The effect of temporal interference of physiological signals on time-lag effective connectivity, derived from a functional network connectivity tool box (FNC), was examined by a blood-oxygen-level-dependent functional MRI study of action. The known effect of physiological signals on time-lag FNC was verified by (a) comparison of time-lag FNC analyses without and with retrospective image-based correction (RETROICOR) and (b) the other time-lag FNC analysis including the ventricular component related to the cerebrospinal fluid with dominant physiological effects. Twenty-five right-handed normal individuals performed motor task with motor response by the right middle/index fingers. Behavioral data of the reaction time (RT) and physiological signals (electrocardiogram, respiration, and pulsation) were recorded during neuroimaging studies of a 2-s repetition time at 3T. After standard image preprocessing, RETROICOR of the physiological effects and group independent component analysis (ICA), five action-related components were selected from 59 ICA components according to spatial extension involving known functional correlates of visuomotor tasks. Time-lag FNC was constructed by calculating the maximal correlation coefficients among five selected components. Attenuation of the physiological effect at 0.02-0.25 Hz was an average of 0.63 dB after RETROICOR (P<0.0005). Results of FNC analyses without and with RETROICOR were compatible with the action networks using the right hand. On the basis of the time-lag FNC after RETROICOR, the connectivity among the ventricular component and other components of action network attenuated. The FNC map with RETROICOR was more explicable with known action networks, for example interhemispheric inhibition. The effects of physiological signals significantly misled the interpretation of time-lag FNC in terms of direction and connectivity strength.

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Purpose This work investigates the effects of flow acceleration in the superior sagittal sinus on slice‐dependent variations in venous oxygen saturation (SvO2) estimations using susceptibility‐based MR oximetry. Methods Three‐dimensional multiple gradient‐echo images, with first‐order flow compensation along the anterior–posterior readout direction for the first echo, were acquired twice from 15 healthy volunteers. For all slices, phases within the superior sagittal sinus were fitted using linear regression across four TEs to obtain the Pearson’s correlation coefficients (PCCs), the largest of which corresponded to minimum acceleration influence. SvO2 derived from odd echoes on this slice was used to assess interscan difference, and compared with the central 15th slice for slice‐dependent difference, both using Bland‐Altman analysis. Within‐scan interslice SvO2 consistency was examined versus PCC. Multislice‐averaged SvO2 values were then computed from slices with PCCs above a certain threshold. Results Slice‐dependent difference in SvO2 varied from −16.2% to 21.5% at two SDs, in agreement with a recent report, and about twice larger than interscan differences for the automatically selected slice (−7.5% to 10.3%) and for the central 15th slice (−8.0% to 8.8%). For slices with PCCs higher than −0.98, interslice SvO2 deviations were all found to be less than 5.0%. Multislice‐averaged SvO2 with PCCs higher than −0.98 further reduced interscan difference to −4.7% to 8.2%. Conclusion Slice‐dependent variations in SvO2 may partly be explained by the effects of flow acceleration. Our method may enable conventional 3D multiple gradient echo to be used for SvO2 estimations in the presence of pulsatile flow.

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IntroductionPrimary dysmenorrhea (PDM) is a common condition among women of reproductive age, characterized by menstrual pain in the absence of any organic causes. Previous research has established a link between the A118G polymorphism in the mu-opioid receptor (OPRM1) gene and pain experience in PDM. Specifically, carriers of the G allele have been found to exhibit maladaptive functional connectivity between the descending pain modulatory system and the motor system in young women with PDM. This study aims to explore the potential relationship between the OPRM1 A118G polymorphism and changes in white matter in young women with PDM.MethodsThe study enrolled 43 individuals with PDM, including 13 AA homozygotes and 30 G allele carriers. Diffusion tensor imaging (DTI) scans were performed during both the menstrual and peri-ovulatory phases, and tract-based spatial statistics (TBSS) and probabilistic tractography were used to explore variations in white matter microstructure related to the OPRM1 A118G polymorphism. The short-form McGill Pain Questionnaire (MPQ) was used to access participants’ pain experience during the MEN phase.ResultsTwo-way ANOVA on TBSS analysis revealed a significant main effect of genotype, with no phase effect or phase-gene interaction detected. Planned contrast analysis showed that during the menstrual phase, G allele carriers had higher fractional anisotropy (FA) and lower radial diffusivity in the corpus callosum and the left corona radiata compared to AA homozygotes. Tractographic analysis indicated the involvement of the left internal capsule, left corticospinal tract, and bilateral medial motor cortex. Additionally, the mean FA of the corpus callosum and the corona radiata was negatively correlated with MPQ scales in AA homozygotes, but this correlation was not observed in G allele carriers. No significant genotype difference was found during the pain-free peri-ovulary phase.DiscussionOPRM1 A118G polymorphism may influence the connection between structural integrity and dysmenorrheic pain, where the G allele could impede the pain-regulating effects of the A allele. These novel findings shed light on the underlying mechanisms of both adaptive and maladaptive structural neuroplasticity in PDM, depending on the specific OPRM1 polymorphism.