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Although we understand how serotonin receptors function at the single-cell level, what role different serotonin receptors play in regulating brain-wide activity and, in turn, human behavior, remains unknown. Here, we developed transcriptomic–neuroimaging mapping to characterize brain-wide functional signatures associated with specific serotonin receptors: serotonin receptor networks (SRNs). Probing SRNs with optogenetics–functional magnetic resonance imaging (MRI) and pharmacology in mice, we show that activation of dorsal raphe serotonin neurons differentially modulates the amplitude and functional connectivity of different SRNs, showing that receptors’ spatial distributions can confer specificity not only at the local, but also at the brain-wide, network level. In humans, using resting-state functional MRI, SRNs replicate established divisions of serotonin effects on impulsivity and negative biases. These results provide compelling evidence that heterogeneous brain-wide distributions of different serotonin receptor types may underpin behaviorally distinct modes of serotonin regulation. This suggests that serotonin neurons may regulate multiple aspects of human behavior via modulation of large-scale receptor networks. Combining brain imaging, genetics and behavioral data, this study shows that distinct brainwide distributions of serotonin receptors explain the known division of serotonin effects on human impulsivity and aversive processing.

Cerebellar abnormalities, particularly in Right Crus I (RCrusI), are consistently reported in autism spectrum disorders (ASD). Although RCrusI is functionally connected with ASD-implicated circuits, the contribution of RCrusI dysfunction to ASD remains unclear. Here neuromodulation of RCrusI in neurotypical humans resulted in altered functional connectivity with the inferior parietal lobule, and children with ASD showed atypical functional connectivity in this circuit. Atypical RCrusI–inferior parietal lobule structural connectivity was also evident in the Purkinje neuron (PN) TscI ASD mouse model. Additionally, chemogenetically mediated inhibition of RCrusI PN activity in mice was sufficient to generate ASD-related social, repetitive, and restricted behaviors, while stimulation of RCrusI PNs rescued social impairment in the PN TscI ASD mouse model. Together, these studies reveal important roles for RCrusI in ASD-related behaviors. Further, the rescue of social behaviors in an ASD mouse model suggests that investigation of the therapeutic potential of cerebellar neuromodulation in ASD may be warranted. Cerebellar right Crus I (RCrusI) has been implicated in autism spectrum disorder (ASD). RCrusI modulation altered RCrusI–inferior parietal lobule connectivity, and this connectivity was atypical in children with ASD and in a TscI mouse model of ASD. Inhibition of RCrusI in mice led to autism-related behaviors, and RCrusI activation rescued social impairments in TscI mice.

Sex differences exist in behaviors, disease and neuropsychiatric disorders. Sexual dimorphisms however, have yet to be studied across the whole brain and across a comprehensive time course of postnatal development. Here, we use manganese-enhanced MRI (MEMRI) to longitudinally image male and female C57BL/6J mice across 9 time points, beginning at postnatal day 3. We recapitulate findings on canonically dimorphic areas, demonstrating MEMRI’s ability to study neuroanatomical sex differences. We discover, upon whole-brain volume correction, that neuroanatomical regions larger in males develop earlier than those larger in females. Groups of areas with shared sexually dimorphic developmental trajectories reflect behavioral and functional networks, and expression of genes involved with sex processes. Also, post-pubertal neuroanatomy is highly individualized, and individualization occurs earlier in males. Our results demonstrate the ability of MEMRI to reveal comprehensive developmental differences between male and female brains, which will improve our understanding of sex-specific predispositions to various neuropsychiatric disorders. Sex differences occur in various aspects of neurodevelopment. Here the authors use manganese-enhanced MRI at nine different postnatal stages to detail the development of structural sex differences in the mouse brain.

