SIGNIFICANCE: Advances in genetically encoded sensors and two-photon imaging have unlocked functional imaging at the level of single dendritic spines. Synaptic activity can be measured in real time in awake animals. However, tools are needed to facilitate the analysis of the large datasets acquired by the approach. Commonly available software suites for imaging calcium transients in cell bodies are ill-suited for spine imaging as dendritic spines have structural characteristics distinct from those of the cell bodies. We present an automated tuning analysis tool (AUTOTUNE), which provides analysis routines specifically developed for the extraction and analysis of signals from subcellular compartments, including dendritic subregions and spines. AIM: Although the acquisition of in vivo functional synaptic imaging data is increasingly accessible, a hurdle remains in the computation-heavy analyses of the acquired data. The aim of this study is to overcome this barrier by offering a comprehensive software suite with a user-friendly interface for easy access to nonprogrammers. APPROACH: We demonstrate the utility and effectiveness of our software with demo analyses of dendritic imaging data acquired from layer 2/3 pyramidal neurons in mouse V1 in vivo. A user manual and demo datasets are also provided. RESULTS: AUTOTUNE provides a robust workflow for analyzing functional imaging data from neuronal dendrites. Features include source image registration, segmentation of regions-of-interest and detection of structural turnover, fluorescence transient extraction and smoothing, subtraction of signals from putative backpropagating action potentials, and stimulus and behavioral parameter response tuning analyses. CONCLUSIONS: AUTOTUNE is open-source and extendable for diverse functional synaptic imaging experiments. The ease of functional characterization of dendritic spine activity provided by our software can accelerate new functional studies that complement decades of morphological studies of dendrites, and further expand our understanding of neural circuits in health and in disease.

The mouse visual cortex contains interconnected higher visual areas, but their functional specializations are unclear. Here, we used a data-driven approach to examine the representations of complex visual stimuli by L2/3 neurons across mouse higher visual areas, measured using large-field-of-view two-photon calcium imaging. Using specialized stimuli, we found higher fidelity representations of texture in area LM, compared to area AL. Complementarily, we found higher fidelity representations of motion in area AL, compared to area LM. We also observed this segregation of information in response to naturalistic videos. Finally, we explored how receptive field models of visual cortical neurons could produce the segregated representations of texture and motion we observed. These selective representations could aid in behaviors such as visually guided navigation.

Imaging the activity of neurons that are widely distributed across brain regions deep in scattering tissue at high speed remains challenging. Here, we introduce an open-source system with Dual Independent Enhanced Scan Engines for Large field-of-view Two-Photon imaging (Diesel2p). Combining optical design, adaptive optics, and temporal multiplexing, the system offers subcellular resolution over a large field-of-view of ~25 mm², encompassing distances up to 7 mm, with independent scan engines. We demonstrate the flexibility and various use cases of this system for calcium imaging of neurons in the living brain.

Mice use vision to navigate and avoid predators in natural environments. However, their visual systems are compact compared to other mammals, and it is unclear how well mice can discriminate ethologically relevant scenes. Here, we examined natural scene discrimination in mice using an automated touch-screen system. We estimated the discrimination difficulty using the computational metric structural similarity (SSIM), and constructed psychometric curves. However, the performance of each mouse was better predicted by the mean performance of other mice than SSIM. This high inter-mouse agreement indicates that mice use common and robust strategies to discriminate natural scenes. We tested several other image metrics to find an alternative to SSIM for predicting discrimination performance. We found that a simple, primary visual cortex (V1)-inspired model predicted mouse performance with fidelity approaching the inter-mouse agreement. The model involved convolving the images with Gabor filters, and its performance varied with the orientation of the Gabor filter. This orientation dependence was driven by the stimuli, rather than an innate biological feature. Together, these results indicate that mice are adept at discriminating natural scenes, and their performance is well predicted by simple models of V1 processing.

Background

The pyrethroid deltamethrin (DM) is broadly used for insect control. Although DM hyperexcites neuronal networks by delaying inactivation of axonal voltage-dependent [Formula: see text] channels, this mechanism is unlikely to mediate neurotoxicity at lower exposure levels during critical perinatal periods in mammals.

Objectives

We aimed to identify mechanisms by which acute and subchronic DM altered axonal and dendritic growth, patterns of synchronous [Formula: see text] oscillations (SCOs), and electrical spike activity (ESA) functions critical to neuronal network formation.

Methods

Measurements of SCOs using [Formula: see text] imaging, ESA using microelectrode array (MEA) technology, and dendritic complexity using Sholl analysis were performed in primary murine cortical neurons from wild-type (WT) and/or ryanodine receptor 1 ([Formula: see text]) mice between 5 and 14 d in vitro (DIV). [Formula: see text] binding analysis and a single-channel voltage clamp were utilized to measure engagement of RyRs as a direct target of DM.

Results

Neuronal networks responded to DM ([Formula: see text]) as early as 5 DIV, reducing SCO amplitude and depressing ESA and burst frequencies by 60-70%. DM ([Formula: see text]) enhanced axonal growth in a nonmonotonic manner. [Formula: see text] enhanced dendritic complexity. DM stabilized channel open states of RyR1, RyR2, and cortical preparations expressing all three isoforms. DM ([Formula: see text]) altered gating kinetics of RyR1 channels, increasing mean open time, decreasing mean closed time, and thereby enhancing overall open probability. SCO patterns from cortical networks expressing [Formula: see text] were more responsive to DM than WT. [Formula: see text] neurons showed inherently longer axonal lengths than WT neurons and maintained less length-promoting responses to nanomolar DM.

Conclusions

Our findings suggested that RyRs were sensitive molecular targets of DM with functional consequences likely relevant for mediating abnormal neuronal network connectivity in vitro. https://doi.org/10.1289/EHP4583.

Multiphoton microscopy can resolve fluorescent structures and dynamics deep in scattering tissue and has transformed neural imaging, but applying this technique in vivo can be limited by the mechanical and optical constraints of conventional objectives. Short working distance objectives can collide with compact surgical windows or other instrumentation and preclude imaging. Here we present an ultra-long working distance (20 mm) air objective called the Cousa objective. It is optimized for performance across multiphoton imaging wavelengths, offers a more than 4 mm2 field of view with submicrometer lateral resolution and is compatible with commonly used multiphoton imaging systems. A novel mechanical design, wider than typical microscope objectives, enabled this combination of specifications. We share the full optical prescription, and report performance including in vivo two-photon and three-photon imaging in an array of species and preparations, including nonhuman primates. The Cousa objective can enable a range of experiments in neuroscience and beyond.