In vivo structural connectome of arousal and motor brainstem nuclei by 7 Tesla and 3 Tesla MRI

Brainstem nuclei are key participants in the generation and maintenance of arousal, which is a basic function that modulates wakefulness/sleep, autonomic responses, affect, attention, and consciousness. Their mechanism is based on diffuse pathways ascending from the brainstem to the thalamus, hypothalamus, basal forebrain and cortex. Several arousal brainstem nuclei also participate in motor functions that allow humans to respond and interact with the surrounding through a multipathway motor network. Yet, little is known about the structural connectivity of arousal and motor brainstem nuclei in living humans. This is due to the lack of appropriate tools able to accurately visualize brainstem nuclei in conventional imaging. Using a recently developed in vivo probabilistic brainstem nuclei atlas and 7 Tesla diffusion-weighted images (DWI), we built the structural connectome of 18 arousal and motor brainstem nuclei in living humans (n = 19). Furthermore, to investigate the translatability of our findings to standard clinical MRI, we acquired 3 Tesla DWI on the same subjects, and measured the association of the connectome across scanners. For both arousal and motor circuits, our results showed high connectivity within brainstem nuclei, and with expected subcortical and cortical structures based on animal studies. The association between 3 Tesla and 7 Tesla connectivity values was good, especially within the brainstem. The resulting structural connectome might be used as a baseline to better understand arousal and motor functions in health and disease in humans

Structural connectivity of autonomic, pain, limbic, and sensory brainstem nuclei in living humans based on 7 Tesla and 3 Tesla MRI

Autonomic, pain, limbic, and sensory processes are mainly governed by the central nervous system, with brainstem nuclei as relay centers for these crucial functions. Yet, the structural connectivity of brainstem nuclei in living humans remains understudied. These tiny structures are difficult to locate using conventional in vivo MRI, and ex vivo brainstem nuclei atlases lack precise and automatic transformability to in vivo images. To fill this gap, we mapped our recently developed probabilistic brainstem nuclei atlas developed in living humans to high-spatial resolution (1.7 mm isotropic) and diffusion weighted imaging (DWI) at 7 Tesla in 20 healthy participants. To demonstrate clinical translatability, we also acquired 3 Tesla DWI with conventional resolution (2.5 mm isotropic) in the same participants. Results showed the structural connectome of 15 autonomic, pain, limbic, and sensory (including vestibular) brainstem nuclei/nuclei complex (superior/inferior colliculi, ventral tegmental area-parabrachial pigmented, microcellular tegmental-parabigeminal, lateral/medial parabrachial, vestibular, superior olivary, superior/inferior medullary reticular formation, viscerosensory motor, raphe magnus/pallidus/obscurus, parvicellular reticular nucleus-alpha part), derived from probabilistic tractography computation. Through graph measure analysis, we identified network hubs and demonstrated high intercommunity communication in these nuclei. We found good (r = .5) translational capability of the 7 Tesla connectome to clinical (i.e., 3 Tesla) datasets. Furthermore, we validated the structural connectome by building diagrams of autonomic/pain/limbic connectivity, vestibular connectivity, and their interactions, and by inspecting the presence of specific links based on human and animal literature. These findings offer a baseline for studies of these brainstem nuclei and their functions in health and disease, including autonomic dysfunction, chronic pain, psychiatric, and vestibular disorders

Challenges for detection of neuronal currents by MRI

Neuronal current MRI (nc-MRI) is an imaging method that directly maps magnetic field changes caused by neuronal currents with, at the same time, a high spatial and temporal resolution. A viable nc-MRI method would be of great benefit, both for the study of human brain function and for clinical applications in the field of epilepsy, especially for the noninvasive presurgical mapping of epileptogenic foci. A survey of fundamental issues in nc-MRI is reviewed, and challenges for future developments of the method are described within this context. Particularly, an overview of the models for signal generation is given, and the origin and physiology of different sources of neuronal currents are described. Prospects for predicting neuronal currents by electromagnetic field mapping and using this information, both a priori and a posteriori, for nc-MRI are considered. Ways of increasing specificity in nc-MRI by minimizing secondary hemodynamic and metabolic effects are described as well as means of optimizing the nc-MRI method for pushing the detection limit. Previously published works are described within these categories and future directions for nc-MRI are proposed. (c) 2006 Elsevier Inc. All rights reserved

Ultra High Field fMRI of Human Superior Colliculi Activity during Affective Visual Processing

Research on rodents and non-human primates has established the involvement of the superior colliculus in defensive behaviours and visual threat detection. The superior colliculus has been well-studied in humans for its functional roles in saccade and visual processing, but less is known about its involvement in affect. In standard functional MRI studies of the human superior colliculus, it is challenging to discern activity in the superior colliculus from activity in surrounding nuclei such as the periaqueductal gray due to technological and methodological limitations. Employing high-field strength (7 Tesla) fMRI techniques, this study imaged the superior colliculus at high (0.75 mm isotropic) resolution, which enabled isolation of the superior colliculus from other brainstem nuclei. Superior colliculus activation during emotionally aversive image viewing blocks was greater than that during neutral image viewing blocks. These findings suggest that the superior colliculus may play a role in shaping subjective emotional experiences in addition to its visuomotor functions, bridging the gap between affective research on humans and non-human animals

The effect of physiological noise in phase functional magnetic resonance imaging: from blood oxygen level-dependent effects to direct detection of neuronal currents

