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A [14C]iodoantipyrine study of inter-regional correlations of neural substrates following central post-stroke pain in rats.

Lu HC, Chang WJ, Kuan YH, Huang AC, Shyu BC - Mol Pain (2015)

Bottom Line: These results corroborate previous findings that the STT and thalamocingulate pathway are involved in the pathophysiological mechanisms of CPSP symptoms.The mPFC, amygdala, and periaqueductal gray emerged as having important correlations in pain processing in CPSP.The present data provide a basis for a neural correlation hypothesis of CPSP, with implications for CPSP treatment.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Sciences, Academia Sinica, Taipei, 11529, Taiwan. nhnsc@hotmail.com.

ABSTRACT

Background: Central pain syndrome is characterized by a combination of abnormal pain sensations, and pain medications often provide little or no relief. Accumulating animal and clinical studies have shown that impairments of the spinothalamic tract (STT) and thalamocingulate pathway causes somatosensory dysfunction in central post-stroke pain (CPSP), but the involvement of other neuronal circuitries in CPSP has not yet been systematically examined. The aim of the present study was to evaluate changes in brain activity and neuronal circuitry using [(14)C]iodoantipyrine (IAP) in an animal model of CPSP.

Results: Rats were subjected to lateral thalamic hemorrhage to investigate the characteristics of CPSP. Thermal and mechanical hyperalgesia developed in rats that were subjected to thalamic hemorrhagic lesion. The medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), striatum, thalamus, hypothalamus, and amygdala were more active in the CPSP group compared with rats that were not subjected to lateral thalamic hemorrhage. The inter-regional correlation analysis showed that regional cerebral blood flow in the mPFC was highly correlated with the amygdala in the right brain, and the right brain showed complex connections among subregions of the ACC. Rats with CPSP exhibited strong activation of the thalamocingulate and mPFC-amygdala pathways.

Conclusions: These results corroborate previous findings that the STT and thalamocingulate pathway are involved in the pathophysiological mechanisms of CPSP symptoms. The mPFC, amygdala, and periaqueductal gray emerged as having important correlations in pain processing in CPSP. The present data provide a basis for a neural correlation hypothesis of CPSP, with implications for CPSP treatment.

No MeSH data available.


Related in: MedlinePlus

Differences in inter-regional correlations of rCBF of neural substrates in the CPSP and sham groups. A and B. Left and right brain connectivity. The matrix of Fisher’s Z-statistics represents differences in Pearson correlation coefficients (r) between the CPSP and sham groups. Positive Z values indicate a greater r in the CPSP group, and negative Z values indicate a smaller r. C-F. The inter-regional correlation of neural substrates is represented by a graph. The ROIs are represented by nodes, and significant correlations between different ROIs are represented by different line values. The red lines denote significant positive correlations, and blue lines denote significant negative correlations.
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Fig7: Differences in inter-regional correlations of rCBF of neural substrates in the CPSP and sham groups. A and B. Left and right brain connectivity. The matrix of Fisher’s Z-statistics represents differences in Pearson correlation coefficients (r) between the CPSP and sham groups. Positive Z values indicate a greater r in the CPSP group, and negative Z values indicate a smaller r. C-F. The inter-regional correlation of neural substrates is represented by a graph. The ROIs are represented by nodes, and significant correlations between different ROIs are represented by different line values. The red lines denote significant positive correlations, and blue lines denote significant negative correlations.

Mentions: Brain activation patterns in the left and right hemispheres in the sham and CPSP groups are shown in Figures 7A and B, respectively. Figure 7A shows the matrix of Fisher’s Z-statistics, representing differences in Pearson correlation coefficients (r) between the CPSP and sham groups in the left hemisphere. A total of 114 significant correlations were identified (24.7%), of which 84 were positive (73.7%) and 30 were negative (26.3%) at the threshold of p < 0.05. Figure 7B shows the results in the right hemisphere. A total of 140 significant correlations were identified (30.3%), of which 104 were positive (74.3%) and 36 were negative (25.7%) at the threshold of p < 0.05.Figure 7


A [14C]iodoantipyrine study of inter-regional correlations of neural substrates following central post-stroke pain in rats.

