The Digital Fruit Fly Brain

Lead Research Organisation: University of Sheffield
Department Name: Automatic Control and Systems Eng

Abstract

Several highly ambitious, large-scale, billion-pound research projects that aim to understand the human brain are currently under way. In Europe, The Human Brain Project is focused on accelerating brain research by integrating data available from a multitude of disparate research projects through the development of a multi-scale, multi-level model of the human brain - the 100 billion neurons modelling and simulation challenge. In US, The Brain Initiative aims to reconstruct the full record of neural activity across complete neural circuits - the 100 billion neurons recording challenge. These are clearly huge but worthy challenges that, we believe, can benefit from an understanding of the principles of neural computation of much smaller but sufficiently complex brains.
The fruit fly brain has become one of the most popular model organisms to study neural computation and for relating brain structure to function. Many of the genes and proteins expressed in the mammalian brain are also conserved in the genome of Drosophila. Remarkably, the fruit fly is capable of a host of complex nonreactive behaviors that are governed by a brain containing only ~100000 neurons. The relationship between the fly's brain and its behaviors can be experimentally probed using a powerful toolkit of genetic techniques for manipulation of the fly's neural circuitry. Novel experimental methods for precise recordings of the fly's neuronal responses to stimuli and for mapping neurons and synapses in Drosophila nervous system have provided access to an immense amount of valuable data regarding the fly's neural connectivity map and its processing of sensory stimuli. These features coupled with the growing ethical and economic pressures to reduce the use of mammals in research, explain the growing interest in Drosophila-based brain models, not only to understand sensing, perception and neural computation but also to elucidate human neurodegenerative diseases such as Alzheimer's disease.
Despite significant investment and huge progress in understanding Drosophila neural circuits and the availability of excellent genomic and genetic community databases, a major obstacle in understanding the fly brain is the lack of communication/collaboration across the modelling community as well as lack of shared models, modelling tools and data repositories. Vast amounts of experimental data that have yet to be distilled into new models or used to validate and refine existing models, have been generated by labs around the world. Knowledge and information of the detailed neuroanatomy, neuron connectivity and gene expression of the adult Drosophila melanogaster brain has been made publicly available thanks to the efforts of earlier pioneering efforts.
This aim to develop an open source, modular software platform that will help researchers to work collaboratively and exploit the wealth of knowledge, data, models, and tools available to build and simulate a complete model of the fly brain. The software platform exploits relatively cheap supercomputing services that use Graphic Processor Units, which many academic institutions in the UK, US and worldwide haave adopted in recent years.

Technical Summary

This project aims to design, implement and experimentally evaluate a potentially transformative open-source fly brain simulation platform capable of simulating ~135,000 neurons that make up the adult Drosophila brain. This computational infrastructure will be based on the recently established GPU-enabled Neurokernel software platform. The modular simulation platform will integrate all knowledge about the Drosophila brain as a set of interconnected simulation modules which describe the operation of about 41 Local Processing Units (LPUs), six hubs and their interconnections, partly elucidated by detailed EM imaging studies. The simulation platform will be used to develop and validate a first draft model that incorporates the most advanced biophysical and/or functional models of the neurons and the latest published synaptic connections maps. The main focus will be on developing detailed models of the early visual system (retina, lamina, medulla) and of the early olfactory system (OSNs, antennal lobe, mushroom body, lateral horn). These models will integrate complete models of the visual and olfactory systems. The brain simulation platform will enable for the first time the isolated and integrated emulation of fly brain model neural circuits and their connectivity patterns (e.g., sensory and locomotion systems) and other parts of the fly's nervous system on clusters of GPUs. Using the Neurokernel simulation platform it will be possible to generate data sufficiently fast to enable researchers to compare and tune the input-output characteristics of virtual neurons on-line, while the experiment is running.

