A neural circuit state change underlying skilled movements.

In motor neuroscience, state changes are hypothesized to time-lock neural assemblies coordinating complex movements, but evidence for this remains slender. We tested whether a discrete change from more autonomous to coherent spiking underlies skilled movement by imaging cerebellar Purkinje neuron complex spikes in mice making targeted forelimb-reaches. As mice learned the task, millimeter-scale spatiotemporally coherent spiking emerged ipsilateral to the reaching forelimb, and consistent neural synchronization became predictive of kinematic stereotypy. Before reach onset, spiking switched from more disordered to internally time-locked concerted spiking and silence. Optogenetic manipulations of cerebellar feedback to the inferior olive bi-directionally modulated neural synchronization and reaching direction. A simple model explained the reorganization of spiking during reaching as reflecting a discrete bifurcation in olivary network dynamics. These findings argue that to prepare learned movements, olivo-cerebellar circuits enter a self-regulated, synchronized state promoting motor coordination. State changes facilitating behavioral transitions may generalize across neural systems.

Correlated Neural Activity and Encoding of Behavior across Brains of Socially Interacting Animals.

Social interactions involve complex decision-making tasks that are shaped by dynamic, mutual feedback between participants. An open question is whether and how emergent properties may arise across brains of socially interacting individuals to influence social decisions. By simultaneously performing microendoscopic calcium imaging in pairs of socially interacting mice, we find that animals exhibit interbrain correlations of neural activity in the prefrontal cortex that are dependent on ongoing social interaction. Activity synchrony arises from two neuronal populations that separately encode one's own behaviors and those of the social partner. Strikingly, interbrain correlations predict future social interactions as well as dominance relationships in a competitive context. Together, our study provides conclusive evidence for interbrain synchrony in rodents, uncovers how synchronization arises from activity at the single-cell level, and presents a role for interbrain neural activity coupling as a property of multi-animal systems in coordinating and sustaining social interactions between individuals.

The Ancient Origins of Neural Substrates for Land Walking.

Walking is the predominant locomotor behavior expressed by land-dwelling vertebrates, but it is unknown when the neural circuits that are essential for limb control first appeared. Certain fish species display walking-like behaviors, raising the possibility that the underlying circuitry originated in primitive marine vertebrates. We show that the neural substrates of bipedalism are present in the little skate Leucoraja erinacea, whose common ancestor with tetrapods existed ∼420 million years ago. Leucoraja exhibits core features of tetrapod locomotor gaits, including left-right alternation and reciprocal extension-flexion of the pelvic fins. Leucoraja also deploys a remarkably conserved Hox transcription factor-dependent program that is essential for selective innervation of fin/limb muscle. This network encodes peripheral connectivity modules that are distinct from those used in axial muscle-based swimming and has apparently been diminished in most modern fish. These findings indicate that the circuits that are essential for walking evolved through adaptation of a genetic regulatory network shared by all vertebrates with paired appendages. VIDEO ABSTRACT.

Integration of Parallel Opposing Memories Underlies Memory Extinction.

Accurately predicting an outcome requires that animals learn supporting and conflicting evidence from sequential experience. In mammals and invertebrates, learned fear responses can be suppressed by experiencing predictive cues without punishment, a process called memory extinction. Here, we show that extinction of aversive memories in Drosophila requires specific dopaminergic neurons, which indicate that omission of punishment is remembered as a positive experience. Functional imaging revealed co-existence of intracellular calcium traces in different places in the mushroom body output neuron network for both the original aversive memory and a new appetitive extinction memory. Light and ultrastructural anatomy are consistent with parallel competing memories being combined within mushroom body output neurons that direct avoidance. Indeed, extinction-evoked plasticity in a pair of these neurons neutralizes the potentiated odor response imposed in the network by aversive learning. Therefore, flies track the accuracy of learned expectations by accumulating and integrating memories of conflicting events.

Color Processing in the Early Visual System of Drosophila.

Color vision extracts spectral information by comparing signals from photoreceptors with different visual pigments. Such comparisons are encoded by color-opponent neurons that are excited at one wavelength and inhibited at another. Here, we examine the circuit implementation of color-opponent processing in the Drosophila visual system by combining two-photon calcium imaging with genetic dissection of visual circuits. We report that color-opponent processing of UVshort/blue and UVlong/green is already implemented in R7/R8 inner photoreceptor terminals of "pale" and "yellow" ommatidia, respectively. R7 and R8 photoreceptors of the same type of ommatidia mutually inhibit each other directly via HisCl1 histamine receptors and receive additional feedback inhibition that requires the second histamine receptor Ort. Color-opponent processing at the first visual synapse represents an unexpected commonality between Drosophila and vertebrates; however, the differences in the molecular and cellular implementation suggest that the same principles evolved independently.

