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Beyond the "Pain Matrix," inter-run synchronization during mechanical nociceptive stimulation.

Cauda F, Costa T, Diano M, Duca S, Torta DM - Front Hum Neurosci (2014)

Bottom Line: One hypothesis is that the traditional analysis of pain-related cerebral responses, by relying on the correlation of a predictor and the canonical hemodynamic response function (HRF)- the general linear model (GLM)- may under-detect the activity of those areas involved in stimulus processing that do not present a canonical HRF.With this method we were able to evidence the involvement of several brain regions that are not usually found when using predictor-based analysis.These areas are synchronized during the administration of mechanical punctate stimuli and are characterized by a BOLD response different from the canonical HRF.

View Article: PubMed Central - PubMed

Affiliation: GCS fMRI, Koelliker Hospital and Department of Psychology, University of Turin Turin, Italy ; Department of Psychology, University of Turin Turin, Italy.

ABSTRACT
Pain is a complex experience that is thought to emerge from the activity of multiple brain areas, some of which are inconsistently detected using traditional fMRI analysis. One hypothesis is that the traditional analysis of pain-related cerebral responses, by relying on the correlation of a predictor and the canonical hemodynamic response function (HRF)- the general linear model (GLM)- may under-detect the activity of those areas involved in stimulus processing that do not present a canonical HRF. In this study, we employed an innovative data-driven processing approach- an inter-run synchronization (IRS) analysis- that has the advantage of not establishing any pre-determined predictor definition. With this method we were able to evidence the involvement of several brain regions that are not usually found when using predictor-based analysis. These areas are synchronized during the administration of mechanical punctate stimuli and are characterized by a BOLD response different from the canonical HRF. This finding opens to new approaches in the study of pain imaging.

No MeSH data available.


Related in: MedlinePlus

IRS results variability. This map shows the probability that each voxel has to be found active in one or more subjects when using the IRS. At each spatial location, such maps represent the relative number of subjects reporting a significant IRS activation. The probability map is calculated by summing voxel value of each subject-related IRS result and dividing this value by the number of subjects.
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Figure 5: IRS results variability. This map shows the probability that each voxel has to be found active in one or more subjects when using the IRS. At each spatial location, such maps represent the relative number of subjects reporting a significant IRS activation. The probability map is calculated by summing voxel value of each subject-related IRS result and dividing this value by the number of subjects.

Mentions: Figure 5 shows the probability that a voxel is activated in one or in more subjects (IRS analysis). At each spatial location, the map represents the number of subjects showing significant activations. This map indicates that significant areas of activations obtained with the IRS can be observed in >60% of the participants.


Beyond the "Pain Matrix," inter-run synchronization during mechanical nociceptive stimulation.

Cauda F, Costa T, Diano M, Duca S, Torta DM - Front Hum Neurosci (2014)

IRS results variability. This map shows the probability that each voxel has to be found active in one or more subjects when using the IRS. At each spatial location, such maps represent the relative number of subjects reporting a significant IRS activation. The probability map is calculated by summing voxel value of each subject-related IRS result and dividing this value by the number of subjects.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4017139&req=5

Figure 5: IRS results variability. This map shows the probability that each voxel has to be found active in one or more subjects when using the IRS. At each spatial location, such maps represent the relative number of subjects reporting a significant IRS activation. The probability map is calculated by summing voxel value of each subject-related IRS result and dividing this value by the number of subjects.
Mentions: Figure 5 shows the probability that a voxel is activated in one or in more subjects (IRS analysis). At each spatial location, the map represents the number of subjects showing significant activations. This map indicates that significant areas of activations obtained with the IRS can be observed in >60% of the participants.

Bottom Line: One hypothesis is that the traditional analysis of pain-related cerebral responses, by relying on the correlation of a predictor and the canonical hemodynamic response function (HRF)- the general linear model (GLM)- may under-detect the activity of those areas involved in stimulus processing that do not present a canonical HRF.With this method we were able to evidence the involvement of several brain regions that are not usually found when using predictor-based analysis.These areas are synchronized during the administration of mechanical punctate stimuli and are characterized by a BOLD response different from the canonical HRF.

View Article: PubMed Central - PubMed

Affiliation: GCS fMRI, Koelliker Hospital and Department of Psychology, University of Turin Turin, Italy ; Department of Psychology, University of Turin Turin, Italy.

ABSTRACT
Pain is a complex experience that is thought to emerge from the activity of multiple brain areas, some of which are inconsistently detected using traditional fMRI analysis. One hypothesis is that the traditional analysis of pain-related cerebral responses, by relying on the correlation of a predictor and the canonical hemodynamic response function (HRF)- the general linear model (GLM)- may under-detect the activity of those areas involved in stimulus processing that do not present a canonical HRF. In this study, we employed an innovative data-driven processing approach- an inter-run synchronization (IRS) analysis- that has the advantage of not establishing any pre-determined predictor definition. With this method we were able to evidence the involvement of several brain regions that are not usually found when using predictor-based analysis. These areas are synchronized during the administration of mechanical punctate stimuli and are characterized by a BOLD response different from the canonical HRF. This finding opens to new approaches in the study of pain imaging.

No MeSH data available.


Related in: MedlinePlus