A genetically encoded sensor for in vivo imaging of orexin neuropeptides.

Orexins (also called hypocretins) are hypothalamic neuropeptides that carry out essential functions in the central nervous system; however, little is known about their release and range of action in vivo owing to the limited resolution of current detection technologies. Here we developed a genetically encoded orexin sensor (OxLight1) based on the engineering of circularly permutated green fluorescent protein into the human type-2 orexin receptor. In mice OxLight1 detects optogenetically evoked release of endogenous orexins in vivo with high sensitivity. Photometry recordings of OxLight1 in mice show rapid orexin release associated with spontaneous running behavior, acute stress and sleep-to-wake transitions in different brain areas. Moreover, two-photon imaging of OxLight1 reveals orexin release in layer 2/3 of the mouse somatosensory cortex during emergence from anesthesia. Thus, OxLight1 enables sensitive and direct optical detection of orexin neuropeptides with high spatiotemporal resolution in living animals.

Local and Global Spatial Organization of Interaural Level Difference and Frequency Preferences in Auditory Cortex.

Despite decades of microelectrode recordings, fundamental questions remain about how auditory cortex represents sound-source location. Here, we used in vivo 2-photon calcium imaging to measure the sensitivity of layer II/III neurons in mouse primary auditory cortex (A1) to interaural level differences (ILDs), the principal spatial cue in this species. Although most ILD-sensitive neurons preferred ILDs favoring the contralateral ear, neurons with either midline or ipsilateral preferences were also present. An opponent-channel decoder accurately classified ILDs using the difference in responses between populations of neurons that preferred contralateral-ear-greater and ipsilateral-ear-greater stimuli. We also examined the spatial organization of binaural tuning properties across the imaged neurons with unprecedented resolution. Neurons driven exclusively by contralateral ear stimuli or by binaural stimulation occasionally formed local clusters, but their binaural categories and ILD preferences were not spatially organized on a more global scale. In contrast, the sound frequency preferences of most neurons within local cortical regions fell within a restricted frequency range, and a tonotopic gradient was observed across the cortical surface of individual mice. These results indicate that the representation of ILDs in mouse A1 is comparable to that of most other mammalian species, and appears to lack systematic or consistent spatial order.

Stimulus information guides the emergence of behavior-related signals in primary somatosensory cortex during learning.

Neurons in the primary cortex carry sensory- and behavior-related information, but it remains an open question how this information emerges and intersects together during learning. Current evidence points to two possible learning-related changes: sensory information increases in the primary cortex or sensory information remains stable, but its readout efficiency in association cortices increases. We investigated this question by imaging neuronal activity in mouse primary somatosensory cortex before, during, and after learning of an object localization task. We quantified sensory- and behavior-related information and estimated how much sensory information was used to instruct perceptual choices as learning progressed. We find that sensory information increases from the start of training, while choice information is mostly present in the later stages of learning. Additionally, the readout of sensory information becomes more efficient with learning as early as in the primary sensory cortex. Together, our results highlight the importance of primary cortical neurons in perceptual learning.

Enhanced bioactivity of internally functionalized cationic dendrimers with PEG cores.

Hybrid dendritic-linear block copolymers based on a 4-arm poly(ethylene glycol) (PEG) core were synthesized using an accelerated AB2/CD2 dendritic growth approach through orthogonal amine/epoxy and thiol-yne chemistries. The biological activity of these 4-arm and the corresponding 2-arm hybrid dendrimers revealed an enhanced, dendritic effect with an exponential increase in cell internalization concomitant with increasing amine end groups and low cytotoxicity. Furthermore, the ability of these hybrid dendrimers to induce endosomal escape combined with their facile and efficient synthesis makes them attractive platforms for gene transfection. The 4-arm-based dendrimer showed significantly improved DNA binding and gene transfection capabilities in comparison with the 2-arm derivative. These results combined with the MD simulation indicate a significant effect of both the topology of the PEG core and the multivalency of these hybrid macromolecules on their DNA binding and delivery capablities.

A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging.

In vivo two-photon calcium imaging is a powerful approach in neuroscience. However, processing two-photon calcium imaging data is computationally intensive and time-consuming, making online frame-by-frame analysis challenging. This is especially true for large field-of-view (FOV) imaging. Here, we present CITE-On (Cell Identification and Trace Extraction Online), a convolutional neural network-based algorithm for fast automatic cell identification, segmentation, identity tracking, and trace extraction in two-photon calcium imaging data. CITE-On processes thousands of cells online, including during mesoscopic two-photon imaging, and extracts functional measurements from most neurons in the FOV. Applied to publicly available datasets, the offline version of CITE-On achieves performance similar to that of state-of-the-art methods for offline analysis. Moreover, CITE-On generalizes across calcium indicators, brain regions, and acquisition parameters in anesthetized and awake head-fixed mice. CITE-On represents a powerful tool to speed up image analysis and facilitate closed-loop approaches, for example in combined all-optical imaging and manipulation experiments.

Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments.

Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends, we developed pyControl, a system of open-source hardware and software for controlling behavioural experiments comprising a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high-throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier, and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features. Here, we outline the system's design and rationale, present validation experiments characterising system performance, and demonstrate example applications in freely moving and head-fixed mouse behaviour.

Complexity of frequency receptive fields predicts tonotopic variability across species.

Primary cortical areas contain maps of sensory features, including sound frequency in primary auditory cortex (A1). Two-photon calcium imaging in mice has confirmed the presence of these global tonotopic maps, while uncovering an unexpected local variability in the stimulus preferences of individual neurons in A1 and other primary regions. Here we show that local heterogeneity of frequency preferences is not unique to rodents. Using two-photon calcium imaging in layers 2/3, we found that local variance in frequency preferences is equivalent in ferrets and mice. Neurons with multipeaked frequency tuning are less spatially organized than those tuned to a single frequency in both species. Furthermore, we show that microelectrode recordings may describe a smoother tonotopic arrangement due to a sampling bias towards neurons with simple frequency tuning. These results help explain previous inconsistencies in cortical topography across species and recording techniques.

Quasi-simultaneous multiplane calcium imaging of neuronal circuits.

Two-photon excitation fluorescence microscopy is widely used to study the activity of neuronal circuits. However, the fast imaging is typically constrained to a single lateral plane for a standard microscope design. Given that cortical neuronal networks in a mouse brain are complex three-dimensional structures organised in six histologically defined layers which extend over many hundreds of micrometres, there is a strong demand for microscope systems that can record neuronal signalling in volumes. Henceforth, we developed a quasi-simultaneous multiplane imaging technique combining an acousto-optic deflector and static remote focusing to provide fast imaging of neurons from different axial positions inside the cortical layers without the need for mechanical disturbance of either the objective lens or the specimen. The hardware and the software are easily adaptable to existing two-photon microscopes. Here, we demonstrated that our imaging method can record, at high speed and high image contrast, the calcium dynamics of neurons in two different imaging planes separated axially with the in-focus and the refocused planes 120 µm and 250 µm below the brain surface respectively.