Recently, the possibility to use both magnitude and phase image sets for the statistical evaluation of fMRI has been proposed, with the prospective of increasing both statistical power and the spatial specificity. In the present work, several issues that affect the spatial and temporal stability in fMRI phase time series in the presence of physiologic noise processes are reviewed, discussed and illustrated by experiments performed at 3 T. The observed phase value is a fingerprint of the underlying voxel averaged magnetic field variations. Those related to physiological processes can be considered static or dynamic in relation to the temporal scale of a 2D acquisition and will play out on different spatial scales as well: globally across the entire images slice, and locally depending on the constituents and their relative fractions inside the MRI voxel. The 'static' respiration-induced effects lead to magneto-mechanic scan-to-scan variations in the global magnetic field but may also contribute to local BOLD fluctuations due to respiration-related variations in arterial carbon dioxide. Likewise, the 'dynamic' cardiac-related effects will lead to global susceptibility effects caused by pulsatile motion of the brain as well as local blood pressure-related changes in BOLD and changes in blood flow velocity. Finally, subject motion may lead to variations in both local and global tissue susceptibility that will be especially pronounced close to air cavities. Since dissimilar manifestations of physiological processes can be expected in phase and in magnitude images, a direct relationship between phase and magnitude scan-to-scan fluctuations cannot be assumed a priori. Therefore three different models were defined for the phase stability, each dependent on the relation between phase and magnitude variations and the best will depend on the underlying noise processes. By experiments on healthy volunteers at rest, we showed that phase stability depends on the type of post-processing and can be improved by reducing the low-frequency respiration-induced mechano-magnetic effects. Although the manifestations of physiological noise were in general more pronounced in phase than in magnitude images, due to phase wraps and global Bo effects, we Suggest that a phase stability similar to that found in magnitude could theoretically be achieved by adequate correction methods. Moreover, as suggested by out-experimental data regarding BOLD-related phase effects, phase stability could even supersede magnitude stability in voxels covering dense microvascular networks with BOLD-related fluctuations as the dominant noise contributor. In the interest of the quality of both BOLD-based and nc-MRI methods, future studies are required to find alternative methods that can improve phase stability, designed to match the temporal and spatial scale of the underlying neuronal activity. (c) 2008 Elsevier Inc. All rights reserved

Phase stability in fMRI time series: Effect of noise regression, off-resonance correction and spatial filtering techniques

Although the majority of fMRI studies exploit magnitude changes only, there is an increasing interest regarding the potential additive information conveyed by the phase signal. This integrated part of the complex number furnished by the MR scanners can also be used for exploring direct detection of neuronal activity and for thermography. Few studies have explicitly addressed the issue of the available signal stability in the context of phase time-series, and therefore we explored the spatial pattern of frequency specific phase fluctuations, and evaluated the effect of physiological noise components (heart beat and respiration) on the phase signal. Three categories of retrospective noise reduction techniques were explored and the temporal signal stability was evaluated in terms of a physiologic noise model, for seven fMRI measurement protocols in eight healthy subjects at 3T, for segmented CSF, gray and white matter voxels. We confirmed that for most processing methods, an efficient use of the phase information is hampered by the fact that noise from physiological and instrumental sources contributes significantly more to the phase than to the magnitude instability. Noise regression based on the phase evolution of the central k-space point, RETROICOR, or an orthonormalized combination of these were able to reduce their impact, but without bringing phase stability down to levels expected from the magnitude signal. Similar results were obtained after targeted removal of scan-to-scan variations in the bulk magnetic field by the dynamic off-resonance in k-space (DORK) method and by the temporal off-resonance alignment of single-echo time series technique (TOAST). We found that spatial high-pass filtering was necessary, and in vivo a Gaussian filter width of 20mm was sufficient to suppress physiological noise and bring the phase fluctuations to magnitude levels. Stronger filters brought the fluctuations down to levels dictated by thermal noise contributions, and for 62.5mm 3 voxels the phase stability was as low as 5mrad (0.27°). In conditions of low SNR o and high temporal sampling rate (short TR); we achieved an upper bound for the phase instabilities at 0.0017ppm, which is close to the dHb contribution to the GM/WM phase contrast. © 2011 Elsevier Inc

Methods using recurrence quantification analysis to analyze and generate images.

Methods for identifying and quantifying recurrent and deterministic patterns in digital images are provided. The methods, which are based on Recurrence Quantification Analysis (RQA), generate similarity or dissimilarity distance matrices for digital images that may be used to calculate a variety of quantitative characteristics for the images. Also provided are methods for identifying and imaging spatial distributions of time variable signals generated from dynamic systems. In these methods a time variable signal is recorded for a plurality of area or volume elements into which a dynamic system has been sectioned and RQA is used to calculate one or more RQA variables for each of the area or volume elements, which may then be used to generate a two or three dimensional image displaying the spatial distribution of the RQA variables across the system

Early anti-correlated BOLD signal changes of physiologic origin

Negative BOLD signals that are synchronous with resting state fluctuations have been observed in large vessels in the cortical sulci and surrounding the ventricles. In this study, we investigated the origin of these negative BOLD signals by applying a Cued Deep Breathing (CDB) task to create transient hypocapnia and a resultant global fMRI signal decrease. We hypothesized that a global stimulus would amplify the effect in large vessels and that using a global negative (vasoconstrictive) stimulus would test whether these voxels exhibit either inherently negative or simply anti-correlated BOLD responses. Significantly anti-correlated, but positive, BOLD signal changes during respiratory challenges were identified in voxels primarily located near edges of brain spaces containing CSF. These positive BOLD responses occurred earlier than the negative CDB response across most of gray matter voxels. These findings confirm earlier suggestions that in some brain regions, local, fractional changes in CSF volume may overwhelm BOLD-related signal changes, leading to signal anti-correlation. We show that regions with CDB anti-correlated signals coincide with most, but not all, of the regions with negative BOLD signal changes observed during a visual and motor stimulus task. Thus, the addition of a physiological challenge to fMRI experiments can help identify which negative BOLD signals are passive physiological anti-correlations and which may have a putative neuronal origin