Connectome to behaviour: modelling C. elegans at cellular resolution

09:05-09:30 Connecting a connectome to behaviour: evolution and ensemble analysis of integrated neuromechanical models of C. elegans

Dr Eduardo Izquierdo, Indiana University, USA

Abstract

Brain, body and environment are in continuous dynamical interaction, and it is becoming increasingly clear that an animal's behavior must be understood as a product not only of its nervous system, but also of the ongoing feedback of this neural activity through the biomechanics of its body and the ecology of its environment. Modeling has an essential integrative role to play in such an understanding. Successful whole-animal modeling requires an animal for which detailed behavioral, biomechanical and neural information is available and a modeling methodology which can gracefully cope with the constantly changing balance of known and unknown biological constraints. We will discuss recent progress on neuromechanical modeling in the nematode worm, with a special focus on our unique methodology for exploring the unknown biological parameters of the model through the use of evolutionary algorithms. We evolve the neural networks of the model worms on what they should do, behaviorally, with little or no instructions on how to do it. The effort is then to analyze and understand the solutions as a way to generate novel, often unexpected, hypotheses. We will focus the talk on how the rhythmic pattern is both generated and propagated along the body during locomotion. We discuss both the feasibility and challenges of whole-animal modeling.

• Listen to audio (mp3)

09:35-10:00 Powerful and interpretable behavioural features for classifying worms and constraining simulations

Dr André Brown, MRC LMS, Imperial College London, UK

Abstract

Behaviour is a sensitive and integrative readout of nervous system function and an attractive measure for assessing the performance of generative neural simulations. In C. elegans, most behavioural quantification starts with recording freely behaving animals crawling on the surface of an agar plate or swimming in fluid. Video data is rich but high-dimensional and so the next step of analysis is typically some form of tracking and feature extraction. Modern machine learning methods are powerful but notoriously difficult to interpret, while handcrafted features are interpretable but do not always perform as well. Here André reports a new set of handcrafted features to compactly quantify worm behaviour. André’s group combine clustering and feature selection to analyse behavioural differences with a tunable level of granularity that balances power and interpretability for a given application. The group use the new feature set to study the impact of mutations and optogenetic perturbations on worm behaviour and suggest how the same approach can be used to evaluate and constrain simulation output from the OpenWorm project.

• Listen to audio (mp3)

10:05-10:30 Three-dimensional simulation of the C. elegans body and muscle cells in liquid and gel environments for behavioural analysis

Dr Andrey Palyanov, AP Ershov Institute of Informatics Systems, Siberian Branch of the Russian Academy of Sciences, Russia

Abstract

In order to better understand how a nervous system may control the movements of an organism, Dr Andrey Palyanov has created a three-dimensional simulated physical model of the C. elegans body. The body model is created with a particle-system-based simulation engine known as Sibernetic, which implements the smoothed particle hydrodynamics algorithm. The model includes a body-wall cuticle subject to hydrostatic pressure. This cuticle is then driven by body wall muscle cells whose positions and shape are derived from C. elegans anatomy, determined from light microscopy and electron micrograph data. Andrey shows that by using different muscle activation patterns, this model is capable of producing C. elegans-like behaviours, including crawling and swimming locomotion in environments with different viscosities while fitting multiple additional known biomechanical properties of the animal.

• Listen to audio (mp3)

10:35-11:05 Coffee

11:05-11:30

Professor Netta Cohen, University of Leeds, UK

• Listen to audio (mp3)

11:35-12:20 Panel discussion

• Listen to audio (mp3)

13:15-13:40 Ion channels: from literature to computational model

Vahid Ghayoomie, The Openworm Foundation, USA

Abstract

Ion channels are pore-forming proteins, found in the membranes of all cells. They are responsible for many known functions include shaping action potentials and gating the flow of ions across the cell membrane. The nematode Caenorhabditis elegans genome codes for members of almost all the main families of ion channels. Many studies and electrophysiological experiments have been focused on ion channels and transporter functional genomics in C. elegans. However, due to lack of computational approaches in such investigations and obstacles in acquiring original experimental data, building a toolkit for collecting and digitizing data from available publications and then modelling ion channels in cells of interest was the main requirement at the first place. As part of the OpenWorm project, Vahid created the ChannelWorm in order to: 1) integrate and structure data related to ion channels in C. elegans; 2) digitize and curate electrophysiological data from publications; 3) develop APIs for accessing data and keeping data up-to-date; 4) build Hodgkin-Huxley models for ion channels based on experimental patch clamp studies; and 5) estimate kinetics and build models for ion channels with no patch clamp data available based on homologous channel types.

