By employing the latent representations emerging from the autoencoders, we enhanced patients' diagnostics and severity classification. Furthermore, we showed how low-dimensional representation increased the accuracy of recovery prediction.

New horizons in emotional well-being and brain aging: Potential lessons from cross-species research

Emotional wellbeing (EWB) is a multi-faceted concept of immediate relevance to human health. NIH recently initiated a series of research networks to advance understanding of EWB. Our network (NEW Brain Aging) focuses on mechanistic understanding of EWB in relation to brain aging. Here, by synthesizing the literature on emotional processing and the underlying brain circuit mechanisms in human and non-human animals, we propose a reactivity and reappraisal model for understanding EWB and its age-related changes. This model emphasizes the dynamic interactions between affective stimuli, behavioral/physiological responses, brain emotional states, and subjective feelings. It also aims to integrate the unique emotional processes involved in explaining EWB in aging humans with the emerging mechanistic insight of topologically conserved emotional brain networks from cross-species studies. We also highlight the research opportunities and challenges in EWB and brain aging research and the potential application of the model in addressing these issues.

Effective and efficient neural networks for spike inference from in vivo calcium imaging

Calcium imaging provides advantages in monitoring large populations of neuronal activities simultaneously. However, it lacks the signal quality provided by neural spike recording in traditional electrophysiology. To address this issue, we developed a supervised data-driven approach to extract spike information from calcium signals. We propose the ENS2 (effective and efficient neural networks for spike inference from calcium signals) system for spike-rate and spike-event predictions using ΔF/F0 calcium inputs based on a U-Net deep neural network. When testing on a large, ground-truth public database, it consistently outperformed state-of-the-art algorithms in both spike-rate and spike-event predictions with reduced computational load. We further demonstrated that ENS2 can be applied to analyses of orientation selectivity in primary visual cortex neurons. We conclude that it would be a versatile inference system that may benefit diverse neuroscience studies.

Efficient inference of synaptic plasticity rule with Gaussian process regression

Finding the form of synaptic plasticity is critical to understanding its functions underlying learning and memory. We investigated an efficient method to infer synaptic plasticity rules in various experimental settings. We considered biologically plausible models fitting a wide range of in-vitro studies and examined the recovery of their firing-rate dependence from sparse and noisy data. Among the methods assuming low-rankness or smoothness of plasticity rules, Gaussian process regression (GPR), a nonparametric Bayesian approach, performs the best. Under the conditions measuring changes in synaptic weights directly or measuring changes in neural activities as indirect observables of synaptic plasticity, which leads to different inference problems, GPR performs well. Also, GPR could simultaneously recover multiple plasticity rules and robustly perform under various plasticity rules and noise levels. Such flexibility and efficiency, particularly at the low sampling regime, make GPR suitable for recent experimental developments and inferring a broader class of plasticity models.

Novel Design and Application of High-NA Fiber Imaging Bundles for In Vivo Brain Imaging with Two-Photon Scanning Fluorescence Microscopy

Here, we provide experimental verification supporting the use of short-section imaging bundles for two-photon microscopy imaging of the mouse brain. The 8 mm long bundle is made of a pair of heavy-metal oxide glasses with a refractive index contrast of 0.38 to ensure a high numerical aperture NA = 1.15. The bundle is composed of 825 multimode cores, ordered in a hexagonal lattice with a pixel size of 14 μm and a total diameter of 914 μm. We demonstrate successful imaging through custom-made bundles with 14 μm resolution. As the input, we used a 910 nm Ti-sapphire laser with 140 fs pulse and a peak power of 9 × 10⁴ W. The excitation beam and fluorescent image were transferred through the fiber imaging bundle. As test samples, we used 1 μm green fluorescent latex beads, ex vivo hippocampal neurons expressing green fluorescent protein and cortical neurons in vivo expressing the fluorescent reporter GCaMP6s or immediate early gene Fos fluorescent reporter. This system can be used for minimal-invasive in vivo imaging of the cerebral cortex, hippocampus, or deep brain areas as a part of a tabletop system or an implantable setup. It is a low-cost solution, easy to integrate and operate for high-throughput experiments.

Spectrally Resolved Fiber Photometry for In Vivo Multi-Color Fluorescence Measurements

This article describes how to assemble and operate a spectrometer-based fiber photometry system for in vivo simultaneous measurements of multiple fluorescent biosensors in freely moving mice. The first section of the article describes the step-by-step procedure to assemble a basic single-spectrometer fiber photometry system and how to expand it into a dual-spectrometer system that allows for simultaneous recordings from two sites. The second part describes the steps for a typical fiber probe implantation surgery. The last section describes how to acquire and analyze the time-lapsed spectral data. This article is intended for teaching labs how to build their own fiber photometry systems (with a video tutorial) from commercially available parts and perform in vivo recordings in behaving mice. © Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Basic Protocol 1: Assembling a dual-laser, single-spectrometer fiber photometry system Support Protocol: Dual-spectrometer fiber photometry assembly Basic Protocol 2: Optical fiber probe implantation Basic Protocol 3: Data acquisition and analysis.

Multiscale photoacoustic tomography of neural activities with GCaMP calcium indicators

SIGNIFICANCE

Optical imaging of responses in fluorescently labeled neurons has progressed significantly in recent years. However, there is still a need to monitor neural activities at divergent spatial scales and at depths beyond the optical diffusion limit.

AIM

To meet these needs, we aim to develop multiscale photoacoustic tomography (PAT) to image neural activities across spatial scales with a genetically encoded calcium indicator GCaMP.

APPROACH

First, using photoacoustic microscopy, we show that depth-resolved GCaMP signals can be monitored in vivo from a fly brain in response to odor stimulation without depth scanning and even with the cuticle intact. In vivo monitoring of GCaMP signals was also demonstrated in mouse brains. Next, using photoacoustic computed tomography, we imaged neural responses of a mouse brain slice at depths beyond the optical diffusion limit.

RESULTS

We provide the first unambiguous demonstration that multiscale PAT can be used to record neural activities in transgenic flies and mice with select neurons expressing GCaMP.

CONCLUSIONS

Our results indicate that the combination of multiscale PAT and fluorescent neural activity indicators provides a methodology for imaging targeted neurons at various scales.

A one-photon endoscope for simultaneous patterned optogenetic stimulation and calcium imaging in freely behaving mice

Optogenetics and calcium imaging can be combined to simultaneously stimulate and record neural activity in vivo. However, this usually requires two-photon microscopes, which are not portable nor affordable. Here we report the design and implementation of a miniaturized one-photon endoscope for performing simultaneous optogenetic stimulation and calcium imaging. By integrating digital micromirrors, the endoscope makes it possible to activate any neuron of choice within the field of view, and to apply arbitrary spatiotemporal patterns of photostimulation while imaging calcium activity. We used the endoscope to image striatal neurons from either the direct pathway or the indirect pathway in freely moving mice while activating any chosen neuron in the field of view. The endoscope also allows for the selection of neurons based on their relationship with specific animal behaviour, and to recreate the behaviour by mimicking the natural neural activity with photostimulation. The miniaturized endoscope may facilitate the study of how neural activity gives rise to behaviour in freely moving animals.

Development of Compact Readout Device for Neural Observation System using Fluorescence Imaging and Fast-scan Cyclic Voltammetry

A readout device for a dual-functional neural observation system is presented. The authors separately developed the reading operation of an implantable CMOS image sensor and a setup for fast-scan cyclic voltammetry and implemented them together in a microcontroller-based device. The developed imaging readout device with a size of [Formula: see text] can reach the highest reading rate of 160 fps with a 120×268 pixel image sensor. The voltammetry function was verified through an experiment using commercial carbon fiber electrodes in phosphate-buffered saline. When the imaging is sequentially operated with 400 V/s-scan rate voltammetry from -0.4 to 1.3 V, the system can operate at up to 60 fps. With this system, calcium imaging and dopamine recording in a freely behaving mouse can be achieved together in a simpler manner. This study aims to be the basis for the development of an implantable multi-functional sensor.

Cranial and Spinal Window Preparation for in vivo Optical Neuroimaging in Rodents and Related Experimental Techniques

Optical neuroimaging provides an effective neuroscience tool for multi-scale investigation of the neural structures and functions, ranging from molecular, cellular activities to the inter-regional connectivity assessment. Amongst experimental preparations, the implementation of an artificial window to the central nervous system (CNS) is primarily required for optical visualization of the CNS and associated brain activities through the opaque skin and bone. Either thinning down or removing portions of the skull or spine is necessary for unobstructed long-term in vivo observations, for which types of the cranial and spinal window and applied materials vary depending on the study objectives. As diversely useful, a window can be designed to accommodate other experimental methods such as electrophysiology or optogenetics. Moreover, auxiliary apparatuses would allow the recording in synchrony with behavior of large-scale brain connectivity signals across the CNS, such as olfactory bulb, cerebral cortex, cerebellum, and spinal cord. Such advancements in the cranial and spinal window have resulted in a paradigm shift in neuroscience, enabling in vivo investigation of the brain function and dysfunction at the microscopic, cellular level. This Review addresses the types and classifications of windows used in optical neuroimaging while describing how to perform in vivo studies using rodent models in combination with other experimental modalities during behavioral tests. The cranial and spinal window has enabled longitudinal examination of evolving neural mechanisms via in situ visualization of the brain. We expect transformable and multi-functional cranial and spinal windows to become commonplace in neuroscience laboratories, further facilitating advances in optical neuroimaging systems.

Neuropathic pain caused by miswiring and abnormal end organ targeting

Nerve injury leads to chronic pain and exaggerated sensitivity to gentle touch (allodynia) as well as a loss of sensation in the areas in which injured and non-injured nerves come together1-3. The mechanisms that disambiguate these mixed and paradoxical symptoms are unknown. Here we longitudinally and non-invasively imaged genetically labelled populations of fibres that sense noxious stimuli (nociceptors) and gentle touch (low-threshold afferents) peripherally in the skin for longer than 10 months after nerve injury, while simultaneously tracking pain-related behaviour in the same mice. Fully denervated areas of skin initially lost sensation, gradually recovered normal sensitivity and developed marked allodynia and aversion to gentle touch several months after injury. This reinnervation-induced neuropathic pain involved nociceptors that sprouted into denervated territories precisely reproducing the initial pattern of innervation, were guided by blood vessels and showed irregular terminal connectivity in the skin and lowered activation thresholds mimicking low-threshold afferents. By contrast, low-threshold afferents-which normally mediate touch sensation as well as allodynia in intact nerve territories after injury4-7-did not reinnervate, leading to an aberrant innervation of tactile end organs such as Meissner corpuscles with nociceptors alone. Genetic ablation of nociceptors fully abrogated reinnervation allodynia. Our results thus reveal the emergence of a form of chronic neuropathic pain that is driven by structural plasticity, abnormal terminal connectivity and malfunction of nociceptors during reinnervation, and provide a mechanistic framework for the paradoxical sensory manifestations that are observed clinically and can impose a heavy burden on patients.

Three-Photon Adaptive Optics for Mouse Brain Imaging

Three-photon microscopy (3PM) was shown to allow deeper imaging than two-photon microscopy (2PM) in scattering biological tissues, such as the mouse brain, since the longer excitation wavelength reduces tissue scattering and the higher-order non-linear excitation suppresses out-of-focus background fluorescence. Imaging depth and resolution can further be improved by aberration correction using adaptive optics (AO) techniques where a spatial light modulator (SLM) is used to correct wavefront aberrations. Here, we present and analyze a 3PM AO system for in vivo mouse brain imaging. We use a femtosecond source at 1300 nm to generate three-photon (3P) fluorescence in yellow fluorescent protein (YFP) labeled mouse brain and a microelectromechanical (MEMS) SLM to apply different Zernike phase patterns. The 3P fluorescence signal is used as feedback to calculate the amount of phase correction without direct phase measurement. We show signal improvement in the cortex and the hippocampus at greater than 1 mm depth and demonstrate close to diffraction-limited imaging in the cortical layers of the brain, including imaging of dendritic spines. In addition, we characterize the effective volume for AO correction within brain tissues, and discuss the limitations of AO correction in 3PM of mouse brain.

