Oscillatory stimuli differentiate adapting circuit topologies.

Biology emerges from interactions between molecules, which are challenging to elucidate with current techniques. An orthogonal approach is to probe for 'response signatures' that identify specific circuit motifs. For example, bistability, hysteresis, or irreversibility are used to detect positive feedback loops.

Dynamic structure of locomotor behavior in walking fruit flies.

The function of the brain is unlikely to be understood without an accurate description of its output, yet the nature of movement elements and their organization remains an open problem. Here, movement elements are identified from dynamics of walking in flies, using unbiased criteria. On one time scale, dynamics of walking are consistent over hundreds of milliseconds, allowing elementary features to be defined.

Specific kinematics and motor-related neurons for aversive chemotaxis in Drosophila.

Background: Chemotaxis, the ability to direct movements according to chemical cues in the environment, is important for the survival of most organisms. The vinegar fly, Drosophila melanogaster, displays robust olfactory aversion and attraction, but how these behaviors are executed via changes in locomotion remains poorly understood. In particular, it is not clear whether aversion and attraction bidirectionally modulate a shared circuit or recruit distinct circuits for execution.

Fast multicolor 3D imaging using aberration-corrected multifocus microscopy.

Conventional acquisition of three-dimensional (3D) microscopy data requires sequential z scanning and is often too slow to capture biological events. We report an aberration-corrected multifocus microscopy method capable of producing an instant focal stack of nine 2D images. Appended to an epifluorescence microscope, the multifocus system enables high-resolution 3D imaging in multiple colors with single-molecule sensitivity, at speeds limited by the camera readout time of a single image.

Symmetries in stimulus statistics shape the form of visual motion estimators.

The estimation of visual motion has long been studied as a paradigmatic neural computation, and multiple models have been advanced to explain behavioral and neural responses to motion signals. A broad class of models, originating with the Reichardt correlator model, proposes that animals estimate motion by computing a temporal cross-correlation of light intensities from two neighboring points in visual space. These models provide a good description of experimental data in specific contexts but cannot explain motion percepts in stimuli lacking pairwise correlations.

Motion processing streams in Drosophila are behaviorally specialized.

Motion vision is an ancient faculty, critical to many animals in a range of ethological contexts, the underlying algorithms of which provide central insights into neural computation. However, how motion cues guide behavior is poorly understood, as the neural circuits that implement these computations are largely unknown in any organism. We develop a systematic, forward genetic approach using high-throughput, quantitative behavioral analyses to identify the neural substrates of motion vision in Drosophila in an unbiased fashion.