The Emerging Nature of Astrocyte Diversity.

Astrocytes are morphologically complex, ubiquitous cells that are viewed as a homogeneous population tiling the entire central nervous system (CNS). However, this view has been challenged in the last few years with the availability of RNA sequencing, immunohistochemistry, electron microscopy, morphological reconstruction, and imaging data. These studies suggest that astrocytes represent a diverse population of cells and that they display brain area- and disease-specific properties and functions. In this review, we summarize these observations, emphasize areas where clear conclusions can be made, and discuss potential unifying themes. We also identify knowledge gaps that need to be addressed in order to exploit astrocyte diversity as a biological phenomenon of physiological relevance in the CNS. We thus provide a summary and a perspective on astrocyte diversity in the vertebrate CNS.

MDGAs perform activity-dependent synapse type-specific suppression via distinct extracellular mechanisms.

MDGA (MAM domain containing glycosylphosphatidylinositol anchor) family proteins were previously identified as synaptic suppressive factors. However, various genetic manipulations have yielded often irreconcilable results, precluding precise evaluation of MDGA functions. Here, we found that, in cultured hippocampal neurons, conditional deletion of MDGA1 and MDGA2 causes specific alterations in synapse numbers, basal synaptic transmission, and synaptic strength at GABAergic and glutamatergic synapses, respectively. Moreover, MDGA2 deletion enhanced both N-methyl-D-aspartate (NMDA) receptor- and α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptor-mediated postsynaptic responses. Strikingly, ablation of both MDGA1 and MDGA2 abolished the effect of deleting individual MDGAs that is abrogated by chronic blockade of synaptic activity. Molecular replacement experiments further showed that MDGA1 requires the meprin/A5 protein/PTPmu (MAM) domain, whereas MDGA2 acts via neuroligin-dependent and/or MAM domain-dependent pathways to regulate distinct postsynaptic properties. Together, our data demonstrate that MDGA paralogs act as unique negative regulators of activity-dependent postsynaptic organization at distinct synapse types, and cooperatively contribute to adjustment of excitation-inhibition balance.

Hox gene-specific cellular targeting using split intein Trojan exons.

The Trojan exon method, which makes use of intronically inserted T2A-Gal4 cassettes, has been widely used in Drosophila to create thousands of gene-specific Gal4 driver lines. These dual-purpose lines provide genetic access to specific cell types based on their expression of a native gene while simultaneously mutating one allele of the gene to enable loss-of-function analysis in homozygous animals. While this dual use is often an advantage, the truncation mutations produced by Trojan exons are sometimes deleterious in heterozygotes, perhaps by creating translation products with dominant negative effects. Such mutagenic effects can cause developmental lethality as has been observed with genes encoding essential transcription factors. Given the importance of transcription factors in specifying cell type, alternative techniques for generating specific Gal4 lines that target them are required. Here, we introduce a modified Trojan exon method that retains the targeting fidelity and plug-and-play modularity of the original method but mitigates its mutagenic effects by exploiting the self-splicing capabilities of split inteins. "Split Intein Trojan exons" (siTrojans) ensure that the two truncation products generated from the interrupted allele of the native gene are trans-spliced to create a full-length native protein. We demonstrate the efficacy of siTrojans by generating a comprehensive toolkit of Gal4 and Split Gal4 lines for the segmentally expressed Hox transcription factors and illustrate their use in neural circuit mapping by targeting neurons according to their position along the anterior-posterior axis. Both the method and the Hox gene-specific toolkit introduced here should be broadly useful.

A Guide to Emerging Technologies for Large-Scale and Whole-Brain Optical Imaging of Neuronal Activity.

The mammalian brain is a densely interconnected network that consists of millions to billions of neurons. Decoding how information is represented and processed by this neural circuitry requires the ability to capture and manipulate the dynamics of large populations at high speed and high resolution over a large area of the brain. Although the use of optical approaches by the neuroscience community has rapidly increased over the past two decades, most microscopy approaches are unable to record the activity of all neurons comprising a functional network across the mammalian brain at relevant temporal and spatial resolutions. In this review, we survey the recent development in optical technologies for Ca2+ imaging in this regard and provide an overview of the strengths and limitations of each modality and its potential for scalability. We provide guidance from the perspective of a biological user driven by the typical biological applications and sample conditions. We also discuss the potential for future advances and synergies that could be obtained through hybrid approaches or other modalities.