Two-photon microscopy with enhanced resolution and signal-to-background ratio using hollow Gaussian beam excitation

Two-photon microscopy (TPM) offers deeper imaging depth inside the scattering medium, however, it suffers from limited resolution owing to the longer excitation wavelength. We demonstrate the use of a hollow Gaussian beam (HGB) at the therapeutic window to improve the resolution and signal-to-background ratio (SBR). The HGB was produced by omitting the azimuthal phase term from the vortex mode, and the excitation point spread function (PSF) can be readily tuned by the mode order. The performance of the TPM with HGB was evaluated by experimentally imaging 100 nm fluorescent beads to estimate the PSF. The HGB improved the lateral resolution of the TPM by 36% in contrast to the conventional TPM. The HGB also furnishes an improvement of SBR by eliminating the out-of-focus light owing to its ring shape. Furthermore, we have used a translating lens-based module for additional lateral resolution tuning and reduced the resolution further down to 44% with respect to conventional TPM. Finally, we have performed imaging with merely two-dimensional scanning of a 50 µm thick mouse brain slice (Thy-YFP H-line) using the developed TPM with HGB. Our compact, robust, and low-cost design of the HGB generation scheme can easily be integrated into the commercial TPM to accommodate the improvements.

Deep-learning two-photon fiberscopy for video-rate brain imaging in freely-behaving mice

Scanning two-photon (2P) fiberscopes (also termed endomicroscopes) have the potential to transform our understanding of how discrete neural activity patterns result in distinct behaviors, as they are capable of high resolution, sub cellular imaging yet small and light enough to allow free movement of mice. However, their acquisition speed is currently suboptimal, due to opto-mechanical size and weight constraints. Here we demonstrate significant advances in 2P fiberscopy that allow high resolution imaging at high speeds (26 fps) in freely-behaving mice. A high-speed scanner and a down-sampling scheme are developed to boost imaging speed, and a deep learning (DL) algorithm is introduced to recover image quality. For the DL algorithm, a two-stage learning transfer strategy is established to generate proper training datasets for enhancing the quality of in vivo images. Implementation enables video-rate imaging at ~26 fps, representing 10-fold improvement in imaging speed over the previous 2P fiberscopy technology while maintaining a high signal-to-noise ratio and imaging resolution. This DL-assisted 2P fiberscope is capable of imaging the arousal-induced activity changes in populations of layer2/3 pyramidal neurons in the primary motor cortex of freely-behaving mice, providing opportunities to define the neural basis of behavior.

The acquisition speed of two-photon fiberscopes is currently suboptimal. Here the authors report advances, including a high-speed scanner and down-sampling scheme as well as a two-stage deep learning (DL) algorithm, to allow high-speed, high-resolution imaging in freely moving mice.

Intracortical microstimulation pulse waveform and frequency recruits distinct spatiotemporal patterns of cortical neuron and neuropil activation

OBJECTIVE

Neural prosthetics often use intracortical microstimulation (ICMS) for sensory restoration. To restore natural and functional feedback, we must first understand how stimulation parameters influence the recruitment of neural populations. ICMS waveform asymmetry modulates the spatial activation of neurons around an electrode at 10 Hz; however, it is unclear how asymmetry may differentially modulate population activity at frequencies typically employed in the clinic (e.g. 100 Hz). We hypothesized that stimulation waveform asymmetry would differentially modulate preferential activation of certain neural populations, and the differential population activity would be frequency-dependent.

APPROACH

We quantified how asymmetric stimulation waveforms delivered at 10 Hz or 100 Hz for 30s modulated spatiotemporal activity of cortical layer II/III pyramidal neurons using in vivo two-photon and mesoscale calcium imaging in anesthetized mice. Asymmetry is defined in terms of the ratio of the duration of the leading phase to the duration of the return phase of charge-balanced cathodal- and anodal-first waveforms (i.e. longer leading phase relative to return has larger asymmetry).

MAIN RESULTS

Neurons within 40-60µm of the electrode display stable stimulation-induced activity indicative of direct activation, which was independent of waveform asymmetry. The stability of 72% of activated neurons and the preferential activation of 20-90 % of neurons depended on waveform asymmetry. Additionally, this asymmetry-dependent activation of different neural populations was associated with differential progression of population activity. Specifically, neural activity tended to increase over time during 10 hz stimulation for some waveforms, whereas activity remained at the same level throughout stimulation for other waveforms. During 100 Hz stimulation, neural activity decreased over time for all waveforms, but decreased more for the waveforms that resulted in increasing neural activity during 10 Hz stimulation.

SIGNIFICANCE

These data demonstrate that at frequencies commonly used for sensory restoration, stimulation waveform alters the pattern of activation of different but overlapping populations of excitatory neurons. The impact of these waveform specific responses on the activation of different subtypes of neurons as well as sensory perception merits further investigation.

In vivo visualization of murine melanoma cells B16-derived exosomes through magnetic resonance imaging

BACKGROUND

Numerous studies demonstrated that exosomes play a powerful role in mediating intercellular communication to induce a pro-tumoral environment to promote tumor progression, including pre-metastatic niche formation and metastasis. Noninvasive imaging could determine the in vivo kinetics of exosomes in real time to provide better understanding of the mechanisms of the tumor formation, progression and metastasis. Magnetic resonance imaging (MRI) is an ideal technique which provides excellent anatomical resolution, intrinsic soft tissue contrast, unlimited penetration depth and no radiation exposure.

METHODS

A fusion protein composed of ferritin heavy chain (FTH1) and lactadherin was designed for visualizing exosomes through MRI. FTH1 was served as MRI reporter protein and lactadherin is a membrane-associated protein that is distributed on exosome surface. The characterizations of labeled exosomes were validated through transmission electron microscopy, western blot, nanoparticle tracking analysis and finally visualized in vitro and in vivo through MRI.

RESULTS

MR imaging showed that the labeled exosomes are able to be visualized in vitro and in vivo. Verification of the characterizations of exosomes observed no significant difference between labeled and unlabeled exosomes.

CONCLUSION

The proposed FTH1 labeling method was useful for visualizing exosomes through MRI.

GENERAL SIGNIFICANCE

The present study first reported a novel self-label method for imaging labeled exosomes of tumor cells in vivo through MR with cell endogenous MRI reporter protein. It may be further used as a tool to enhance understanding the role of exosomes in various pathophysiological conditions.

Synchronous inhibitory pathways create both efficiency and diversity in the retina

Complex connections in neural circuits make it difficult to quantitatively assign even the most basic neural computations to the actions of specific neurons. Retinal ganglion cells are most sensitive to changes in intensity across space and over time. This property, caused by a region known as the receptive field surround, improves information transmission about natural scenes. We dynamically manipulated individual interneurons to directly measure their effect on retinal receptive fields, finding that two inhibitory neuron types, horizontal cells and amacrine cells, synchronously create the same contribution to the receptive field surround at different spatial scales. By analyzing large populations of ganglion cells, we show that this arrangement increases diversity in retinal signaling while preserving maximal information transmission about natural scenes.

