Neural correlates of pain in the healthy human brain [electronic resource] : distinguishing painful and nonpainful stimuli with fMRI

Across the human neuroimaging literature, there is general consensus that the primary somatosensory cortex, secondary somatosensory cortex, anterior cingulate cortex, insular cortex, and thalamus are activated during pain. Many other brain regions have been implicated in pain processing, including the dorsolateral prefrontal cortex, primary motor cortex, and amygdala. Unfortunately, inter-study differences make it unclear which of these regions are or are not activated during pain. Furthermore, it remains unclear how the many brain regions that are activated during pain interact to distinguish stimuli that are painful from those that are not. The first study in this thesis is a meta-analysis in which we synthesizes the neuroimaging literature on pain and reveal that 14 brain regions are significantly more activated during painful than nonpainful stimulation. These 14 brain regions are the contralateral primary somatosensory cortex, contralateral primary motor cortex, contralateral anterior midcingulate cortex, contralateral supplementary motor area, ventral tegmental area, right anterior insular cortex, bilateral midinsular cortex, bilateral thalamus, bilateral secondary somatosensory cortex, and bilateral superior temporal lobe. The second and third studies in this thesis investigate two mechanisms by which neural activity in distributed brain regions might be integrated to distinguish painful from nonpainful stimulation. The second study in this thesis uses a support vector machine to distinguish painful and nonpainful stimuli based on the linear summation of neural activity across the whole brain. Using whole-brain patterns of neural activity and a support vector machine, we distinguish painful and nonpainful stimuli with 81% accuracy. These results suggest that the linear summation of activity in distributed brain regions may constitute a neural mechanism for distinguishing painful and nonpainful stimuli. Furthermore, the results demonstrate that it is possible to objectively measure pain and we discuss tasks that should be undertaken the advance this approach towards clinical use. The third study in this thesis investigates temporal correlations in neural activity as a potential mechanism of by which the brain may distinguishing painful and nonpainful stimuli. We found that the brain regions activated during pain are significantly correlated in their response to painful and nonpainful stimulation. Furthermore, we found that the brain regions activated during pain are functionally connected during rest. These results do not support the hypothesis that correlations in brain activity distinguish painful and nonpainful stimuli. Importantly however, these results demonstrate that the brain regions activated during pain comprise a resting state network, that is, they are temporally correlated at rest. Together, the studies presented here have spatially defined the distributed brain regions that are activated during pain, and suggest that these brain regions comprise a neural network in which overall activity is increased during pain.

Keywords: Neurosciences.
Advisor: Mackey Sean primary advisor. Thesis advisor
Glover Gary H.
Grill-Spector Kalanit advisor. Thesis advisor
Yeomans David