Behavior Reveals Selective Summation and Max Pooling among Olfactory Processing Channels

Bell, Joseph S.; Wilson, Rachel I.

doi:10.1016/j.neuron.2016.06.011

Cited by 82 publications

(127 citation statements)

References 60 publications

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“…A recent paper used optogenetics and systematically expressed a UV-light-sensitive Channelrhodopsin-2 protein in specific ORN types, and tested behavior activated by light (Bell 2016). Surprisingly, activation of the Or56a+, Or85a+ and the Ir64a+ ORNs led to attraction instead of aversion as would have been expected from previous studies.…”

Section: Activation Of Olfactory Receptors Dedicated To Aversionmentioning

confidence: 99%

Olfactory Mechanisms for Discovery of Odorants to Reduce Insect-Host Contact

Clark

Ray

2016

J Chem Ecol

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Insects have developed highly sophisticated and sensitive olfactory systems to find animal or plant hosts for feeding. Some insects vector pathogens that cause diseases in hundreds of millions of people and destroy billions of dollars of food products every year. There is great interest, therefore, in understanding how the insect olfactory system can be manipulated to reduce their contact with hosts. Here, we review recent advances in our understanding of insect olfactory detection mechanisms, which may serve as a foundation for designing insect control programs based on manipulation of their behaviors by using odorants. Because every insect species has a unique set of olfactory receptors and olfactory-mediated behaviors, we focus primarily on general principles of odor detection that potentially apply to most insects. While these mechanisms have emerged from studies on model systems for study of insect olfaction, such as Drosophila melanogaster, they provide a foundation for discovery of odorants to repel insects or reduce host-seeking behavior.

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Section: Activation Of Olfactory Receptors Dedicated To Aversionmentioning

confidence: 99%

Olfactory Mechanisms for Discovery of Odorants to Reduce Insect-Host Contact

Clark

Ray

2016

J Chem Ecol

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“…'the neural code' has been a topic of great debate in neuroscience [1][2][3][4][5][6] . Both patterns of spiking activities distributed across an ensemble of neurons [7][8][9][10][11][12][13][14] (i.e. 'the spatial code'), and the temporal features of these neural spike trains such as their synchronicity 15,16 , relative response latencies [17][18][19] , dynamics 4,[20][21][22][23][24][25][26] (i.e.…”

Section: Introductionmentioning

confidence: 99%

Dynamic contrast enhancement and flexible odor codes

Nizampatnam

Saha

Chandak

et al. 2017

Preprint

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Sensory stimuli evoke spiking activities patterned across neurons and time that are hypothesized to encode information about their identity. Since the same stimulus can be encountered in a multitude of ways, how stable or flexible are these stimulus-evoked responses? Here, we examined this issue in the locust olfactory system. In the antennal lobe, we found that both spatial and temporal features of odor-evoked responses varied in a stimulus-history dependent manner. The response variations were not random, but allowed the antennal lobe circuit to enhance the uniqueness of the current stimulus. Nevertheless, information about the odorant identity became confounded due to this contrast-enhancement computation. Notably, a linear logical classifier (OR-of-ANDs) that can decode information distributed in flexible subsets of neurons generated predictions that matched results from our behavioral experiments. In sum, our results reveal a simple computational logic for achieving the stability vs. flexibility tradeoff in sensory coding. INTRODUCTIONThe key task of a sensory system is to transduce and represent information about environmental cues as electrical neural activities so that the organism may generate an appropriate behavioral response. The precise format in which neural activities represents stimulus specific information i.e. 'the neural code' has been a topic of great debate in neuroscience

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“…The genetic model organism Drosophila melanogaster exhibits a range of robust and complex behaviors such as acoustic communication during courtship (Coen et al 2014;Clemens et al 2015a;Coen et al 2016), detection and integration of multisensory cues to locate food sources (van Breugel and Dickinson 2014;Bell and Wilson 2016), visually guided flight control (Clark et al 2011;Aptekar et al 2012;de Vries and Clandinin 2012;Silies et al 2014), and avoidance of threats (Reyn et al 2014). Recording Drosophila behaviors can be done in high-throughput, and its numerically compact and largely hardwired nervous system facilitates identifying the underlying neurons.…”

Section: The Challengementioning

confidence: 99%

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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Behavior Reveals Selective Summation and Max Pooling among Olfactory Processing Channels

Cited by 82 publications

References 60 publications

Olfactory Mechanisms for Discovery of Odorants to Reduce Insect-Host Contact

Olfactory Mechanisms for Discovery of Odorants to Reduce Insect-Host Contact

Dynamic contrast enhancement and flexible odor codes

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

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