Sensory receptive fields combine features that originate in different neural pathways. Retinal ganglion cell receptive fields compute intensity changes across space and time using a peripheral region known as the surround, a property that improves information transmission about natural scenes. The visual features that construct this fundamental property have not been quantitatively assigned to specific interneurons. Here, we describe a generalizable approach using simultaneous intracellular and multielectrode recording to directly measure and manipulate the sensory feature conveyed by a neural pathway to a downstream neuron. By directly controlling the gain of individual interneurons in the circuit, we show that rather than transmitting different temporal features, inhibitory horizontal cells and linear amacrine cells synchronously create the linear surround at different spatial scales and that these two components fully account for the surround. By analyzing a large population of ganglion cells, we observe substantial diversity in the relative contribution of amacrine and horizontal cell visual features while still allowing individual cells to increase information transmission under the statistics of natural scenes. Established theories of efficient coding have shown that optimal information transmission under natural scenes allows a diverse set of receptive fields. Our results give a mechanism for this theory, showing how distinct neural pathways synthesize a sensory computation and how this architecture both generates computational diversity and achieves the objective of high information transmission.

The role of women scientists in the development of ultrashort pulsed laser technology-based biomedical research in Armenia

PURPOSE

To describe the contribution of women scientists in the development of biomedical studies conducted on research facilities based on the ultrashort pulsed laser technologies in Armenia.

CONCLUSION

Given the opportunities provided by the ultrashort pulsed laser driven two-photon microscopy and electron beam linac facilities at CANDLE Synchrotron Research Institute, the Armenian women scientists initiated and conducted interdisciplinary research to understand of the biomedical effects of ultrashort pulsed electron beam irradiation, as well as to experience and apply the advantages of the two-photon microscopy in their fields of research. Women scientists had a crucial role and unique impact in the development of ultrashort pulsed laser technology-based biomedical studies in Armenia.

Strobe photography mapping of cell membrane potential with nanosecond resolution

The ability to directly observe membrane potential charging dynamics across a full microscopic field of view is vital for understanding interactions between a biological system and a given electrical stimulus. Accurate empirical knowledge of cell membrane electrodynamics will enable validation of fundamental hypotheses posited by the single shell model, which includes the degree of voltage change across a membrane and cellular sensitivity to external electric field non-uniformity and directionality. To this end, we have developed a high-speed strobe microscopy system with a time resolution of ~ 6 ns that allows us to acquire time-sequential data for temporally repeatable events (non-injurious electrostimulation). The imagery from this system allows for direct comparison of membrane voltage change to both computationally simulated external electric fields and time-dependent membrane charging models. Acquisition of a full microscope field of view enables the selection of data from multiple cell locations experiencing different electrical fields in a single image sequence for analysis. Using this system, more realistic membrane parameters can be estimated from living cells to better inform predictive models. As a proof of concept, we present evidence that within the range of membrane conductivity used in simulation literature, higher values are likely more valid.

Differentiable model-based adaptive optics for two-photon microscopy

Aberrations limit scanning fluorescence microscopy when imaging in scattering materials such as biological tissue. Model-based approaches for adaptive optics take advantage of a computational model of the optical setup. Such models can be combined with the optimization techniques of machine learning frameworks to find aberration corrections, as was demonstrated for focusing a laser beam through aberrations onto a camera [Opt. Express2826436 (26436)10.1364/OE.403487]. Here, we extend this approach to two-photon scanning microscopy. The developed sensorless technique finds corrections for aberrations in scattering samples and will be useful for a range of imaging application, for example in brain tissue.

Multicolor fiber-optic two-photon endomicroscopy for brain imaging

Visualizing activity patterns of distinct cell types during complex behaviors is essential to understand complex neural networks. It remains challenging to excite multiple fluorophores simultaneously so that different types of neurons can be imaged. In this Letter, we report a multicolor fiber-optic two-photon endomicroscopy platform in which two pulses from a Ti:sapphire laser and an optical parametric oscillator were synchronized and delivered through a single customized double-clad fiber to excite multiple chromophores. A third virtual wavelength could also be generated by spatial-temporal overlapping of the two pulses. The performance of the fiber-optic multicolor two-photon endomicroscope was demonstrated by in vivo imaging of a mouse cerebral cortex with "Brainbow" labeling.

Signal-to-signal neural networks for improved spike estimation from calcium imaging data

Spiking information of individual neurons is essential for functional and behavioral analysis in neuroscience research. Calcium imaging techniques are generally employed to obtain activities of neuronal populations. However, these techniques result in slowly-varying fluorescence signals with low temporal resolution. Estimating the temporal positions of the neuronal action potentials from these signals is a challenging problem. In the literature, several generative model-based and data-driven algorithms have been studied with varied levels of success. This article proposes a neural network-based signal-to-signal conversion approach, where it takes as input raw-fluorescence signal and learns to estimate the spike information in an end-to-end fashion. Theoretically, the proposed approach formulates the spike estimation as a single channel source separation problem with unknown mixing conditions. The source corresponding to the action potentials at a lower resolution is estimated at the output. Experimental studies on the spikefinder challenge dataset show that the proposed signal-to-signal conversion approach significantly outperforms state-of-the-art-methods in terms of Pearson's correlation coefficient, Spearman's rank correlation coefficient and yields comparable performance for the area under the receiver operating characteristics measure. We also show that the resulting system: (a) has low complexity with respect to existing supervised approaches and is reproducible; (b) is layer-wise interpretable, and (c) has the capability to generalize across different calcium indicators.

Multicolor three-photon fluorescence imaging with single-wavelength excitation deep in mouse brain

Multiphoton fluorescence microscopy is a powerful technique for deep-tissue observation of living cells. In particular, three-photon microscopy is highly beneficial for deep-tissue imaging because of the long excitation wavelength and the high nonlinear confinement in living tissues. Because of the large spectral separation of fluorophores of different color, multicolor three-photon imaging typically requires multiple excitation wavelengths. Here, we report a new three-photon excitation scheme: excitation to a higher-energy electronic excited state instead of the conventional excitation to the lowest-energy excited state, enabling multicolor three-photon fluorescence imaging with deep-tissue penetration in the living mouse brain using single-wavelength excitation. We further demonstrate that our excitation method results in ≥10-fold signal enhancement for some of the common red fluorescent molecules. The multicolor imaging capability and the possibility of enhanced three-photon excitation cross section will open new opportunities for life science applications of three-photon microscopy.

