HomeResearchNeural Circuits and Functional Algorithms for Behavior

Our Scientists

Neural Circuits and Functional Algorithms for Behavior

Research Summary

Mark Frye wants to understand how complex multisensory behaviors are controlled by compact neural circuits.

My lab is using Drosophila melanogaster to understand the functional algorithms and structural circuits with which information from multiple sensory modalities is integrated and transformed into the mechanics of locomotion. Making extensive use of state-of-the-art electronic flight and walking simulators ("virtual reality" for flies; Figure 1), we quantify the influence of visual and olfactory stimuli on behavioral dynamics under conditions in which the animals actively control their sensory experience. We assess performance deficits resulting from targeted and conditional gene expression (e.g., the pGal4-UAS system) to reversibly silence specific neuronal circuits.

Visual Behavior, Computations, and Circuits
During my postdoctoral fellowship in Michael Dickinson's lab, I used a digital flight simulator, in which a tethered fly controls its sensory experience in a manner similar to free flight, to disclose a novel form of visual reflex in flies. Simply stated, flies are highly sensitive to patterns of optic flow generated by the apparent expansion of approaching features. In my own lab I wanted to know whether this reflex operates through a dedicated neural "channel" or is instead part of a well-studied visual response to panoramic rotation. By systematically varying the properties for each of the two primary forms of optic flow and examining the motor control of steering during tethered flight, we showed that different axes of optic flow are processed along independent control pathways.

Figure 1: Behavioral assays...

Complex patterns of optic flow as well as simple motion stimuli generate tractable patterns of luminance—imagine a bright bug crawling across dark tree bark. But humans and nonhuman primates also detect motion generated by variations in contrast or texture instead of luminance—imagine a butterfly flapping its wings through shafts of sunlight. In primates, luminance-based first-order motion and contrast- and texture-based second-order motion cues are thought to be processed by two parallel cortical streams. We have shown that flies robustly track second-order motion cues, even when these cues are competing with first-order signals. This is surprising because the standard implementation of a well-known computational model for elementary motion detection in flies tracks first-order cues but is completely blind to second-order motion. Yet the fly brain, which is extremely limited in its resources, can also somehow extract these high-order visual features.

Ultimately, we are interested in genetically identifying the neural circuits that implement the visual computations that transform motion signals into robust behaviors. We recently developed a high-throughput, real-time walking simulator (a sort of virtual reality "fly stampede") that allows us to examine several independent and subtle visual-motor behavioral phenotypes in a large group of walking flies under reversible genetic inactivation of specific brain microcircuits (Figure 1). Flies with genetically deactivated peripheral visual circuits interconnecting neighboring visual columns are completely insensitive to motion cues, but they are normally attracted to bright light, highlighting the specific role of this microcircuit for motion computation in contrast to general light sensitivity.

Olfactory Behavior, Computations, and Circuits
Our understanding of olfactory processing diminishes between primary sensory function and odor-mediated behavioral responses. We created a "virtual odor arena" in which a tethered fly is suspended in a magnetic field that allows it to voluntarily steer in the horizontal (yaw) plane. As the fly actively orients into narrow odor plumes or in response to controlled visual motion, its body orientation is tracked in real-time with digital video (Figure 1). By varying the timing of odor pulses, we have mapped the temporal resolution of odor-tracking behavior by the whole fly. In the spatial domain, we have shown that flies can behaviorally track an intensity gradient of odor delivered across the two antennae, despite the fact that these olfactory organs are separated by a fraction of a millimeter. We are currently using well-established genetic techniques to alter the spatial activation and temporal fidelity of neural circuits involved in both temporal and spatial computation of olfactory signals.

Visual and Olfactory Cross-Modal Integration
Although flies can track a spatial odor gradient, we recently showed that they can only do so when the visual panorama is clearly visible to the fly. Reducing the contrast of the visual background diminishes the flies' tracking ability, such that they behave as if there were no odor at all. Furthermore, we showed that the visual dependence is context specific: it requires a panoramic landscape rather than small objects or landmarks. It would appear that the computations for stabilizing gaze against the visual panorama to enable an animal to fly straight are influenced by olfactory signals. Do olfactory signals cross-modally enhance the sensitivity to visual signals? To investigate, we compared visual responses before and after presentation of an attractive odor in a flight simulator in which we presented two optic flow fields: rotation and expansion. We found that odor generally increases the perceptual salience of visual motion cues and that odor activates visual reflexes in a context-specific manner with respect to the same parallel visual-processing channels we had described previously.

Exploratory Behavior and Active Search
In the fruit fly, visual-olfactory fusion presumably evolved for a single purpose: to enable an adult to disperse and locate patchy food resources within widely varying visual environments. This is a "needle in a haystack" problem. We recently tested the hypothesis that flies use something other than a Brownian motion random search when seeking distant odor sources. Our results suggest that the reiterated pattern of straight segments and turns that characterizes Drosophila flight paths constitutes a mathematically optimal, spatially scale-free search strategy known as a Lévy flight. This is somewhat similar to the fractal pattern on a snowflake: it appears similar whether viewed up close or from a distance. Similar search patterns have been revealed in foraging birds, monkeys, zooplankton, and even human hunter-gatherers. Our work shows, however, that near the odor source the Lévy search is terminated in favor of a Brownian random walk. We are keenly interested in the circuits and physiological triggers that mediate the switch between sensory-independent distant exploratory search and sensory-dependent local search.

Socially Enhanced Sensory Function
During our walking behavior experiments, we found that optomotor reflexes are increased by testing the animals in a single large group rather than many small groups. There appears to be a strong social effect on the strength of optomotor reflexes. We have collected evidence suggesting that this apparent social influence may be mediated by a pheromone-like signal, known to be released by stressed flies, that activates the olfactory system. We are using genetic techniques to investigate how olfaction acts to lower the behavioral response threshold of external sensory signals.

This work is supported in part by the National Science Foundation and the National Institutes of Health.

As of May 30, 2012

Scientist Profile

Early Career Scientist
University of California, Los Angeles