Macroscale coupling between structural and effective connectivity in the mouse brain.

Exploring how the emergent functional connectivity (FC) relates to the underlying anatomy (structural connectivity, SC) is one of the major goals of modern neuroscience. At the macroscale level, no one-to-one correspondence between structural and functional links seems to exist. And we posit that to better understand their coupling, two key aspects should be considered: the directionality of the structural connectome and limitations in explaining networks functions through an undirected measure such as FC. Here, we employed an accurate directed SC of the mouse brain acquired through viral tracers and compared it with single-subject effective connectivity (EC) matrices derived from a dynamic causal model (DCM) applied to whole-brain resting-state fMRI data. We analyzed how SC deviates from EC and quantified their respective couplings by conditioning on the strongest SC links and EC links. We found that when conditioning on the strongest EC links, the obtained coupling follows the unimodal-transmodal functional hierarchy. Whereas the reverse is not true, as there are strong SC links within high-order cortical areas with no corresponding strong EC links. This mismatch is even more clear across networks; only within sensory motor networks did we observe connections that align in terms of both effective and structural strength.

Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains.

Previous studies have adopted an edge-centric framework to study fine-scale network dynamics in human fMRI. To date, however, no studies have applied this framework to data collected from model organisms. Here, we analyze structural and functional imaging data from lightly anesthetized mice through an edge-centric lens. We find evidence of "bursty" dynamics and events - brief periods of high-amplitude network connectivity. Further, we show that on a per-frame basis events best explain static FC and can be divided into a series of hierarchically-related clusters. The co-fluctuation patterns associated with each cluster centroid link distinct anatomical areas and largely adhere to the boundaries of algorithmically detected functional brain systems. We then investigate the anatomical connectivity undergirding high-amplitude co-fluctuation patterns. We find that events induce modular bipartitions of the anatomical network of inter-areal axonal projections. Finally, we replicate these same findings in a human imaging dataset. In summary, this report recapitulates in a model organism many of the same phenomena observed in previously edge-centric analyses of human imaging data. However, unlike human subjects, the murine nervous system is amenable to invasive experimental perturbations. Thus, this study sets the stage for future investigation into the causal origins of fine-scale brain dynamics and high-amplitude co-fluctuations. Moreover, the cross-species consistency of the reported findings enhances the likelihood of future translation.

Integrating direct electrical brain stimulation with the human connectome.

Neurological and neurodevelopmental conditions are a major public health concern for which new therapies are urgently needed. The development of effective therapies relies on the precise mapping of the neural substrates causally involved in behaviour generation. Direct electrical stimulation (DES) performed during cognitive and neurological monitoring in awake surgery is currently considered the gold standard for the causal mapping of brain functions. However, DES is limited by the focal nature of the stimulation sites, hampering a real holistic exploration of human brain functions at the network level. We used 4137 DES points derived from 612 glioma patients in combination with human connectome data-resting-state functional MRI, n = 1000 and diffusion weighted imaging, n = 284-to provide a multimodal description of the causal macroscale functional networks subtending 12 distinct behavioural domains. To probe the validity of our procedure, we (i) compared the network topographies of healthy and clinical populations; (ii) tested the predictive capacity of DES-derived networks; (iii) quantified the coupling between structural and functional connectivity; and (iv) built a multivariate model able to quantify single subject deviations from a normative population. Lastly, we probed the translational potential of DES-derived functional networks by testing their specificity and sensitivity in identifying critical neuromodulation targets and neural substrates associated with postoperative language deficits. The combination of DES and human connectome data resulted in an average 29.4-fold increase in whole brain coverage compared to DES alone. DES-derived functional networks are predictive of future stimulation points (97.8% accuracy) and strongly supported by the anatomical connectivity of subcortical stimulations. We did not observe any significant topographical differences between the patients and the healthy population at both group and single subject level. Showcasing concrete clinical applications, we found that DES-derived functional networks overlap with effective neuromodulation targets across several functional domains, show a high degree of specificity when tested with the intracranial stimulation points of a different stimulation technique and can be used effectively to characterize postoperative behavioural deficits. The integration of DES with the human connectome fundamentally advances the quality of the functional mapping provided by DES or functional imaging alone. DES-derived functional networks can reliably predict future stimulation points, have a strong correspondence with the underlying white matter and can be used for patient specific functional mapping. Possible applications range from psychiatry and neurology to neuropsychology, neurosurgery and neurorehabilitation.