Cross-species neuroscience: closing the explanatory gap

Neuroscience has seen substantial development in non-invasive methods available for investigating the living human brain. However, these tools are limited to coarse macroscopic measures of neural activity that aggregate the diverse responses of thousands of cells. To access neural activity at the cellular and circuit level, researchers instead rely on invasive recordings in animals. Recent advances in invasive methods now permit large-scale recording and circuit-level manipulations with exquisite spatio-temporal precision. Yet, there has been limited progress in relating these microcircuit measures to complex cognition and behaviour observed in humans. Contemporary neuroscience thus faces an explanatory gap between macroscopic descriptions of the human brain and microscopic descriptions in animal models. To close the explanatory gap, we propose adopting a cross-species approach. Despite dramatic differences in the size of mammalian brains, this approach is broadly justified by preserved homology. Here, we outline a three-armed approach for effective cross-species investigation that highlights the need to translate different measures of neural activity into a common space. We discuss how a cross-species approach has the potential to transform basic neuroscience while also benefiting neuropsychiatric drug development where clinical translation has, to date, seen minimal success. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

Rodent and fly models in behavioral neuroscience: An evaluation of methodological advances, comparative research, and future perspectives

The assessment of behavioral outcomes is a central component of neuroscientific research, which has required continuous technological innovations to produce more detailed and reliable findings. In this article, we provide an in-depth review on the progress and future implications for three model organisms (mouse, rat, and Drosophila) essential to our current understanding of behavior. By compiling a comprehensive catalog of popular assays, we are able to compare the diversity of tasks and usage of these animal models in behavioral research. This compilation also allows for the evaluation of existing state-of-the-art methods and experimental applications, including optogenetics, machine learning, and high-throughput behavioral assays. We go on to discuss novel apparatuses and inter-species analyses for centrophobism, feeding behavior, aggression and mating paradigms, with the goal of providing a unique view on comparative behavioral research. The challenges and recent advances are evaluated in terms of their translational value, ethical procedures, and trustworthiness for behavioral research.

The near-infrared autofluorescence fingerprint of the brain

The brain is a vital organ involved in most of the central nervous system disorders. Their diagnosis and treatment require fast, cost-effective, high-resolution and high-sensitivity imaging. The combination of a new generation of luminescent nanoparticles and imaging systems working in the second biological window (near-infrared II [NIR-II]) is emerging as a reliable alternative. For NIR-II imaging to become a robust technique at the preclinical level, full knowledge of the NIR-II brain autofluorescence, responsible for the loss of image resolution and contrast, is required. This work demonstrates that the brain shows a peculiar infrared autofluorescence spectrum that can be correlated with specific molecular components. The existence of particular structures within the brain with well-defined NIR autofluorescence fingerprints is also evidenced, opening the door to in vivo anatomical imaging. Finally, we propose a rational selection of NIR luminescent probes suitable for low-noise brain imaging based on their spectral overlap with brain autofluorescence.

Improved hyperacuity estimation of spike timing from calcium imaging

Two-photon imaging is a major recording technique used in neuroscience. However, it suffers from several limitations, including a low sampling rate, the nonlinearity of calcium responses, the slow dynamics of calcium dyes and a low SNR, all of which severely limit the potential of two-photon imaging to elucidate neuronal dynamics with high temporal resolution. We developed a hyperacuity algorithm (HA_time) based on an approach that combines a generative model and machine learning to improve spike detection and the precision of spike time inference. Bayesian inference was performed to estimate the calcium spike model, assuming constant spike shape and size. A support vector machine using this information and a jittering method maximizing the likelihood of estimated spike times enhanced spike time estimation precision approximately fourfold (range, 2–7; mean, 3.5–4.0; 2SEM, 0.1–0.25) compared to the sampling interval. Benchmark scores of HA_time for biological data from three different brain regions were among the best of the benchmark algorithms. Simulation of broader data conditions indicated that our algorithm performed better than others with high firing rate conditions. Furthermore, HA_time exhibited comparable performance for conditions with and without ground truths. Thus HA_time is a useful tool for spike reconstruction from two-photon imaging.

The temporal pattern of Intracortical Microstimulation pulses elicits distinct temporal and spatial recruitment of cortical neuropil and neurons

OBJECTIVE

The spacing or distribution of stimulation pulses of therapeutic neurostimulation waveforms-referred to here as the Temporal Pattern (TP)-has emerged as an important parameter for tuning the response to deep-brain stimulation and intracortical microstimulation (ICMS). While it has long been assumed that modulating the TP of ICMS may be effective by altering the rate coding of the neural response, it is unclear how it alters the neural response at the neural network level. The present study is designed to elucidate the neural response to TP at the network level.

APPROACH

We use in vivo two-photon imaging of ICMS in mice expressing the calcium sensor Thy1-GCaMP or the glutamate sensor hSyn-iGluSnFr to examine the layer II/III neural response to stimulations with different TPs. We study the neuronal calcium and glutamate response to TPs with the same average frequency (10Hz) and same total charge injection, but varying degrees of bursting. We also investigate one control pattern with an average frequency of 100Hz and 10X the charge injection.

MAIN RESULTS

Stimulation trains with the same average frequency (10 Hz) and same total charge injection but distinct temporal patterns recruits distinct sets of neurons. More-than-half (60% of 309 cells) prefer one temporal pattern over the other. Despite their distinct spatial recruitment patterns, both cells exhibit similar ability to follow 30s trains of both TPs without failing, and they exhibit similar levels of glutamate release during stimulation. Both neuronal calcium and glutamate release train to the bursting TP pattern (~21-fold increase in relative power at the frequency of bursting. Bursting also results in a statistically significant elevation in the correlation between somatic calcium activity and neuropil activity, which we explore as a metric for inhibitory-excitatory tone. Interestingly, soma-neuropil correlation during the bursting pattern is a statistically significant predictor of cell preference for TP, which exposes a key link between inhibitory-excitatory tone. Finally, using mesoscale imaging, we show that both TPs result in distal inhibition during stimulation, which reveals complex spatial and temporal interactions between temporal pattern and inhibitory-excitatory tone in ICMS.

SIGNIFICANCE

Our results may ultimately suggest that TP is a valuable parameter space to modulate inhibitory-excitatory tone as well as distinct network activity in ICMS. This presents a broader mechanism of action than rate coding, as previously thought. By implicating these additional mechanisms, TP may have broader utility in the clinic and should be pursued to expand the efficacy of ICMS therapies.

