Mapping the Fine-Scale Organization and Plasticity of the Brain Vasculature.

The cerebral vasculature is a dense network of arteries, capillaries, and veins. Quantifying variations of the vascular organization across individuals, brain regions, or disease models is challenging. We used immunolabeling and tissue clearing to image the vascular network of adult mouse brains and developed a pipeline to segment terabyte-sized multichannel images from light sheet microscopy, enabling the construction, analysis, and visualization of vascular graphs composed of over 100 million vessel segments. We generated datasets from over 20 mouse brains, with labeled arteries, veins, and capillaries according to their anatomical regions. We characterized the organization of the vascular network across brain regions, highlighting local adaptations and functional correlates. We propose a classification of cortical regions based on the vascular topology. Finally, we analysed brain-wide rearrangements of the vasculature in animal models of congenital deafness and ischemic stroke, revealing that vascular plasticity and remodeling adopt diverging rules in different models.

Neuromodulatory Control of Long-Term Behavioral Patterns and Individuality across Development.

Animals generate complex patterns of behavior across development that may be shared or unique to individuals. Here, we examine the contributions of developmental programs and individual variation to behavior by monitoring single Caenorhabditis elegans nematodes over their complete developmental trajectories and quantifying their behavior at high spatiotemporal resolution. These measurements reveal reproducible trajectories of spontaneous foraging behaviors that are stereotyped within and between developmental stages. Dopamine, serotonin, the neuropeptide receptor NPR-1, and the TGF-ß peptide DAF-7 each have stage-specific effects on behavioral trajectories, implying the existence of a modular temporal program controlled by neuromodulators. In addition, a fraction of individuals within isogenic populations raised in controlled environments have consistent, non-genetic behavioral biases that persist across development. Several neuromodulatory systems increase or decrease the degree of non-genetic individuality to shape sustained patterns of behavior across the population.

Mapping of Brain Activity by Automated Volume Analysis of Immediate Early Genes.

Understanding how neural information is processed in physiological and pathological states would benefit from precise detection, localization, and quantification of the activity of all neurons across the entire brain, which has not, to date, been achieved in the mammalian brain. We introduce a pipeline for high-speed acquisition of brain activity at cellular resolution through profiling immediate early gene expression using immunostaining and light-sheet fluorescence imaging, followed by automated mapping and analysis of activity by an open-source software program we term ClearMap. We validate the pipeline first by analysis of brain regions activated in response to haloperidol. Next, we report new cortical regions downstream of whisker-evoked sensory processing during active exploration. Last, we combine activity mapping with axon tracing to uncover new brain regions differentially activated during parenting behavior. This pipeline is widely applicable to different experimental paradigms, including animal species for which transgenic activity reporters are not readily available.

Network-level encoding of local neurotransmitters in cortical astrocytes.

Astrocytes, the most abundant non-neuronal cell type in the mammalian brain, are crucial circuit components that respond to and modulate neuronal activity through calcium (Ca2+) signalling1-7. Astrocyte Ca2+ activity is highly heterogeneous and occurs across multiple spatiotemporal scales-from fast, subcellular activity3,4 to slow, synchronized activity across connected astrocyte networks8-10-to influence many processes5,7,11. However, the inputs that drive astrocyte network dynamics remain unclear. Here we used ex vivo and in vivo two-photon astrocyte imaging while mimicking neuronal neurotransmitter inputs at multiple spatiotemporal scales. We find that brief, subcellular inputs of GABA and glutamate lead to widespread, long-lasting astrocyte Ca2+ responses beyond an individual stimulated cell. Further, we find that a key subset of Ca2+ activity-propagative activity-differentiates astrocyte network responses to these two main neurotransmitters, and may influence responses to future inputs. Together, our results demonstrate that local, transient neurotransmitter inputs are encoded by broad cortical astrocyte networks over a minutes-long time course, contributing to accumulating evidence that substantial astrocyte-neuron communication occurs across slow, network-level spatiotemporal scales12-14. These findings will enable future studies to investigate the link between specific astrocyte Ca2+ activity and specific functional outputs, which could build a consistent framework for astrocytic modulation of neuronal activity.