13:45-14:10 The pan-neuronal regulator CMK-1 acts locally to enable flexible behaviours

Professor Miriam B Goodman, Stanford University, USA

Abstract

The ability to adapt behaviour to environmental fluctuations is critical for survival of organisms ranging from invertebrates to mammals. The behavioural repertoire of Caenorhabditis elegans nematodes includes several that are modulated by prior experience, including thermotaxis, mechanosensation, and chemotaxis. Work by Miriam's research group and others (e.g. Yu et al., 2014; Schild et al., 2014) has linked plasticity in many of these behaviours to a calcium and calmodulin-dependent kinase encoded by the cmk-1 gene. CMK-1 is the sole ortholog of mammalian CaMKI/IV. Despite the expression of CMK-1 in most, if not all of the 302 neurons that make up the hermaphrodite nervous system, CMK-1 seems to function cell-autonomously in primary sensory neurons to enable flexible behaviours. This presentation will review studies of CMK-1 function in the C. elegans nervous system as an entry point for considering the ways in which flexibility and experience shape behaviour.

• Listen to audio (mp3)

14:15-14:40 Developmental connectomics and circuit insights for rhythm generation

Professor Mei Zhen, Lunenfeld-Tanenbaum Research Institute and University of Toronto, Canada

Abstract

The ability of animals to generate goal oriented motor behaviors ensures their survival. Professor Mei Zhen will present results that begin to describe the molecular and cellular origins of motor rhythm in C. elegans. Through cell ablation, electrophysiology, and calcium imaging, Mei will show the following: 1) forward and reverse movements are driven by different oscillators; 2) the cholinergic and excitatory A class motor neurons exhibit intrinsic and oscillatory activity that is sufficient to drive reverse movements without premotor interneurons; 3) the UNC-2 P/Q/N VGCC (voltage-activated calcium current) underlies A motor neuron’s oscillation; 4) the descending premotor interneurons AVA, via a conserved gap junction and chemical synapse configuration, exert state-dependent inhibition and potentiation of A motor neuron’s intrinsic activity to determine the propensity and duration of reverse movements. Previously, Professor Zhen’s group and others showed that only the body wall muscles generate L-VGCC-dependent action potential bursts. Hence excitatory motor neurons themselves derive P/Q/N-VGCC-dependent oscillatory motor rhythms and body wall muscles control bursting; descending interneurons regulate their motor neuron activity to control the reversal motor state. Hence, the C. elegans locomotory behaviors are driven by a fundamentally conserved (CPG-driven), but anatomically compressed motor circuit. Mei proposes that functional compression, that a single neuron or neuron class adopt multiple roles when a nervous system constrained by cell numbers, is a property that allows small animals to serve as compact models to dissect the organizational logic of circuits.

• Listen to audio (mp3)

14:45-15:10 Fast whole-brain imaging with complete neural identity in C. elegans

Dr Eviatar Yemini, University of Columbia, USA

Abstract

Stereotypy of the C. elegans nervous system affords single-neuron registration across animals, and consequently, robust statistics for neurobehavioral coding and transcriptomics. Fast methods of whole-brain imaging in worm exist, but unfortunately determining the identity of neurons within these volumes remains a bottleneck – requiring a long, difficult, ad hoc process. The group have developed a landmarked strain for whole-brain neural identification, NeuroPAL (a Neuronal Polychromatic Atlas of Landmarks). Each neuron is assigned an invariant fluorophore barcode such that colour and position specify unambiguous neural identity via the unique 3-tuple (colour, position, ganglion). The GFP channel is preserved for reporters of neural activity (GCaMP) and transcriptomics (GFP). The NeuroPAL permits complete neural identification at all larval stages including males. To visualise the strain the group’s collaborators, the Samuel Lab at Harvard, have created a new microscope with the capability of imaging 9 unique fluorescence channels generated by 3 excitation lines and 4 emission bands. This microscope acquires whole-brain volumes, of 4 fluorophores, simultaneously, at 10Hz. Together, these two innovations permit fast whole-brain imaging, with single-neuron identity and neuronal registration, across an animal populace.

15:15-15:45 Tea

15:45-16:30 Panel discussion

• Listen to audio (mp3)

09:00-09:25 Modelling, visualizing and understanding the neural dynamics of Caenorhabditis elegans

Dr Eli Shlizerman, University of Washington, USA

Abstract

Connectomes of organisms, such as the nematode Caenorhabditis elegans (C. elegans), have been mapped on various scales: from macro to single neuron level. In addition, decades of research in describing biophysical processes have provided foundations for modeling single neuron dynamics as well as synaptic and electric processes between neurons. Thereby, models which incorporate biophysical dynamical system acting on top of the static connectome, called dynomes, become more detailed and realizable. Availability of near-complete connectome data along with experimental quantification of responses and interactions allowed us to develop a detailed dynome model for C. elegans’ somatic nervous system. Employing an interactive visualization platform to simulate the dynome we apply various stimuli regimes and show robust low-dimensional bifurcation structures which drive a variety of multistable neural voltage modes, such as fixed points, limit cycles, multi-oscillatory dynamics. Comparison of these modes with experimental studies allows us to link behavioral states with network responses in the form of low-dimensional attractors and transitions between them.