Histaminergic neurons in the tuberomammillary nucleus as a control centre for wakefulness

Histamine plays pleiotropic roles as a neurotransmitter in the physiology of brain function, this includes the maintenance of wakefulness, appetite regulation and memory retrieval. Since numerous studies have revealed an association between histaminergic dysfunction and diverse neuropsychiatric disorders, such as Alzheimer's disease and schizophrenia, a large number of compounds acting on the brain histamine system have been developed to treat neurological disorders. In 2016, pitolisant, which was developed as a histamine H₃ receptor inverse agonist by Schwartz and colleagues, was launched for the treatment of narcolepsy, emphasising the prominent role of brain histamine on wakefulness. Recent advances in neuroscientific techniques such as chemogenetic and optogenetic approaches have led to remarkable progress in the understanding of histaminergic neural circuits essential for the control of wakefulness. In this review article, we summarise the basic knowledge about the histaminergic nervous system and the mechanisms underlying sleep/wake regulation that are controlled by the brain histamine system. LINKED ARTICLES: This article is part of a themed issue on Neurochemistry in Japan. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.4/issuetoc.

Differentiable model-based adaptive optics with transmitted and reflected light

Aberrations limit optical systems in many situations, for example when imaging in biological tissue. Machine learning offers novel ways to improve imaging under such conditions by learning inverse models of aberrations. Learning requires datasets that cover a wide range of possible aberrations, which however becomes limiting for more strongly scattering samples, and does not take advantage of prior information about the imaging process. Here, we show that combining model-based adaptive optics with the optimization techniques of machine learning frameworks can find aberration corrections with a small number of measurements. Corrections are determined in a transmission configuration through a single aberrating layer and in a reflection configuration through two different layers at the same time. Additionally, corrections are not limited by a predetermined model of aberrations (such as combinations of Zernike modes). Focusing in transmission can be achieved based only on reflected light, compatible with an epidetection imaging configuration.

Imaging volumetric dynamics at high speed in mouse and zebrafish brain with confocal light field microscopy

A detailed understanding of the function of neural networks and how they are supported by a dynamic vascular system requires fast three-dimensional imaging in thick tissues. Here we present confocal light field microscopy, a method that enables fast volumetric imaging in the brain at depths of hundreds of micrometers. It uses a generalized confocal detection scheme that selectively collects fluorescent signals from the in-focus volume and provides optical sectioning capability to improve imaging resolution and sensitivity in thick tissues. We demonstrate recording of whole-brain calcium transients in freely swimming zebrafish larvae and observe behaviorally correlated activities in single neurons during prey capture. Furthermore, in the mouse brain, we detect neural activities at depths of up to 370 μm and track blood cells at 70 Hz over a volume of diameter 800 μm × thickness 150 μm and depth of up to 600 μm.

Second Harmonic Generation Imaging of Collagen in Chronically Implantable Electrodes in Brain Tissue

Advances in neural engineering have brought about a number of implantable devices for improved brain stimulation and recording. Unfortunately, many of these micro-implants have not been adopted due to issues of signal loss, deterioration, and host response to the device. While glial scar characterization is critical to better understand the mechanisms that affect device functionality or tissue viability, analysis is frequently hindered by immunohistochemical tissue processing methods that result in device shattering and tissue tearing artifacts. Devices are commonly removed prior to sectioning, which can itself disturb the quality of the study. In this methods implementation study, we use the label free, optical sectioning method of second harmonic generation (SHG) to examine brain slices of various implanted intracortical electrodes and demonstrate collagen fiber distribution not found in normal brain tissue. SHG can easily be used in conjunction with multiphoton microscopy to allow direct intrinsic visualization of collagen-containing glial scars on the surface of cortically implanted electrode probes without imposing the physical strain of tissue sectioning methods required for other high resolution light microscopy modalities. Identification and future measurements of these collagen fibers may be useful in predicting host immune response and device signal fidelity.

Functional ultrasound imaging of deep visual cortex in awake nonhuman primates

Nowadays, several techniques exist to study and better understand how the brain works (fMRI, EEG, electrophysiology, etc.). Each has its own advantages and disadvantages (spatiotemporal resolution, maximal recording depth, signal-to-noise ratio, etc.). In this article, we show that the new functional ultrasound (fUS) imaging technique is appropriate to record and map brain activity in awake primates on a scale previously unreachable. It allows distinguishing patterns similar to ocular dominance bands in the visual cortex through all layers of the cortex, which was impossible before with common techniques. This paper demonstrates the utility of fUS imaging for studying brain activity in awake primates and its interest to all neuroscientists.

Deep regions of the brain are not easily accessible to investigation at the mesoscale level in awake animals or humans. We have recently developed a functional ultrasound (fUS) technique that enables imaging hemodynamic responses to visual tasks. Using fUS imaging on two awake nonhuman primates performing a passive fixation task, we constructed retinotopic maps at depth in the visual cortex (V1, V2, and V3) in the calcarine and lunate sulci. The maps could be acquired in a single-hour session with relatively few presentations of the stimuli. The spatial resolution of the technology is illustrated by mapping patterns similar to ocular dominance (OD) columns within superficial and deep layers of the primary visual cortex. These acquisitions using fUS suggested that OD selectivity is mostly present in layer IV but with extensions into layers II/III and V. This imaging technology provides a new mesoscale approach to the mapping of brain activity at high spatiotemporal resolution in awake subjects within the whole depth of the cortex.

Spatial and Spectral Mapping and Decomposition of Neural Dynamics and Organization of the Mouse Brain with Multispectral Optoacoustic Tomography

In traditional optical imaging, limited light penetration constrains high-resolution interrogation to tissue surfaces. Optoacoustic imaging combines the superb contrast of optical imaging with deep penetration of ultrasound, enabling a range of new applications. We used multispectral optoacoustic tomography (MSOT) for functional and structural neuroimaging in mice at resolution, depth, and specificity unattainable by other neuroimaging modalities. Based on multispectral readouts, we computed hemoglobin gradient and oxygen saturation changes related to processing of somatosensory signals in different structures along the entire subcortical-cortical axis. Using temporal correlation analysis and seed-based maps, we reveal the connectivity between cortical, thalamic, and sub-thalamic formations. With the same modality, high-resolution structural tomography of intact mouse brain was achieved based on endogenous contrasts, demonstrating near-perfect matches with anatomical features revealed by histology. These results extend the limits of noninvasive observations beyond the reach of standard high-resolution neuroimaging, verifying the suitability of MSOT for small-animal studies.

