Kavita Singh

The brainstem is vulnerable to aging and prodromal synucleinopathy, yet whether these processes disrupt shared or distinct functional pathways linking the brainstem to the cortex remains unknown. Using high-resolution 7-Tesla fMRI, we mapped connectivity between 58 brainstem nuclei and cortical regions in young adults, older adults and individuals with isolated REM sleep behavior disorder (iRBD), a prodromal synucleinopathy. Long-range brainstem-cortical connectivity weakened with aging and further in iRBD. However, the two conditions affected distinct systems: aging involved arousal- and cognition-related nuclei and association cortex, whereas iRBD involved sleep- and autonomic-related nuclei and extended to sensory-motor cortex. These alterations were associated with distinct neurophysiological, metabolic and neurotransmitter architectures and spatial transcriptomic signatures. Brainstem-cortical connectivity also followed the cortical unimodal-transmodal hierarchy, with reduced differentiation in aging. Independent 3-Tesla data reproduced the broader connectivity patterns. Together, our findings reveal shared and distinct multiscale patterns of brainstem pathway vulnerability in aging and prodromal synucleinopathy.

Background: Cognitive impairment with age remains undetected until it interferes daily life activity or presents dementia symptoms. In the US, 61% of dementia population is not diagnosed, which is in part due to limited sensitivity of clinical neuroimaging modalities in assessing early gray matter (GM) changes. Here we look at microstructural changes in GM using mean apparent propagator (MAP‐MRI) in cognitively underperforming (CU) and healthy aging (HA) cohorts, grouped according to their cognitive performance based on the NIH Toolbox.Methods: 725 subjects aged 36 to 90 years were included in this study using the Human Connectome Project‐Aging (HCP‐A) imaging dataset (T1w, multi‐shell diffusion ‐dMRI). Nine NIH Toolbox measures were used to classify CU and HA population groups (Figure 1). Each test score was z‐normalized and subjects in the lower and upper 50^th percentile in all 9 tests were considered as CU and HA, respectively. Diffusion data was processed using TORTOISE dMRI processing package. Corrected DWIs were processed using MAP‐MRI, which yielded the following parameters: return to origin/axis/plane probability (RTOP, RTAP, RTPP), non‐Gaussianity (NG), and propagator anisotropy (PA) (Figure 2a). The T1w images were processed generating 125 SLANT cortical and subcortical regions of interest (Figure 2b). Two‐way ANOVA was used to investigate group differences while accounting for age, sex, education and site. All statistical analysis was done in Matlab2022b.Results: The list of tests and respective scores of the two groups is provided in Figure 1. Zero‐displacement probabilities were more sensitive in detecting group differences compared to NG and PA. The two groups displayed notable differences in the following brain regions: the operculum, involved in visuospatial cognition; the precuneus, key to memory retrieval; and the posterior cingulate, which plays a role in processing speed, executive function, and memory. Additionally, the auditory and sensory‐related areas exhibited significant variations, aligning with expectations. These group differences are shown in Figure 3.Conclusion: This study underscores the common occurrence of cognitive aging among the healthy population and demonstrates that MAP‐MRI is a valuable tool for assessing GM microstructural changes, particularly when comparing these changes to those observed in resilient aging populations.

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.

Despite remarkable advances in mapping the functional connectivity of the cortex, the functional connectivity of subcortical regions is understudied in living humans. This is the case for brainstem nuclei that control vital processes, such as autonomic, limbic, nociceptive and sensory functions. This is because of the lack of precise brainstem nuclei localization, of adequate sensitivity and resolution in the deepest brain regions, as well as of optimized processing for the brainstem. To close the gap between the cortex and the brainstem, on 20 healthy subjects, we computed a correlation-based functional connectome of 15 brainstem nuclei involved in autonomic, limbic, nociceptive, and sensory function (superior and inferior colliculi, ventral tegmental area-parabrachial pigmented nucleus complex, microcellular tegmental nucleus-prabigeminal nucleus complex, lateral and medial parabrachial nuclei, vestibular and superior olivary complex, superior and inferior medullary reticular formation, viscerosensory motor nucleus, raphe magnus, pallidus, and obscurus, and parvicellular reticular nucleus – alpha part) with the rest of the brain. Specifically, we exploited 1.1mm isotropic resolution 7 Tesla resting-state fMRI, ad-hoc coregistration and physiological noise correction strategies, and a recently developed probabilistic template of brainstem nuclei. Further, we used 2.5mm isotropic resolution resting-state fMRI data acquired on a 3 Tesla scanner to assess the translatability of our results to conventional datasets. We report highly consistent correlation coefficients across subjects, confirming available literature on autonomic, limbic, nociceptive and sensory pathways, as well as high interconnectivity within the central autonomic network and the vestibular network. Interestingly, our results showed evidence of vestibulo-autonomic interactions in line with previous work. Comparison of 7 Tesla and 3 Tesla findings showed high translatability of results to conventional settings for brainstem-cortical connectivity and good yet weaker translatability for brainstem-brainstem connectivity. The brainstem functional connectome might bring new insight in the understanding of autonomic, limbic, nociceptive and sensory function in health and disease.

Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor function in living humans in health and disease.

Introduction: The mesencephalic reticular formation, isthmic reticular formation, microcellular tegmental nucleus, ventral tegmental area nuclei and linear raphe nuclei are small brainstem regions crucially involved in arousal, sleep, and reward. Yet, these nuclei are difficult to identify in magnetic resonance imaging (MRI) of living humans. In the current work we developed a probabilistic atlas of these brainstem nuclei in living humans, using non-invasive ultra-high field MRI. Methods: In 12 healthy subjects we acquired single-subject multi-contrast (diffusion and T2-weighted) 1.1mm-isotropic resolution 7 Tesla MRI images. After pre-processing and alignment to stereotactic space, these images were used to delineate in each subject the nuclei of interest based on the image contrast as well as on neighboring nuclei and landmarks. Nuclei labels were averaged across subjects to yield probabilistic labels. The latter were further validated by assessment of the label inter-rater agreement, internal consistency and volume. Results: Labels were delineated for each nucleus with good overlap across subjects. The inter-rater agreement and internal consistency were below (p < 10-8) the linear spatial imaging resolution (1.1 mm), thus validating the generated probabilistic atlas labels. The volume of our labels did not differ from literature volumes (p < 0.05) further validating our atlas. Discussion and Conclusion: The probabilistic atlas of these five mesopontine nuclei expands current in vivo brainstem nuclei atlases and can be used as a tool to identify the location of these areas in conventional (e.g. 3Tesla) images. This might serve to unravel the brainstem structure to function link and thus improve clinical outcome.

The lateral parabrachial nucleus, medial parabrachial nucleus, vestibular nuclei complex, and medullary viscero-sensory-motor (VSM) nuclei complex (the latter including among others the solitary nucleus, vagus nerve nucleus, and hypoglossal nucleus) are anatomically and functionally connected brainstem gray matter structures that convey signals across multiple modalities between the brain and the spinal cord to regulate vital bodily functions. It is remarkably difficult to precisely extrapolate the location of these nuclei from ex vivo atlases to conventional 3 Tesla in vivo images; thus, a probabilistic brainstem template in stereotaxic neuroimaging space in living humans is needed. We delineated these nuclei using single-subject high contrast 1.1 mm isotropic resolution 7 Tesla MRI images. After precise coregistration of nuclei labels to stereotaxic space, we generated a probabilistic template of their anatomical locations. Finally, we validated the nuclei labels in the template by assessing their inter-rater agreement, consistency across subjects and volumes. We also performed a preliminary comparison of their location and microstructural properties to histologic sections of a postmortem human brainstem specimen. In future, the resulting probabilistic template of these brainstem nuclei in stereotaxic space may assist researchers and clinicians in evaluating autonomic, vestibular and VSM nuclei structure, function and connectivity in living humans using conventional 3 Tesla MRI scanners.

The lateral parabrachial nucleus, medial parabrachial nucleus, vestibular nuclei complex and medullary viscero-sensory-motor nuclei complex (the latter including among others the solitary nucleus, vagus nerve nucleus, and hypoglossal nucleus) are anatomically and functionally connected brainstem gray-matter structures that convey signals across multiple modalities between the brain and the spinal cord to regulate vital bodily functions. It is remarkably difficult to precisely extrapolate the location of these nuclei from ex vivo atlases to conventional 3 Tesla in vivo images; thus, a probabilistic brainstem atlas in stereotaxic neuroimaging space in living humans is needed. We delineated these nuclei using single-subject high contrast 1.1 mm isotropic resolution 7 Tesla MRI images. After precise coregistration of nuclei labels to stereotaxic space, we generated a probabilistic atlas of their anatomical locations. Finally, we validated the nuclei labels in the atlas by assessing their inter-rater agreement, consistency across subjects and volumes. We also performed a preliminary comparison of their location and microstructural properties to histologic sections of a postmortem human brainstem specimen. In future, the resulting probabilistic atlas of these brainstem nuclei in stereotaxic space may assist researchers and clinicians in evaluating autonomic, vestibular and viscero-sensory-motor nuclei structure, function and connectivity in living humans using conventional 3 Tesla MRI scanners.