• Listen to audio (mp3)

09:30-09:55 Modelling the neural network of C. elegans at multiple scales with c302

Dr Padraig Gleeson, University College London, UK

Abstract

Computational models of the nervous system are developed at multiple scales to answer questions about how low level interactions between biological entities lead to higher level functions. Models of the nematode C. elegans have also been created at levels from individual neurons and muscles, subcircuits responsible for processing specific sensory inputs, body wide processes including locomotion, and detailed nervous system/musculature models. These models usually select a subset of anatomical and physiological properties of the worm and can address a specific set of questions relevant to that level of detail. The OpenWorm project has developed c302, a framework in Python which aims to facilitate creation of models of the nervous system and musculature of C. elegans, comprising all known cells or subsets thereof, and incorporating varying levels of detail for neurons, muscles and synapses. Information on the numbers, types, and polarity of synaptic connections are included in the models from the structured information on these gathered by the project. The models generated can be used with a variety of tools for model visualisation, simulation and analysis. Dr Padraig Gleeson will present c302 and show how these nervous system models are being incorporated into detailed 3D worm body models in OpenWorm.

• Listen to audio (mp3)

10:00-10:25 Taming complexity: controlling networks

Professor Albert-László Barabási, Northeastern University and Harvard Medical School, USA

Abstract

The ultimate proof of our understanding of biological or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state, we lack a framework to control complex self-organized systems. Here Albert-László will explore the controllability of an arbitrary complex network, identifying the set of driver nodes whose time-dependent control can guide the system’s entire dynamics. Virtually all technological and biological networks must be able to control their internal processes. Given that, issues related to control deeply shape the topology and the vulnerability of real systems. Consequently, unveiling the control principles of real networks, the goal of our research, forces us to address series of fundamental questions pertaining to our understanding of complex systems. Finally, Albert-László will discuss how control principles inform our ability to predict neurons involved in specific processes in the brain, offering an avenue to experimentally falsify and test the predictions of network control. 

• Listen to audio (mp3)

10:30-10:35 Geppetto - An open platform for biology data exploration, visualization and simulation

Mr Matteo Cantarelli, OpenWorm Foundation, USA

Abstract

Geppetto (geppetto.org) is an open-source web-based platform to explore and simulate neuroscience data and models. The platform, originally designed to support the simulation of a cell-level model of C. elegans as part of the OpenWorm project, has grown into a generic framework suitable for various neuroscience applications, offering out of the box solutions for data visualisation, integration and simulation. Geppetto is today used by Open Source Brain (opensourcebrain.org), to explore and simulate computational neuroscience models described in NeuroML version 2 with a variety of simulators and by the Virtual Fly Brain (virtualflybrain.org) to explore and visualise anatomy (including neuropil, segmented neurons and gene expression pattern data) and ontology knowledge base of Drosophila melanogaster. Geppetto is also being used to build a new experimental UI for the NEURON simulation environment based on Python and Jupyter. WormSim (wormsim.org) embeds Geppetto to let users explore dynamic mechanical and electrophysiological models of C. elegans produced by the OpenWorm project. Geppetto is capable of reading and visualising experimental data in the NWB format (nwb.org) to allow experimental and computational neuroscientists to share and compare data and models using a common platform.

• Listen to audio (mp3)

11:00-11:30 Coffee

11:30-11:55 Reproducibility and rigour: testing the data driven model in C. elegans

Professor Sharon Crook, Arizona State University, USA

Abstract

Computational models provide a framework for integrating data across spatial scales and for exploring hypotheses about the mechanisms underlying neuronal and network dynamics. We have contributed to a successful system of interoperable, open source tools to address issues around creating, exchanging, and re-using models in neuroscience. In spite of this promising movement toward model sharing and reproducibility in the neuroscience community, it is extremely rare to see a specific, rigorous statement of the criteria used for evaluating models against experimental data. Another collaborative project from our group is providing a flexible infrastructure for assessing the scope and quality of models. The goal is to integrate experimental data with modeling efforts for more efficiency, better transparency, and greater impact of computational models in neuroscience research. We highlight examples of model validation from the C. elegans nervous system and also propose how hierarchical model validation, proceeding from the testing of small model components all the way to entire systems, can be used to systematically build a biologically-inspired model of an entire organism.