Wavefront correction for adaptive optics with reflected light and deep neural networks

Light scattering and aberrations limit optical microscopy in biological tissue, which motivates the development of adaptive optics techniques. Here, we develop a method for wavefront correction in adaptive optics with reflected light and deep neural networks compatible with an epi-detection configuration. Large datasets of sample aberrations which consist of excitation and detection path aberrations as well as the corresponding reflected focus images are generated. These datasets are used for training deep neural networks. After training, these networks can disentangle and independently correct excitation and detection aberrations based on reflected light images recorded from scattering samples. A similar deep learning approach is also demonstrated with scattering guide stars. The predicted aberration corrections are validated using two photon imaging.

Simultaneous fluorescence imaging of distinct nerve and blood vessel patterns in dual Thy1-YFP and Flt1-DsRed transgenic mice

Blood vessels and nerve tissues are critical to the development and functionality of many vital organs. However, little is currently known about their interdependency during development and after injury. In this study, dual fluorescence transgenic reporter mice were utilized to observe blood vessels and nervous tissues in organs postnatally. Thy1-YFP and Flt1-DsRed (TYFD) mice were interbred to achieve dual fluorescence in the offspring, with Thy1-YFP yellow fluorescence expressed primarily in nerves, and Flt1-DsRed fluorescence expressed selectively in blood vessels. Using this dual fluorescent mouse strain, we were able to visualize the networks of nervous and vascular tissue simultaneously in various organ systems both in the physiological state and after injury. Using ex vivo high-resolution imaging in this dual fluorescent strain, we characterized the organizational patterns of both nervous and vascular systems in a diverse set of organs and tissues. In the cornea, we also observed the dynamic patterns of nerve and blood vessel networks following epithelial debridement injury. These findings highlight the versatility of this dual fluorescent strain for characterizing the relationship between nerve and blood vessel growth and organization.

Single-cavity dual-wavelength all-fiber femtosecond laser for multimodal multiphoton microscopy

A single-cavity dual-wavelength all-fiber femtosecond laser is designed to generate 1030 nm wavelength for high resolution multiphoton imaging and 1700 nm wavelength for long penetration depth imaging. Considering two-photon and three-photon microscopy (2PM and 3PM), the proposed laser provides the single-photon wavelength equivalent to 343 nm, 515 nm, 566 nm and 850 nm, that can be employed to excite a wide variety of intrinsic fluorophores, dyes, and fluorescent proteins. Generating two excitation wavelengths from a single laser reduces the footprint and cost significantly compared to having two separate lasers. Furthermore, an all-reflective microscope is designed to eliminate the chromatic aberration while employing two excitation wavelengths. The compact all-fiber alignment-free laser design makes the overall size of the microscope appropriate for clinical applications.

The cellular and molecular basis of in vivo synaptic plasticity in rodents

Plasticity within the neuronal networks of the brain underlies the ability to learn and retain new information. The initial discovery of synaptic plasticity occurred by measuring synaptic strength in vivo, applying external stimulation and observing an increase in synaptic strength termed long-term potentiation (LTP). Many of the molecular pathways involved in LTP and other forms of synaptic plasticity were subsequently uncovered in vitro. Over the last few decades, technological advances in recording and imaging in live animals have seen many of these molecular mechanisms confirmed in vivo, including structural changes both pre- and postsynaptically, changes in synaptic strength, and changes in neuronal excitability. A well-studied aspect of neuronal plasticity is the capacity of the brain to adapt to its environment, gained by comparing the brains of deprived and experienced animals in vivo, and in direct response to sensory stimuli. Multiple in vivo studies have also strongly linked plastic changes to memory by interfering with the expression of plasticity and by manipulating memory engrams. Plasticity in vivo also occurs in the absence of any form of external stimulation, i.e., during spontaneous network activity occurring with brain development. However, there is still much to learn about how plasticity is induced during natural learning and how this is altered in neurological disorders.

A virtual reality system to analyze neural activity and behavior in adult zebrafish

Virtual realities are powerful tools to analyze and manipulate interactions between animals and their environment and to enable measurements of neuronal activity during behavior. In many species, however, optical access to the brain and/or the behavioral repertoire are limited. We developed a high-resolution virtual reality for head-restrained adult zebrafish, which exhibit cognitive behaviors not shown by larvae. We noninvasively measured activity throughout the dorsal telencephalon by multiphoton calcium imaging. Fish in the virtual reality showed regular swimming patterns and were attracted to animations of conspecifics. Manipulations of visuo-motor feedback revealed neurons that responded selectively to the mismatch between the expected and the actual visual consequences of motor output. Such error signals were prominent in multiple telencephalic areas, consistent with models of predictive processing. A virtual reality system for adult zebrafish therefore provides opportunities to analyze neuronal processing mechanisms underlying higher brain functions including decision making, associative learning, and social interactions.

Visualizing cortical response to optogenetic stimulation and sensory inputs using multispectral handheld optoacoustic imaging

To date, the vast majority of intra-vital neuroimaging systems applied in clinic and diagnostics is stationary with a rigid scanning element, requires specialized facilities and costly infrastructure. Here, we describe a simple yet radical approach for optoacoustic (photoacoustic) brain imaging in vivo using a light-weight handheld probe. It enables multispectral video-rate visualization of hemoglobin gradient changes in the cortex of adult rats induced by whisker and forelimb sensory inputs, as well as by optogenetic stimulation of intra-cortical connections. With superb penetration and molecular specificity, described here in method holds major promises for future applications in research, routine ambulatory neuroimaging, and diagnostics.

Investigating learning-related neural circuitry with chronic in vivo optical imaging

Fundamental aspects of brain function, including development, plasticity, learning, and memory, can take place over time scales of days to years. Chronic in vivo imaging of neural activity with cellular resolution is a powerful method for tracking the long-term activity of neural circuits. We review recent advances in our understanding of neural circuit function from diverse brain regions that have been enabled by chronic in vivo cellular imaging. Insight into the neural basis of learning and decision-making, in particular, benefit from the ability to acquire longitudinal data from genetically identified neuronal populations, deep brain areas, and subcellular structures. We propose that combining chronic imaging with further experimental and computational innovations will advance our understanding of the neural circuit mechanisms of brain function.