Regional specialization manifests in the reliability of neural population codes.

The brain has the remarkable ability to learn and guide the performance of complex tasks. Decades of lesion studies suggest that different brain regions perform specialized functions in support of complex behaviors1-3. Yet recent large-scale studies of neural activity reveal similar patterns of activity and encoding distributed widely throughout the brain4-6. How these distributed patterns of activity and encoding are compatible with regional specialization of brain function remains unclear. Two frontal brain regions, the dorsal medial prefrontal cortex (dmPFC) and orbitofrontal cortex (OFC), are a paradigm of this conundrum. In the setting complex behaviors, the dmPFC is necessary for choosing optimal actions2,7,8, whereas the OFC is necessary for waiting for3,9 and learning from2,7,9-12 the outcomes of those actions. Yet both dmPFC and OFC encode both choice- and outcome-related quantities13-20. Here we show that while ensembles of neurons in the dmPFC and OFC of rats encode similar elements of a cognitive task with similar patterns of activity, the two regions differ in when that coding is consistent across trials ("reliable"). In line with the known critical functions of each region, dmPFC activity is more reliable when animals are making choices and less reliable preceding outcomes, whereas OFC activity shows the opposite pattern. Our findings identify the dynamic reliability of neural population codes as a mechanism whereby different brain regions may support distinct cognitive functions despite exhibiting similar patterns of activity and encoding similar quantities.

Resolving Non-identifiability Mitigates Bias in Models of Neural Tuning and Functional Coupling.

In the brain, all neurons are driven by the activity of other neurons, some of which maybe simultaneously recorded, but most are not. As such, models of neuronal activity need to account for simultaneously recorded neurons and the influences of unmeasured neurons. This can be done through inclusion of model terms for observed external variables (e.g., tuning to stimuli) as well as terms for latent sources of variability. Determining the influence of groups of neurons on each other relative to other influences is important to understand brain functioning. The parameters of statistical models fit to data are commonly used to gain insight into the relative importance of those influences. Scientific interpretation of models hinge upon unbiased parameter estimates. However, evaluation of biased inference is rarely performed and sources of bias are poorly understood. Through extensive numerical study and analytic calculation, we show that common inference procedures and models are typically biased. We demonstrate that accurate parameter selection before estimation resolves model non-identifiability and mitigates bias. In diverse neurophysiology data sets, we found that contributions of coupling to other neurons are often overestimated while tuning to exogenous variables are underestimated in common methods. We explain heterogeneity in observed biases across data sets in terms of data statistics. Finally, counter to common intuition, we found that model non-identifiability contributes to bias, not variance, making it a particularly insidious form of statistical error. Together, our results identify the causes of statistical biases in common models of neural data, provide inference procedures to mitigate that bias, and reveal and explain the impact of those biases in diverse neural data sets.

Network-level encoding of local neurotransmitters in cortical astrocytes.

Astrocytes-the most abundant non-neuronal cell type in the mammalian brain-are crucial circuit components that respond to and modulate neuronal activity via calcium (Ca 2+ ) signaling 1-8 . Astrocyte Ca 2+ activity is highly heterogeneous and occurs across multiple spatiotemporal scales: from fast, subcellular activity 3,4 to slow, synchronized activity that travels across connected astrocyte networks 9-11 . Furthermore, astrocyte network activity has been shown to influence a wide range of processes 5,8,12 . While astrocyte network activity has important implications for neuronal circuit function, the inputs that drive astrocyte network dynamics remain unclear. Here we used ex vivo and in vivo two-photon Ca 2+ imaging of astrocytes while mimicking neuronal neurotransmitter inputs at multiple spatiotemporal scales. We find that brief, subcellular inputs of GABA and glutamate lead to widespread, long-lasting astrocyte Ca 2+ responses beyond an individual stimulated cell. Further, we find that a key subset of Ca 2+ activity-propagative events-differentiates astrocyte network responses to these two major neurotransmitters, and gates responses to future inputs. Together, our results demonstrate that local, transient neurotransmitter inputs are encoded by broad cortical astrocyte networks over the course of minutes, contributing to accumulating evidence across multiple model organisms that significant astrocyte-neuron communication occurs across slow, network-level spatiotemporal scales 13-15 . We anticipate that this study will be a starting point for future studies investigating the link between specific astrocyte Ca 2+ activity and specific astrocyte functional outputs, which could build a consistent framework for astrocytic modulation of neuronal activity.