Lu HC, Chang WJ, Kuan YH, Huang AC, Shyu BC - Mol Pain (2015)

Differences in inter-regional correlations of rCBF of neural substrates in the CPSP and sham groups. A and B. Left and right brain connectivity. The matrix of Fisher’s Z-statistics represents differences in Pearson correlation coefficients (r) between the CPSP and sham groups. Positive Z values indicate a greater r in the CPSP group, and negative Z values indicate a smaller r. C-F. The inter-regional correlation of neural substrates is represented by a graph. The ROIs are represented by nodes, and significant correlations between different ROIs are represented by different line values. The red lines denote significant positive correlations, and blue lines denote significant negative correlations.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4358859&req=5

Fig7: Differences in inter-regional correlations of rCBF of neural substrates in the CPSP and sham groups. A and B. Left and right brain connectivity. The matrix of Fisher’s Z-statistics represents differences in Pearson correlation coefficients (r) between the CPSP and sham groups. Positive Z values indicate a greater r in the CPSP group, and negative Z values indicate a smaller r. C-F. The inter-regional correlation of neural substrates is represented by a graph. The ROIs are represented by nodes, and significant correlations between different ROIs are represented by different line values. The red lines denote significant positive correlations, and blue lines denote significant negative correlations.
Mentions: Brain activation patterns in the left and right hemispheres in the sham and CPSP groups are shown in Figures 7A and B, respectively. Figure 7A shows the matrix of Fisher’s Z-statistics, representing differences in Pearson correlation coefficients (r) between the CPSP and sham groups in the left hemisphere. A total of 114 significant correlations were identified (24.7%), of which 84 were positive (73.7%) and 30 were negative (26.3%) at the threshold of p < 0.05. Figure 7B shows the results in the right hemisphere. A total of 140 significant correlations were identified (30.3%), of which 104 were positive (74.3%) and 36 were negative (25.7%) at the threshold of p < 0.05.Figure 7

Bottom Line: These results corroborate previous findings that the STT and thalamocingulate pathway are involved in the pathophysiological mechanisms of CPSP symptoms.The mPFC, amygdala, and periaqueductal gray emerged as having important correlations in pain processing in CPSP.The present data provide a basis for a neural correlation hypothesis of CPSP, with implications for CPSP treatment.

View Article: PubMed Central - PubMed

Affiliation: Institute of Biomedical Sciences, Academia Sinica, Taipei, 11529, Taiwan. nhnsc@hotmail.com.

ABSTRACT

Background: Central pain syndrome is characterized by a combination of abnormal pain sensations, and pain medications often provide little or no relief. Accumulating animal and clinical studies have shown that impairments of the spinothalamic tract (STT) and thalamocingulate pathway causes somatosensory dysfunction in central post-stroke pain (CPSP), but the involvement of other neuronal circuitries in CPSP has not yet been systematically examined. The aim of the present study was to evaluate changes in brain activity and neuronal circuitry using [(14)C]iodoantipyrine (IAP) in an animal model of CPSP.

Results: Rats were subjected to lateral thalamic hemorrhage to investigate the characteristics of CPSP. Thermal and mechanical hyperalgesia developed in rats that were subjected to thalamic hemorrhagic lesion. The medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), striatum, thalamus, hypothalamus, and amygdala were more active in the CPSP group compared with rats that were not subjected to lateral thalamic hemorrhage. The inter-regional correlation analysis showed that regional cerebral blood flow in the mPFC was highly correlated with the amygdala in the right brain, and the right brain showed complex connections among subregions of the ACC. Rats with CPSP exhibited strong activation of the thalamocingulate and mPFC-amygdala pathways.

Conclusions: These results corroborate previous findings that the STT and thalamocingulate pathway are involved in the pathophysiological mechanisms of CPSP symptoms. The mPFC, amygdala, and periaqueductal gray emerged as having important correlations in pain processing in CPSP. The present data provide a basis for a neural correlation hypothesis of CPSP, with implications for CPSP treatment.

No MeSH data available.


Related in: MedlinePlus