Planned Impact

The end-users of this research are anticipated to be:
a) NVIDIA (Project Partner)
As many universities have invested in GPU-based commodity supercomputing services, NVIDIA is very interested to understand and meet the needs of the science community in order to develop successful products for very competitive market. It should be noted that big players like Intel and IMB are in direct competition with NVIDIA in the High-Performance Computing/Supercomputing market. As Project Partner NVIDIA will have direct, first-hand access to our results. The project will give the valuable insight into the current limitations of, particularly, their connectivity architecture for such applications. NVIDIA will also have access to novel software architectures that exploit parallelism, which will enable them to optimize and develop further their CUDA tools, libraries, languages and other development tools.
b) Rolls-Royce
The Automatic Control and Systems Engineering Department at the University of Sheffield hosts the Rolls-Royce University Technology Centre in Control and Systems Engineering (RR-UTC). RR-UTC provides the company with the necessary technology to support the efficient production of world-class engine control and monitoring systems. The Centre recently achieved economic impact by developing the first radically new control laws for gas turbine engines for 30 years, which are now operating across the entire engine range, including the flagship Rolls-Royce Trent 1000 engines powering the Boeing Dreamliner.
One of the research areas being investigated within the Centre is the use of compressive sensing techniques for efficient, transmission and reconstruction of the signals from the sensors acquiring the data. This has the potential to reduce significantly the bandwidth required for data transfer from a vast array of sensors and pave the way for the implementation of wireless control systems. Another area of active research is in distributed decision support systems for health management of the fleet of engines, supported by high performance computing architectures. The proposed project is of particular interest because the brain employs exactly the type of low-energy, low bandwidth but highly robust coding strategies that are desired by the company. Moreover, by understanding the brain, which in effect is a highly sophisticated control system, it would be possible to develop alternative neuromorphic distributed control architectures which could be much cheaper to implement as well as more robust and fault tolerant.
 
Description 1-We demonstrated that fly photoreceptors use nonlinear transformations of visual stimuli to encode efficiently edges present in temporal stimuli.
Specifically we showed recently that nonlinear encoding achieves near optimal rate/distortion bound.
2- We have demonstrated that photoreceptors use a nonlinear coding scheme to improve communication robustness in noisy environments 3- By exploiting the concept of structural controllability we analysed and interpreted for the first time the control profiles for the Drosophila Melanogaster connectome. Using the synaptically inferred connectome of ~20,000 neurons spanning the drosophila brain, we show that in contrast to the simple source-driven connectome of the C. Elegans, the individual neuropils of the Drosophila brain span the entire control profile space, which reflects its much larger functional and behavioural repertoire. Specifically, around 38% of the
largest 40 neuropils analysed are source dominated which reflects distributed processing and 30% are external-dilation dominated indicating correlated/synchronized behaviour driven by source nodes. About 17% of neuropils are internal-dilation dominated which indicate they operate to a larger extent independently of the external stimulation. The remaining neuropils's exhibit a relatively balanced control profile.
Finally, we compared and contrasted the controllability profiles of specific functional neural circuits that mediate visual, olfactory and auditory processing as well as locomotion. We found significant differences between control profiles which indicate that internal neuropil structure is tailored to reflect not only the specific function performed by the circuit but also the computations (or algorithm) that support that function.
4-We developed NeuroArch, a graph database for codifying knowledge about fruit fly brain circuits. It is designed with two user communities in mind: (i) neurobiologists/neurogeneticists interested in querying the database to address questions regarding neuroanatomy, neural circuits, neurons, synapses, neurotransmitters, and gene expression, and (ii) computational/theoretical neuroscientists and computer science/engineers interested in the instantiation of models of neural circuits and architectures, their program execution, and validation of hypotheses regarding brain function. A key aim of NeuroArch is to provide a resource that supports and connects interface the research carried out between concerns of these two communities. To this end, NeuroArch defines a data model for the representation of both biological data and model structure and the relationships between them within a single graph database (Givon et al., 2015).
The connectomic and anatomical data currently in the FFBO platform includes all available open fly brain data from the (i) FlyCircuit (Chiang et al., 2011), spanning some 20,000 neurons and 1,260,000 inferred synaptic connections (Huang et al., 2019), and (ii) the Janelia seven column Medulla EM reconstruction that includes some 500 neurons and 67,000 synapses (Takemura et al., 2015; Takemura et al., 2017), and (iii) the Janelia larval EM reconstruction that currently includes some 500 neurons and 138,000 synapses (Berck et al., 2016; Eichler et al., 2017). The physiological data currently in the database consists of 1.6 hours of electrophysiology recordings from photoreceptors (Friederich et al., 2016; Juusola et al., 2017), olfactory sensory neurons (Kim et al., 2011) and antennal lobe projection neurons (Kim et al., 2015).
The current NeuroArch database also includes two different models of the retina, developed by two research groups, and a model of the lamina neuropil of the Drosophila. Additionally, a model of the early olfactory system, including the antenna and antennal lobe resides in the current NeuroArch.
5-We developed Neurokernel, an open-source engine implemented in Python for the collaborative emulation and validation of fruit fly brain models on multiple Graphics Processing Units (GPUs) (Givon and Lazar, 2016). 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. Neurokernel defines application programming interfaces for communication between LPUs regardless of their internal design. Researchers can independently model different regions of the fly brain as LPUs and easily interconnect these for more complex functional validations.
6-NeuroNLP provides a modern web-based portal for navigating biological data relating to fruit fly brain circuits. It is equipped with a user-friendly, graphical interface to aggregate cell-type, connectome, synaptome and physiology data in the NeuroArch database, with the ability to simultaneously query against and retrieve information from disparate datasets.
NeuroNLP features a novel natural language interface that constructs complex queries against the underlying database from plain English instructions such as "show GABAergic neurons that have dendrites in left antennal lobe and axons in both left lateral horn and right dorsolateral protocerebrum" (or simply "show GABAergic neurons that have dendrites in al and axons in both lh and DLP"). This provides highly intuitive access to the integrated fruit fly brain circuit data, without the presumption of knowledge of a query language, syntax or cumbersome user interfaces. The results of the queries are presented using powerful 3D visualization and can be shared using a tag or by a demo script for publication and collaboration. In addition, any neuron in the scene can be explored in greater detail using the information panel, which provide one stop access to all data associated with a particular neuron.
7-We developed NeuroGFX an environment to easily explore circuit structure and function ultimately leading to biological validation. On the whole brain level NeuroGFX lays out the guidelines for the development of whole brain emulation. On the neuropil level, NeuroGFX allows users to study the I/O of each LPU. The canonical circuits (circuit motifs) are also identified on this level and NeuroGFX can be used to study the effect of different compositions mediated by local neurons.
NeuroGFX features a set of highly intuitive tools for exploring the function of neural circuit models, which can be accessed through. It provides a graphical user interface (GUI), allowing the user that can be used to (i) associate circuit diagrams with biological data, (ii) graphically construct an in silico experiment and execute manipulated circuits on GPUs, (iii) visualize the execution results in the context of biological brain structure. These capabilities are supported by a seamless integration of the NeuroArch database and the Neurokernel engine in the FFBO architecture.
Specifically, NeuroGFX assembles executable circuits of the fruit fly brain neuropils through flexible queries of the NeuroArch database that hosts executable models alongside biological data.
Exploitation Route Improve the design of artificial retinas
Development of new bio-inspired, robust information processing and coding strategies
Sectors Aerospace, Defence and Marine,Education,Healthcare,Pharmaceuticals and Medical Biotechnology

