Chronic pain remains a primary reason for people seeking health care, which, if untreated, can lead to depression, insomnia, depressed immune function, changes in eating patterns, and other long-term deleterious effects. Chronic pain patients have a fluctuating but persistent spontaneous pain percept and therefore their brain, compared with healthy subjects, is never truly at rest. The overall objective of this project is to identify the nature and long-term consequences of the burden imposed by this unrest condition on the well being of the brain. This objective is greatly facilitated by recent fMRI results in healthy subjects which have identified the subset of cortical areas active during idle or passive mental processes engaged in the so called """"""""Resting State Networks"""""""" (RSN).
Aim I is to identify the brain regions comprising the RSNs in chronic low back pain patients as compared with those in healthy subjects.
Aim II will determine the functional interactions between the components of each RSN in patients and normal subjects to better understand the basic cortical mechanisms at work in chronic pain. Finally Aim III will determine gender differences and hormonal dependence in the organization of these Resting State Networks, both in health and disease. FMRI data will be collected from healthy subjects and pain patients and analyzed with multivariate techniques such as Probabilistic Independent Component Analysis, which as shown in our preliminary results is able to unambiguously identify the major components involved in the RSN. The validation of the composition of each resting state and chronic pain networks will be conducted by hypothesis-driven General Linear Model bivariate analysis based on the current understanding of the cortical involvement in chronic pain. Since the identification of the spatio-temporal components of resting state network in chronic pain patients equals to a precise knowledge of """"""""where the pain is in the brain"""""""", its successful uncovering will dramatically change our understanding of the brain areas responsible for chronic pain. This knowledge should impact both the experimental approach in the study of pain using fMRI, and the diagnosis and therapy outcome of this invalidating disease.
There is accumulated evidence indicating that chronic pain if untreated, can lead to depression, insomnia, depressed immune function, changes in eating patterns, and other long- term deleterious effects. Chronic pain patients have a fluctuating but persistent spontaneous pain percept and therefore their brain, compared with healthy subjects, is never truly at rest. The project will isolate the components of the brain network subserving the resting state in chronic pain patients such us to identify the effect of the burden imposed by this unrest condition on the long term well being of the brain. This precise knowledge of """"""""where the pain is in the brain"""""""", will dramatically change our understanding of the brain areas responsible for chronic pain, impacting both the experimental approaches in the study of pain using fMRI, and the diagnosis and therapy outcome of this invalidating disease.
Cifre, Ignacio; Sitges, Carolina; Fraiman, Daniel et al. (2012) Disrupted functional connectivity of the pain network in fibromyalgia. Psychosom Med 74:55-62 |
Tagliazucchi, Enzo; Balenzuela, Pablo; Fraiman, Daniel et al. (2011) Spontaneous BOLD event triggered averages for estimating functional connectivity at resting state. Neurosci Lett 488:158-63 |
Expert, Paul; Lambiotte, Renaud; Chialvo, Dante R et al. (2011) Self-similar correlation function in brain resting-state functional magnetic resonance imaging. J R Soc Interface 8:472-9 |
Tagliazucchi, Enzo; Balenzuela, Pablo; Fraiman, Daniel et al. (2010) Brain resting state is disrupted in chronic back pain patients. Neurosci Lett 485:26-31 |
Fraiman, Daniel; Balenzuela, Pablo; Foss, Jennifer et al. (2009) Ising-like dynamics in large-scale functional brain networks. Phys Rev E Stat Nonlin Soft Matter Phys 79:061922 |
Perotti, Juan I; Billoni, Orlando V; Tamarit, Francisco A et al. (2009) Emergent self-organized complex network topology out of stability constraints. Phys Rev Lett 103:108701 |
Anteneodo, C; Chialvo, D R (2009) Unraveling the fluctuations of animal motor activity. Chaos 19:033123 |