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Formation of Opioid-Induced Memory and Its Prevention: A Computational Study

Overview of attention for article published in Frontiers in Computational Neuroscience, August 2018
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Title
Formation of Opioid-Induced Memory and Its Prevention: A Computational Study
Published in
Frontiers in Computational Neuroscience, August 2018
DOI 10.3389/fncom.2018.00063
Pubmed ID
Authors

Mehdi Borjkhani, Fariba Bahrami, Mahyar Janahmadi

Abstract

There are several experimental studies which suggest opioids consumption forms pathological memories in different brain regions. For example it has been empirically demonstrated that the theta rhythm which appears during chronic opioid consumption is correlated with the addiction memory formation. In this paper, we present a minimal computational model that shows how opioids can change firing patterns of the neurons during acute and chronic opioid consumption and also during withdrawal periods. The model consists of a pre- and post-synaptic neuronal circuits and the astrocyte that monitors the synapses. The output circuitry consists of inhibitory interneurons and excitatory pyramidal neurons. Our simulation results demonstrate that acute opioid consumption induces synchronous patterns in the beta frequency range, while, chronic opioid consumption provokes theta frequency oscillations. This allows us to infer that the theta rhythm appeared during chronic treatment can be an indication of brain engagement in opioid-induced memory formation. Our results also suggest that changing the inputs of the interneurons and the inhibitory neuronal network is not an appropriate method for preventing the formation of pathological memory. However, the same results suggest that prevention of pathological memory formation is possible by manipulating the input of the stimulatory network and the excitatory connections in the neuronal network. They also show that during withdrawal periods, firing rate is reduced and random fluctuations are generated in the modeled neural network. The random fluctuations disappear and synchronized patterns emerge when the activities of the astrocytic transporters are decreased. These results suggest that formation of the synchronized activities can be correlated with the relapse. Our model also predicts that reduction in gliotransmitter release can eliminate the synchrony and thereby it can reduce the likelihood of the relapse occurrence.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 22%
Student > Master 2 11%
Professor 2 11%
Other 1 6%
Student > Bachelor 1 6%
Other 1 6%
Unknown 7 39%
Readers by discipline Count As %
Engineering 4 22%
Psychology 2 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Computer Science 1 6%
Medicine and Dentistry 1 6%
Other 1 6%
Unknown 8 44%
Attention Score in Context

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 August 2018.
All research outputs
#13,267,809
of 23,096,849 outputs
Outputs from Frontiers in Computational Neuroscience
#509
of 1,358 outputs
Outputs of similar age
#162,120
of 331,118 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#15
of 29 outputs
Altmetric has tracked 23,096,849 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,358 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 61% 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 331,118 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 50% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.