publication . Preprint . 2017

Specific Patterns of Bold Variability Associated with the Processing of Pain Stimuli

Costa, Tommaso; Nani, Andrea; Manuello, Jordi; Vercelli, Ugo; Tatu, Mona-Karina; Cauda, Franco;
Open Access
  • Published: 28 Jun 2017
  • Publisher: Cold Spring Harbor Laboratory
Abstract
<jats:title>ABSTRACT</jats:title><jats:p>It is well known that the blood oxygen level dependent (BOLD) signal varies according to task performance and region specificity. This ongoing and fluctuating activity reflects the organization of functional brain networks. Peculiar dynamics of BOLD signal are therefore supposed to characterize brain activity in different conditions. Within this framework, we investigated through a multivoxel pattern analysis whether patterns of BOLD variability convey information that may allow an efficient discrimination between task (i.e., painful stimulation) and rest conditions. We therefore identified the most discriminative brain a...
Subjects
free text keywords: Bioinformatics, Stimulus (physiology), Entropy rate, Neuroscience, Blood-oxygen-level dependent, Brain activity and meditation, Sample entropy, Anterior cingulate cortex, medicine.anatomical_structure, medicine, Biology, Insula, Periaqueductal gray
Related Organizations
37 references, page 1 of 3

Applebaum, D. (1996). Probability and information: An integrated approach. Cambridge University Press.

Bandt, C., & Pompe, B. (2002). Permutation entropy - a natural complexity measure for time series, 1-5. [OpenAIRE]

Baumgärtner, U., Iannetti, G. D., Zambreanu, L., Stoeter, P., Treede, R.-D., & Tracey, I. (2010). Multiple somatotopic representations of heat and mechanical pain in the operculo-insular cortex: a high-resolution fMRI study. Journal of Neurophysiology, 104(5), 2863-72. http://doi.org/10.1152/jn.00253.2010

Bishop, C. (2006). Pattern recognition and machine learning. Retrieved from http://cds.cern.ch/record/998831/files/9780387310732_TOC.pdf

Cauda, F., Costa, T., Diano, M., Duca, S., & Torta, D. M. E. (2014). Beyond the “Pain Matrix, ” interrun synchronization during mechanical nociceptive stimulation. Frontiers in Human Neuroscience, 8(MAY). http://doi.org/10.3389/fnhum.2014.00265

Cauda, F., Costa, T., Diano, M., Sacco, K., Duca, S., Geminiani, G., & Torta, D. M. E. (2014). Massive modulation of brain areas after mechanical pain stimulation: a time-resolved FMRI study. Cerebral Cortex (New York, N.Y. : 1991), 24(11), 2991-3005. http://doi.org/10.1093/cercor/bht153

Cauda, F., Costa, T., Torta, D. M. E., Sacco, K., D'Agata, F., Duca, S., … Vercelli, A. (2012). Metaanalytic clustering of the insular cortex: characterizing the meta-analytic connectivity of the insula when involved in active tasks. NeuroImage, 62(1), 343-55. http://doi.org/10.1016/j.neuroimage.2012.04.012 [OpenAIRE]

Cauda, F., Costa, T., Torta, D. M. E., Sacco, K., D'Agata, F., Duca, S., … Vercelli, A. (2012). Metaanalytic clustering of the insular cortex. Characterizing the meta-analytic connectivity of the insula when involved in active tasks. NeuroImage, 62(1), 343-355. http://doi.org/10.1016/j.neuroimage.2012.04.012 [OpenAIRE]

Cauda, F., D'Agata, F., Sacco, K., Duca, S., Geminiani, G., & Vercelli, A. (2011). Functional connectivity of the insula in the resting brain. NeuroImage, 55(1), 8-23. http://doi.org/10.1016/j.neuroimage.2010.11.049 [OpenAIRE]

Cauda, F., Torta, D. M. E., Sacco, K., D'Agata, F., Geda, E., Duca, S., … Vercelli, A. (2013). Functional anatomy of cortical areas characterized by Von Economo neurons. Brain Structure & Function, 218(1), 1-20. http://doi.org/10.1007/s00429-012-0382-9

D'Agata, F. (2011). ClassTAL. http://doi.org/10.1038/npre.2011.6142.2

Dayan, P. (2005). Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems. Retrieved from https://books.google.it/books/about/Theoretical_Neuroscience.html?id=hrZYAAAACAAJ&pgis =1

De Martino, F., Valente, G., Staeren, N., Ashburner, J., Goebel, R., & Formisano, E. (2008). Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns. NeuroImage, 43(1), 44-58. http://doi.org/10.1016/j.neuroimage.2008.06.037

Deco, G., Jirsa, V. K., & McIntosh, A. R. (2011). Emerging concepts for the dynamical organization of resting-state activity in the brain. Nature Reviews. Neuroscience, 12(1), 43-56. http://doi.org/10.1038/nrn2961

Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O., & Kotter, R. (2009). Key role of coupling, delay, and noise in resting brain fluctuations. Proceedings of the National Academy of Sciences, 106(25), 10302-10307. http://doi.org/10.1073/pnas.0901831106 [OpenAIRE]

