NeuroImage
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Despite the clinical relevance of nocebo effects, few studies have addressed their underlying neural mechanisms in clinically-relevant pain models. We aimed to address the contribution of nocebo effects and their underlying neural circuitry to central pain amplification in visceral pain, as it may develop over repeated painful experiences due to negative pain-related expectations. Healthy volunteers received verbal suggestions of pain sensitization (nocebo group, N=28) or neutral instructions (control group, N=16). fMRI was used to investigate changes in neural responses during cued pain anticipation and painful rectal distensions delivered in successive fMRI sessions. ⋯ A subsequent psycho-physiological interaction analysis of the pain phase showed increased functional connectivity between the anterior insula, which was set-up as seed region based on group results, and midcingulate cortex as a function of negative expectations. These findings support that negative pain-related expectations can play a crucial role in pain amplification of visceral pain, which is mediated, at least in part, by a neural up-regulation of pain-associated areas and their connectivity. These findings may have implications for the pathophysiology and treatment of chronic abdominal pain.
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EEG-fMRI is an established technique to allow mapping BOLD changes in response to interictal discharges recorded in the EEG of epilepsy patients. Traditional fMRI experiments rely on an echo planar imaging (EPI) sequence with a time resolution given by its time-to-repetition (TR) of ~2 s. Recently, multiple fast fMRI sequences have been developed to get around the limited temporal resolution of the EPI sequence, and achieved a TR in the 100 ms range or lower. ⋯ In addition, we show that a mismatch between the assumed and actual HRF impairs more MREG detection performance, but that EPI is more affected by non-modeled spike-to-spike variations of response amplitude. Filtering-out physiological noise, which is not aliased at the fast sampling rate of MREG, and the modeling of temporal autocorrelation are advantageous in increasing the detection power of MREG. This simulation study 1) warrants care when interpreting statistical t-values from fast fMRI sequences, 2) proposes thresholds for valid inferences and processing methods for maximal sensitivities, and 3) demonstrates the relative robustness/susceptibility of MREG and EPI to violation of the GLM's assumptions.
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Diffusion tensor imaging (DTI) measures are commonly used as imaging markers to investigate individual differences in relation to behavioral and health-related characteristics. However, the ability to detect reliable associations in cross-sectional or longitudinal studies is limited by the reliability of the diffusion measures. Several studies have examined the reliability of diffusion measures within (i.e. intra-site) and across (i.e. inter-site) scanners with mixed results. ⋯ Our findings indicate that investigations relating diffusion measures to external variables must consider variable reliability across the distinct regions of interest and that correction factors can be used to improve consistency of measurement across field strengths. An important result of this work is that inter-scanner and field strength effects can be partially mitigated with linear correction factors specific to regions of interest. These data-driven linear correction techniques can be applied in cross-sectional or longitudinal studies.