Literature DB >> 18263893

The dynamical response properties of neocortical neurons to temporally modulated noisy inputs in vitro.

Harold Köndgen1, Caroline Geisler, Stefano Fusi, Xiao-Jing Wang, Hans-Rudolf Lüscher, Michele Giugliano.   

Abstract

Cortical neurons are often classified by current-frequency relationship. Such a static description is inadequate to interpret neuronal responses to time-varying stimuli. Theoretical studies suggested that single-cell dynamical response properties are necessary to interpret ensemble responses to fast input transients. Further, it was shown that input-noise linearizes and boosts the response bandwidth, and that the interplay between the barrage of noisy synaptic currents and the spike-initiation mechanisms determine the dynamical properties of the firing rate. To test these model predictions, we estimated the linear response properties of layer 5 pyramidal cells by injecting a superposition of a small-amplitude sinusoidal wave and a background noise. We characterized the evoked firing probability across many stimulation trials and a range of oscillation frequencies (1-1000 Hz), quantifying response amplitude and phase-shift while changing noise statistics. We found that neurons track unexpectedly fast transients, as their response amplitude has no attenuation up to 200 Hz. This cut-off frequency is higher than the limits set by passive membrane properties (approximately 50 Hz) and average firing rate (approximately 20 Hz) and is not affected by the rate of change of the input. Finally, above 200 Hz, the response amplitude decays as a power-law with an exponent that is independent of voltage fluctuations induced by the background noise.

Mesh:

Year:  2008        PMID: 18263893      PMCID: PMC3140196          DOI: 10.1093/cercor/bhm235

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  78 in total

1.  Frequency response functions and information capacities of paired spider mechanoreceptor neurons.

Authors:  A S French; U Höger; S Sekizawa; P H Torkkeli
Journal:  Biol Cybern       Date:  2001-10       Impact factor: 2.086

2.  Cellular and network mechanisms of slow oscillatory activity (<1 Hz) and wave propagations in a cortical network model.

Authors:  Albert Compte; Maria V Sanchez-Vives; David A McCormick; Xiao-Jing Wang
Journal:  J Neurophysiol       Date:  2003-01-15       Impact factor: 2.714

3.  From subthreshold to firing-rate resonance.

Authors:  Magnus J E Richardson; Nicolas Brunel; Vincent Hakim
Journal:  J Neurophysiol       Date:  2002-12-27       Impact factor: 2.714

4.  What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance.

Authors:  Nicolas Brunel; Xiao-Jing Wang
Journal:  J Neurophysiol       Date:  2003-02-26       Impact factor: 2.714

5.  Spike frequency adaptation and neocortical rhythms.

Authors:  Galit Fuhrmann; Henry Markram; Misha Tsodyks
Journal:  J Neurophysiol       Date:  2002-08       Impact factor: 2.714

6.  Gain modulation from background synaptic input.

Authors:  Frances S Chance; L F Abbott; Alex D Reyes
Journal:  Neuron       Date:  2002-08-15       Impact factor: 17.173

7.  Firing-rate resonance in a generalized integrate-and-fire neuron with subthreshold resonance.

Authors:  Nicolas Brunel; Vincent Hakim; Magnus J E Richardson
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2003-05-19

8.  States of high conductance in a large-scale model of the visual cortex.

Authors:  Michael Shelley; David McLaughlin; Robert Shapley; Jacob Wielaard
Journal:  J Comput Neurosci       Date:  2002 Sep-Oct       Impact factor: 1.621

9.  Neocortical very fast oscillations (ripples, 80-200 Hz) during seizures: intracellular correlates.

Authors:  François Grenier; Igor Timofeev; Mircea Steriade
Journal:  J Neurophysiol       Date:  2003-02       Impact factor: 2.714

10.  Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons.

Authors:  A Destexhe; M Rudolph; J M Fellous; T J Sejnowski
Journal:  Neuroscience       Date:  2001       Impact factor: 3.590

View more
  43 in total

Review 1.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

2.  Conditional bursting enhances resonant firing in neocortical layer 2-3 pyramidal neurons.

Authors:  Matthew H Higgs; William J Spain
Journal:  J Neurosci       Date:  2009-02-04       Impact factor: 6.167

3.  Temporal whitening by power-law adaptation in neocortical neurons.

Authors:  Christian Pozzorini; Richard Naud; Skander Mensi; Wulfram Gerstner
Journal:  Nat Neurosci       Date:  2013-06-09       Impact factor: 24.884

4.  Action potential initiation in a multi-compartmental model with cooperatively gating Na channels in the axon initial segment.

Authors:  Pinar Öz; Min Huang; Fred Wolf
Journal:  J Comput Neurosci       Date:  2015-05-23       Impact factor: 1.621

5.  Effects of spike-triggered negative feedback on receptive-field properties.

Authors:  Eugenio Urdapilleta; Inés Samengo
Journal:  J Comput Neurosci       Date:  2015-01-21       Impact factor: 1.621

6.  Dynamic Gain Analysis Reveals Encoding Deficiencies in Cortical Neurons That Recover from Hypoxia-Induced Spreading Depolarizations.

Authors:  Omer Revah; Ohad Stoler; Andreas Neef; Fred Wolf; Ilya A Fleidervish; Michael J Gutnick
Journal:  J Neurosci       Date:  2019-08-09       Impact factor: 6.167

7.  Correlation Transfer by Layer 5 Cortical Neurons Under Recreated Synaptic Inputs In Vitro.

Authors:  Daniele Linaro; Gabriel K Ocker; Brent Doiron; Michele Giugliano
Journal:  J Neurosci       Date:  2019-07-25       Impact factor: 6.167

8.  Spike phase locking in CA1 pyramidal neurons depends on background conductance and firing rate.

Authors:  Tilman Broicher; Paola Malerba; Alan D Dorval; Alla Borisyuk; Fernando R Fernandez; John A White
Journal:  J Neurosci       Date:  2012-10-10       Impact factor: 6.167

Review 9.  Cortical Specializations Underlying Fast Computations.

Authors:  Maxim Volgushev
Journal:  Neuroscientist       Date:  2015-02-17       Impact factor: 7.519

10.  Precisely timed signal transmission in neocortical networks with reliable intermediate-range projections.

Authors:  Martin Paul Nawrot; Philipp Schnepel; Ad Aertsen; Clemens Boucsein
Journal:  Front Neural Circuits       Date:  2009-02-10       Impact factor: 3.492

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.