Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period

Norman, Sharon; Butera, Robert J.; Canavier, Carmen C.

doi:10.1152/jn.00193.2016

Cited by 8 publications

(6 citation statements)

References 37 publications

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“…Dozens of publications ( S3 File ) have used RTXI. Examples include investigation of the contribution of specific ion channels or synaptic receptors to spiking and bursting activity in a variety of neuronal cell types, oscillatory behavior of pacemaker neurons [ 12 ], the effect of network topology and intrinsic neuronal properties on population activity in a hybrid network [ 13 ], and effects of transcranial alternating current stimulation (tACS) on cortical activity [ 11 , 14 ]. Each example utilized RTXI to create a custom, hard RT closed-loop protocol with the goal of dynamically probing the target system.…”

Section: Introductionmentioning

confidence: 99%

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

et al. 2017

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The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols.

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Section: Introductionmentioning

confidence: 99%

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

et al. 2017

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“…Pioneering works in building such interactions go back almost three decades ago (Yarom, 1991) with many successfull implementation since then, e.g. see (Szücs et al, 2000;Pinto et al, 2000;Varona et al, 2001;Le Masson et al, 2002;Nowotny et al, 2003;Olypher et al, 2006;Arsiero et al, 2007;Grashow et al, 2010;Brochini et al, 2011;Wang et al, 2012;Hooper et al, 2015;Norman et al, 2016;Broccard et al, 2017;Mishchenko et al, 2018). Hybrid circuits are typically implemented through a dynamic clamp protocol that injects current computed by a model from an instantaneous voltage recording (Robinson and Kawai, 1993;Sharp et al, 1993;Prinz et al, 2004;Destexhe and Bal, 2009;Nowotny and Varona, 2014).…”

Section: Introductionmentioning

confidence: 99%

Automatic Adaptation of Model Neurons and Connections to Build Hybrid Circuits with Living Networks

et al. 2020

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Hybrid circuits built by creating mono-or bi-directional interactions among living cells and model neurons and synapses are an effective way to study neuron, synaptic and neural network dynamics. However, hybrid circuit technology has been largely underused in the context of neuroscience studies mainly because of the inherent difficulty in implementing and tuning this type of interactions. In this paper, we present a set of algorithms for the automatic adaptation of model neurons and connections in the creation of hybrid circuits with living neural networks. The algorithms perform model time and amplitude scaling, drift compensation, goal-driven synaptic and model tuning/calibration and also automatic parameter mapping. These algorithms have been implemented in RTHybrid, an open-source library that works with hard real-time constraints. We provide validation examples by building hybrid circuits in a central pattern generator. The results of the validation experiments show that the proposed dynamic adaptation facilitates building hybrid circuits and closedloop communication among living and artificial model neurons and connections. Furthermore contributes to characterize system dynamics, achieve control, automate experimental protocols and extend the lifespan of the preparations.

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“…A highly relevant example of closed-loop interactions can be found in hybrid circuits, which are networks built by connecting model neurons and synapses to living cells. They are a powerful tool to explore and characterize neural system dynamics, as well as a means to assess the role of specific circuit components (e.g., see Yarom, 1991 ; Pinto et al, 2000 ; Szücs et al, 2000 ; Varona et al, 2001 ; Le Masson et al, 2002 ; Nowotny et al, 2003 ; Oprisan et al, 2004 ; Arsiero et al, 2007 ; Chamorro et al, 2009 ; Grashow et al, 2010 ; Brochini et al, 2011 ; Kispersky et al, 2011 ; Wang et al, 2012 ; Thounaojam et al, 2014 ; Hooper et al, 2015 ; Norman et al, 2016 ; Broccard et al, 2017 ). The most common paradigm to build hybrid circuits consists in using dynamic-clamp to read the membrane potential of a cell and, after computing a model using this voltage, inject the resulting current into the same or into a different cell (Robinson and Kawai, 1993 ; Sharp et al, 1993 ; Prinz et al, 2004 ; Destexhe and Bal, 2009 ; Nowotny and Varona, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience

Amaducci

Reyes-Sanchez

Elices

et al. 2019

Front. Neuroinform.

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Closed-loop technologies provide novel ways of online observation, control and bidirectional interaction with the nervous system, which help to study complex non-linear and partially observable neural dynamics. These protocols are often difficult to implement due to the temporal precision required when interacting with biological components, which in many cases can only be achieved using real-time technology. In this paper we introduce RTHybrid (www.github.com/GNB-UAM/RTHybrid), a free and open-source software that includes a neuron and synapse model library to build hybrid circuits with living neurons in a wide variety of experimental contexts. In an effort to encourage the standardization of real-time software technology in neuroscience research, we compared different open-source real-time operating system patches, RTAI, Xenomai 3 and Preempt-RT, according to their performance and usability. RTHybrid has been developed to run over Linux operating systems supporting both Xenomai 3 and Preempt-RT real-time patches, and thus allowing an easy implementation in any laboratory. We report a set of validation tests and latency benchmarks for the construction of hybrid circuits using this library. With this work we want to promote the dissemination of standardized, user-friendly and open-source software tools developed for open- and closed-loop experimental neuroscience.

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Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period

Cited by 8 publications

References 37 publications

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

Automatic Adaptation of Model Neurons and Connections to Build Hybrid Circuits with Living Networks

RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience

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