In vivo imaging of calcium and glutamate responses to intracortical microstimulation reveals distinct temporal responses of the neuropil and somatic compartments in layer II/III neurons

OBJECTIVE

Intracortical microelectrode implants can generate a tissue response hallmarked by glial scarring and neuron cell death within 100-150 μm of the biomaterial device. Many have proposed that any performance decline in intracortical microstimulation (ICMS) due to this foreign body tissue response could be offset by increasing the stimulation amplitude. The mechanisms of this approach are unclear, however, as there has not been consensus on how increasing amplitude affects the spatial and temporal recruitment patterns of ICMS.

APPROACH

We clarify these unknowns using in vivo two-photon imaging of mice transgenically expressing the calcium sensor GCaMP6s in Thy1 neurons or virally expressing the glutamate sensor iGluSnFr in neurons. Calcium and neurotransmitter activity are tracked in the neuronal somas and neuropil during long-train stimulation in Layer II/III of somatosensory cortex.

MAIN RESULTS

Neural calcium activity and glutamate release are dense and strongest within 20-40 μm around the electrode, falling off with distance from the electrode. Neuronal calcium increases with higher amplitude stimulations. During prolonged stimulation trains, a sub-population of somas fail to maintain calcium activity. Interestingly, neuropil calcium activity is 3-fold less correlated to somatic calcium activity for cells that drop-out during the long stimulation train compared to cells that sustain activity throughout the train. Glutamate release is apparent only within 20 μm of the electrode and is sustained for at least 10s after cessation of the 15 and 20 μA stimulation train, but not lower amplitudes.

SIGNIFICANCE

These results demonstrate that increasing amplitude can increase the radius and intensity of neural recruitment, but it also alters the temporal response of some neurons. Further, dense glutamate release is highest within the first 20 μm of the electrode site even at high amplitudes, suggesting that there may be spatial limitations to the amplitude parameter space. The glutamate elevation outlasts stimulation, suggesting that high-amplitude stimulation may affect neurotransmitter re-uptake. This ultimately suggests that increasing the amplitude of ICMS device stimulation may fundamentally alter the temporal neural response, which could have implications for using amplitude to improve the ICMS effect or "offset" the effects of glial scarring.

Operant conditioning paradigm for juxtacellular recordings in functionally identified cortical neurons during motor execution in head-fixed rats

BACKGROUND

Understanding the configuration of neural circuits and the specific role of distinct cortical neuron types involved in behavior, requires the study of structure-function and connectivity relationships with single cell resolution in awake behaving animals. Despite head-fixed behaving rats have been used for in vivo measuring of neuronal activity, it is a concern that head fixation could change the performance of behavioral task.

NEW METHOD

We describe the procedures for efficiently training Wistar rats to develop a behavioral task, involving planning and execution of a qualified movement in response to a visual cue under head-fixed conditions. The behavioral and movement performance in freely moving vs head-fixed conditions was analyzed.

RESULTS

The best behavioral performance was obtained in the rats that were trained first in freely moving conditions and then placed in a head-restrained condition compared with the animals which first were habituated to head-restriction and then learned the task. Moreover, head restriction did not alter the movement performance. Stable juxtacellular recordings from sensorimotor cortex neurons were obtained while the rats were performing forelimb movements. Biocytin electroporation and retrograde tracer injections, permits identify the hodology of individual long-range projecting neurons.

COMPARISON WITH EXISTING METHODS

Our method shows no difference in the behavioral performance of head fixed and freely moving conditions. Also includes a computer aided design of a discrete and ergonomic head-post allowing enough stability to perform juxtacellular recording and labeling of cortical neurons.

CONCLUSIONS

Our method is suitable for the in vivo characterization of neuronal circuits and their long-range connectivity.

Understanding the circuit basis of cognitive functions using mouse models

Understanding how cognitive functions arise from computations occurring in the brain requires the ability to measure and perturb neural activity while the relevant circuits are engaged for specific cognitive processes. Rapid technical advances have led to the development of new approaches to transiently activate and suppress neuronal activity as well as to record simultaneously from hundreds to thousands of neurons across multiple brain regions during behavior. To realize the full potential of these approaches for understanding cognition, however, it is critical that behavioral conditions and stimuli are effectively designed to engage the relevant brain networks. Here, we highlight recent innovations that enable this combined approach. In particular, we focus on how to design behavioral experiments that leverage the ever-growing arsenal of technologies for controlling and measuring neural activity in order to understand cognitive functions.

In vivo imaging reveals reduced activity of neuronal circuits in a mouse tauopathy model

Pathological alterations of tau protein play a significant role in the emergence and progression of neurodegenerative disorders. Tauopathies are characterized by detachment of the tau protein from neuronal microtubules, and its subsequent aberrant hyperphosphorylation, aggregation and cellular distribution. The exact nature of tau protein species causing neuronal malfunction and degeneration is still unknown. In the present study, we used mice transgenic for human tau with the frontotemporal dementia with parkinsonism-associated P301S mutation. These mice are prone to develop fibrillar tau inclusions, especially in the spinal cord and brainstem. At the same time, cortical neurons are not as strongly affected by fibrillar tau forms, but rather by soluble tau forms. We took advantage of the possibility to induce formation of neurofibrillary tangles in a subset of these cortical neurons by local injection of preformed synthetic tau fibrils. By using chronic in vivo two-photon calcium imaging in awake mice, we were able for the first time to follow the activity of individual tangle-bearing neurons and compare it to the activity of tangle-free neurons over the disease course. Our results revealed strong reduction of calcium transient frequency in layer 2/3 cortical neurons of P301S mice, independent of neurofibrillary tangle presence. These results clearly point to the impairing role of soluble, mutated tau protein species present in the majority of the neurons investigated in this study.

The Visual Cortex in Context

In this article, we review the anatomical inputs and outputs to the mouse primary visual cortex, area V1. Our survey of data from the Allen Institute Mouse Connectivity project indicates that mouse V1 is highly interconnected with both cortical and subcortical brain areas. This pattern of innervation allows for computations that depend on the state of the animal and on behavioral goals, which contrasts with simple feedforward, hierarchical models of visual processing. Thus, to have an accurate description of the function of V1 during mouse behavior, its involvement with the rest of the brain circuitry has to be considered. Finally, it remains an open question whether the primary visual cortex of higher mammals displays the same degree of sensorimotor integration in the early visual system.