Dynamics of glia and neurons regulate homeostatic rest, sleep and feeding behavior in Drosophila.

Homeostatic processes, including sleep, are critical for brain function. Here we identify astrocyte-like glia (or astrocytes, AL) and ensheathing glia (EG), the two major classes of glia that arborize inside the brain, as brain-wide, locally acting homeostats for the short, naturally occurring rest and sleep bouts of Drosophila, and show that a subset of neurons in the fan-shaped body encodes feeding homeostasis. We show that the metabolic gas carbon dioxide, changes in pH and behavioral activity all induce long-lasting calcium responses in EG and AL, and that calcium levels in both glia types show circadian modulation.

Differentiable optimization of the Debye-Wolf integral for light shaping and adaptive optics in two-photon microscopy.

Control of light through a microscope objective with a high numerical aperture is a common requirement in applications such as optogenetics, adaptive optics, or laser processing. Light propagation, including polarization effects, can be described under these conditions using the Debye-Wolf diffraction integral. Here, we take advantage of differentiable optimization and machine learning for efficiently optimizing the Debye-Wolf integral for such applications.

A place learning assay for tethered walking Drosophila.

Background: Drosophila shows a range of visually guided memory and learning behaviors, including place learning. Investigating the dynamics of neural circuits underlying such behaviors requires learning assays in tethered animals, compatible with in vivo imaging experiments.

New Method: Here, we introduce an assay for place learning for tethered walking flies.

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.

Automated long-term two-photon imaging in head-fixed walking Drosophila.

Background: The brain of Drosophila shows dynamics at multiple timescales, from the millisecond range of fast voltage or calcium transients to functional and structural changes occurring over multiple days. To relate such dynamics to behavior requires monitoring neural circuits across these multiple timescales in behaving animals.

New Method: Here, we develop a technique for automated long-term two-photon imaging in fruit flies, during wakefulness and extended bouts of immobility, as typically observed during sleep, navigating in virtual reality over up to seven days.

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.

Integration of sleep homeostasis and navigation in Drosophila.

During sleep, the brain undergoes dynamic and structural changes. In Drosophila, such changes have been observed in the central complex, a brain area important for sleep control and navigation. The connectivity of the central complex raises the question about how navigation, and specifically the head direction system, can operate in the face of sleep related plasticity.

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.

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.

Virtual reality for animal navigation with camera-based optical flow tracking.

Background: Virtual reality combined with a spherical treadmill is used across species for studying neural circuits underlying navigation and learning.

New Method: We developed an optical flow-based method for tracking treadmill ball motion in real time using a single high-resolution camera.

Results: Tracking accuracy and timing were determined using calibration data.

Two-photon Bessel beam tomography for fast volume imaging.

Light microscopy on dynamic samples, for example neural activity in the brain, often requires imaging volumes that extend over several 100 µm in axial direction at a rate of at least several tens of Hertz. Here, we develop a tomography approach for scanning fluorescence microscopy which allows recording a volume image in a single frame scan. Volumes are imaged by simultaneously recording four independent projections at different angles using temporally multiplexed, tilted Bessel beams.

Light scattering control in transmission and reflection with neural networks.

Scattering often limits the controlled delivery of light in applications such as biomedical imaging, optogenetics, optical trapping, and fiber-optic communication or imaging. Such scattering can be controlled by appropriately shaping the light wavefront entering the material. Here, we develop a machine-learning approach for light control.

Angular velocity integration in a fly heading circuit.

Many animals maintain an internal representation of their heading as they move through their surroundings. Such a compass representation was recently discovered in a neural population in the central complex, a brain region implicated in spatial navigation. Here, we use two-photon calcium imaging and electrophysiology in head-fixed walking flies to identify a different neural population that conjunctively encodes heading and angular velocity, and is excited selectively by turns in either the clockwise or counterclockwise direction.

Video-rate volumetric functional imaging of the brain at synaptic resolution.

Neurons and neural networks often extend hundreds of micrometers in three dimensions. Capturing the calcium transients associated with their activity requires volume imaging methods with subsecond temporal resolution. Such speed is a challenge for conventional two-photon laser-scanning microscopy, because it depends on serial focal scanning in 3D and indicators with limited brightness.

Neural dynamics for landmark orientation and angular path integration.

Many animals navigate using a combination of visual landmarks and path integration. In mammalian brains, head direction cells integrate these two streams of information by representing an animal's heading relative to landmarks, yet maintaining their directional tuning in darkness based on self-motion cues. Here we use two-photon calcium imaging in head-fixed Drosophila melanogaster walking on a ball in a virtual reality arena to demonstrate that landmark-based orientation and angular path integration are combined in the population responses of neurons whose dendrites tile the ellipsoid body, a toroidal structure in the centre of the fly brain.

Feature detection and orientation tuning in the Drosophila central complex.

Many animals, including insects, are known to use visual landmarks to orient in their environment. In Drosophila melanogaster, behavioural genetics studies have identified a higher brain structure called the central complex as being required for the fly's innate responses to vertical visual features and its short- and long-term memory for visual patterns. But whether and how neurons of the fly central complex represent visual features are unknown.

Studying sensorimotor processing with physiology in behaving Drosophila.

The neural underpinnings of sensorimotor integration are best studied in the context of well-characterized behavior. A rich trove of Drosophila behavioral genetics research offers a variety of well-studied behaviors and candidate brain regions that can form the bases of such studies. The development of tools to perform in vivo physiology from the Drosophila brain has made it possible to monitor activity in defined neurons in response to sensory stimuli.

Walking modulates speed sensitivity in Drosophila motion vision.

Changes in behavioral state modify neural activity in many systems. In some vertebrates such modulation has been observed and interpreted in the context of attention and sensorimotor coordinate transformations. Here we report state-dependent activity modulations during walking in a visual-motor pathway of Drosophila.

Two-photon calcium imaging from head-fixed Drosophila during optomotor walking behavior.

Drosophila melanogaster is a model organism rich in genetic tools to manipulate and identify neural circuits involved in specific behaviors. Here we present a technique for two-photon calcium imaging in the central brain of head-fixed Drosophila walking on an air-supported ball. The ball's motion is tracked at high resolution and can be treated as a proxy for the fly's own movements.