Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

Givon, Lev E.; Lazar, Aurel A.

doi:10.1371/journal.pone.0146581

Cited by 30 publications

(31 citation statements)

References 58 publications

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“…Architecture of the FFBO Supporting the two FFBO web applications is a highly sophisticated software architecture sketched in Figure 1. The two key components at the back-end are NeuroArch [2] and Neurokernel [3]. NeuroArch is a novel, graph-based database that supports integration of biological and modeling data within a single unified database accessed via a query-based API designed with the explicit aim of facilitating the generation of executable neural circuit models.…”

Section: Resultsmentioning

confidence: 99%

The Fruit Fly Brain Observatory: from structure to function

Ukani¹,

Yeh²,

Tomkins³

et al. 2016

Preprint

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SummaryThe Fruit Fly Brain Observatory (FFBO) is a collaborative effort between experimentalists, theorists and computational neuroscientists at Columbia University, National Tsing Hua University and Sheffield University with the goal to (i) create an open platform for the emulation and biological validation of fruit fly brain models in health and disease, (ii) standardize tools and methods for graphical rendering, representation and manipulation of brain circuits, (iii) standardize tools for representation of fruit fly brain data and its abstractions and support for natural language queries, (iv) create a focus for the neuroscience community with interests in the fruit fly brain and encourage the sharing of fruit fly brain structural data and executable code worldwide. NeuroNLP and NeuroGFX, two key FFBO applications, aim to address two major challenges, respectively: i) seamlessly integrate structural and genetic data from multiple sources that can be intuitively queried, effectively visualized and extensively manipulated, ii) devise executable brain circuit models anchored in structural data for understanding and developing novel hypotheses about brain function. NeuroNLP enables researchers to use plain English (or other languages) to probe biological data that are integrated into a novel database system, called NeuroArch, that we developed for integrating biological and abstract data models of the fruit fly brain. With powerful 3D graphical visualization, NeuroNLP presents a highly accessible portal for the fruit fly brain data. NeuroGFX provides users highly intuitive tools to execute neural circuit models with Neurokernel, an open-source platform for emulating the fruit fly brain, with full data support from the NeuroArch database and visualization support from an interactive graphical interface. Brain circuits can be configured with high flexibility and investigated on multiple levels, e.g., whole brain, neuropil, and local circuit levels. The FFBO is publicly available and accessible at http://fruitflybrain.org from any modern web browsers, including those running on smartphones. *

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Section: Resultsmentioning

confidence: 99%

The Fruit Fly Brain Observatory: from structure to function

Ukani¹,

Yeh²,

Tomkins³

et al. 2016

Preprint

Self Cite

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“…The system architecture of the FFBO (shown in Figure S1) is built around an expanding modular architecture. At the heart of the FFBO is the NeuroArch database [40], that integrates both biological data and computational models of brain circuits into a single database, and Neurokernel, a GPU-enabled computational engine for emulating the fruit fly brain [41]. The integrated database can be leveraged through the NeuroNLP and NeuroGFX front-ends.…”

Section: The Fruit Fly Brain Observatorymentioning

confidence: 99%

“…Neurokernel is an open-source engine implemented in Python for the collaborative emulation and validation of fruit fly brain models on multiple Graphics Processing Units (GPUs) [41]. Neurokernel provides a programming model based on the structural organization of the fly brain that consists of some 50 functional modules called Local Processing Units (LPUs) and the connectivity patterns that link them.…”

Section: The Fruit Fly Brain Observatorymentioning

confidence: 99%

The Fruit Fly Brain Observatory: From Structure to Function

Nh¹,

C²,

Tomkins

et al. 2019

Preprint

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The fruit fly is a key model organism for studying the activity of interconnected brain circuits. A large scattered global research community of neurobiologists and neurogeneticists, computational and theoretical neuroscientists, and computer scientists and engineers has been developing a vast trove of experimental and modeling data that has yet to be distilled into new knowledge and understanding of the functional logic of the brain. Developing open shared models, modelling tools and data repositories that can be accessed from anywhere in the world is the necessary engine for accelerating our understanding of how the brain works.To that end we developed the Fruit Fly Brain Observatory (FFBO), the next generation open-source platform to support open, collaborative Drosophila neuroscience research. FFBO provides a (i) hub for storing and integrating fruit fly brain research data from multiple data sources worldwide, (ii) unified repository of tools and methods to build, emulate and compare fruit fly brain models in health and disease, and (iii) an open framework for fruit fly brain data processing and model execution. FFBO provides access to application tools for visualizing, configuring, simulating and analyzing computational models of brain circuits of the (i) cell type map, (ii) connectome, (iii) synaptome, and (iv) activity map using intuitive queries in plain English. Tools are provided to extract the function inherent in these structural maps. All applications can be accessed with any modern browser.

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“…The Fruit Fly Brain Observatory (FFBO) (Ukani et al, 2019) is an open-source platform for the emulation and biological validation of fruit fly brain models in health and disease. It provides users highly intuitive tools to execute neural circuit models on modern commodity hardware (Givon and Lazar, 2016). NeuroGFX is the key FFBO component supporting the implementation of AMP LPU.…”

Section: Simulation Setup In the Fruit Fly Brain Observatory Platformmentioning

confidence: 99%

A Molecular Odorant Transduction Model and the Complexity of Combinatorial Encoding in the Drosophila Antenna

Lazar¹,

Yeh²

2017

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In the past two decades, substantial amount of work characterized the odorant receptors, neuroanatomy and odorant response properties of the early olfactory system of Drosophila melanogaster. Yet many odorant receptors remain only partly characterized, the odorant transduction process and the axon hillock spiking mechanism have yet to be fully determined.The essential functionality of olfactory sensory neurons (OSNs) is to jointly encode both odorant identity and odorant concentration. We model identity and concentration by an odorant-receptor binding rate tensor modulated by the odorant concentration profile and an odorant-receptor dissociation rate tensor, and quantitatively describe the ligand binding/dissociation process.To validate our modeling approach, we first propose an algorithm for estimating the affinity and the dissociation rate of an odorant-receptor pair. We then apply the algorithm to estimate the affinity and dissociation rate for (acetone, Or59b) using two different datasets of electrophysiology recordings. Second, we evaluate the temporal response of the Or59b OSN model to acetone with a multitude of stimuli, including step, ramp and parabolic odorant waveforms. We further interrogate the model with staircase and noisy waveforms.. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/237669 doi: bioRxiv preprint first posted online Dec. 21, 2017; 2 Lastly, we evaluate the affinity and the dissociation rate for different odorantreceptor pairs including (methyl butyrate, Or59b) and (butyraldehyde, Or7a).We demonstrate how to evaluate the odorant transduction process and biological spike generator cascade underlying the fruit fly OSN model at the circuit level of the antennae and maxillary palps under two scenarios. First, we empirically estimate the odorant-receptor affinity of the active receptor model in response to constant concentration odorants using the spike count records in the DoOR database. Second, we evaluate and graphically visualize the temporal response of the antennae and maxillary palps using a staircase odorant concentration waveform. Finally, we describe how to construct, execute and explore various instantiations of the antennae and maxillary palps as a parallel information preprocessor in the open-source Fruit Fly Brain Observatory platform.

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Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

Cited by 30 publications

References 58 publications

The Fruit Fly Brain Observatory: from structure to function

The Fruit Fly Brain Observatory: from structure to function

The Fruit Fly Brain Observatory: From Structure to Function

A Molecular Odorant Transduction Model and the Complexity of Combinatorial Encoding in the Drosophila Antenna

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