Thalamocortical Relay cell under current clamp in high-conductance state (Zeldenrust et al 2018)

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Accession:232876
Mammalian thalamocortical relay (TCR) neurons switch their firing activity between a tonic spiking and a bursting regime. In a combined experimental and computational study, we investigated the features in the input signal that single spikes and bursts in the output spike train represent and how this code is influenced by the membrane voltage state of the neuron. Identical frozen Gaussian noise current traces were injected into TCR neurons in rat brain slices to adjust, fine-tune and validate a three-compartment TCR model cell (Destexhe et al. 1998, accession number 279). Three currents were added: an h-current (Destexhe et al. 1993,1996, accession number 3343), a high-threshold calcium current and a calcium- activated potassium current (Huguenard & McCormick 1994, accession number 3808). The information content carried by the various types of events in the signal as well as by the whole signal was calculated. Bursts phase-lock to and transfer information at lower frequencies than single spikes. On depolarization the neuron transits smoothly from the predominantly bursting regime to a spiking regime, in which it is more sensitive to high-frequency fluctuations. Finally, the model was used to in the more realistic “high-conductance state” (Destexhe et al. 2001, accession number 8115), while being stimulated with a Poisson input (Brette et al. 2007, Vogels & Abbott 2005, accession number 83319), where fluctuations are caused by (synaptic) conductance changes instead of current injection. Under “standard” conditions bursts are difficult to initiate, given the high degree of inactivation of the T-type calcium current. Strong and/or precisely timed inhibitory currents were able to remove this inactivation.
References:
1 . Destexhe A, Bal T, McCormick DA, Sejnowski TJ (1996) Ionic mechanisms underlying synchronized oscillations and propagating waves in a model of ferret thalamic slices. J Neurophysiol 76:2049-70 [PubMed]
2 . Huguenard JP, Mccormick DA (1994) Electrophysiology of the Neuron: An Interactive Tutorial
3 . Destexhe A, Rudolph M, Fellous JM, Sejnowski TJ (2001) Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience 107:13-24 [PubMed]
4 . Brette R, Rudolph M, Carnevale T, Hines M, Beeman D, Bower JM, Diesmann M, Morrison A, et al. (2007) Simulation of networks of spiking neurons: A review of tools and strategies. J Comp Neurosci 23:349-98 [PubMed]
5 . Vogels TP, Abbott LF (2005) Signal propagation and logic gating in networks of integrate-and-fire neurons. J Neurosci 25(46):10786-95 [PubMed]
6 . Destexhe A, Neubig M, Ulrich D, Huguenard J (1998) Dendritic low-threshold calcium currents in thalamic relay cells. J Neurosci 18:3574-88 [PubMed]
7 . Destexhe A, Babloyantz A, Sejnowski TJ (1993) Ionic mechanisms for intrinsic slow oscillations in thalamic relay neurons. Biophys J 65:1538-52 [PubMed]
8 . Zeldenrust F, Chameau P, Wadman WJ (2018) Spike and Burst Coding in Thalamocortical Relay Cells PLoS Comput Biol, in press 14(2):e1005960
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Thalamus;
Cell Type(s): Thalamus geniculate nucleus/lateral principal neuron;
Channel(s): I L high threshold; I K,Ca; I h; I T low threshold;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Bursting; Information transfer; Rebound firing; Sensory coding;
Implementer(s): Zeldenrust, Fleur [fleurzeldenrust at gmail.com];
Search NeuronDB for information about:  Thalamus geniculate nucleus/lateral principal neuron; I L high threshold; I T low threshold; I h; I K,Ca;
/
TCR
current_clamp
high_conductance_state
influence_ih_iT
README.txt
                            
Model files from the paper:

F. Zeldenrust, P. Chameau, W. J. Wadman, ‘Spike and Burst Coding in
Thalamocortical Relay Cells’, PLoS Computational Biology, 2018

Questions on how to use this model should be directed to
f.zeldenrust at neurophysiology.nl

Synopsis:
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Mammalian thalamocortical relay (TCR) neurons switch their firing
activity between a tonic spiking and a bursting regime. In a combined
experimental and computational study, we investigated the features in
the input signal that single spikes and bursts in the output spike
train represent and how this code is influenced by the membrane
voltage state of the neuron. Identical frozen Gaussian noise current
traces were injected into TCR neurons in rat brain slices to adjust,
fine-tune and validate a three-compartment TCR model cell (Destexhe et
al. 1998, accession number 279). Three currents were added: an
h-current (Destexhe et al. 1993,1996, accession number 3343), a
high-threshold calcium current and a calcium- activated potassium
current (Huguenard & McCormick 1994, accession number 3808). The
information content carried by the various types of events in the
signal as well as by the whole signal was calculated. Bursts
phase-lock to and transfer information at lower frequencies than
single spikes. On depolarization the neuron transits smoothly from the
predominantly bursting regime to a spiking regime, in which it is more
sensitive to high-frequency fluctuations. Finally, the model was used
to in the more realistic “high-conductance state” (Destexhe et
al. 2001, accession number 8115), while being stimulated with a
Poisson input (Brette et al. 2007, Vogels & Abbott 2005, accession
number 83319), where fluctuations are caused by (synaptic) conductance
changes instead of current injection. Under “standard” conditions
bursts are difficult to initiate, given the high degree of
inactivation of the T-type calcium current. Strong and/or precisely
timed inhibitory currents were able to remove this inactivation.

Use:
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There are three folders. For each folder: extract the archive, run
nrnivmodl in the channels directory (linux/unix) or mknrndll (mswin or
mac os x) (see
http://senselab.med.yale.edu/ModelDB/NEURON_DwnldGuide.html for more
help) to compile the channels, and run the .hoc file.

1) The ‘current clamp’ folder, simulates the experiments. It will
result in the voltage traces (and resulting spike trains) used in
figures 9-11. The used ‘holding currents’ are set as ‘El1.stim.amp’
(i.e. the amplitude of the current injected via electrode 1). The data
can be saved with procedures ‘fileopen()’ and ‘slaop()’.

2) In the ‘influence_ih_iT’ folder, the current-clamp experiments are
repeated, but now the h-current is reduced by a factor (see figure 12
of the paper), that can be set at the top of the .hoc-file (as well as
the ‘holding potential’ or ‘membrane state’ Vhold). This will then
automatically adjust the mean input current (‘El1.stim.amp’), the
h-current conductivity and change the relevant filenames for saving
(procedures ‘fileopen()’ and ‘slaop()’).

3) In the ‘high_conductance_state’, the experiment as shown in figure
13 of the paper is simulated. A ‘high-conductance-state ion channel’
(fl) is used to either simulate a ‘classic’, no or an inhibitory
high-conductance-state. Moreover, two (exponential) synapses that
receive (the same) Poisson spike trains, ‘Esynapse’ and ‘Esynapse_i’
are added to the dendrite. Again, ‘fileopen()’ and ‘slaop()’ can be
used to save the results.

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