37 references, page 1 of 3
Abstract
<jats:title>ABSTRACT</jats:title><jats:p>It is well known that the blood oxygen level dependent (BOLD) signal varies according to task performance and region specificity. This ongoing and fluctuating activity reflects the organization of functional brain networks. Peculiar dynamics of BOLD signal are therefore supposed to characterize brain activity in different conditions. Within this framework, we investigated through a multivoxel pattern analysis whether patterns of BOLD variability convey information that may allow an efficient discrimination between task (i.e., painful stimulation) and rest conditions. We therefore identified the most discriminative brain a...
Subjects
free text keywords: Bioinformatics, Stimulus (physiology), Entropy rate, Neuroscience, Blood-oxygen-level dependent, Brain activity and meditation, Sample entropy, Anterior cingulate cortex, medicine.anatomical_structure, medicine, Biology, Insula, Periaqueductal gray
Related Organizations
37 references, page 1 of 3

Applebaum, D. (1996). Probability and information: An integrated approach. Cambridge University Press.

Bandt, C., & Pompe, B. (2002). Permutation entropy - a natural complexity measure for time series, 1-5. [OpenAIRE]

Baumgärtner, U., Iannetti, G. D., Zambreanu, L., Stoeter, P., Treede, R.-D., & Tracey, I. (2010). Multiple somatotopic representations of heat and mechanical pain in the operculo-insular cortex: a high-resolution fMRI study. Journal of Neurophysiology, 104(5), 2863-72. http://doi.org/10.1152/jn.00253.2010

Bishop, C. (2006). Pattern recognition and machine learning. Retrieved from http://cds.cern.ch/record/998831/files/9780387310732_TOC.pdf

Cauda, F., Costa, T., Diano, M., Duca, S., & Torta, D. M. E. (2014). Beyond the “Pain Matrix, ” interrun synchronization during mechanical nociceptive stimulation. Frontiers in Human Neuroscience, 8(MAY). http://doi.org/10.3389/fnhum.2014.00265

Cauda, F., Costa, T., Diano, M., Sacco, K., Duca, S., Geminiani, G., & Torta, D. M. E. (2014). Massive modulation of brain areas after mechanical pain stimulation: a time-resolved FMRI study. Cerebral Cortex (New York, N.Y. : 1991), 24(11), 2991-3005. http://doi.org/10.1093/cercor/bht153

Cauda, F., Costa, T., Torta, D. M. E., Sacco, K., D'Agata, F., Duca, S., … Vercelli, A. (2012). Metaanalytic clustering of the insular cortex: characterizing the meta-analytic connectivity of the insula when involved in active tasks. NeuroImage, 62(1), 343-55. http://doi.org/10.1016/j.neuroimage.2012.04.012 [OpenAIRE]

Cauda, F., Costa, T., Torta, D. M. E., Sacco, K., D'Agata, F., Duca, S., … Vercelli, A. (2012). Metaanalytic clustering of the insular cortex. Characterizing the meta-analytic connectivity of the insula when involved in active tasks. NeuroImage, 62(1), 343-355. http://doi.org/10.1016/j.neuroimage.2012.04.012 [OpenAIRE]

Cauda, F., D'Agata, F., Sacco, K., Duca, S., Geminiani, G., & Vercelli, A. (2011). Functional connectivity of the insula in the resting brain. NeuroImage, 55(1), 8-23. http://doi.org/10.1016/j.neuroimage.2010.11.049 [OpenAIRE]

Cauda, F., Torta, D. M. E., Sacco, K., D'Agata, F., Geda, E., Duca, S., … Vercelli, A. (2013). Functional anatomy of cortical areas characterized by Von Economo neurons. Brain Structure & Function, 218(1), 1-20. http://doi.org/10.1007/s00429-012-0382-9

D'Agata, F. (2011). ClassTAL. http://doi.org/10.1038/npre.2011.6142.2

Dayan, P. (2005). Theoretical Neuroscience: Computational And Mathematical Modeling of Neural Systems. Retrieved from https://books.google.it/books/about/Theoretical_Neuroscience.html?id=hrZYAAAACAAJ&pgis =1

De Martino, F., Valente, G., Staeren, N., Ashburner, J., Goebel, R., & Formisano, E. (2008). Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns. NeuroImage, 43(1), 44-58. http://doi.org/10.1016/j.neuroimage.2008.06.037

Deco, G., Jirsa, V. K., & McIntosh, A. R. (2011). Emerging concepts for the dynamical organization of resting-state activity in the brain. Nature Reviews. Neuroscience, 12(1), 43-56. http://doi.org/10.1038/nrn2961

Deco, G., Jirsa, V., McIntosh, A. R., Sporns, O., & Kotter, R. (2009). Key role of coupling, delay, and noise in resting brain fluctuations. Proceedings of the National Academy of Sciences, 106(25), 10302-10307. http://doi.org/10.1073/pnas.0901831106 [OpenAIRE]

37 references, page 1 of 3
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publication . Preprint . 2017

Specific Patterns of Bold Variability Associated with the Processing of Pain Stimuli

Costa, Tommaso; Nani, Andrea; Manuello, Jordi; Vercelli, Ugo; Tatu, Mona-Karina; Cauda, Franco;