An Odorant Encoding Machine for Sampling, Reconstruction and Robust Representation of Odorant Identity

Lazar, Aurel A.; Liu, Tingkai; Yeh, Chung-Heng

doi:10.1109/icassp40776.2020.9054588

Cited by 6 publications

(21 citation statements)

References 21 publications

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“…(d3) Input stimulus consisting of a bar moving back and forth across the screen, and a second fixed bar with lower brightness. Figure 3: Analysis, evaluation and comparison between 2 models of the antenna and antennal lobe circuit of the adult fly based on the FlyCircuit (left) dataset [33] and an exploratory model based on the Hemibrain (right) dataset. (a) Morphology of olfactory sensory neurons, local neurons and projection neurons in the antennal lobe for the two datasets.…”

Section: Analyzing Evaluating and Comparing Of Adult Antenna And Antmentioning

confidence: 99%

“…3(a)). Following [33], we first constructed the two layer circuit shown in Figure 3(b) (left) and then constructed a more connectome/synaptome-realistic model of the adult antennal lobe shown in Fig. 3…”

Section: Analyzing Evaluating and Comparing Of Adult Antenna And Antmentioning

confidence: 99%

“…3(d)). A prediction [36,33] made by the antenna and antennal lobe circuit shown in Figure 3(b) (left) using the FlyCircuit data has been that the PN activity, bundled according to the source glomerulus, is proportional to the vector characterizing the affinity of the odorant-receptor pairs ( Fig. 3(c), left column).…”

Section: Analyzing Evaluating and Comparing Of Adult Antenna And Antmentioning

confidence: 99%

“…Detailed connectivity information informed the model construction for both the adult and larva EOS, that we developed based on parameterized versions of the previous literature [33]. In particular, the larval model includes fewer number of OSNs, PNs and LNs in Antenna and Antennal Lobe circuit as shown in Fig.…”

Section: Analyzing Evaluating and Comparing Early Olfactory Circuitmentioning

confidence: 99%

“…MBcircuits: Modeled after the third neuropil of the olfactory pathway, the MBcircuits Library describes the expansion-and-sparsification circuit consisting of a population of Antennal Lobe Projection Neurons and Mushroom Body Kenyon Cells (KCs) [33].…”

Section: Eoscircuits Library For Larva and Adult Early Olfactory Circmentioning

confidence: 99%

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FlyBrainLab: Accelerating the Discovery of the Functional Logic of theDrosophilaBrain in the Connectomic/Synaptomic Era

Lazar¹,

Liu²,

Türkcan³

et al. 2020

Preprint

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In recent years, a wealth of Drosophila neuroscience data have become available. These include cell type, connectome and synaptome datasets for both the larva and adult fly. To facilitate integration across data modalities and to accelerate the understanding of the functional logic of the fly brain, we developed an interactive computing environment called FlyBrainLab.FlyBrainLab is uniquely positioned towards accelerating the discovery of the functional logic of the Drosophila brain. Its interactive open source architecture seamlessly integrates and brings together computational models with neuroanatomical, neurogenetic and electrophysiological data, changing the organization of neuroscientific fly brain data from a group of unconnected databases, arrays and tables, to a well structured data and executable circuit repository. The FlyBrainLab User Interface supports a highly intuitive and automated workflow that streamlines the 3D exploration and visualization of fly brain circuits, and the interactive exploration of the functional logic of executable circuits created directly from the explored and visualized fly brain data.FlyBrainLab methodologically supports the efficient comparison of fly brain circuit models, across model instances developed by different researchers, across different developmental stages of the fruit fly and across different datasets. The FlyBrainLab Utility and Circuit Libraries accelerate the creation of models of executable circuits. The Utility Libraries help untangle the graph structure of neural circuits from raw connectome and synaptome data. The Circuit Libraries facilitate the exploration of neural circuits of the neuropils of the central complex and, the development and implementation of models of the adult and larva fruit fly early olfactory systems.To elevate its executable circuit construction capability beyond the connectome, FlyBrainLab provides additional libraries for molecular transduction arising in sensory coding in vision and olfaction. Together with sensory neuron activity data, these libraries serve as entry points for discovering circuit function in the sensory systems of the fruit fly brain. They also enable the biological validation of developed executable circuits within the same platform.

