NeuroImage
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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.
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Seizures are increasingly understood to arise from epileptogenic networks across which ictal activity is propagated and sustained. In patients undergoing invasive monitoring for epilepsy surgery, high frequency oscillations have been observed within the seizure onset zone during both ictal and interictal intervals. We hypothesized that the patterns by which high frequency activity is propagated would help elucidate epileptogenic networks and thereby identify network nodes relevant for surgical planning. ⋯ This pattern was observed in both subdural and depth electrode recordings of patients with focal ictal onset, but not in patients with a widely distributed ictal onset. In patients with focal ictal onsets, the patterns of propagation recorded during pre-ictal (up to 5 min immediately preceding ictal onset) and interictal (more than 24h before and after seizures) intervals were very similar to those recorded during seizures. The ability to characterize epileptogenic networks from interictal recordings could have important clinical implications for epilepsy surgery planning by reducing the need for prolonged invasive monitoring to record spontaneous seizures.
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The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA) and increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. ⋯ Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice.