NeuroImage
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Emotions are an indispensable part of our mental life. The term emotion regulation refers to those processes that influence the generation, the experience and the expression of emotions. There is a great variety of strategies to regulate emotions efficiently, which are used in daily life and that have been investigated by cognitive neuroscience. ⋯ Compared to the other regulation strategies, Reinterpretation specifically recruited a different control network comprising left ventrolateral prefrontal cortex and orbitofrontal gyrus and was not effective in downregulation of the amygdala. We conclude that Detachment, Distraction and Expressive Suppression recruit very similar emotion regulation networks, whereas Reinterpretation is associated with activation of a qualitatively different network, making this regulation strategy a special one. Notably, Reinterpretation also proved to be the least effective strategy in neural terms, as measured by downregulation of amygdala activation.
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The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a powerful tool for causally investigating cortical mechanisms and networks. However, various artefacts contaminate TMS-EEG recordings, particularly over regions such as the dorsolateral prefrontal cortex (DLPFC). The aim of this study was to substantiate removal of artefacts from TMS-EEG recordings following stimulation of the DLPFC and motor cortex using independent component analysis (ICA). ⋯ Various different artefacts contaminate TMS-EEG recordings over the DLPFC and motor cortex. However, these artefacts can be removed with apparent minimal impact on neural activity using ICA, allowing the study of TMS-evoked cortical network properties.
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The dorsolateral prefrontal cortex (dlPFC) has often been suggested as a key modulator of emotional stimulus appraisal and regulation. Therefore, in clinical trials, it is one of the most frequently targeted regions for non-invasive brain stimulation such as repetitive transcranial magnetic stimulation (rTMS). In spite of various encouraging reports that demonstrate beneficial effects of rTMS in anxiety disorders, psychophysiological studies exploring the underlying neural mechanisms are sparse. ⋯ Moreover, increased fear-specific activation was found in the right TPJ area in a time-interval between 110 and 170 ms. These neurophysiological effects were reflected in slowed reaction times for fearful, but not for neutral faces in a facial expression identification task while there was no such effect on a gender discrimination control task. Our study confirms the specific and important role of the dlPFC in regulation of early emotional attention and encourages future clinical research to use minimal invasive methods such as transcranial magnetic (TMS) or direct current stimulation (tDCS).
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Multicenter Study
Multisite longitudinal reliability of tract-based spatial statistics in diffusion tensor imaging of healthy elderly subjects.
Large-scale longitudinal neuroimaging studies with diffusion imaging techniques are necessary to test and validate models of white matter neurophysiological processes that change in time, both in healthy and diseased brains. The predictive power of such longitudinal models will always be limited by the reproducibility of repeated measures acquired during different sessions. At present, there is limited quantitative knowledge about the across-session reproducibility of standard diffusion metrics in 3T multi-centric studies on subjects in stable conditions, in particular when using tract based spatial statistics and with elderly people. ⋯ The atlas-based ROI analysis showed that the mean reproducibility errors largely remained in the 2-4% range for FA and AD and 2-6% for MD and RD, averaged across ROIs. Our results show reproducibility values comparable to those reported in studies using a smaller number of MRI scanners, slightly different DTI protocols and mostly younger populations. We therefore show that the acquisition and analysis protocols used are appropriate for multi-site experimental scenarios.
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Advances in image segmentation of magnetic resonance images (MRI) have demonstrated that multi-atlas approaches improve segmentation over regular atlas-based approaches. These approaches often rely on a large number of manually segmented atlases (e.g. 30-80) that take significant time and expertise to produce. We present an algorithm, MAGeT-Brain (Multiple Automatically Generated Templates), for the automatic segmentation of the hippocampus that minimises the number of atlases needed whilst still achieving similar agreement to multi-atlas approaches. Thus, our method acts as a reliable multi-atlas approach when using special or hard-to-define atlases that are laborious to construct. ⋯ We demonstrate that MAGeT-Brain produces consistent whole hippocampal segmentations using only 9 atlases, or fewer, with various hippocampal definitions, disease populations, and image acquisition types. Additionally, we show that MAGeT-Brain identifies hippocampal subfields in standard 3T T1-weighted images with overlap scores comparable to competing methods.