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Section: Analyzing Evaluating and Comparing Of Adult Antenna And Antmentioning

confidence: 99%

Section: Analyzing Evaluating and Comparing Of Adult Antenna And Antmentioning

confidence: 99%

Section: Analyzing Evaluating and Comparing Of Adult Antenna And Antmentioning

confidence: 99%

Section: Analyzing Evaluating and Comparing Early Olfactory Circuitmentioning

confidence: 99%

Section: Eoscircuits Library For Larva and Adult Early Olfactory Circmentioning

confidence: 99%

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FlyBrainLab: Accelerating the Discovery of the Functional Logic of theDrosophilaBrain in the Connectomic/Synaptomic Era

Lazar¹,

Liu²,

Türkcan³

et al. 2020

Preprint

Self Cite

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The Functional Logic of Odor Information Processing in the Drosophila Antennal Lobe

Lazar

Liu

Yeh

2021

Preprint

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In the early olfactory pathway of Drosophila, Olfactory Sensory Neurons (OSNs) multiplicatively encode the odorant identity and the concentration profile. Projection Neurons (PNs) responses in the Antennal Lobe (AL), in turn, exhibit strong transients at odorant onset/offset and stable steady-state behavior. What is the functional logic the of diverse set of Local Neurons (LNs) in the AL Addressing this question may shed light on the key characteristics of odor information processing in the AL, and odorant recognition and olfactory associative learning in the downstream neuropils of the early olfactory system. To address the computation performed by each LN type, we exhaustively evaluated all circuit configurations of the Antennal Lobe. We found that, across model parameterizations, presynaptic inhibition of the OSN-to-PN synapse is essential for odorant identity recovery in steady-state, while postsynaptic excitation and inhibition facilitate on-/off-set event detection. The onset and offset events indicate changing odorant identities, and together with the identity recovery in steady-state, suggest that the AL is an event-based odorant identity recovery processor.

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A Programmable Ontology Encompassing the Functional Logic of the Drosophila Brain

Lazar

Türkcan

Zhou

2021

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The Drosophila brain has only a fraction of the number of neurons of higher organisms such as mice. Yet the sheer complexity of its neural circuits recently revealed by large connectomics datasets suggests that computationally modeling the function of fruit fly brain at this scale posits significant challenges. To address these challenges, we present here a programmable ontology that expands the scope of the current Drosophila brain anatomy ontologies to encompass the functional logic of the fly brain. The programmable ontology provides a language not only for defining functional circuit motifs but also for programmatically exploring their functional logic. To achieve this goal, we tightly integrated the programmable ontology with the workflow of the interactive FlyBrainLab computing platform. As part of the programmable ontology, we developed NeuroNLP++, a web application that supports free-form English queries for constructing functional brain circuits fully anchored on the available connectome/synaptome datasets, and the published worldwide literature. In addition, we present a methodology for including a model of the space of odorants into the programmable ontology, and for modeling olfactory sensory circuits of the antenna of the fruit fly brain that detect odorant sources. Furthermore, we describe a methodology for modeling the functional logic of the antennal lobe circuit consisting of massive local feedback loops, a characteristic feature observed across Drosophila brain regions. Finally, using a circuit library, we demonstrate the power of our methodology for interactively exploring the functional logic of the massive number of feedback loops in the antennal lobe.

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An Odorant Encoding Machine for Sampling, Reconstruction and Robust Representation of Odorant Identity

Cited by 6 publications

References 21 publications

FlyBrainLab: Accelerating the Discovery of the Functional Logic of theDrosophilaBrain in the Connectomic/Synaptomic Era

FlyBrainLab: Accelerating the Discovery of the Functional Logic of theDrosophilaBrain in the Connectomic/Synaptomic Era

The Functional Logic of Odor Information Processing in the Drosophila Antennal Lobe

A Programmable Ontology Encompassing the Functional Logic of the Drosophila Brain

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