Confirmation of resting-state BOLD fluctuations in the human brainstem and spinal cord after identification and removal of physiological noise.

PURPOSE: Resting-state functional MRI (rs-fMRI) has been used to investigate networks within the cortex, but its use in the brainstem (BS) and spinal cord (SC) has been limited. This region presents challenges for fMRI, partly because of sources of physiological noise. This study aims to quantify noise contributions to rs-fMRI, and to obtain evidence of resting-state blood oxygenation level-dependent (BOLD) fluctuations. METHODS: Resting-state-fMRI data were obtained from the BS/SC in 16 participants, at 3 Tesla, with T2 -weighted single-shot fast spin-echo imaging. The peripheral pulse, respiration, and expired CO2 were recorded continuously. Physiological noise was modeled from these recordings, movement parameters, and white matter regions. Model fits were then subtracted from the data. BOLD contributions were then investigated through connectivity. RESULTS: Bulk motion was the largest contributor to the signal variance (19% of the total), followed by cardiac-related motion (14%), nonspecific signal variations detected in white matter (10%), respiratory-related motion (2.6%), and end-tidal CO2 variations (0.7%). After noise was removed, significant left-right connectivity was detected in the SC dorsal horns and ventral horns. CONCLUSIONS: Resting-state BOLD fluctuations are demonstrated in the SC, as are the dominant noise contributions. These findings are an essential step toward establishing rs-fMRI in the BS/SC. Magn Reson Med 78:2149-2156, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Opposing brain signatures of sleep in task-based and resting-state conditions.

Sleep and depression have a complex, bidirectional relationship, with sleep-associated alterations in brain dynamics and structure impacting a range of symptoms and cognitive abilities. Previous work describing these relationships has provided an incomplete picture by investigating only one or two types of sleep measures, depression, or neuroimaging modalities in parallel. We analyze the correlations between brainwide neural signatures of sleep, cognition, and depression in task and resting-state data from over 30,000 individuals from the UK Biobank and Human Connectome Project. Neural signatures of insomnia and depression are negatively correlated with those of sleep duration measured by accelerometer in the task condition but positively correlated in the resting-state condition. Our results show that resting-state neural signatures of insomnia and depression resemble that of rested wakefulness. This is further supported by our finding of hypoconnectivity in task but hyperconnectivity in resting-state data in association with insomnia and depression. These observations dispute conventional assumptions about the neurofunctional manifestations of hyper- and hypo-somnia, and may explain inconsistent findings in the literature.

Mapping Inter-individual Functional Connectivity Variability in TMS Targets for Major Depressive Disorder.

Transcranial magnetic stimulation (TMS) is an emerging alternative to existing treatments for major depressive disorder (MDD). The effects of TMS on both brain physiology and therapeutic outcomes are known to be highly variable from subject to subject, however. Proposed reasons for this variability include individual differences in neurophysiology, in cortical geometry, and in brain connectivity. Standard approaches to TMS target site definition tend to focus on coordinates or landmarks within the individual brain regions implicated in MDD, such as the dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC). Additionally considering the network connectivity of these sites (i.e., the wider set of brain regions that may be mono- or poly-synaptically activated by TMS stimulation) has the potential to improve subject-specificity of TMS targeting and, in turn, improve treatment outcomes. In this study, we looked at the functional connectivity (FC) of dlPFC and OFC TMS targets, based on induced electrical field (E-field) maps, estimated using the SimNIBS library. We hypothesized that individual differences in spontaneous functional brain dynamics would contribute more to downstream network engagement than individual differences in cortical geometry (i.e., E-field variability). We generated individualized E-field maps on the cortical surface for 121 subjects (67 female) from the Human Connectome Project database using tetrahedral head models generated from T1- and T2-weighted MR images. F3 and Fp1 electrode positions were used to target the left dlPFC and left OFC, respectively. We analyzed inter-subject variability in the shape and location of these TMS target E-field patterns, their FC, and the major functional networks to which they belong. Our results revealed the key differences in TMS target FC between the dlPFC and OFC, and also how this connectivity varies across subjects. Three major functional networks were targeted across the dlPFC and OFC: the ventral attention, fronto-parietal and default-mode networks in the dlPFC, and the fronto-parietal and default mode networks in the OFC. Inter-subject variability in cortical geometry and in FC was high. Our analyses showed that the use of normative neuroimaging reference data (group-average or representative FC and subject E-field) allows prediction of which networks are targeted, but fails to accurately quantify the relative loading of TMS targeting on each of the principal networks. Our results characterize the FC patterns of canonical therapeutic TMS targets, and the key dimensions of their variability across subjects. The high inter-individual variability in cortical geometry and FC, leading to high variability in distributions of targeted brain networks, may account for the high levels of variability in physiological and therapeutic TMS outcomes. These insights should, we hope, prove useful as part of the broader effort by the psychiatry, neurology, and neuroimaging communities to help improve and refine TMS therapy, through a better understanding of the technology and its neurophysiological effects.

Investigation of Resting-State BOLD Networks in the Human Brainstem and Spinal Cord.

Resting-state functional magnetic resonance imaging (rs-fMRI) has been used to investigate networks within the cortex and has also provided some insight into the networks present in the brainstem (BS) and spinal cord (SC). The purpose of this study was to investigate resting-state blood oxygenation-level dependent (BOLD) fluctuations in the BS/SC and to identify resting-state networks (RSNs) across these regions. Resting-state BOLD fMRI data were obtained from the entire BS and cervical SC in 16 healthy participants, at 3 T, with T2-weighted single-shot fast spin-echo imaging. Data were spatially normalized and processed to remove physiological noise. Cluster-cluster functional connectivity was investigated across the entire 3D region by means of temporal correlations, and structural equation modeling (SEM) was used to investigate RSNs. Extensive connectivity was observed within and across BS and SC regions, with connections spanning up to 120 mm, although shorter connections were more prevalent. SEM results revealed extensive brainstem-cord connectivity that included specific anatomical regions within the brainstem. The results indicate the presence of a complex resting-state network which is highly interconnected in the spinal cord. Known anatomical connections between cortical and BS regions support the conclusion that the observed resting-state BOLD fluctuations in the BS/SC may be related to autonomic regulation. Future studies are required to further investigate these resting-state BOLD networks.