URL http://fruitflybrain.org/
 
Description The Fruit Fly Brain Observatory we developed (http://fruitflybrain.org/) is a great education resource that has started to be used by educators. It provides a modern web-based portal for navigating fruit fly brain circuit data. It enables in-depth exploration and investigation of brain structure, using intuitive plain English queries, such as "show glutamatergic local neurons in the left antennal lobe". The Natural Language Interface allowis non-experts to query, visualise and explore the fruit fly brain using normal language.
First Year Of Impact 2017
Sector Education,Healthcare
Impact Types Societal

 
Description Fruit Fly Brain Observatory-Open Science Prize Competition
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
Impact Mental and neurological disorders pose major medical and socioeconomic challenges for society. Understanding human brain function and disease is arguably the biggest challenge in neuroscience. To help address this challenge, smaller but sufficiently complex brains can be used. This application will store and process connected data related to the neural circuits of the fruit fly brain. Using computational disease models, researchers can make targeted modifications that are difficult to perform in vivo with current genetic techniques. These capabilities will significantly accelerate the development of powerful new ways to predict the effects of pharmaceuticals upon neural circuit functions. Using computational disease models, researchers can make targeted modifications that are difficult to perform in vivo with current genetic techniques. Models of neural circuits affected by disease will enable parallel recording of the responses of multiple components of a model circuit that are currently difficult - if not impossible - to perform in vivo. These capabilities will significantly accelerate the development of powerful new ways to predict the effects of pharmaceuticals upon neural circuit functions.
URL https://www.nih.gov/news-events/news-releases/open-science-prize-announces-six-team-finalists-first-...
 
Description Microsoft Azure for Research
Amount $5,000 (USD)
Funding ID CRM:0518115 
Organisation Microsoft Corporation 
Sector Public
Country United States
Start 01/2017 
End 12/2018
 
Description Open Science Prize
Amount $80,000 (USD)
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 04/2016 
End 12/2016
 
Description SURE: Sheffield Undergraduate Research Experience
Amount £1,080 (GBP)
Organisation University of Sheffield 
Sector Academic/University
Country United Kingdom
Start 06/2018 
End 08/2018
 
