Spatial integration of optic flow signals in fly motion-sensitive neurons

Context-dependence of deterministic and nondeterministic contributions to closed-loop steering control

In natural circumstances, sensory systems operate in a closed loop with motor output, whereby actions shape subsequent sensory experiences. A prime example of this is the sensorimotor processing required to align one's direction of travel, or heading, with one's goal, a behavior we refer to as steering. In steering, motor outputs work to eliminate errors between the direction of heading and the goal, modifying subsequent errors in the process. The closed-loop nature of the behavior makes it challenging to determine how deterministic and nondeterministic processes contribute to behavior. We overcome this by applying a nonparametric, linear kernel-based analysis to behavioral data of monkeys steering through a virtual environment in two experimental contexts. In a given context, the results were consistent with previous work that described the transformation as a second-order linear system. Classically, the parameters of such second-order models are associated with physical properties of the limb such as viscosity and stiffness that are commonly assumed to be approximately constant. By contrast, we found that the fit kernels differed strongly across tasks in these and other parameters, suggesting context-dependent changes in neural and biomechanical processes. We additionally fit residuals to a simple noise model and found that the form of the noise was highly conserved across both contexts and animals. Strikingly, the fitted noise also closely matched that found previously in a human steering task. Altogether, this work presents a kernel-based analysis that characterizes the context-dependence of deterministic and non-deterministic components of a closed-loop sensorimotor task.

Neural Integration Underlying a Time-Compensated Sun Compass in the Migratory Monarch Butterfly

Migrating eastern North American monarch butterflies use a time-compensated sun compass to adjust their flight to the southwest direction. Although the antennal genetic circadian clock and the azimuth of the sun are instrumental for proper function of the compass, it is unclear how these signals are represented on a neuronal level and how they are integrated to produce flight control. To address these questions, we constructed a receptive field model of the compound eye that encodes the solar azimuth. We then derived a neural circuit model that integrates azimuthal and circadian signals to correct flight direction. The model demonstrates an integration mechanism, which produces robust trajectories reaching the southwest regardless of the time of day and includes a configuration for remigration. Comparison of model simulations with flight trajectories of butterflies in a flight simulator shows analogous behaviors and affirms the prediction that midday is the optimal time for migratory flight.

Surround motion silences signals from same-direction motion

The response of motion-sensitive neurons to stimuli presented within their receptive field is often affected by stimulation in the surrounding region. These effects have perceptually relevant consequences that can be measured using behavioral techniques. We used psychophysical reverse correlation to characterize directional selectivity in human observers while they processed a local motion stimulus and studied the effect of adding an additional motion signal in the surrounding region. The surround had no effect on response gain for signals of opposite direction but selectively reduced gain for those of same direction. Surprisingly this reduction was close to 100%, effectively amounting to a gating process whereby signals of same direction were completely silenced. Our data indicate that by far the most prominent perceptual manifestation of center-surround antagonism is gain suppression by motion in the same direction without any appreciable change in directional tuning.

Fast-scale adaptive changes of directional tuning in fly tangential cells are explained by a static nonlinearity

The response of vertebrate motion-sensitive neurons to a directional stimulus is affected by the direction of the stimulus that immediately preceded it. These nonlinear effects are also observed for orientation tuning and are typically interpreted as fast-scale adaptive changes. We verified that similar effects are observed for spiking tangential cells in the fly lobula plate. We also investigated the spatial selectivity of these effects by presenting multiple patches at different positions within the receptive field,and found that the effects are strictly local.

We modelled the data using elementary operators (linear filters and threshold nonlinearities). A satisfactory account of the results is obtained when an early static nonlinearity acts on the outputs of multiple front-end filters that are subsequently pooled in a spatially restricted manner by the tangential cell. In line with recent studies, these findings emphasize the importance of testing simple nonlinear models before attempting more elaborate interpretations of fast-scale adaptive phenomena in single neurons. We discuss a potential neural implementation of the model based on medullar projections to the lobula plate.