Abstract
Connectivity and biophysical processes determine the functionality of neuronal networks. We, therefore, developed a real-time framework, called Neural Interactome1,2, to simultaneously visualize and interact with the structure and dynamics of such networks. Neural Interactome is a cross-platform framework, which combines graph visualization with the simulation of neural dynamics, or experimentally recorded multi neural time series, to allow application of stimuli to neurons to examine network responses. In addition, Neural Interactome supports structural changes, such as disconnection of neurons from the network (ablation feature). Neural dynamics can be explored on a single neuron level (using a zoom feature), back in time (using a review feature), and recorded (using presets feature). The development of the Neural Interactome was guided by generic concepts to be applicable to neuronal networks with different neural connectivity and dynamics. We implement the framework using a model of the nervous system of Caenorhabditis elegans (C. elegans) nematode, a model organism with resolved connectome and neural dynamics. We show that Neural Interactome assists in studying neural response patterns associated with locomotion and other stimuli. In particular, we demonstrate how stimulation and ablation help in identifying neurons that shape particular dynamics. We examine scenarios that were experimentally studied, such as touch response circuit, and explore new scenarios that did not undergo elaborate experimental studies.
Highlights
Modeling neuronal systems involves incorporating two modeling layers
We proceed to demonstrate how application of Neural Interactome to C. elegans nervous system can assist in the study of neural dynamics
We target two sub circuits (i) a circuit associated with a touch response, which stimulation is known to be associated with forward and backward locomotion (ii) explore neural dynamic patterns induced by the excitation of sub group of sensory neurons, which recently were discovered to be associated with nictation behavior
Summary
Modeling neuronal systems involves incorporating two modeling layers. The first fundamental layer is of neuronal connectivity (connectome). The layer on top of it is of biophysical processes of neural responses and interactions. Connectomes of several organisms and systems, such as the nematode Caenorhabditis elegans (C. elegans), the Drosophila medulla, the mouse retina, mouse primary visual cortex, and others have been fully or partially mapped on various scales: from macro to single neuron level (White et al, 1986; Open Connectome Project, 2010; Van Den Heuvel and Pol, 2010; Bock et al, 2011; Briggman et al, 2011; Haspel and O’Donovan, 2011; Varshney et al, 2011). Decades of research in describing and modeling biophysical processes have provided both experimental and computational foundations for modeling single neuron dynamics as well
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