Title Early Olfaction Parkinson's Disease Model 
Description This app investigates the effect of the Parkinson's Disease in the early olfactory system. The antennal lobe is the first neuropil in the olfaction sensory pathway, which can be decomposed to ~50 subregions, called glomerulus. Each glomerulus consists of some 50 olfactory sensory neurons (input), and 3-5 projection neurons (output). Glomeruli are interconnected by over 100 local neurons. In total, the antennal lobe has about 2500 olfactory sensory neurons, 150 projection neurons, and 100 local neurons. A healthy model of the antennal lobe developed by the research team is simulated for a given input odorant profile. The ensemble response of projection neurons of each glomerulus is viusalised in both biological view and as an interactive plot. A separate disease model based on the hypothesis that the Parkinson's Disease causes the abnormal inhibitory neurotransmitter (GABA) release was also implemented. The diseased model is simulated with the same input odorant as the healthy model, and its response is provide below alongside the result of the healthy model. 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2018 
Provided To Others? Yes  
Impact NA at this time 
URL https://neuroapps.fruitflybrain.org/parkinsons/olfaction/
 
Title Fruit Fly Brain Observatory 
Description Mental and neurological disorders pose major medical and socioeconomic challenges for society. Understanding human brain function and disease is arguably the biggest challenge in neuroscience. To address this challenge, smaller but sufficiently complex brains like that of the fruit fly have been increasingly used for investigating the mechanisms of human neurological and psychiatric disorders, such as Epilepsy or Parkinson's disease, at molecular, cellular and circuit level. The Fruit Fly Brain Observatory (FFBO) is an open source software platform that stores and processes data related to the neural circuits of the fly brain including location, morphology, connectivity and biophysical properties of every neuron; seamlessly integrates the structural and genetic data from multiple sources that can be queried, visualized and interpreted; automatically generates models of the fly brain that can be simulated efficiently using multiple Graphics Processing Units (GPUs) to help elucidate the mechanisms of human neurological disorders and identify drug targets. 
Type Of Material Improvements to research infrastructure 
Year Produced 2016 
Provided To Others? Yes  
Impact Using computational disease models, researchers make targeted modifications that are difficult to perform in vivo with current genetic techniques. Models of neural circuits affected by disease will enable parallel recording of the responses of multiple components of a model circuit that are currently difficult - if not impossible - to perform in vivo. These capabilities significantly accelerate the development of powerful new ways to predict the effects of pharmaceuticals upon neural circuit functions. The software platform has been used to develop and simulate models of Parkinson's disease, retinal degeneration and epilepsy. 
URL http://fruitflybrain.org/
 
Title NeuroApp - retina degeneration 
Description This app that is part of the Fruit Fly Brain Observatory implements a simulation model of retinal degeneration and a rescue scheme by optogenetics means. The compound eye of the fruit fly consists of 700-800 facets, called ommatidia. We model the retina here to have 721 ommatidia, positioned on a hemispherical surface. Each ommatidium hosts 8 photoreceptors. For simplicity, we consider only one photoreceptor in each ommatidium. Each photoreceptor has a microvillar structure called rhabdomere, which is the functional equivalent of the rod and cone outer segment in vertebrate retina. The rhabdomere contains ~30000 microvilli where rhodopsin (light receptor) are hosted. Retinal degeneration often results in reduced size of rhabdomere and partially or completely lacking of rhodopsin. Consequently, the diseased eye has low or no light sensitivity. This simulate a diseased eye by reducing the number of microvilli in each photoreceptor to 5% of the health photoreceptors. The simulated responses of the diseased photoreceptor array can be visualised in real time. 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2018 
Provided To Others? Yes  
Impact NA 
URL https://neuroapps.fruitflybrain.org/retinal_degeneration/
 
Title NeuroApp: Epilepsy model 
Description This application implements a whole-brain simulation model of epileptic activity using the fruit-fly brain connectome. In the Healthy model, when stimulus is onset at 2000ms, average rate rise to 2Hz and decrease to below 0.5Hz. Epilepsy is induced by diseased sodium channel that leads to an average firing rate change rapidly from 5Hz to 25Hz. In a rescued model. high activity only emerges in 2000~2100ms. After 2100ms brain reaches a low activity level. 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2018 
Provided To Others? Yes  
Impact NA at this time 
URL https://neuroapps.fruitflybrain.org/epilepsy/
 
Title NeuroApp: Parkinsons Disease Model 
Description Parkinson's is a progressive neurological condition. It is estimated that 6.3 million people have Parkinson's worldwide. Some people with Parkinson's disease notice that as the disease progresses their vision loses sharpness or becomes blurred. Difficulties related to the eyes and vision often progress alongside other Parkinson's symptoms. This model-based study investigates the role of Parkinson's disease in the Visual System, using a mathematical model of the early visual system of Drosophila. It has been shown experimentally that both human, and fly models of the disease show a loss of visual acuity, caused by underlying changes in the photoreceptors ability to deal with changing light contrast levels. The disease state is modelled as a change in the capacity of photoreceptors to adapt to changes in contrast in the visual stimuli. 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2018 
Provided To Others? Yes  
Impact NA at this time 
URL https://neuroapps.fruitflybrain.org/parkinsons/vision/
 