Edinger-Westphal peptidergic neurons enable maternal preparatory nesting.

Optimizing reproductive fitness in mammalians requires behavioral adaptations during pregnancy. Maternal preparatory nesting is an essential behavior for the survival of the upcoming litter. Brain-wide immediate early gene mapping in mice evoked by nesting sequences revealed that phases of nest construction strongly activate peptidergic neurons of the Edinger-Westphal nucleus in pregnant mice. Genetic ablation, bidirectional neuromodulation, and in vitro and in vivo activity recordings demonstrated that these neurons are essential to modulate arousal before sleep to promote nesting specifically. We show that these neurons enable the behavioral effects of progesterone on preparatory nesting by modulating a broad network of downstream targets. Our study deciphers the role of midbrain CART+ neurons in behavioral adaptations during pregnancy vital for reproductive fitness.

Breakdown of order preservation in symmetric oscillator networks with pulse-coupling.

Symmetric networks of coupled dynamical units exhibit invariant subspaces with two or more units synchronized. In time-continuously coupled systems, these invariant sets constitute barriers for the dynamics. For networks of units with local dynamics defined on the real line, this implies that the units' ordering is preserved and that their winding number is identical. Here, we show that in permutation-symmetric networks with pulse-coupling, the order is often no longer preserved. We analytically study a class of pulse-coupled oscillators (characterizing for instance the dynamics of spiking neural networks) and derive quantitative conditions for the breakdown of order preservation. We find that in general pulse-coupling yields additional dimensions to the state space such that units may change their order by avoiding the invariant sets. We identify a system of two symmetrically pulse-coupled identical oscillators where, contrary to intuition, the oscillators' average frequencies and thus their winding numbers are different.

From networks of unstable attractors to heteroclinic switching.

We present a dynamical system that naturally exhibits two unstable attractors that are completely enclosed by each other's basin volume. This counterintuitive phenomenon occurs in networks of pulse-coupled oscillators with delayed interactions. We analytically show that upon continuously removing a local noninvertibility of the system, the two unstable attractors become a set of two nonattracting saddle states that are heteroclinically connected. This transition equally occurs from larger networks of unstable attractors to heteroclinic structures and constitutes a new type of singular bifurcation in dynamical systems.

hPSC Modeling Reveals that Fate Selection of Cortical Deep Projection Neurons Occurs in the Subplate.

Cortical deep projection neurons (DPNs) are implicated in neurodevelopmental disorders. Although recent findings emphasize post-mitotic programs in projection neuron fate selection, the establishment of primate DPN identity during layer formation is not well understood. The subplate lies underneath the developing cortex and is a post-mitotic compartment that is transiently and disproportionately enlarged in primates in the second trimester. The evolutionary significance of subplate expansion, the molecular identity of its neurons, and its contribution to primate corticogenesis remain open questions. By modeling subplate formation with human pluripotent stem cells (hPSCs), we show that all classes of cortical DPNs can be specified from subplate neurons (SPNs). Post-mitotic WNT signaling regulates DPN class selection, and DPNs in the caudal fetal cortex appear to exclusively derive from SPNs. Our findings indicate that SPNs have evolved in primates as an important source of DPNs that contribute to cortical lamination prior to their known role in circuit formation.

