Temporal Responses of C. elegans Chemosensory Neurons Are Preserved in Behavioral Dynamics

Kato, Saul; Xu, Yifan; Cho, Christine E.; Abbott, L. F.; Bargmann, Cornelia I.

doi:10.1016/j.neuron.2013.11.020

Cited by 121 publications

(174 citation statements)

References 53 publications

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“…Similar biphasic filters have been found in numerous other systems (Hart and Alon, 2013;Kato et al, 2014;Nagel and Doupe, 2006); there they are proposed to support efficient coding (Atick and Redlich, 1990;Zhao and Zhaoping, 2011). Here, we add another aspect that makes biphasic filters advantageous: the two lobes correspond to two neuronal response features -tonic and phasic -and signal distinct song features -song amount and bout number.…”

Section: Linking Computations In the Auditory Pathway With Female Behmentioning

confidence: 52%

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Clemens¹,

Girardin²,

Coen³

et al. 2018

Neuron

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SummaryBrains are optimized for processing ethologically relevant sensory signals. However, few studies have characterized the neural coding mechanisms that underlie the transformation from natural sensory information to behavior. Here, we focus on acoustic communication in Drosophila melanogaster, and use computational modeling to link natural courtship song, neuronal codes, and female behavioral responses to song. We show that melanogaster females are sensitive to long timescale song structure (on the order of tens of seconds). From intracellular recordings, we generate models that recapitulate neural responses to acoustic stimuli. We link these neural codes with female behavior by generating model neural responses to natural courtship song. Using a simple decoder, we predict female behavioral responses to the same song stimuli with high accuracy. Our modeling approach reveals how long timescale song features are represented by the Drosophila brain, and how neural representations can be decoded to generate behavioral selectivity for acoustic communication signals.

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Section: Linking Computations In the Auditory Pathway With Female Behmentioning

confidence: 52%

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Clemens¹,

Girardin²,

Coen³

et al. 2018

Neuron

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“…The prediction of turning frequency to the stimulus waveform compares favorably with experimentally observed behavior, suggesting that the linear filter captures much of the sensorimotor transformation underlying larval thermotaxis. We expect that the prediction could be further improved by including nonlinearities into the transformation (e.g., linear-nonlinear models) or additional factors (e.g., generalized linear models) (16,17).…”

Section: Resultsmentioning

confidence: 99%

Sensory determinants of behavioral dynamics in Drosophila thermotaxis

Klein

Afonso

Vonner

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

152

206

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Complex animal behaviors are built from dynamical relationships between sensory inputs, neuronal activity, and motor outputs in patterns with strategic value. Connecting these patterns illuminates how nervous systems compute behavior. Here, we study Drosophila larva navigation up temperature gradients toward preferred temperatures (positive thermotaxis). By tracking the movements of animals responding to fixed spatial temperature gradients or random temperature fluctuations, we calculate the sensitivity and dynamics of the conversion of thermosensory inputs into motor responses. We discover three thermosensory neurons in each dorsal organ ganglion (DOG) that are required for positive thermotaxis. Random optogenetic stimulation of the DOG thermosensory neurons evokes behavioral patterns that mimic the response to temperature variations. In vivo calcium and voltage imaging reveals that the DOG thermosensory neurons exhibit activity patterns with sensitivity and dynamics matched to the behavioral response. Temporal processing of temperature variations carried out by the DOG thermosensory neurons emerges in distinct motor responses during thermotaxis. N avigation toward environmental conditions that improve survival and fitness is of near-universal importance in motile biological organisms. Quantitative analysis of such animal behaviors to defined sensory inputs is a powerful approach to elucidate how behavior is encoded in underlying neurons and circuits. The advantage of studying navigation in small, optically transparent, genetically modifiable animals like Caenorhabditis elegans (1) or Drosophila larvae (2) is the opportunity to dissect sensory, neuronal, and behavioral dynamics in live animals by using optical neurophysiology and optogenetics throughout the nervous system.The Drosophila melanogaster larva navigates gradients of many sensory cues, including light, temperature, odors, and tastes, but with fewer neurons in its sensory periphery and brain than the adult. Moreover, the simpler body plan and crawling movements of the larva facilitate the precise quantification of behavioral dynamics. Poikilotherms like C. elegans or Drosophila use sensitive thermosensory mechanisms to navigate moderate temperature ranges, thereby enabling them to use their environments to regulate their own body temperatures (3, 4). Here, we study sensory and behavioral dynamics during positive thermotaxis (i.e., cool avoidance) by the Drosophila larva. Tracking the movements of Drosophila exploring temperature, olfactory, or gaseous gradients has shown that their navigation is generated by a sequence of two alternating motor programs: runs involving peristaltic forward movement that are interrupted by turns involving probing side-to-side head sweeps until the initiation of a new run (5-8). Larvae negotiating temperature gradients stochastically transition between runs and turns by strategies that cause runs pointed in favorable directions to be more frequent and longer than runs pointed in unfavorable directions. These transitions b...

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“…(Schwartz et al 2006;Pillow et al 2008;Sharpee 2013;Aljadeff et al 2016)) but has also recently found applications in predicting behavior from both sensory stimuli and neuronal responses (e.g. (Kato et al 2014;Coen et al 2014;Schulze et al 2015;Clemens et al 2015a)). LN models treat the brain as a black box, i.e.…”

Section: The Approachmentioning

confidence: 99%

“…A simple generalization enables applying the STA approach to continuous outputs like neuronal calcium levels or the amplitude of the animal's communication signal (Kato et al 2014;Coen et al 2016). In these cases, the filter is estimated by weighting the stimulus by the response value.…”

Section: The Approachmentioning

confidence: 99%

“…Instead of using a linearnonlinear model to represent the dynamical codes underlying concentration coding in these OSN, they employed a model of the signal transduction cascade involved in the transformation of odorant concentration to OSN firing rate. Similar models have been used to model neural codes in other chemosensory systems (Kato et al 2014) or in the vertebrate retina (Ozuysal and Baccus 2012). This encoding model revealed the temporal stimulus features represented in the time-varying OSN firing rate: for positive concentration gradients, OSNs encode the slope; for negative gradients, OSNs act as offset detectors.…”

Section: Linking Sensory Stimuli With Neural Responses -Neuronal Encomentioning

confidence: 99%

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The use of computational modeling to link sensory processing with behavior in Drosophila

Clemens

Murthy

2017

Preprint

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A major goal of systems neuroscience is to understand how the brain represents information, and how those representations are used to drive behavior. Even though genetic model organisms like Drosophila grant unprecedented experimental access to the nervous system for manipulating and recording neural activity, the complexity of natural stimuli and natural behaviors still poses a challenge for solving the connections between neural activity and behavior. Here, we advocate for the use of computational modeling to complement (and enhance) the Drosophila toolkit. We first lay out a modelling framework for making sense of the relation between natural sensory stimuli, neuronal responses, and natural behavior. We then highlight how this framework can be used to reveal how neural circuits drive behavior, using selected case studies.PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2720v1 | CC BY 4.0 Open Access |

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Temporal Responses of C. elegans Chemosensory Neurons Are Preserved in Behavioral Dynamics

Cited by 121 publications

References 53 publications

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Connecting Neural Codes with Behavior in the Auditory System of Drosophila

Sensory determinants of behavioral dynamics in Drosophila thermotaxis

The use of computational modeling to link sensory processing with behavior in Drosophila

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