Axon-axon interactions determine modality-specific wiring and subcellular synaptic specificity in a somatosensory circuit.

Synaptic connections between neurons are often formed in precise subcellular regions of dendritic arbors with implications for information processing within neurons. Cell-cell interactions are widely important for circuit wiring; however, their role in subcellular specificity is not well understood. We studied the role of axon-axon interactions in precise targeting and subcellular wiring of Drosophila somatosensory circuitry. Axons of nociceptive and gentle touch neurons terminate in adjacent, non-overlapping layers in the central nervous system (CNS). Nociceptor and touch receptor axons synapse onto distinct dendritic regions of a second-order interneuron, the dendrites of which span these layers, forming touch-specific and nociceptive-specific connectivity. We found that nociceptor ablation elicited extension of touch receptor axons and presynapses into the nociceptor recipient region, supporting a role for axon-axon interactions in somatosensory wiring. Conversely, touch receptor ablation did not lead to expansion of nociceptor axons, consistent with unidirectional axon-axon interactions. Live imaging provided evidence for sequential arborization of nociceptive and touch neuron axons in the CNS. We propose that axon-axon interactions and modality-specific timing of axon targeting play key roles in subcellular connection specificity of somatosensory circuitry.

Cables1 links Slit/Robo and Wnt/Frizzled signaling in commissural axon guidance.

During neural circuit formation, axons navigate from one intermediate target to the next, until they reach their final target. At intermediate targets, axons switch from being attracted to being repelled by changing the guidance receptors on the growth cone surface. For smooth navigation of the intermediate target and the continuation of their journey, the switch in receptor expression has to be orchestrated in a precisely timed manner. As an alternative to changes in expression, receptor function could be regulated by phosphorylation of receptors or components of signaling pathways. We identified Cables1 as a linker between floor-plate exit of commissural axons, regulated by Slit/Robo signaling, and the rostral turn of post-crossing axons, regulated by Wnt/Frizzled signaling. Cables1 localizes ß-catenin, phosphorylated at tyrosine 489 by Abelson kinase, to the distal axon, which in turn is necessary for the correct navigation of post-crossing commissural axons in the developing chicken spinal cord.

Significance of the anterior cingulate cortex in neurogenesis plasticity: Connections, functions, and disorders across postnatal and adult stages.

The anterior cingulate cortex (ACC) is a complex and continually evolving brain region that remains a primary focus of research due to its multifaceted functions. Various studies and analyses have significantly advanced our understanding of how the ACC participates in a wide spectrum of memory and cognitive processes. However, despite its strong connections to brain areas associated with hippocampal and olfactory neurogenesis, the functions of the ACC in regulating postnatal and adult neurogenesis in these regions are still insufficiently explored. Investigating the intricate involvement of the ACC in neurogenesis could enhance our comprehension of essential aspects of brain plasticity. This involvement stems from its complex circuitry with other relevant brain regions, thereby exerting both direct and indirect impacts on the neurogenesis process. This review sheds light on the promising significance of the ACC in orchestrating postnatal and adult neurogenesis in conditions related to memory, cognitive behavior, and associated disorders.

Brain-inspired neural circuit evolution for spiking neural networks.

In biological neural systems, different neurons are capable of self-organizing to form different neural circuits for achieving a variety of cognitive functions. However, the current design paradigm of spiking neural networks is based on structures derived from deep learning. Such structures are dominated by feedforward connections without taking into account different types of neurons, which significantly prevent spiking neural networks from realizing their potential on complex tasks. It remains an open challenge to apply the rich dynamical properties of biological neural circuits to model the structure of current spiking neural networks. This paper provides a more biologically plausible evolutionary space by combining feedforward and feedback connections with excitatory and inhibitory neurons. We exploit the local spiking behavior of neurons to adaptively evolve neural circuits such as forward excitation, forward inhibition, feedback inhibition, and lateral inhibition by the local law of spike-timing-dependent plasticity and update the synaptic weights in combination with the global error signals. By using the evolved neural circuits, we construct spiking neural networks for image classification and reinforcement learning tasks. Using the brain-inspired Neural circuit Evolution strategy (NeuEvo) with rich neural circuit types, the evolved spiking neural network greatly enhances capability on perception and reinforcement learning tasks. NeuEvo achieves state-of-the-art performance on CIFAR10, DVS-CIFAR10, DVS-Gesture, and N-Caltech101 datasets and achieves advanced performance on ImageNet. Combined with on-policy and off-policy deep reinforcement learning algorithms, it achieves comparable performance with artificial neural networks. The evolved spiking neural circuits lay the foundation for the evolution of complex networks with functions.