Phospholipid scramblase Xkr8 is required for developmental axon pruning via phosphatidylserine exposure.

The mature mammalian brain connectome emerges during development via the extension and pruning of neuronal connections. Glial cells have been identified as key players in the phagocytic elimination of neuronal synapses and projections. Recently, phosphatidylserine has been identified as neuronal "eat-me" signal that guides elimination of unnecessary input sources, but the associated transduction systems involved in such pruning are yet to be described. Here, we identified Xk-related protein 8 (Xkr8), a phospholipid scramblase, as a key factor for the pruning of axons in the developing mammalian brain. We found that mouse Xkr8 is highly expressed immediately after birth and required for phosphatidylserine exposure in the hippocampus. Mice lacking Xkr8 showed excess excitatory nerve terminals, increased density of cortico-cortical and cortico-spinal projections, aberrant electrophysiological profiles of hippocampal neurons, and global brain hyperconnectivity. These data identify phospholipid scrambling by Xkr8 as a central process in the labeling and discrimination of developing neuronal projections for pruning in the mammalian brain.

Macroscale coupling between structural and effective connectivity in the mouse brain.

How the emergent functional connectivity (FC) relates to the underlying anatomy (structural connectivity, SC) is one of the biggest questions of modern neuroscience. At the macro-scale level, no one-to-one correspondence between structural and functional links seems to exist. And we posit that to better understand their coupling, two key aspects should be taken into account: the directionality of the structural connectome and the limitations of describing network functions in terms of FC. Here, we employed an accurate directed SC of the mouse brain obtained by means of viral tracers, and related it with single-subject effective connectivity (EC) matrices computed by applying a recently developed DCM to whole-brain resting-state fMRI data. We analyzed how SC deviates from EC and quantified their couplings by conditioning both on the strongest SC links and EC links. We found that when conditioning on the strongest EC links, the obtained coupling follows the unimodal-transmodal functional hierarchy. Whereas the reverse is not true, as there are strong SC links within high-order cortical areas with no corresponding strong EC links. This mismatch is even more clear across networks. Only the connections within sensory motor networks align both in terms of effective and structural strength.

Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex.

While shaped and constrained by axonal connections, fMRI-based functional connectivity reorganizes in response to varying interareal input or pathological perturbations. However, the causal contribution of regional brain activity to whole-brain fMRI network organization remains unclear. Here we combine neural manipulations, resting-state fMRI and in vivo electrophysiology to probe how inactivation of a cortical node causally affects brain-wide fMRI coupling in the mouse. We find that chronic inhibition of the medial prefrontal cortex (PFC) via overexpression of a potassium channel increases fMRI connectivity between the inhibited area and its direct thalamo-cortical targets. Acute chemogenetic inhibition of the PFC produces analogous patterns of fMRI overconnectivity. Using in vivo electrophysiology, we find that chemogenetic inhibition of the PFC enhances low frequency (0.1-4 Hz) oscillatory power via suppression of neural firing not phase-locked to slow rhythms, resulting in increased slow and δ band coherence between areas that exhibit fMRI overconnectivity. These results provide causal evidence that cortical inactivation can counterintuitively increase fMRI connectivity via enhanced, less-localized slow oscillatory processes.

Unique spatiotemporal fMRI dynamics in the awake mouse brain.