Infectious or noninfectious maternal immune activation (MIA) is an environmental risk factor for psychiatric and neurological disorders with neurodevelopmental etiologies. Whilst there is increasing evidence for significant health consequences, the effects of MIA on the offspring appear to be variable. Here, we aimed to identify and characterize subgroups of isogenic mouse offspring exposed to identical MIA, which was induced in C57BL6/N mice by administration of the viral mimetic, poly(I:C), on gestation day 12. Cluster analysis of behavioral data obtained from a first cohort containing >150 MIA and control offspring revealed that MIA offspring could be stratified into distinct subgroups that were characterized by the presence or absence of multiple behavioral dysfunctions. The two subgroups also differed in terms of their transcriptional profiles in cortical and subcortical brain regions and brain networks of structural covariance, as measured by ex vivo structural magnetic resonance imaging (MRI). In a second, independent cohort containing 50 MIA and control offspring, we identified a subgroup of MIA offspring that displayed elevated peripheral production of innate inflammatory cytokines, including IL-1β, IL-6, and TNF-α, in adulthood. This subgroup also showed significant impairments in social approach behavior and sensorimotor gating, whereas MIA offspring with a low inflammatory cytokine status did not. Taken together, our results highlight the existence of subgroups of MIA-exposed offspring that show dissociable behavioral, transcriptional, brain network, and immunological profiles even under conditions of genetic homogeneity. These data have relevance for advancing our understanding of the variable neurodevelopmental effects induced by MIA and for biomarker-guided approaches in preclinical psychiatric research.

The ever-increasing use of mouse models in preclinical neuroscience research calls for an improvement in the methods used to translate findings between mouse and human brains. Previously, we showed that the brains of primates can be compared in a direct quantitative manner using a common reference space built from white matter tractography data (Mars et al., 2018b). Here, we extend the common space approach to evaluate the similarity of mouse and human brain regions using openly accessible brain-wide transcriptomic data sets. We show that mouse-human homologous genes capture broad patterns of neuroanatomical organization, but the resolution of cross-species correspondences can be improved using a novel supervised machine learning approach. Using this method, we demonstrate that sensorimotor subdivisions of the neocortex exhibit greater similarity between species, compared with supramodal subdivisions, and mouse isocortical regions separate into sensorimotor and supramodal clusters based on their similarity to human cortical regions. We also find that mouse and human striatal regions are strongly conserved, with the mouse caudoputamen exhibiting an equal degree of similarity to both the human caudate and putamen.

Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression.

Advances in image segmentation of magnetic resonance images (MRI) have demonstrated that multi-atlas approaches improve segmentation over regular atlas-based approaches. These approaches often rely on a large number of manually segmented atlases (e.g. 30–80) that take significant time and expertise to produce. We present an algorithm, MAGeT-Brain (Multiple Automatically Generated Templates), for the automatic segmentation of the hippocampus that minimises the number of atlases needed whilst still achieving similar agreement to multi-atlas approaches. Thus, our method acts as a reliable multi-atlas approach when using special or hard-to-define atlases that are laborious to construct. MAGeT-Brain works by propagating atlas segmentations to a template library, formed from a subset of target images, via transformations estimated by nonlinear image registration. The resulting segmentations are then propagated to each target image and fused using a label fusion method. We conduct two separate Monte Carlo cross-validation experiments comparing MAGeT-Brain and basic multi-atlas whole hippocampal segmentation using differing atlas and template library sizes, and registration and label fusion methods. The first experiment is a 10-fold validation (per parameter setting) over 60 subjects taken from the Alzheimer's Disease Neuroimaging Database (ADNI), and the second is a five-fold validation over 81 subjects having had a first episode of psychosis. In both cases, automated segmentations are compared with manual segmentations following the Pruessner-protocol. Using the best settings found from these experiments, we segment 246 images of the ADNI1:Complete 1Yr 1.5T dataset and compare these with segmentations from existing automated and semi-automated methods: FSL FIRST, FreeSurfer, MAPER, and SNT. Finally, we conduct a leave-one-out cross-validation of hippocampal subfield segmentation in standard 3T T1-weighted images, using five high-resolution manually segmented atlases (Winterburn et al., 2013). In the ADNI cross-validation, using 9 atlases MAGeT-Brain achieves a mean Dice's Similarity Coefficient (DSC) score of 0.869 with respect to manual whole hippocampus segmentations, and also exhibits significantly lower variability in DSC scores than multi-atlas segmentation. In the younger, psychosis dataset, MAGeT-Brain achieves a mean DSC score of 0.892 and produces volumes which agree with manual segmentation volumes better than those produced by the FreeSurfer and FSL FIRST methods (mean difference in volume: 80mm3, 1600mm3, and 800mm3, respectively). Similarly, in the ADNI1:Complete 1Yr 1.5T dataset, MAGeT-Brain produces hippocampal segmentations well correlated (r>0.85) with SNT semi-automated reference volumes within disease categories, and shows a conservative bias and a mean difference in volume of 250mm3 across the entire dataset, compared with FreeSurfer and FSL FIRST which both overestimate volume differences by 2600mm3 and 2800mm3 on average, respectively. Finally, MAGeT-Brain segments the CA1, CA4/DG and subiculum subfields on standard 3T T1-weighted resolution images with DSC overlap scores of 0.56, 0.65, and 0.58, respectively, relative to manual segmentations. We demonstrate that MAGeT-Brain produces consistent whole hippocampal segmentations using only 9 atlases, or fewer, with various hippocampal definitions, disease populations, and image acquisition types. Additionally, we show that MAGeT-Brain identifies hippocampal subfields in standard 3T T1-weighted images with overlap scores comparable to competing methods. •We propose an automated MR image hippocampus (and subfield) segmentation method.•Our method is optimised for use with a small number (<10) of training images.•Consistent, accurate identification of the whole hippocampus and subfields•Validated on healthy, Alzheimer's disease, and first episode psychosis subjects•Source code and high-resolution training subfield atlases available online