Title NeuroGFX 
Description NeuroGFX provides an environment to easily explore circuit structure and function ultimately leading to biological validation. On the whole brain level NeuroGFX lays out the guidelines for the development of whole brain emulation. On the neuropil level, NeuroGFX allows users to study the I/O of each LPU. The canonical circuits (circuit motifs) are also identified on this level and NeuroGFX can be used to study the effect of different compositions mediated by local neurons. NeuroGFX features a set of highly intuitive tools for exploring the function of neural circuit models, which can be accessed through. It provides a graphical user interface (GUI), allowing the user that can be used to (i) associate circuit diagrams with biological data, (ii) graphically construct an in silico experiment and execute manipulated circuits on GPUs, (iii) visualize the execution results in the context of biological brain structure. These capabilities are supported by a seamless integration of the NeuroArch database and the Neurokernel engine in the FFBO architecture. 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact This tool is actively used by a number of research groups in US and UK 
URL https://neurogfx.fruitflybrain.org/
 
Title NeuroNLP 
Description NeuroNLP provides a modern web-based portal for navigating biological data relating to fruit fly brain circuits. It is equipped with a user-friendly, graphical interface to aggregate cell-type, connectome, synaptome and physiology data in the NeuroArch database, with the ability to simultaneously query against and retrieve information from disparate datasets. NeuroNLP features a novel natural language interface that constructs complex queries against the underlying database from plain English instructions such as "show GABAergic neurons that have dendrites in left antennal lobe and axons in both left lateral horn and right dorsolateral protocerebrum" (or simply "show GABAergic neurons that have dendrites in al and axons in both lh and DLP"). This provides highly intuitive access to the integrated fruit fly brain circuit data, without the presumption of knowledge of a query language, syntax or cumbersome user interfaces. The results of the queries are presented using powerful 3D visualization and can be shared using a tag for publication and collaboration. In addition, any neuron in the scene can be explored in greater detail using the information panel, which provides a one stop access to all data associated with a particular neuron. 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact The tool is being used both by researchers as well as educators 
URL https://neuronlp.fruitflybrain.org/
 
Title New identification approach for neural circuits 
Description We developed two new algorithmic tool for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based on experimental data. 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact The new tool was used successfully to analyse data from the Allen Brain Atlas. Too early to quantify the full impact. 
URL https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01051
 
Title Improved model of fly photoreceptor 
Description We developed a new model of R1-R6 photoreceptors in Drosophila, which can reproduce the photoreceptor responses of wild as well as histamine deficient flies for arbitrary stimuli over the entire environmental range. The new model addresses the limitations of the previously developed empirical photoreceptor model (Friederich et al., 2016) in predicting the responses of histamine-deficient mutants by introducing a new model structure incorporating separate adaptation mechanisms for mean and contrast of the stimuli. By comparing the mean and contrast gains of the wild-type fly against their mutant counterparts it seems the brighter the stimuli the more important the role that the network of interneurons play in shaping the response of the photoreceptors. 
Type Of Material Computer model/algorithm 
Year Produced 2018 
Provided To Others? Yes  
Impact This model forms the basis for the first integrated model of the fly retina that reproduces accurately electrophysiological measurements. 
URL http://fruitflybrain.org/
 
Title NeuroGFX and NeuroNLP 
Description NeuroNLP provides a modern web-based portal for navigating fruit fly brain circuit data. It enables in-depth exploration and investigation of brain structure, using intuitive plain English queries, such as "show glutamatergic local neurons in the left antennal lobe". NeuroNLP can be accessed from any browser supporting WebGL. NeuroGFX is a database and user interface for executable neural circuits. With an intuitive graphical interface that visualizes biological circuit and their corresonding circuit diagrams with a hierarchical structure, NeuroGFX makes it easy to reconfigure brain circuits stored in the database, and, most importantly, execute them on GPUs to explore functions of the intact and reconfigured circuits. It presents a brain architecture in which models of different parts of the fruit fly brain can be integrated towards the exploration of whole brain function. 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
Impact The system has been used to implement and simulate models of neurodegenerative disease. It is currently being used by a number of research labs. It cal also be used as an educational tool. 
URL https://neuronlp.fruitflybrain.org/
 
Title Retina - Lamina model 
Description A complete model of the fruit fly retina and lamina incoprporating 860 ommatidia cartriges with six photoreceptors for each cartridge 
Type Of Material Computer model/algorithm 
Year Produced 2018 
Provided To Others? Yes  
Impact To early to comment. The model forms the basis for a Parkinson's disease model. 
 
