Sex-biasing influence of autism-associated Ube3a gene overdosage at connectomic, behavioral, and transcriptomic levels.

Genomic mechanisms enhancing risk in males may contribute to sex bias in autism. The ubiquitin protein ligase E3A gene (Ube3a) affects cellular homeostasis via control of protein turnover and by acting as transcriptional coactivator with steroid hormone receptors. Overdosage of Ube3a via duplication or triplication of chromosomal region 15q11-13 causes 1 to 2% of autistic cases. Here, we test the hypothesis that increased dosage of Ube3a may influence autism-relevant phenotypes in a sex-biased manner. We show that mice with extra copies of Ube3a exhibit sex-biasing effects on brain connectomics and autism-relevant behaviors. These effects are associated with transcriptional dysregulation of autism-associated genes, as well as genes differentially expressed in 15q duplication and in autistic people. Increased Ube3a dosage also affects expression of genes on the X chromosome, genes influenced by sex steroid hormone, and genes sex-differentially regulated by transcription factors. These results suggest that Ube3a overdosage can contribute to sex bias in neurodevelopmental conditions via influence on sex-differential mechanisms.

A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity.

The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features-e.g. diffusion parameters-or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the networks maintain a number of desirable features. In summary, we offer a simple framework for weighting connectome data, demonstrating both its ease of implementation while benchmarking its utility for typical connectome analyses, including graph theoretic modeling and brain-behavior associations.

Cortico-cortical transfer of socially derived information gates emotion recognition.

Emotion recognition and the resulting responses are important for survival and social functioning. However, how socially derived information is processed for reliable emotion recognition is incompletely understood. Here, we reveal an evolutionarily conserved long-range inhibitory/excitatory brain network mediating these socio-cognitive processes. Anatomical tracing in mice revealed the existence of a subpopulation of somatostatin (SOM) GABAergic neurons projecting from the medial prefrontal cortex (mPFC) to the retrosplenial cortex (RSC). Through optogenetic manipulations and Ca2+ imaging fiber photometry in mice and functional imaging in humans, we demonstrate the specific participation of these long-range SOM projections from the mPFC to the RSC, and an excitatory feedback loop from the RSC to the mPFC, in emotion recognition. Notably, we show that mPFC-to-RSC SOM projections are dysfunctional in mouse models relevant to psychiatric vulnerability and can be targeted to rescue emotion recognition deficits in these mice. Our findings demonstrate a cortico-cortical circuit underlying emotion recognition.

Functional MRI of imprinting memory: a new avenue for neurobiology of early learning.

Filial imprinting, a crucial ethological paradigm, provides insights into the neurobiology of early learning and its long-term impact on behaviour. To date, only invasive techniques, such as autoradiography or lesion, have been employed to understand this behaviour. The primary limitation of these methods lies in their constrained access to the entire brain, impeding the exploration of brain networks crucial at various stages of this paradigm. Recently, advances in functional magnetic resonance imaging (fMRI) in the avian brain have opened new windows to explore bird's brain function at the network level. Here, we developed a ground-breaking non-invasive functional MRI technique for awake, newly hatched chicks that record whole-brain BOLD signal changes throughout imprinting experiments. While the initial phases of memory acquisition imprinting behaviour have been unravelled, the long-term storage and retrieval components of imprinting memories are still unknown. Our findings identified potential long-term storage of imprinting memories across a neural network, including the hippocampal formation, the medial striatum, the arcopallium, and the prefrontal-like nidopallium caudolaterale. This platform opens up new avenues for exploring the broader landscape of learning and memory processes in neonatal vertebrates, contributing to a more comprehensive understanding of the intricate interplay between behaviour and brain networks.

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.