Tools and techniques to bridge the gap between models and closed-loop neuroscience experiments

         

CNS 2020 half-day tutorial	July 18th
Berlin Time	16:00 - 19:00h
New York Time	10:00 - 13:00h

CNS*2020 webpage and OCNS webpage.

Join the session

Thanks to all attendees for joining us, we hope you found it useful and you have learned.

Instructions to the attendees

Please do not forget to register for the conference. Registration is free at https://www.cnsorg.org/cns-2020

Please, use the chat to ask questions

Please, mute your microphone and turn off your camera during the talks and only turn them on to ask your question when indicated by the speaker who will select the order of the questions

Organizers

Name	Email
Pablo Varona	pablo.varona@uam.es
Manuel Reyes Sanchez	manuel.reyes@uam.es
Rodrigo Amaducci	rodrigo.amaducci@uam.es

Grupo de Neurocomputación Biológica, Escuela Politécnica Superior, Universidad Autónoma de Madrid.

Tutorial Description

Models in computational neuroscience are typically used to reproduce and explain experimental findings, to draw new hypotheses from their predictive power, to undertake the low observability of the brain, etc. However, computational models can also be employed to interact directly with living nervous systems, which is a powerful way of unveiling key neural dynamics by combining experimental and theoretical efforts. However, protocols that simultaneously combine recordings from living neurons and input/outputs from computational models are not easy to design or implement. In this tutorial, we will describe several tools and techniques to build such kind of open and closed-loop interactions: from basic dynamic-clamp approaches to build hybrid circuits to more complex configurations that can include several interacting living and artificial elements. We will emphasize the need of open-source real-time software technology for some of these interactions.

In particular, we will focus on two software packages that can implement closed-loop interactions between living neurons and computational neuroscience models. The first one, RTHybrid, is a solution to build hybrid circuits between living neurons and models. This program, developed by the organizers, includes a library of neuron and synapse models and different algorithms for the automatic calibration and adaptation of hybrid configurations. The second software tool, RTXI, allows to program specific modules to implement a wide variety of closed-loop configurations and includes many handy modularization and visualization tools. Both programs can be used in very wide contexts of hybrid experimental design and deal with real-time constraints. During the tutorial, we will show how to install and use these programs in standard computer platforms, and we will provide attendees the possibility of building and testing their first designs.

Software tools

RTHybrid: https://github.com/GNB-UAM/RTHybrid

RTXI: http://rtxi.org/

Important demo instructions

For the practical part of the tutorial, please download beforehand the latest RTXI version from http://rtxi.org/install/. It is not necessary to install it in your computer for this tutorial, you can just create a live-USB and boot from the live image following the instructions on the web or install it on a virtual machine.

Also, please download RTHybrid modules for RTXI from https://github.com/GNB-UAM/rthybrid-for-rtxi and install them following the instructions.

Tutorial content and schedule

Time	Title	Speaker
16:00-16:30h Berlin Time 10:00-10:30h New York Time	Introduction to Closed-loop Neuroscience	Pablo Varona
16:30-17:00h Berlin Time 10:30-11:00h New York Time	Hybrid Circuits: interacting living neurons, model neurons and robots	Rodrigo Amaducci
17:00-17:30h Berlin Time 11:00-11:30h New York Time	Automatic adaptation and mappings of hybrid circuits	Manuel Reyes-Sánchez
17:30-17:45h Berlin Time 11:30-11:45h New York Time	Break
17:45-19:00h Berlin Time 11:45-13:00h New York Time	Software installation, software demos, interactive discussion	Rodrigo Amaducci Manuel Reyes-Sánchez

Introduction to Closed-loop Neuroscience

Presentation slides • Video

Hybrid Circuits: interacting living neurons, model neurons and robots

Presentation slides • Video

Automatic adaptation and mappings of hybrid circuits

Presentation slides • Video

Demo

Part 1 - RTXI

Part 2 - RTHybrid

References and background reading

M. Reyes-Sanchez, R. Amaducci, I. Elices, F.B. Rodriguez, P. Varona. 2020. Automatic adaptation of model neurons and connections to build hybrid circuits with living networks. Neuroinformatics 18: 377–393.

R. Amaducci, M. Reyes-Sanchez, I. Elices, F.B. Rodriguez, P. Varona. 2019. RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience. Frontiers in Neuroinformatics 13:11.

Patel, Y. A., George, A., Dorval, A. D., White, J. A., Christini, D. J., & Butera, R. J. 2017. Hard real- time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI). PLoS Computational Biology, 13(5), e1005430.

P. Varona, D. Arroyo, F.B. Rodriguez, T. Nowotny. Online event detection requirements in closed-loop neuroscience. In Closed-Loop Neuroscience. El Hady A. (Ed), Academic Press. 2016. ISBN 9780128024522.

P. Chamorro, C. Muñiz, R. Levi, D. Arroyo. F.B. Rodriguez, P. Varona. 2012. Generalization of the dynamic clamp concept in neurophysiology and behavior. PLoS ONE 7(7): e40887.

Zrenner, C., Belardinelli, P., Müller-Dahlhaus, F., & Ziemann, U. 2016. Closed-loop neuroscience and non-invasive brain stimulation: a tale of two loops. Frontiers in Cellular Neuroscience, 10, 92.

Potter, S. M., El Hady, A., & Fetz, E. E. 2014. Closed-loop neuroscience and neuroengineering. Frontiers in Neural Circuits, 8, 115.

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