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Models of passive and active dendrite motoneuron pools and their differences in muscle force control

Overview of attention for article published in Journal of Computational Neuroscience, May 2012
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  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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3 tweeters

Citations

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21 Dimensions

Readers on

mendeley
41 Mendeley
Title
Models of passive and active dendrite motoneuron pools and their differences in muscle force control
Published in
Journal of Computational Neuroscience, May 2012
DOI 10.1007/s10827-012-0398-4
Pubmed ID
Authors

Leonardo Abdala Elias, Vitor Martins Chaud, André Fabio Kohn

Abstract

Motoneuron (MN) dendrites may be changed from a passive to an active state by increasing the levels of spinal cord neuromodulators, which activate persistent inward currents (PICs). These exert a powerful influence on MN behavior and modify the motor control both in normal and pathological conditions. Motoneuronal PICs are believed to induce nonlinear phenomena such as the genesis of extra torque and torque hysteresis in response to percutaneous electrical stimulation or tendon vibration in humans. An existing large-scale neuromuscular simulator was expanded to include MN models that have a capability to change their dynamic behaviors depending on the neuromodulation level. The simulation results indicated that the variability (standard deviation) of a maintained force depended on the level of neuromodulatory activity. A force with lower variability was obtained when the motoneuronal network was under a strong influence of PICs, suggesting a functional role in postural and precision tasks. In an additional set of simulations when PICs were active in the dendrites of the MN models, the results successfully reproduced experimental results reported from humans. Extra torque was evoked by the self-sustained discharge of spinal MNs, whereas differences in recruitment and de-recruitment levels of the MNs were the main reason behind torque and electromyogram (EMG) hysteresis. Finally, simulations were also used to study the influence of inhibitory inputs on a MN pool that was under the effect of PICs. The results showed that inhibition was of great importance in the production of a phasic force, requiring a reduced co-contraction of agonist and antagonist muscles. These results show the richness of functionally relevant behaviors that can arise from a MN pool under the action of PICs.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 5 12%
United States 1 2%
Unknown 35 85%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 27%
Student > Ph. D. Student 6 15%
Student > Bachelor 5 12%
Researcher 5 12%
Unspecified 4 10%
Other 10 24%
Readers by discipline Count As %
Engineering 19 46%
Unspecified 5 12%
Neuroscience 5 12%
Agricultural and Biological Sciences 4 10%
Medicine and Dentistry 3 7%
Other 5 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 May 2012.
All research outputs
#6,074,083
of 11,627,462 outputs
Outputs from Journal of Computational Neuroscience
#68
of 206 outputs
Outputs of similar age
#46,393
of 107,671 outputs
Outputs of similar age from Journal of Computational Neuroscience
#3
of 5 outputs
Altmetric has tracked 11,627,462 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 206 research outputs from this source. They receive a mean Attention Score of 2.4. This one has gotten more attention than average, scoring higher than 66% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 107,671 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.