Growing access to large-scale longitudinal structural neuroimaging data has fundamentally altered our understanding of cortical development en route to human adulthood, with consequences for basic science, medicine, and public policy. In striking contrast, basic anatomical development of subcortical structures such as the striatum, pallidum, and thalamus has remained poorly described—despite these evolutionarily ancient structures being both intimate working partners of the cortical sheet and critical to diverse developmentally emergent skills and disorders. Here, to begin addressing this disparity, we apply methods for the measurement of subcortical volume and shape to 1,171 longitudinally acquired structural magnetic resonance imaging brain scans from 618 typically developing males and females aged 5–25 y. We show that the striatum, pallidum, and thalamus each follow curvilinear trajectories of volume change, which, for the striatum and thalamus, peak after cortical volume has already begun to decline and show a relative delay in males. Four-dimensional mapping of subcortical shape reveals that (i) striatal, pallidal, and thalamic domains linked to specific fronto-parietal association cortices contract with age whereas other subcortical territories expand, and (ii) each structure harbors hotspots of sexually dimorphic change over adolescence—with relevance for sex-biased mental disorders emerging in youth. By establishing the developmental dynamism, spatial heterochonicity, and sexual dimorphism of human subcortical maturation, these data bring our spatiotemporal understanding of subcortical development closer to that of the cortex—allowing evolutionary, basic, and clinical neuroscience to be conducted within a more comprehensive developmental framework.

Brain size among normal humans varies as much as twofold. Reardon et al. surveyed the cortical and subcortical structure of more than 3000 human brains by noninvasive imaging (see the Perspective by Van Essen). They found that the scaling of different regions across the range of brain sizes is not consistent: Some brain regions are metabolically costly and are favored in larger brains. This shifts the balance between associative and sensorimotor brain systems in a brain size–dependent way. Science , this issue p. 1222 ; see also p. 1184 A metabolically expensive brain network is preferentially expanded in individuals that have larger brains. Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology.

Compromised placental function or premature loss has been linked to diverse neurodevelopmental disorders. Here we show that placenta allopregnanolone (ALLO), a progesterone-derived GABA-A receptor (GABA A R) modulator, reduction alters neurodevelopment in a sex-linked manner. A new conditional mouse model, in which the gene encoding ALLO’s synthetic enzyme ( akr1c14 ) is specifically deleted in trophoblasts, directly demonstrated that placental ALLO insufficiency led to cerebellar white matter abnormalities that correlated with autistic-like behavior only in male offspring. A single injection of ALLO or muscimol, a GABA A R agonist, during late gestation abolished these alterations. Comparison of male and female human preterm infant cerebellum also showed sex-linked myelination marker alteration, suggesting similarities between mouse placental ALLO insufficiency and human preterm brain development. This study reveals a new role for a placental hormone in shaping brain regions and behaviors in a sex-linked manner. Placental hormone replacement might offer novel therapeutic opportunities to prevent later neurobehavioral disorders. Placental dysfunction has been implicated in abnormal neurodevelopment. Vacher et al. found that loss of a neuroactive hormone from the placenta alters brain development in a regional and sex-linked manner, resulting in autism-like behaviors in male offspring.