A neural probe for concurrent real-time measurement of multiple neurochemicals with electrophysiology in multiple brain regions in vivo.

Real-time monitoring of various neurochemicals with high spatial resolution in multiple brain regions in vivo can elucidate neural circuits related to various brain diseases. However, previous systems for monitoring neurochemicals have limitations in observing multiple neurochemicals without crosstalk in real time, and these methods cannot record electrical activity, which is essential for investigating neural circuits. Here, we present a real-time bimodal (RTBM) neural probe that uses monolithically integrated biosensors and multiple shanks to study the connectivity of neural circuits by measuring multiple neurochemicals and electrical neural activity in real time. Using the RTBM probe, we demonstrate concurrent measurements of four neurochemicals-glucose, lactate, choline, and glutamate without cross-talking each other-and electrical activity in real time in vivo. Additionally, we show the functional connectivity between the medial prefrontal cortex and mediodorsal thalamus through the simultaneous measurement of chemical and electrical signals. We expect that our device will contribute to not only elucidating the role of neurochemicals in neural circuits related to brain functions but also developing drugs for various brain diseases related to neurochemicals.

Monosynaptic Rabies Tracing Reveals Sex- and Age-Dependent Dorsal Subiculum Connectivity Alterations in an Alzheimer's Disease Mouse Model.

The subiculum (SUB), a hippocampal formation structure, is among the earliest brain regions impacted in Alzheimer's disease (AD). Toward a better understanding of AD circuit-based mechanisms, we mapped synaptic circuit inputs to dorsal SUB using monosynaptic rabies tracing in the 5xFAD mouse model by quantitatively comparing the circuit connectivity of SUB excitatory neurons in age-matched controls and 5xFAD mice at different ages for both sexes. Input-mapped brain regions include the hippocampal subregions (CA1, CA2, CA3), medial septum and diagonal band, retrosplenial cortex, SUB, postsubiculum (postSUB), visual cortex, auditory cortex, somatosensory cortex, entorhinal cortex, thalamus, perirhinal cortex (Prh), ectorhinal cortex, and temporal association cortex. We find sex- and age-dependent changes in connectivity strengths and patterns of SUB presynaptic inputs from hippocampal subregions and other brain regions in 5xFAD mice compared with control mice. Significant sex differences for SUB inputs are found in 5xFAD mice for CA1, CA2, CA3, postSUB, Prh, lateral entorhinal cortex, and medial entorhinal cortex: all of these areas are critical for learning and memory. Notably, we find significant changes at different ages for visual cortical inputs to SUB. While the visual function is not ordinarily considered defective in AD, these specific connectivity changes reflect that altered visual circuitry contributes to learning and memory deficits. Our work provides new insights into SUB-directed neural circuit mechanisms during AD progression and supports the idea that neural circuit disruptions are a prominent feature of AD.

Decomposing Neural Circuit Function into Information Processing Primitives.

It is challenging to measure how specific aspects of coordinated neural dynamics translate into operations of information processing and, ultimately, cognitive functions. An obstacle is that simple circuit mechanisms-such as self-sustained or propagating activity and nonlinear summation of inputs-do not directly give rise to high-level functions. Nevertheless, they already implement simple the information carried by neural activity. Here, we propose that distinct functions, such as stimulus representation, working memory, or selective attention, stem from different combinations and types of low-level manipulations of information or information processing primitives. To test this hypothesis, we combine approaches from information theory with simulations of multi-scale neural circuits involving interacting brain regions that emulate well-defined cognitive functions. Specifically, we track the information dynamics emergent from patterns of neural dynamics, using quantitative metrics to detect where and when information is actively buffered, transferred or nonlinearly merged, as possible modes of low-level processing (storage, transfer and modification). We find that neuronal subsets maintaining representations in working memory or performing attentional gain modulation are signaled by their boosted involvement in operations of information storage or modification, respectively. Thus, information dynamic metrics, beyond detecting which network units participate in cognitive processing, also promise to specify how and when they do it, that is, through which type of primitive computation, a capability that may be exploited for the analysis of experimental recordings.