Human imaging studies have shown that spontaneous brain activity exhibits stereotypic spatiotemporal reorganization in awake, conscious conditions with respect to minimally conscious states. However, whether and how this phenomenon can be generalized to lower mammalian species remains unclear. Leveraging a robust protocol for resting-state fMRI (rsfMRI) mapping in non-anesthetized, head-fixed mice, we investigated functional network topography and dynamic structure of spontaneous brain activity in wakeful animals. We found that rsfMRI networks in the awake state, while anatomically comparable to those observed under anesthesia, are topologically configured to maximize interregional communication, departing from the underlying community structure of the mouse axonal connectome. We further report that rsfMRI activity in wakeful animals exhibits unique spatiotemporal dynamics characterized by a state-dependent, dominant occurrence of coactivation patterns encompassing a prominent participation of arousal-related forebrain nuclei and functional anti-coordination between visual-auditory and polymodal cortical areas. We finally show that rsfMRI dynamics in awake mice exhibits a stereotypical temporal structure, in which state-dominant coactivation patterns are configured as network attractors. These findings suggest that spontaneous brain activity in awake mice is critically shaped by state-specific involvement of basal forebrain arousal systems and document that its dynamic structure recapitulates distinctive, evolutionarily relevant principles that are predictive of conscious states in higher mammalian species.

Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network.

The evolutionarily conserved default mode network (DMN) is a distributed set of brain regions coactivated during resting states that is vulnerable to brain disorders. How disease affects the DMN is unknown, but detailed anatomical descriptions could provide clues. Mice offer an opportunity to investigate structural connectivity of the DMN across spatial scales with cell-type resolution. We co-registered maps from functional magnetic resonance imaging and axonal tracing experiments into the 3D Allen mouse brain reference atlas. We find that the mouse DMN consists of preferentially interconnected cortical regions. As a population, DMN layer 2/3 (L2/3) neurons project almost exclusively to other DMN regions, whereas L5 neurons project in and out of the DMN. In the retrosplenial cortex, a core DMN region, we identify two L5 projection types differentiated by in- or out-DMN targets, laminar position, and gene expression. These results provide a multi-scale description of the anatomical correlates of the mouse DMN.

Network structure of the mouse brain connectome with voxel resolution.

Fine-grained descriptions of brain connectivity are required to understand how neural information is processed and relayed across spatial scales. Previous investigations of the mouse brain connectome have used discrete anatomical parcellations, limiting spatial resolution and potentially concealing network attributes critical to connectome organization. Here, we provide a voxel-level description of the network and hierarchical structure of the directed mouse connectome, unconstrained by regional partitioning. We report a number of previously unappreciated organizational principles in the mammalian brain, including a directional segregation of hub regions into neural sink and sources, and a strategic wiring of neuromodulatory nuclei as connector hubs and critical orchestrators of network communication. We also find that the mouse cortical connectome is hierarchically organized along two superimposed cortical gradients reflecting unimodal-transmodal functional processing and a modality-specific sensorimotor axis, recapitulating a phylogenetically conserved feature of higher mammals. These findings advance our understanding of the foundational wiring principles of the mammalian connectome.

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

Brain activity elicited by viewing pictures of the own virtually amputated body predicts xenomelia.

BACKGROUND: Xenomelia is a rare condition characterized by the persistent desire for the amputation of physically healthy limbs. Prior studies highlighted the importance of superior and inferior parietal lobuli (SPL/IPL) and other sensorimotor regions as key brain structures associated with xenomelia. We expected activity differences in these areas in response to pictures showing the desired body state, i.e. that of an amputee in xenomelia. METHODS: Functional magnetic resonance images were acquired in 12 xenomelia individuals and 11 controls while they viewed pictures of their own real and virtually amputated body. Pictures were rated on several dimensions. Multivariate statistics using machine learning was performed on imaging data. RESULTS: Brain activity when viewing pictures of one's own virtually amputated body predicted group membership accurately with a balanced accuracy of 82.58% (p = 0.002), sensitivity of 83.33% (p = 0.018), specificity of 81.82% (p = 0.015) and an area under the ROC curve of 0.77. Among the highest predictive brain regions were bilateral SPL, IPL, and caudate nucleus, other limb representing areas, but also occipital regions. Pleasantness and attractiveness ratings were higher for amputated bodies in xenomelia. CONCLUSIONS: Findings show that neuronal processing in response to pictures of one's own desired body state is different in xenomelia compared with controls and might represent a neuronal substrate of the xenomelia complaints that become behaviourally relevant, at least when rating the pleasantness and attractiveness of one's own body. Our findings converge with structural peculiarities reported in xenomelia and partially overlap in task and results with that of anorexia and transgender research.