We examined the stimulus-response profile during single-pulse transcranial magnetic stimulation (TMS) by measuring motor-evoked potentials (MEPs) with electromyographic monitoring and hemodynamic responses with functional magnetic resonance imaging (fMRI) at 3 Tesla. In 16 healthy subjects, single TMS pulses were irregularly delivered to the left primary motor cortex at a mean frequency of 0.15 Hz with a wide range of stimulus intensities. The measurement of MEP proved a typical relationship between stimulus intensity and MEP amplitude in the concurrent TMS-fMRI environment. In the population-level analysis of the suprathreshold stimulation conditions, significant increases in hemodynamic responses were detected in the motor/somatosensory network, reflecting both direct and remote effects of TMS, and also the auditory/cognitive areas, perhaps related to detection of clicks. The stimulus-response profile showed both linear and nonlinear components in the direct and remote motor/somatosensory network. A detailed analysis suggested that the nonlinear components of the motor/somatosensory network activity might be induced by nonlinear recruitment of neurons in addition to sensory afferents resulting from movement. These findings expand our basic knowledge of the quantitative relationship between TMS-induced neural activations and hemodynamic signals measured by neuroimaging techniques.

Depiction of most fiber tracts was improved at 3.0-T DT tractography compared with depiction at 1.5-T tractography.

Although the relationship between schizophrenia spectrum disorder (SSD) and autism spectrum disorder (ASD) has long been debated, it has not yet been fully elucidated. The authors quantified and visualized the relationship between ASD and SSD using dual classifiers that discriminate patients from healthy controls (HCs) based on resting-state functional connectivity magnetic resonance imaging. To develop a reliable SSD classifier, sophisticated machine-learning algorithms that automatically selected SSD-specific functional connections were applied to Japanese datasets from Kyoto University Hospital (N = 170) including patients with chronic-stage SSD. The generalizability of the SSD classifier was tested by 2 independent validation cohorts, and 1 cohort including first-episode schizophrenia. The specificity of the SSD classifier was tested by 2 Japanese cohorts of ASD and major depressive disorder. The weighted linear summation of the classifier’s functional connections constituted the biological dimensions representing neural classification certainty for the disorders. Our previously developed ASD classifier was used as ASD dimension. Distributions of individuals with SSD, ASD, and HCs s were examined on the SSD and ASD biological dimensions. We found that the SSD and ASD populations exhibited overlapping but asymmetrical patterns in the 2 biological dimensions. That is, the SSD population showed increased classification certainty for the ASD dimension but not vice versa. Furthermore, the 2 dimensions were correlated within the ASD population but not the SSD population. In conclusion, using the 2 biological dimensions based on resting-state functional connectivity enabled us to discover the quantified relationships between SSD and ASD.

Recent evidence has suggested that blood oxygenation level-dependent (BOLD) signals convey information about brain circulation via low frequency oscillation of systemic origin (sLFO) that travels through the vascular structure (“lag mapping”). Prompted by its promising application in both physiology and pathology, we examined this signal component using multiple approaches. A total of 30 healthy volunteers were recruited to perform two reproducibility experiments at 3 Tesla using multiband echo planar imaging. The first experiment investigated the effect of denoising and the second was designed to study the effect of subject behavior on lag mapping. The lag map's intersession test-retest reproducibility and image contrast were both diminished by removal of either the neuronal or the non-neuronal (e.g., cardiac, respiratory) components by independent component analysis-based denoising, suggesting that the neurovascular coupling also comprises a part of the BOLD lag structure. The lag maps were, at the same time, robust against local perfusion increases due to visuomotor task and global changes in perfusion induced by breath-holding at the same level as the intrasession reliability. The lag structure was preserved after time-locked averaging to the visuomotor task and breath-holding events, while any preceding signal changes were canceled out for the visuomotor task, consistent with the passive effect of neurovascular coupling in the venous side of the vasculature. These findings support the current assumption that lag mapping primarily reflects vascular structure despite the presence of sLFO perturbation of neuronal or non-neuronal origin and, thus, emphasize the vascular origin of the lag map, encouraging application of BOLD-based blood flow tracking.

The development of an artificial graft requires formulation of biomechanical design criteria. The compliance of artifical grafts, based on the intraluminal pressure-internal diameter (Pi-Di) relationship, was measured by a novel method using a digital X-ray imaging system coupled with an edge detection algorithm and a pressure transducer. The Pi-Di values were obtained from digital angiographic images under continuous inflation of a canine femoral artery anastomosed with an expanded poly(tetrafluoroethylene) (ePTFE) vascular graft as a model vessel with a pressurized contrast medium. The Di at Pi using an NIH Image software specially programmed for the entropy filter method, which enables the detection of the edge of the vessel phantoms of the images, was determined. The Pi-Di relationships showed a "J-shape" curve for the artery, a steeper line with a very low pressure-dependent distensibility for the ePTFE graft, and an intermediate curve for the anastomosis protion. The two indices for the vessel compliance, the stiffness parameter (beta value) and the diameter compliance (Cd), both of which were calculated from the Pi-Di relationships, were 10.6 and 6.8%/mmHg x 10(-2) for the artery, 164 and 0.51%/mmHg x 10(-2) for the ePTFE, and 14.4 and 5.5%/mmHg x 10(-2) for the anastomosis portion, respectively. This method can measure compliance at any portions of the sampling vessel in a single experiment on a real-time basis with very high accuracy, compared with conventional methods, and even in cases of intimal thickening and/or connective tissues-adhered vessels, and may serve to provide information on compliant design criteria of artificial and tissue-engineered graft.