Joint-embeddings reveal functional differences in default-mode network architecture between marmosets and humans

Brain inflammation co-localizes highly with tau in mild cognitive impairment due to early-onset Alzheimer's disease

Brain inflammation, with an increased density of microglia and macrophages, is an important component of Alzheimer's disease and a potential therapeutic target. However, it is incompletely characterized, particularly in patients whose disease begins before the age of 65 years and, thus, have few co-pathologies. Inflammation has been usefully imaged with translocator protein (TSPO) PET, but most inflammation PET tracers cannot image subjects with a low-binder TSPO rs6971 genotype. In an important development, participants with any TSPO genotype can be imaged with a novel tracer, 11C-ER176, that has a high binding potential and a more favourable metabolite profile than other TSPO tracers currently available. We applied 11C-ER176 to detect brain inflammation in mild cognitive impairment (MCI) caused by early-onset Alzheimer's disease. Furthermore, we sought to correlate the brain localization of inflammation, volume loss, elevated amyloid-β (Aβ)and tau. We studied brain inflammation in 25 patients with early-onset amnestic MCI (average age 59 ± 4.5 years, 10 female) and 23 healthy controls (average age 65 ± 6.0 years, 12 female), both groups with a similar proportion of all three TSPO-binding affinities. 11C-ER176 total distribution volume (VT), obtained with an arterial input function, was compared across patients and controls using voxel-wise and region-wise analyses. In addition to inflammation PET, most MCI patients had Aβ (n = 23) and tau PET (n = 21). For Aβ and tau tracers, standard uptake value ratios were calculated using cerebellar grey matter as region of reference. Regional correlations among the three tracers were determined. Data were corrected for partial volume effect. Cognitive performance was studied with standard neuropsychological tools. In MCI caused by early-onset Alzheimer's disease, there was inflammation in the default network, reaching statistical significance in precuneus and lateral temporal and parietal association cortex bilaterally, and in the right amygdala. Topographically, inflammation co-localized most strongly with tau (r = 0.63 ± 0.24). This correlation was higher than the co-localization of Aβ with tau (r = 0.55 ± 0.25) and of inflammation with Aβ (0.43 ± 0.22). Inflammation co-localized least with atrophy (-0.29 ± 0.26). These regional correlations could be detected in participants with any of the three rs6971 TSPO polymorphisms. Inflammation in Alzheimer's disease-related regions correlated with impaired cognitive scores. Our data highlight the importance of inflammation, a potential therapeutic target, in the Alzheimer's disease process. Furthermore, they support the notion that, as shown in experimental tissue and animal models, the propagation of tau in humans is associated with brain inflammation.

Decomposing cortical activity through neuronal tracing connectome-eigenmodes in marmosets

Deciphering the complex relationship between neuroanatomical connections and functional activity in primate brains remains a daunting task, especially regarding the influence of monosynaptic connectivity on cortical activity. Here, we investigate the anatomical-functional relationship and decompose the neuronal-tracing connectome of marmoset brains into a series of eigenmodes using graph signal processing. These cellular connectome eigenmodes effectively constrain the cortical activity derived from resting-state functional MRI, and uncover a patterned cellular-functional decoupling. This pattern reveals a spatial gradient from coupled dorsal-posterior to decoupled ventral-anterior cortices, and recapitulates micro-structural profiles and macro-scale hierarchical cortical organization. Notably, these marmoset-derived eigenmodes may facilitate the inference of spontaneous cortical activity and functional connectivity of homologous areas in humans, highlighting the potential generalizing of the connectomic constraints across species. Collectively, our findings illuminate how neuronal-tracing connectome eigenmodes constrain cortical activity and improve our understanding of the brain's anatomical-functional relationship.

A reappraisal of the default mode and frontoparietal networks in the common marmoset brain

In recent years the common marmoset homolog of the human default mode network (DMN) has been a hot topic of discussion in the marmoset research field. Previously, the posterior cingulate cortex regions (PGM, A19M) and posterior parietal cortex regions (LIP, MIP) were defined as the DMN, but some studies claim that these form the frontoparietal network (FPN). We restarted from a neuroanatomical point of view and identified two DMN candidates: Comp-A (which has been called both the DMN and FPN) and Comp-B. We performed GLM analysis on auditory task-fMRI and found Comp-B to be more appropriate as the DMN, and Comp-A as the FPN. Additionally, through fingerprint analysis, a DMN and FPN in the tasking human was closer to the resting common marmoset. The human DMN appears to have an advanced function that may be underdeveloped in the common marmoset brain.

Mapping and comparing fMRI connectivity networks across species

Technical advances in neuroimaging, notably in fMRI, have allowed distributed patterns of functional connectivity to be mapped in the human brain with increasing spatiotemporal resolution. Recent years have seen a growing interest in extending this approach to rodents and non-human primates to understand the mechanism of fMRI connectivity and complement human investigations of the functional connectome. Here, we discuss current challenges and opportunities of fMRI connectivity mapping across species. We underscore the critical importance of physiologically decoding neuroimaging measures of brain (dys)connectivity via multiscale mechanistic investigations in animals. We next highlight a set of general principles governing the organization of mammalian connectivity networks across species. These include the presence of evolutionarily conserved network systems, a dominant cortical axis of functional connectivity, and a common repertoire of topographically conserved fMRI spatiotemporal modes. We finally describe emerging approaches allowing comparisons and extrapolations of fMRI connectivity findings across species. As neuroscientists gain access to increasingly sophisticated perturbational, computational and recording tools, cross-species fMRI offers novel opportunities to investigate the large-scale organization of the mammalian brain in health and disease.

Incorporation of Brain Connectomics for Stereotactic Radiosurgery Treatment Planning

BACKGROUND AND IMPORTANCE

Neurosurgeons have integrated neuroanatomy-based tractography to avoid critical structures during dose planning. However, they have yet to integrate more comprehensive connectome networks for radiosurgical planning.

CLINICAL PRESENTATION

A young man presented with a Spetzler-Martin Grade 3 right temporal arteriovenous malformation.

DISCUSSION

As proof of concept, we incorporated connectomic networks including default mode network, optic radiation and central executive network into the Gamma Knife radiosurgical treatment planning workflow. Connectome networks were created from T1 anatomic and diffusion-weighted images magnetic resonance images using Quicktome software. The resulting networks were voxel-encoded in the magnetic resonance images, imported into GammaPlan, and segmented by image thresholding. The GammaPlan Lightning optimizer was used to create radiosurgical plans with a dose of 20 Gy to the 50% isodose line delivered to the arteriovenous malformation nidus both with and without treating these networks as risk structures. When taking into account the connectome networks, a maximum dose restriction of 14 Gy was placed on each network during lightning dose planning. With default mode network, optic radiation, and central executive network as risk structures, the maximum dose and V 12Gy were reduced by 23.4% and 88.3%, 20% and 34.3%, and 29.8% and 63.2%, respectively.

CONCLUSION

We were able to incorporate connectomes into radiosurgical dose planning approaches. This allowed for dose reductions to the networks while still achieving delivery of a therapeutic dose to the target volume.