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Abnormal processing of somatosensory inputs in the central nervous system (central sensitization) is the mechanism accounting for the enhanced pain sensitivity in the skin surrounding tissue injury (secondary hyperalgesia). Secondary hyperalgesia shares clinical characteristics with neurogenic hyperalgesia in patients with neuropathic pain. Abnormal brain responses to somatosensory stimuli have been found in patients with hyperalgesia as well as in normal subjects during experimental central sensitization. The aim of this study was to assess the effects of gabapentin, a drug effective in neuropathic pain patients, on brain processing of nociceptive information in normal and central sensitization states. Using functional magnetic resonance imaging (fMRI) in normal volunteers, we studied the gabapentin-induced modulation of brain activity in response to nociceptive mechanical stimulation of normal skin and capsaicin-induced secondary hyperalgesia. The dose of gabapentin was 1,800 mg per os, in a single administration. We found that (11 gabapentin reduced the activations in the bilateral operculoinsular cortex, independently of the presence of central sensitization; (i) gabapentin reduced the activation in the brainstem, only during central sensitization; (iii) gabapentin suppressed stimulus-induced deactivations, only during central sensitization; this effect was more robust than the effect on brain activation. The observed drug-induced effects were not due to changes in the baseline fMRI signal. These findings indicate that gabapentin has a measurable antinociceptive effect and a stronger antihyperalgesic effect most evident in the brain areas undergoing deactivation, thus supporting the concept that gabapentin is more effective in modulating nociceptive transmission when central sensitization is present. deactivation | fMRI | hyperalgesia | nociceptive system

Abstract The sensitivity of any treatment comparisons in pond experiments is often limited by large variability among ponds. Standard techniques of increasing the number of replicate ponds to account for the large variability may be inappropriate as only a limited number of ponds may be available for any one experiment. This paper considers various ‘balanced incomplete block’ designs and compares their use with ‘completely randomized designs’ and ‘randomized complete block’ designs. With simulated data, it is shown that ‘balanced incomplete block’ designs can reduce the standard error of a treatment estimate by as much as 50%, and reduce confidence intervals by 25%, although increases of similar sizes may be experienced. The pattern of allocation of blocks to ponds by neighbour or by pond number shows no clear distinction in estimation improvement. Where missing ponds occur a large increase in imprecision may be experienced. These results are supported by data from non-uniformity experiments. Further work is needed to explore block structures for specific types of treatment that may influence the patterns of variability to different extents. [ABSTRACT FROM AUTHOR]