Literature DB >> 29357476

Robust and tunable bursting requires slow positive feedback.

Alessio Franci1, Guillaume Drion2, Rodolphe Sepulchre3.   

Abstract

We highlight that the robustness and tunability of a bursting model critically rely on currents that provide slow positive feedback to the membrane potential. Such currents have the ability to make the total conductance of the circuit negative in a timescale that is termed "slow" because it is intermediate between the fast timescale of the spike upstroke and the ultraslow timescale of even slower adaptation currents. We discuss how such currents can be assessed either in voltage-clamp experiments or in computational models. We show that, while frequent in the literature, mathematical and computational models of bursting that lack the slow negative conductance are fragile and rigid. Our results suggest that modeling the slow negative conductance of cellular models is important when studying the neuromodulation of rhythmic circuits at any broader scale. NEW & NOTEWORTHY Nervous system functions rely on the modulation of neuronal activity between different rhythmic patterns. The mechanisms of this modulation are still poorly understood. Using computational modeling, we show the critical role of currents that provide slow negative conductance, distinct from the fast negative conductance necessary for spike generation. The significance of the slow negative conductance for neuromodulation is often overlooked, leading to computational models that are rigid and fragile.

Entities:  

Keywords:  bursting; feedback; modeling; neuromodulation

Mesh:

Year:  2017        PMID: 29357476      PMCID: PMC5899319          DOI: 10.1152/jn.00804.2017

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  41 in total

1.  Fourier analysis of sinusoidally driven thalamocortical relay neurons and a minimal integrate-and-fire-or-burst model.

Authors:  G D Smith; C L Cox; S M Sherman; J Rinzel
Journal:  J Neurophysiol       Date:  2000-01       Impact factor: 2.714

2.  Activity patterns in a model for the subthalamopallidal network of the basal ganglia.

Authors:  D Terman; J E Rubin; A C Yew; C J Wilson
Journal:  J Neurosci       Date:  2002-04-01       Impact factor: 6.167

3.  Propagating neuronal discharges in neocortical slices: computational and experimental study.

Authors:  D Golomb; Y Amitai
Journal:  J Neurophysiol       Date:  1997-09       Impact factor: 2.714

4.  Phase response properties of half-center oscillators.

Authors:  Calvin Zhang; Timothy J Lewis
Journal:  J Comput Neurosci       Date:  2013-02-28       Impact factor: 1.621

Review 5.  Neuromodulation of circuits with variable parameters: single neurons and small circuits reveal principles of state-dependent and robust neuromodulation.

Authors:  Eve Marder; Timothy O'Leary; Sonal Shruti
Journal:  Annu Rev Neurosci       Date:  2014       Impact factor: 12.449

6.  Dissection of a model for neuronal parabolic bursting.

Authors:  J Rinzel; Y S Lee
Journal:  J Math Biol       Date:  1987       Impact factor: 2.259

Review 7.  Neuromodulation of neuronal circuits: back to the future.

Authors:  Eve Marder
Journal:  Neuron       Date:  2012-10-04       Impact factor: 17.173

8.  Dopamine reduces slow outward current and calcium influx in burst-firing neuron R15 of Aplysia.

Authors:  D V Lewis; G B Evans; W A Wilson
Journal:  J Neurosci       Date:  1984-12       Impact factor: 6.167

9.  Computational model predicts a role for ERG current in repolarizing plateau potentials in dopamine neurons: implications for modulation of neuronal activity.

Authors:  Carmen C Canavier; Sorinel A Oprisan; Joseph C Callaway; Huifang Ji; Paul D Shepard
Journal:  J Neurophysiol       Date:  2007-08-15       Impact factor: 2.714

10.  Dynamic Input Conductances Shape Neuronal Spiking

Authors:  Guillaume Drion; Alessio Franci; Julie Dethier; Rodolphe Sepulchre
Journal:  eNeuro       Date:  2015-03-25
View more
  5 in total

1.  M current regulates firing mode and spike reliability in a collision-detecting neuron.

Authors:  Richard B Dewell; Fabrizio Gabbiani
Journal:  J Neurophysiol       Date:  2018-07-25       Impact factor: 2.714

Review 2.  Co-opting evo-devo concepts for new insights into mechanisms of behavioural diversity.

Authors:  Kim L Hoke; Elizabeth Adkins-Regan; Andrew H Bass; Amy R McCune; Mariana F Wolfner
Journal:  J Exp Biol       Date:  2019-04-15       Impact factor: 3.312

3.  Switchable slow cellular conductances determine robustness and tunability of network states.

Authors:  Guillaume Drion; Julie Dethier; Alessio Franci; Rodolphe Sepulchre
Journal:  PLoS Comput Biol       Date:  2018-04-23       Impact factor: 4.475

4.  A dynamic clamp protocol to artificially modify cell capacitance.

Authors:  Paul Pfeiffer; Federico José Barreda Tomás; Jiameng Wu; Jan-Hendrik Schleimer; Imre Vida; Susanne Schreiber
Journal:  Elife       Date:  2022-04-01       Impact factor: 8.713

5.  Circuit Stability to Perturbations Reveals Hidden Variability in the Balance of Intrinsic and Synaptic Conductances.

Authors:  Sebastian Onasch; Julijana Gjorgjieva
Journal:  J Neurosci       Date:  2020-03-16       Impact factor: 6.167

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.