No time for drifting: Comparing performance and applicability of signal detrending algorithms for real-time fMRI.

As a consequence of recent technological advances in the field of functional magnetic resonance imaging (fMRI), results can now be made available in real-time. This allows for novel applications such as online quality assurance of the acquisition, intra-operative fMRI, brain-computer-interfaces, and neurofeedback. To that aim, signal processing algorithms for real-time fMRI must reliably correct signal contaminations due to physiological noise, head motion, and scanner drift. The aim of this study was to compare performance of the commonly used online detrending algorithms exponential moving average (EMA), incremental general linear model (iGLM) and sliding window iGLM (iGLMwindow). For comparison, we also included offline detrending algorithms (i.e., MATLAB's and SPM8's native detrending functions). Additionally, we optimized the EMA control parameter, by assessing the algorithm's performance on a simulated data set with an exhaustive set of realistic experimental design parameters. First, we optimized the free parameters of the online and offline detrending algorithms. Next, using simulated data, we systematically compared the performance of the algorithms with respect to varying levels of Gaussian and colored noise, linear and non-linear drifts, spikes, and step function artifacts. Additionally, using in vivo data from an actual rt-fMRI experiment, we validated our results in a post hoc offline comparison of the different detrending algorithms. Quantitative measures show that all algorithms perform well, even though they are differently affected by the different artifact types. The iGLM approach outperforms the other online algorithms and achieves online detrending performance that is as good as that of offline procedures. These results may guide developers and users of real-time fMRI analyses tools to best account for the problem of signal drifts in real-time fMRI.

Gender transition affects neural correlates of empathy: A resting state functional connectivity study with ultra high-field 7T MR imaging.

Sex-steroid hormones have repeatedly been shown to influence empathy, which is in turn reflected in resting state functional connectivity (rsFC). Cross-sex hormone treatment in transgender individuals provides the opportunity to examine changes to rsFC over gender transition. We aimed to investigate whether sex-steroid hormones influence rsFC patterns related to unique aspects of empathy, namely emotion recognition and description as well as emotional contagion. RsFC data was acquired with 7Tesla magnetic resonance imaging in 24 male-to-female (MtF) and 33 female-to-male (FtM) transgender individuals before treatment, in addition to 33 male- and 44 female controls. Of the transgender participants, 15 MtF and 20 FtM were additionally assessed after 4 weeks and 4 months of treatment. Empathy scores were acquired at the same time-points. MtF differed at baseline from all other groups and assimilated over the course of gender transition in a rsFC network around the supramarginal gyrus, a region central to interpersonal emotion processing. While changes to sex-steroid hormones did not correlate with rsFC in this network, a sex hormone independent association between empathy scores and rsFC was found. Our results underline that 1) MtF transgender persons demonstrate unique rsFC patterns in a network related to empathy and 2) changes within this network over gender transition are likely related to changes in emotion recognition, -description, and -contagion, and are sex-steroid hormone independent.

[Functional magnetic resonance imaging with ultra-high fields]. / Funktionelle Magnetresonanztomographie bei ultrahohen Feldern.

Functional magnetic resonance imaging (fMRI) is currently the primary method for non-invasive functional localization in the brain. With the emergence of MR systems with field strengths of 4 Tesla and above, neuronal activation may be studied with unprecedented accuracy. In this article we present different approaches to use the improved sensitivity and specificity for expanding current fMRT resolution limits in space and time based on several 7 Tesla studies. In addition to the challenges that arise with ultra-high magnetic fields possible solutions will be discussed.