A Prelimbic Cortex-Thalamus Circuit Bidirectionally Regulates Innate and Stress-Induced Anxiety-Like Behavior.

Anxiety-related disorders respond to cognitive behavioral therapies, which involved the medial prefrontal cortex (mPFC). Previous studies have suggested that subregions of the mPFC have different and even opposite roles in regulating innate anxiety. However, the specific causal targets of their descending projections in modulating innate anxiety and stress-induced anxiety have yet to be fully elucidated. Here, we found that among the various downstream pathways of the prelimbic cortex (PL), a subregion of the mPFC, PL-mediodorsal thalamic nucleus (MD) projection, and PL-ventral tegmental area (VTA) projection exhibited antagonistic effects on anxiety-like behavior, while the PL-MD projection but not PL-VTA projection was necessary for the animal to guide anxiety-related behavior. In addition, MD-projecting PL neurons bidirectionally regulated remote but not recent fear memory retrieval. Notably, restraint stress induced high-anxiety state accompanied by strengthening the excitatory inputs onto MD-projecting PL neurons, and inhibiting PL-MD pathway rescued the stress-induced anxiety. Our findings reveal that the activity of PL-MD pathway may be an essential factor to maintain certain level of anxiety, and stress increased the excitability of this pathway, leading to inappropriate emotional expression, and suggests that targeting specific PL circuits may aid the development of therapies for the treatment of stress-related disorders.

A genetically targeted reporter for PET imaging of deep neuronal circuits in mammalian brains.

Positron emission tomography (PET) allows biomolecular tracking but PET monitoring of brain networks has been hampered by a lack of suitable reporters. Here, we take advantage of bacterial dihydrofolate reductase, ecDHFR, and its unique antagonist, TMP, to facilitate in vivo imaging in the brain. Peripheral administration of radiofluorinated and fluorescent TMP analogs enabled PET and intravital microscopy, respectively, of neuronal ecDHFR expression in mice. This technique can be used to the visualize neuronal circuit activity elicited by chemogenetic manipulation in the mouse hippocampus. Notably, ecDHFR-PET allows mapping of neuronal projections in non-human primate brains, demonstrating the applicability of ecDHFR-based tracking technologies for network monitoring. Finally, we demonstrate the utility of TMP analogs for PET studies of turnover and self-assembly of proteins tagged with ecDHFR mutants. These results establish opportunities for a broad spectrum of previously unattainable PET analyses of mammalian brain circuits at the molecular level.

Developmental and evolutionary constraints on olfactory circuit selection.

SignificanceIn this work, we explore the hypothesis that biological neural networks optimize their architecture, through evolution, for learning. We study early olfactory circuits of mammals and insects, which have relatively similar structure but a huge diversity in size. We approximate these circuits as three-layer networks and estimate, analytically, the scaling of the optimal hidden-layer size with input-layer size. We find that both longevity and information in the genome constrain the hidden-layer size, so a range of allometric scalings is possible. However, the experimentally observed allometric scalings in mammals and insects are consistent with biologically plausible values. This analysis should pave the way for a deeper understanding of both biological and artificial networks.

Synchronous inhibitory pathways create both efficiency and diversity in the retina.

Sensory receptive fields combine features that originate in different neural pathways. Retinal ganglion cell receptive fields compute intensity changes across space and time using a peripheral region known as the surround, a property that improves information transmission about natural scenes. The visual features that construct this fundamental property have not been quantitatively assigned to specific interneurons. Here, we describe a generalizable approach using simultaneous intracellular and multielectrode recording to directly measure and manipulate the sensory feature conveyed by a neural pathway to a downstream neuron. By directly controlling the gain of individual interneurons in the circuit, we show that rather than transmitting different temporal features, inhibitory horizontal cells and linear amacrine cells synchronously create the linear surround at different spatial scales and that these two components fully account for the surround. By analyzing a large population of ganglion cells, we observe substantial diversity in the relative contribution of amacrine and horizontal cell visual features while still allowing individual cells to increase information transmission under the statistics of natural scenes. Established theories of efficient coding have shown that optimal information transmission under natural scenes allows a diverse set of receptive fields. Our results give a mechanism for this theory, showing how distinct neural pathways synthesize a sensory computation and how this architecture both generates computational diversity and achieves the objective of high information transmission.