Predictive coding models for pain perception.
Predictive coding models for pain perception.
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DOI:
10.1007/s10827-021-00780-x
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发表时间:
2021-05
影响因子:
1.2
通讯作者:
Chen ZS
中科院分区:
文献类型:
--
作者:
Song Y;Yao M;Kemprecos H;Byrne A;Xiao Z;Zhang Q;Singh A;Wang J;Chen ZS
Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats—two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out—thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.
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影响因子:
16.2
作者:
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通讯作者:
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影响因子:
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通讯作者:
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DOI:
10.1098/rstb.2000.0769
发表时间:
2001-03-29
影响因子:
6.3
作者:
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通讯作者:
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DOI:
10.1073/pnas.96.14.7705
发表时间:
1999-07-06
影响因子:
11.1
作者:
Bushnell, MC;Duncan, GH;Carrier, B
通讯作者:
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