| Title |
Thalamic reticular cells firing modes and its dependency on the frequency and amplitude ranges of the current stimulus
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, October 2014
|
| DOI | 10.1007/s11517-014-1209-z |
| Pubmed ID | |
| Authors |
Oscar Hernandez, Lilibeth Hernandez, David Vera, Alcides Santander, Eduardo Zurek |
| Abstract |
The neurons of the Thalamic Reticular Nucleus (TRNn) respond to inputs in two activity modes called burst and tonic firing and both can be observed in different physiological states. The functional states of the thalamus depend in part on the properties of synaptic transmission between the TRNn and the thalamocortical and corticothalamic neurons. A dendrite can receive inhibitory and excitatory postsynaptic potentials. The novelties presented in this paper can be summarized as follows: First, it shows, through a computational simulation, that the burst and tonic firings observed in the TRNn soma could be explained as a product of random synaptic inputs on the distal dendrites, the tonic firings are generated by random excitatory stimuli, and the burst firings are generated by two different types of stimuli: inhibitory random stimuli, and a combination of inhibitory (from TRNn) and excitatory (from corticothalamic and thalamocortical neurons) random stimuli; second, according to in vivo recordings, we have found that the burst observed in the TRNn soma has graduate properties that are proportional to the stimuli frequency; and third, a novel method for showing in a quantitative manner the accelerando-decelerando pattern is proposed. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 10% |
| Switzerland | 1 | 10% |
| Unknown | 8 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 40% |
| Professor | 2 | 20% |
| Student > Master | 2 | 20% |
| Professor > Associate Professor | 1 | 10% |
| Student > Postgraduate | 1 | 10% |
| Other | 0 | 0% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 3 | 30% |
| Neuroscience | 3 | 30% |
| Psychology | 1 | 10% |
| Economics, Econometrics and Finance | 1 | 10% |
| Materials Science | 1 | 10% |
| Other | 1 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 October 2014.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from Medical & Biological Engineering & Computing
#1,677
of 2,053 outputs
Outputs of similar age
#163,496
of 271,979 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#5
of 9 outputs
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