Description Ann-Shyn Chiang Laboratrory Taiwan 
Organisation National Tsing Hua University (Taiwan)
Country Taiwan, Province of China 
Sector Academic/University 
PI Contribution Developed analysis and visualisation tools for the fruit fly connectome. See http://fruitflybrain.org/.
Collaborator Contribution Constructed a brain-wide wiring diagram at single-cell resolution
Impact http://fruitflybrain.org/
Start Year 2016
 
Description Bionet 
Organisation Columbia University
Department Electrical Engineering
Country United States 
Sector Academic/University 
PI Contribution We developed, and refined models of the retina for simulation on the Neurokernel platform.
Collaborator Contribution Developed the initial open source simulation platform Neurokernel. Provided tools and resources for our group to use.
Impact Open Science Prize Application This is a multi-disciplinary collaboration to develop models and a software platform for simulating the entire brain of the fruit fly: biology, computer science, control and systems engineering
Start Year 2015
 
Description NVIDIA 
Organisation NVIDIA
Country Global 
Sector Private 
PI Contribution Evaluation of new GPU architectures
Collaborator Contribution Training and technical support. In-kind contribution of £30K
Impact None yet
Start Year 2015
 
Description Oxford 
Organisation University of Oxford
Department Department of Physiology, Anatomy and Genetics
Country United Kingdom 
Sector Academic/University 
PI Contribution We are developing modelling and simulation tools to make experimentally plausible and accurate models of the fruit fly brain.
Collaborator Contribution They support the drosophila brain project with data, evaluation & testing of the software, and to help validate models.
Impact No outputs yet. Multi-disciplinary: biology, systems engineering, control engineering
Start Year 2015
 
Title Fruit fly brain Observatory 
Description The Fruit Fly Brain Observatory is a unique open source platform for studying fruit fly brain function, and for investigating fruit fly brain disease models that are highly relevant to the mechanisms of human neurological and psychiatric disorders. It stores and processes data related to the neural circuits of the fly brain including location, morphology, connectivity and biophysical properties of every neuron, seamlessly integrates the structural and genetic data from multiple sources that can be queried, visualized and interpreted, automatically generates models of the fly brain that can be simulated efficiently using multiple Graphics Processing Units (GPUs) to help elucidate the mechanisms of human neurological disorders and identify drug targets. 
Type Of Technology Webtool/Application 
Year Produced 2016 
Open Source License? Yes  
Impact One of the six winners of the first phase of the Open Science Prize 2016. This project was selected from about 100 entries from teams around the world. 
URL http://fruitflybrain.org/
 
Description Computational and Systems Neuroscience (Cosyne) 2018 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact There is great interest to understand the circuits that modulate behaviour such as the mirror neurons that fire
during action observation as well as action execution. Typically, given the neuron firing rates measured from a
large pool of candidate neurons, the challenge is to identify a subset of neurons that selectively respond during
the execution of a task [1]. Given the considerable evidence that biological neurons can generate spikes with
millisecond temporal precision [2], we argue that the problem of identifying task-specific neurons can be better
addressed by considering the exact timings of the spike sequences instead of the firing rates. Here we propose
a new Liquid State Machine (LSM) architecture, where the Readout unit is spike time based, and a new training
algorithm that implements orthogonal forward selection to identify the best synaptic connectivity for the Readout.
The learning algorithm, which is formulated in the Hilbert space of spike trains [3] with the LSM Readout defined as
an inner product in this space, can be used not only for task-specific neuron identification but also for conventional
machine learning applications. A machine learning example, involving the classification of jittered spike trains,
demonstrates that the introduction of the neuron selection step improves classification accuracy compared to the
standard method [4] and requires fewer synaptic connections to the Readout. A task-specific neuron identification
example shows that using precise spike timings instead of firing rates leads to the identification of a much smaller
set of key neurons that are relevant to the task.
Year(s) Of Engagement Activity 2018
URL http://www.cosyne.org/c/index.php?title=Cosyne_18
 
Description Cosyne 2017 Computational Neuroscience Conference 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact We had the opportunity to demonstrate the Fruit Fly Brain Observatory prototype- our entry for the final of the Open Science Prize
(http://fruitflybrain.org/)
Year(s) Of Engagement Activity 2017
 
