The transition from acute pain to chronic pain entails considerable changes of patients at multiple levels of the nervous system and in psychological states. An accurate differentiation between acute and chronic pain is essential in pain management as it may help optimize analgesic treatments according to the pain state of patients. Given that acute and chronic pain could modulate brain states in different ways and that brain states could greatly shape the neural processing of external inputs, we hypothesized that acute and chronic pain would show differential effects on cortical responses to non-nociceptive sensory information. Here by analyzing auditory-evoked potentials (AEPs) to pure tones in rats with acute or chronic pain, we found opposite influences of acute and chronic pain on cortical responses to auditory inputs. In particular, compared to no-pain controls, the N100 wave of rat AEPs was significantly enhanced in rats with acute pain but significantly reduced in rats with chronic pain, indicating that acute pain facilitated cortical processing of auditory information while chronic pain exerted an inhibitory effect. These findings could be justified by the fact that individuals suffering from acute or chronic pain would have different vigilance states, i.e., the vigilance level to external sensory stimuli would be increased with acute pain, but decreased with chronic pain. Therefore, this auditory response holds promise of being a brain signature to differentiate acute and chronic pain. Instead of investigating the pain system per se, the study of pain-induced influences on cortical processing of non-nocicpetive sensory information might represent a potential strategy to monitor the progress of pain chronification in clinical applications.
Pharmacology, Toxicology and Pharmaceutical Science
3
5%
Other
7
12%
Unknown
15
26%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 05 September 2016.
All research outputs
#8,132,096
of 25,996,988 outputs
Outputs from Frontiers in Computational Neuroscience
#409
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Outputs of similar age
#105,244
of 314,036 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#4
of 32 outputs
Altmetric has tracked 25,996,988 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,479 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 71% 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 314,036 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 66% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.
