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4 Janelia Publications

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    04/03/17 | Sensorimotor neuroscience: motor precision meets vision.
    Longden KD, Huston SJ, Reiser MB
    Current Biology : CB. 2017 Apr 03;27(7):R261-R263. doi: 10.1016/j.cub.2017.02.047

    Visual motion sensing neurons in the fly also encode a range of behavior-related signals. These nonvisual inputs appear to be used to correct some of the challenges of visually guided locomotion.

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    10/21/15 | Neural encoding of odors during active sampling and in turbulent plumes.
    Huston SJ, Stopfer M, Cassenaer S, Aldworth ZN, Laurent G
    Neuron. 2015 Oct 21;88(2):403-18. doi: 10.1016/j.neuron.2015.09.007

    Sensory inputs are often fluctuating and intermittent, yet animals reliably utilize them to direct behavior. Here we ask how natural stimulus fluctuations influence the dynamic neural encoding of odors. Using the locust olfactory system, we isolated two main causes of odor intermittency: chaotic odor plumes and active sampling behaviors. Despite their irregularity, chaotic odor plumes still drove dynamic neural response features including the synchronization, temporal patterning, and short-term plasticity of spiking in projection neurons, enabling classifier-based stimulus identification and activating downstream decoders (Kenyon cells). Locusts can also impose odor intermittency through active sampling movements with their unrestrained antennae. Odors triggered immediate, spatially targeted antennal scanning that, paradoxically, weakened individual neural responses. However, these frequent but weaker responses were highly informative about stimulus location. Thus, not only are odor-elicited dynamic neural responses compatible with natural stimulus fluctuations and important for stimulus identification, but locusts actively increase intermittency, possibly to improve stimulus localization.

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    06/01/12 | Solitary and gregarious locusts differ in circadian rhythmicity of a visual output neuron.
    Gaten E, Huston SJ, Dowse HB, Matheson T
    Journal of BiologicalRrhythms. 2012 Jun;27(3):196-205. doi: 10.1177/0748730412440860

    Locusts demonstrate remarkable phenotypic plasticity driven by changes in population density. This density dependent phase polyphenism is associated with many physiological, behavioral, and morphological changes, including observations that cryptic solitarious (solitary-reared) individuals start to fly at dusk, whereas gregarious (crowd-reared) individuals are day-active. We have recorded for 24-36 h, from an identified visual output neuron, the descending contralateral movement detector (DCMD) of Schistocerca gregaria in solitarious and gregarious animals. DCMD signals impending collision and participates in flight avoidance maneuvers. The strength of DCMD’s response to looming stimuli, characterized by the number of evoked spikes and peak firing rate, varies approximately sinusoidally with a period close to 24 h under constant light in solitarious locusts. In gregarious individuals the 24-h pattern is more complex, being modified by secondary ultradian rhythms. DCMD’s strongest responses occur around expected dusk in solitarious locusts but up to 6 h earlier in gregarious locusts, matching the times of day at which locusts of each type are most active. We thus demonstrate a neuronal correlate of a temporal shift in behavior that is observed in gregarious locusts. Our ability to alter the nature of a circadian rhythm by manipulating the rearing density of locusts under identical light-dark cycles may provide important tools to investigate further the mechanisms underlying diurnal rhythmicity.

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    06/24/11 | Studying sensorimotor integration in insects.
    Huston* SJ, Jayaraman V
    Current Opinion in Neurobiology. 2011 Jun 24;21(4):527-34. doi: 10.1016/j.conb.2011.05.030

    Sensorimotor integration is a field rich in theory backed by a large body of psychophysical evidence. Relating the underlying neural circuitry to these theories has, however, been more challenging. With a wide array of complex behaviors coordinated by their small brains, insects provide powerful model systems to study key features of sensorimotor integration at a mechanistic level. Insect neural circuits perform both hard-wired and learned sensorimotor transformations. They modulate their neural processing based on both internal variables, such as the animal’s behavioral state, and external ones, such as the time of day. Here we present some studies using insect model systems that have produced insights, at the level of individual neurons, about sensorimotor integration and the various ways in which it can be modified by context.

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