Pain
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Advances in pain measurement using ecological momentary assessments offer novel opportunities for understanding the temporal dynamics of pain. This study examined whether regime-switching models, which capture processes characterized by recurrent shifts between different states, provide clinically relevant information for characterizing individuals based on their temporal pain patterns. Patients with rheumatic diseases (N = 116) provided 7 to 8 momentary pain ratings per day for 2 weekly periods, separated by 3 months. ⋯ Longitudinal analyses of changes over the 3 months largely replicated cross-sectional results. Furthermore, patients' retrospective judgments of their pain were uniquely predicted by Amplitude and Dominance of higher pain states, and global impressions of change over the 3 months were predicted by changes on Dominance, controlling for Average pain levels. The results suggest that regime-switching models can usefully capture temporal dynamics of pain and can contribute to an improved measurement of patients' pain intensity.
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Impaired selective fear learning has been advanced as a core mechanism involved in excessive spreading of protective responses such as pain-related fear and avoidance leading to disability in chronic pain conditions. Using the litmus test for selective learning effects, the blocking procedure, we tested the hypothesis that patients with fibromyalgia (FM) show less selective threat learning than healthy controls (HCs). We introduce a novel selective learning task based around a clinical diary scenario. ⋯ Simultaneously, a novel situation was introduced and also followed by "pain" (B+). Within-group comparisons showed blocking (ie, significant difference between B and X) in the HCs, but not in the patients with FM. This study is the first in directly assessing differences in selective learning between patients with FM and HCs using a blocking procedure.
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Individual differences in sensitivity to pain are large and have clinical and scientific importance. Although heavily influenced by situational factors, they also relate to genetic factors and psychological traits, and are reflected by differences in functional activation in pain-related brain regions. Here, we used voxel-based morphometry to investigate if individual pain sensitivity is related to local gray matter volumes. ⋯ Alternatively, associations of PSQ scores with the parahippocampal and fusiform gray matter could relate to the visual imagination of painful situations required by the PSQ, not to pain sensitivity itself. Regarding PPTs, the present data obtained in a large sample strongly suggest an absence of associations of this parameter with gray matter volume. In conclusion, the present results argue against a strong association between pain sensitivity and local gray matter volumes.
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Central poststroke pain (CPSP) is a neuropathic pain disorder, the underlying mechanisms of which are not well understood. It has been suggested that stroke-associated loss of inhibitory neurons in the spinothalamic tract causes disinhibition of thalamic neurons, which autonomously generate ectopic nociceptive action potentials responsible for the pain experience. We hypothesized that CPSP is a result of misinterpretation of afferent sensory input by the sensitized neurons within the brain, rather than generated spontaneously by the damaged central nervous system (CNS) neurons. ⋯ All mechanical/thermal hypersensitivity was abolished by the nerve block. The results suggest that it is unlikely that CPSP is autonomously generated within the CNS. Rather, this pain is dependent on afferent input from the painful region in the periphery, and may be mediated by misinterpretation of peripheral sensory input by sensitized neurons in the CNS.