WNT signaling memory is required for ACTIVIN to function as a morphogen in human gastruloids.

Self-organization of discrete fates in human gastruloids is mediated by a hierarchy of signaling pathways. How these pathways are integrated in time, and whether cells maintain a memory of their signaling history remains obscure. Here, we dissect the temporal integration of two key pathways, WNT and ACTIVIN, which along with BMP control gastrulation. CRISPR/Cas9-engineered live reporters of SMAD1, 2 and 4 demonstrate that in contrast to the stable signaling by SMAD1, signaling and transcriptional response by SMAD2 is transient, and while necessary for pluripotency, it is insufficient for differentiation. Pre-exposure to WNT, however, endows cells with the competence to respond to graded levels of ACTIVIN, which induces differentiation without changing SMAD2 dynamics. This cellular memory of WNT signaling is necessary for ACTIVIN morphogen activity. A re-evaluation of the evidence gathered over decades in model systems, re-enforces our conclusions and points to an evolutionarily conserved mechanism.

Transition to reconstructibility in weakly coupled networks.

Across scientific disciplines, thresholded pairwise measures of statistical dependence between time series are taken as proxies for the interactions between the dynamical units of a network. Yet such correlation measures often fail to reflect the underlying physical interactions accurately. Here we systematically study the problem of reconstructing direct physical interaction networks from thresholding correlations. We explicate how local common cause and relay structures, heterogeneous in-degrees and non-local structural properties of the network generally hinder reconstructibility. However, in the limit of weak coupling strengths we prove that stationary systems with dynamics close to a given operating point transition to universal reconstructiblity across all network topologies.

Dynamic information routing in complex networks.

Flexible information routing fundamentally underlies the function of many biological and artificial networks. Yet, how such systems may specifically communicate and dynamically route information is not well understood. Here we identify a generic mechanism to route information on top of collective dynamical reference states in complex networks. Switching between collective dynamics induces flexible reorganization of information sharing and routing patterns, as quantified by delayed mutual information and transfer entropy measures between activities of a network's units. We demonstrate the power of this mechanism specifically for oscillatory dynamics and analyse how individual unit properties, the network topology and external inputs co-act to systematically organize information routing. For multi-scale, modular architectures, we resolve routing patterns at all levels. Interestingly, local interventions within one sub-network may remotely determine nonlocal network-wide communication. These results help understanding and designing information routing patterns across systems where collective dynamics co-occurs with a communication function.

A Balance between Secreted Inhibitors and Edge Sensing Controls Gastruloid Self-Organization.

The earliest aspects of human embryogenesis remain mysterious. To model patterning events in the human embryo, we used colonies of human embryonic stem cells (hESCs) grown on micropatterned substrate and differentiated with BMP4. These gastruloids recapitulate the embryonic arrangement of the mammalian germ layers and provide an assay to assess the structural and signaling mechanisms patterning the human gastrula. Structurally, high-density hESCs localize their receptors to transforming growth factor ß at their lateral side in the center of the colony while maintaining apical localization of receptors at the edge. This relocalization insulates cells at the center from apically applied ligands while maintaining response to basally presented ones. In addition, BMP4 directly induces the expression of its own inhibitor, NOGGIN, generating a reaction-diffusion mechanism that underlies patterning. We develop a quantitative model that integrates edge sensing and inhibitors to predict human fate positioning in gastruloids and, potentially, the human embryo.

Sequential desynchronization in networks of spiking neurons with partial reset.

The response of a neuron to synaptic input strongly depends on whether or not the neuron has just emitted a spike. We propose a neuron model that after spike emission exhibits a partial response to residual input charges and study its collective network dynamics analytically. We uncover a desynchronization mechanism that causes a sequential desynchronization transition: In globally coupled neurons an increase in the strength of the partial response induces a sequence of bifurcations from states with large clusters of synchronously firing neurons, through states with smaller clusters to completely asynchronous spiking. We briefly discuss key consequences of this mechanism for more general networks of biophysical neurons.