Literature DB >> 10634897

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

G D Smith1, C L Cox, S M Sherman, J Rinzel.   

Abstract

We performed intracellular recordings of relay neurons from the lateral geniculate nucleus of a cat thalamic slice preparation. We measured responses during both tonic and burst firing modes to sinusoidal current injection and performed Fourier analysis on these responses. For comparison, we constructed a minimal "integrate-and-fire-or-burst" (IFB) neuron model that reproduces salient features of the relay cell responses. The IFB model is constrained to quantitatively fit our Fourier analysis of experimental relay neuron responses, including: the temporal tuning of the response in both tonic and burst modes, including a finding of low-pass and sometimes broadband behavior of tonic firing and band-pass characteristics during bursting, and the generally greater linearity of tonic compared with burst responses at low frequencies. In tonic mode, both experimental and theoretical responses display a frequency-dependent transition from massively superharmonic spiking to phase-locked superharmonic spiking near 3 Hz, followed by phase-locked subharmonic spiking at higher frequencies. Subharmonic and superharmonic burst responses also were observed experimentally. Characterizing the response properties of the "tuned" IFB model leads to insights regarding the observed stimulus dependence of burst versus tonic response mode in relay neurons. Furthermore the simplicity of the IFB model makes it a candidate for large scale network simulations of thalamic functioning.

Mesh:

Year:  2000        PMID: 10634897     DOI: 10.1152/jn.2000.83.1.588

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


  52 in total

Review 1.  The role of the thalamus in the flow of information to the cortex.

Authors:  S Murray Sherman; R W Guillery
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2002-12-29       Impact factor: 6.237

2.  Bursting neurons signal input slope.

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Journal:  J Neurosci       Date:  2002-10-15       Impact factor: 6.167

3.  Type I burst excitability.

Authors:  Carlo R Laing; Brent Doiron; André Longtin; Liza Noonan; Ray W Turner; Leonard Maler
Journal:  J Comput Neurosci       Date:  2003 May-Jun       Impact factor: 1.621

4.  Oscillations in large-scale cortical networks: map-based model.

Authors:  N F Rulkov; I Timofeev; M Bazhenov
Journal:  J Comput Neurosci       Date:  2004 Sep-Oct       Impact factor: 1.621

5.  Disrupted thalamic T-type Ca2+ channel expression and function during ethanol exposure and withdrawal.

Authors:  J D Graef; T W Huitt; B K Nordskog; J H Hammarback; D W Godwin
Journal:  J Neurophysiol       Date:  2010-12-08       Impact factor: 2.714

6.  Open-loop organization of thalamic reticular nucleus and dorsal thalamus: a computational model.

Authors:  Adam M Willis; Bernard J Slater; Ekaterina D Gribkova; Daniel A Llano
Journal:  J Neurophysiol       Date:  2015-08-19       Impact factor: 2.714

7.  Bursting as an effective relay mode in a minimal thalamic model.

Authors:  Baktash Babadi
Journal:  J Comput Neurosci       Date:  2005 Mar-Apr       Impact factor: 1.621

8.  Feedback inhibition and throughput properties of an integrate-and-fire-or-burst network model of retinogeniculate transmission.

Authors:  Marco A Huertas; Jeffrey R Groff; Gregory D Smith
Journal:  J Comput Neurosci       Date:  2005-10       Impact factor: 1.621

9.  A multivariate population density model of the dLGN/PGN relay.

Authors:  Marco A Huertas; Gregory D Smith
Journal:  J Comput Neurosci       Date:  2006-06-12       Impact factor: 1.621

10.  Response variability of marmoset parvocellular neurons.

Authors:  J D Victor; E M Blessing; J D Forte; P Buzás; P R Martin
Journal:  J Physiol       Date:  2006-11-23       Impact factor: 5.182

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