• Listen to audio (mp3)

12:00-12:45 Panel discussion

• Listen to audio (mp3)

13:40-14:05 Nested neuronal oscillators orchestrate motor actions at multiple time scales

Dr Manuel Zimmer, Research Institute of Molecular Pathology, Austria

Abstract

The brain organizes behaviours spanning several timescales, embedding individual movements into longer motor programs and action sequences that together serve to achieve behavioural goals. How this multi-timescale organization is implemented by neural circuits remains a fundamental unanswered question. Here, Dr Manuel Zimmer uncovers the functional relationships between three neuronal oscillators, each acting on different timescales to drive distinct behaviours. On the longest timescale, a network-wide oscillator commands the forward and reverse locomotion states. Whole nervous system imaging identified candidates for two shorter-timescale oscillators that are phase coupled to the long timescale brain oscillation and are nested within the forward locomotor program.  Using Ca2+-imaging in freely behaving worms and selective neuronal inhibition tools, the Zimmer group shows that one oscillator drives body movements for locomotion, while the other drives head-casting behaviours superimposed on to these body movements. These head casting behaviours can occur spontaneously or can be evoked by sensory stimulation. Our results establish so-termed ‘phase-nested’ oscillations as a repeated dynamical motif of the C. elegans nervous system and suggest a circuit mechanism for orchestrating motor commands spanning multiple timescales. Manuel will discuss our findings in the context of the meeting’s major objective to model the C. elegans nervous system.

• Listen to audio (mp3)

14:10-14:35 Probing the structure and function of neuronal connectomes

Dr William Schafer, MRC Laboratory of Molecular Biology, UK

Abstract

The synaptic connectome of C. elegans has been mapped completely, and efforts are ongoing to map the connectomes of other animals. However, chemical synapses represent only one of several types of signaling interactions upon which the nervous system depends. In particular, neuromodulatory interactions involving monoamines, neuropeptides, or classical neurotransmitters are widespread in all nervous systems, and these interactions largely occur extrasynaptically between neurons unconnected by wired synapses. In C. elegans it is feasible to map these extrasynaptic networks comprehensively and at a single-cell level. We have compiled a draft extrasynaptic connectome for monoamine signaling, and in collaboration with others have begun mapping the extensive neuropeptide connectome. We are exploring the topologies of the neuromodulatory connectomes and their relationships with the wired synaptic and gap junction networks, as well as their functional roles in the control of behavioural states such as arousal. We are also developing approaches for behavioural analysis that can be used to probe the structure and function of both the synaptic and extrasynaptic networks. Further analysis of the C. elegans multilayer connectome should provide insight into how wired and wireless signaling interact in the brains of more complex animals.

• Listen to audio (mp3)

14:40-15:05 OpenWorm: open science for C. elegans modelling

Dr Stephen Larson, The OpenWorm Foundation, USA

Abstract

The past 30 years of the connectome of C. elegans has both shown its necessity while also demonstrating its insufficiency for a complete explanation of how it functions. Formalization methods from computational neuroscience, neuroinformatics, and computational biophysics have demonstrated great potential to integrate what has been measured and understood about the structure and function of nervous systems in general and enable powerful predictions of its function. At the OpenWorm Foundation, the group has built an open science organization to perform this formalization and unlock these predictions, while placing all of the digital resources that are produced into the public domain immediately. Their current results represent a strong step towards building a working simulation of the C. elegans nervous system in the context of a simulated embodied digital worm, drawing from a multitude of data sources, observations, and existing simulations. In this talk, Dr Stephen Larson will review the progress that the research group has made in this endeavour and paint the picture for where the project is headed next.

• Listen to audio (mp3)

15:10-15:40 Tea

15:40-16:05 Clues to basis of exploratory behaviour of C. elegans snout from head somatotropy

Dr John White FRS, University of Wisconsin-Madison, USA

Abstract

Wave propagation during locomotory movements of C. elegans is constrained to a single dorso/ventral plane. In contrast, the tip of the head (snout) can make rapid exploratory movements in all directions relative to the body axis. These extra degrees of freedom are probably important for animals to seek and identify desirable passages in the interstices of the three dimensional matrix of soil particles, their usual habitat. The differences in degrees of freedom of movement between snout and body are reflected in the innervation of the musculature. Along the length of the body the two quadrants of dorsal muscle receive common innervation as do the two quadrants of ventral muscle. In contrast, muscles in the snout have an octagonal arrangement of innervation. It is likely that the foraging behaviour of the snout is mediated by octant-specific motor and sensory neurons, together with their associated interneurons. The well-defined structure and neural circuitry of the snout together with behavioural observations made with or without experimental interventions should facilitate the implementation of models of snout foraging which could lead to an understanding of the neural basis of this relatively complex behaviour, a behaviour that has similarities to the foraging behaviour of some vertebrates.

• Listen to audio (mp3)

16:10-17:00 Panel discussion

• Listen to audio (mp3)