Description Fly Brain Hackathon 2016 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Workshop organised at Columbia University in New York aimed at providing training and introducing participants to the modelling, simulation and visualisation tools developed as part of this project.
Year(s) Of Engagement Activity 2016
URL http://www.bionet.ee.columbia.edu/hackathons/ffbh/2016
 
Description Fruit Fly Brain Hackathon 2017 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact The 2nd Fruit Fly Brain Hackathon (FFBO 2017) and the first to feature the Fruit Fly Brain Observatory (FFBO) and its key components NeuroNLP and NeuroGFX. The former allows for exploring fruit fly brain data using plain English queries, and the latter facilitates the modeling and execution of such brain circuits. Brief tutorials will be given on the usage of the FFBO as well as developing new tools/features in FFBO. The hackathon is aimed at three main groups of participants: neurobiologists, modelers and software engineers. The goal of the hackathon is to bring together these three groups of participants to develop, use and improve the FFBO platform towards developing executable models of the fruit fly brain.
Year(s) Of Engagement Activity 2017
URL http://www.bionet.ee.columbia.edu/hackathons/ffbh/2017
 
Description Fruit Fly Brain Hackathon 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact We are pleased to announce the 3rd Fruit Fly Brain Hackathon (FFBH 2018). This hackathon will be focused on open neurophysiology data (electrophysiology, imaging, etc.) of, but not limited to, the fruit fly brain.

The hackathon will be focused on the following topics:

Promoting Neurodata Without Board (NWB) as a standard format for storing and sharing neurophysiology data in general, and extend it to standardize the storage and distribution of fruit fly brain electrophysiology and calcium imaging data,
Queryable neurophysiology data: organizing neurophysiology data and metadata in a database to make them easily queryable, and developing comprehensive querying tools accordingly,
Incorporating queried neurophysiology data into computational study.
The goals are to:

create a common language for sharing open neurophysiology data,
speed up pattern search in the data that can often be tedious and inefficient to do manually,
drive the creation of computational models and the validation of them using open data.
The hackathon is aimed at three main groups of participants: neurobiologists, modelers and software engineers. We welcome researchers working on the fruit fly brain as well as those working on other model organisms to participate and broaden the discussion in the hackathon.
Year(s) Of Engagement Activity 2018
URL http://www.bionet.ee.columbia.edu/hackathons/ffbh/2018
 
Description Open Data Science Symposium: How Open Data and Open Science are Transforming Biomedical Research 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Funding agencies and biomedical research organizations are increasingly embracing Open Science research paradigms characterized by new models of collaboration, new modes of data sharing, and new requirements for making data publicly available. The growing availability of open biomedical data and cloud-based infrastructure is creating unprecedented opportunities for using biomedical Big Data in novel ways to help solve pressing public health and biomedical research challenges.

This Symposium featured the Six Team Finalists of the Open Science Prize, an international prize competition led by the NIH Big Data to Knowledge (BD2K) Initiative, in partnership with the Howard Hughes Medical Institute and the UK-based Wellcome Trust, to support the development of innovative tools, products, and services that utilize Open Data.

Our Fruit Fly Brain Observatory prototype was one of the Six Team Finalists (https://www.openscienceprize.org/res/p/finalists/).
At this event, the six projects were made available the Open Science Prize website for the general public to vote.

Public voting comments comments on our Fruit Fly Brain Observatory are summarized below:
• Brain is the final frontier for sure. I really appreciate the effort the neuroscientists put into for better understanding brain and its function, especially for a moderate but achievable aim.

• Such a fantastic competition. I certainly see that linking connectome data with functional imaging data will be the next great revolution in science, and the difficulty and significance will dwarf the findings from the genome project and its relation to gene function. While this is my opinion, I certainly believe that understanding brain function will be massively more difficult than gene function, particularly as gene function can be done one at time but brain function needs to understand multiple interconnecting circuits simultaneously just to understand one small part of the brain. This I would definitely promote the fruit fly brain observatory.

• First, I think the brain researches help we human beings understand what we are, and what we can do next. Even a fruit fly's brain will tell lots of we never know before. Thus, I vote Fruit Fly as the 1st prize.

• I am more fascinated with all teams. they have done wonderful job. we know invertebrate system has given us excellent opportunity to understand the brain. FFBO has given a really good step by open source platform which includes brain imaging techniques, connectivity, morphology and tracing pattern of neurons spanning throughout in brain which will permit us to comprehend the human brain function and its disease related functions that is the biggest challenge in neuroscience.

