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Network dynamics in nociceptive pathways assessed by the neuronal avalanche model

José Jiun-Shian Wu12, Hsi-Chien Shih2, Chen-Tung Yen1 and Bai-Chuang Shyu2*

Author Affiliations

1 Institute of Zoology, National Taiwan University, Taipei, Republic of China

2 Institute of Biomedical Science, Academia Sinica, Taipei, Republic of China

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Molecular Pain 2012, 8:33  doi:10.1186/1744-8069-8-33

Published: 26 April 2012



Traditional electroencephalography provides a critical assessment of pain responses. The perception of pain, however, may involve a series of signal transmission pathways in higher cortical function. Recent studies have shown that a mathematical method, the neuronal avalanche model, may be applied to evaluate higher-order network dynamics. The neuronal avalanche is a cascade of neuronal activity, the size distribution of which can be approximated by a power law relationship manifested by the slope of a straight line (i.e., the α value). We investigated whether the neuronal avalanche could be a useful index for nociceptive assessment.


Neuronal activity was recorded with a 4 × 8 multichannel electrode array in the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC). Under light anesthesia, peripheral pinch stimulation increased the slope of the α value in both the ACC and S1, whereas brush stimulation increased the α value only in the S1. The increase in α values was blocked in both regions under deep anesthesia. The increase in α values in the ACC induced by peripheral pinch stimulation was blocked by medial thalamic lesion, but the increase in α values in the S1 induced by brush and pinch stimulation was not affected.


The neuronal avalanche model shows a critical state in the cortical network for noxious-related signal processing. The α value may provide an index of brain network activity that distinguishes the responses to somatic stimuli from the control state. These network dynamics may be valuable for the evaluation of acute nociceptive processes and may be applied to chronic pathological pain conditions.

Pain assessment; Neuronal avalanche; Network dynamics