• I am really convinced that the proper modelling could save time and resources in research. I liked the fact that the fruit fly observatory project could open other doors into the modelling and analysis of multiple diseases which in turn could lead to a quicker solution.

• I believe that Fruit Fly Brain Observatory concept is were the future of the discovery in medicine - creating interactive prototypes/models that would help identifying roots of the problems and finding resolutions by experimenting with the model. Similarly, new drug discovered via candidates compounds modeling.

• I like that the fruit fly brain observatory has very advanced technology that can allow researchers to perform genetic experiements using software.

• I like the idea of mapping the brain like an electrical system. I had some trouble with the website functionality, and as an IT professional, that needs refined. I also participate in Alzheimer's research as a subject, and see value in anything that can help us defeat this awful disease and many brain diseases that have eluded us so far.

• I vote for the Fruit Fly Brain Observatory since I think that this project has the potential to lead to ground breaking research and could have high impact. The project considers engineering aspects (such as modelling, simulation aspects and computational power) and medical aspects as well.

• If one is to "reverse engineer" the workings of the brain, it makes a lot of sense to start with a simple organism (fruit fly) where one can study small scale neuron interactions. Furthermore, the fruit fly has been very widely studied and consolidating what is known will be very useful. I tried out the system and found it easy to use with very nice visuals.

• Its really beautiful project and research.

• Kudos to all who worked on these prototypes. I wish they could all win. I chose the ones that I hope will advance the efforts to prevent or cure Alzheimer's and other dementias.

• Neurodegenerative diseases are more prevalent worldwide as the human population accumulates aged persons. The Drosophila model is excellent depiction of how we can address the neurodegenerative process in diseases like Alzheimer's and Parkinson's. Drosophila is an excellent model to understand the mechanism(s) of human disease pathologies. This team deserves the first prize.

• Thanks for these great works on SciVis. I am glad to see people to use the power of visualization to improve human life.

• Selected project will help cure mental disorder.

• The data and tools of the Fruit Fly Brain Observatory are pretty awesome, extensive and forward looking! I believe it'll be a pathblazing tool for other organisms as well as they scale up in the years to come.

• The fruit fly brain observatory is a very effective integration of known data and will be very useful to the international neuroscience community.

• The Fruit Fly Brain Observatory is important because we don't want films like Contagion to happen in real life. We need to study brains.

• The fruit fly brain observatory seems promising given that this research could unlock several mysteries to understand the human mind and fight serious degenerative diseases like Parkinson and Alzheimer.

• The Fruit Fly Brain project, seems to have the potential to revolutionize research in blindness.

• The human brain is the beginning and end of every human problem. To understand the brain is to understand avenues to both problems and solutions.

• The most useful for my research!

• Understanding how a brain works is one of the great challenge for this century. Given the complexity of the problem at hand, integrative and large scale approaches are needed to map the architecture. Fruit Fly Brain Observatory is an elegant platform attempting to address these immense challenges. By integrating massive amounts of neuroanatomy data in a common space, and making it approachable to other scientists will go a long way in contributing to the understanding of brain.

• As recession hits the major markets, the funding for an important part of research (basic research) get cut down. I believe this type of modelling should continue no matter what the state of world's capital markets as this type of research is responsible for increasing the real knowledge of the mankind.

• I am most interested in the Open Brain Imaging because I am battling brain cancer. I would love to see this projecs help advance neuroscience to help patients like me in the future.

• There is value in all of the studies. I voted for the two that studied the brain. The brain is our key to life. It holds the secrets of mental illness, including depression, which is one of the largest causes of disability worldwide. Through learning more about the brain we will be able to provide more effective treatments, and hopefully find ways to prevent the development of mental and neurological illnesses.
Year(s) Of Engagement Activity 2016
URL https://datascience.nih.gov/OpenDataScienceSymposiumCal
 
Description Open Days ACSE 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Schools
Results and Impact Presentations were given to visiting students applying to study for undergraduate degrees in Automatic Control and Systems Engineering. Around five events per year.
Year(s) Of Engagement Activity 2016,2017,2018,2019
 
Description Talk UKACC2018 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Postgraduate students
Results and Impact Keynote talk at the 12th UKACC International Conference on Contro.l The scope of the conference is intended to be broad with coverage of theory and applications of control and systems engineering. The talk highlighted how existing methods and tools in control, nonlinear systems and information theory, including system identification, higher-order frequency response and rate-distortion analysis, can be combined with remarkable experimental approaches to elucidate gain adaptation mechanisms and the role of nonlinearity in early visual processing.
Year(s) Of Engagement Activity 2018
URL https://control2018.group.shef.ac.uk/plenary-speakers/daniel-coca/