Long-term labeling and imaging of synaptically connected neuronal networks in vivo using double-deletion-mutant rabies viruses.

Rabies-virus-based monosynaptic tracing is a widely used technique for mapping neural circuitry, but its cytotoxicity has confined it primarily to anatomical applications. Here we present a second-generation system for labeling direct inputs to targeted neuronal populations with minimal toxicity, using double-deletion-mutant rabies viruses. Viral spread requires expression of both deleted viral genes in trans in postsynaptic source cells. Suppressing this expression with doxycycline following an initial period of viral replication reduces toxicity to postsynaptic cells. Longitudinal two-photon imaging in vivo indicated that over 90% of both presynaptic and source cells survived for the full 12-week course of imaging. Ex vivo whole-cell recordings at 5 weeks postinfection showed that the second-generation system perturbs input and source cells much less than the first-generation system. Finally, two-photon calcium imaging of labeled networks of visual cortex neurons showed that their visual response properties appeared normal for 10 weeks, the longest we followed them.

The A53T mutation in α-synuclein enhances pro-inflammatory activation in human microglia.

Parkinson's disease (PD) is characterized by the aggregation of α-synuclein into Lewy bodies and Lewy neurites in the brain. Microglia-driven neuroinflammation may contribute to neuronal death in PD, however the exact role of microglia remains unclear and has been understudied. The A53T mutation in the gene coding for α-synuclein has been linked to early-onset PD, and exposure to A53T-mutant human α-synuclein increases the potential for inflammation of murine microglia. To date, its effect has not been studied in human microglia. Here, we used 2-dimensional cultures of human iPSC-derived microglia and transplantation of these cells into the mouse brain to assess the effects of the A53T mutation on human microglia. We found that A53T-mutant human microglia had an intrinsically increased propensity towards pro-inflammatory activation upon inflammatory stimulus. Additionally, A53T mutant microglia showed a strong decrease in catalase expression in non-inflammatory conditions, and increased oxidative stress. Our results indicate that A53T mutant human microglia display cell-autonomous phenotypes that may worsen neuronal damage in early-onset PD.

Mixtures of strategies underlie rodent behavior during reversal learning.

In reversal learning tasks, the behavior of humans and animals is often assumed to be uniform within single experimental sessions to facilitate data analysis and model fitting. However, behavior of agents can display substantial variability in single experimental sessions, as they execute different blocks of trials with different transition dynamics. Here, we observed that in a deterministic reversal learning task, mice display noisy and sub-optimal choice transitions even at the expert stages of learning. We investigated two sources of the sub-optimality in the behavior. First, we found that mice exhibit a high lapse rate during task execution, as they reverted to unrewarded directions after choice transitions. Second, we unexpectedly found that a majority of mice did not execute a uniform strategy, but rather mixed between several behavioral modes with different transition dynamics. We quantified the use of such mixtures with a state-space model, block Hidden Markov Model (block HMM), to dissociate the mixtures of dynamic choice transitions in individual blocks of trials. Additionally, we found that blockHMM transition modes in rodent behavior can be accounted for by two different types of behavioral algorithms, model-free or inference-based learning, that might be used to solve the task. Combining these approaches, we found that mice used a mixture of both exploratory, model-free strategies and deterministic, inference-based behavior in the task, explaining their overall noisy choice sequences. Together, our combined computational approach highlights intrinsic sources of noise in rodent reversal learning behavior and provides a richer description of behavior than conventional techniques, while uncovering the hidden states that underlie the block-by-block transitions.

Effective and efficient neural networks for spike inference from in vivo calcium imaging.

Calcium imaging provides advantages in monitoring large populations of neuronal activities simultaneously. However, it lacks the signal quality provided by neural spike recording in traditional electrophysiology. To address this issue, we developed a supervised data-driven approach to extract spike information from calcium signals. We propose the ENS2 (effective and efficient neural networks for spike inference from calcium signals) system for spike-rate and spike-event predictions using ΔF/F0 calcium inputs based on a U-Net deep neural network. When testing on a large, ground-truth public database, it consistently outperformed state-of-the-art algorithms in both spike-rate and spike-event predictions with reduced computational load. We further demonstrated that ENS2 can be applied to analyses of orientation selectivity in primary visual cortex neurons. We conclude that it would be a versatile inference system that may benefit diverse neuroscience studies.

Differential Effects of Astrocyte Manipulations on Learned Motor Behavior and Neuronal Ensembles in the Motor Cortex.

Although motor cortex is crucial for learning precise and reliable movements, whether and how astrocytes contribute to its plasticity and function during motor learning is unknown. Here, we report that astrocyte-specific manipulations in primary motor cortex (M1) during a lever push task alter motor learning and execution, as well as the underlying neuronal population coding. Mice that express decreased levels of the astrocyte glutamate transporter 1 (GLT1) show impaired and variable movement trajectories, whereas mice with increased astrocyte Gq signaling show decreased performance rates, delayed response times, and impaired trajectories. In both groups, which include male and female mice, M1 neurons have altered interneuronal correlations and impaired population representations of task parameters, including response time and movement trajectories. RNA sequencing further supports a role for M1 astrocytes in motor learning and shows changes in astrocytic expression of glutamate transporter genes, GABA transporter genes, and extracellular matrix protein genes in mice that have acquired this learned behavior. Thus, astrocytes coordinate M1 neuronal activity during motor learning, and our results suggest that this contributes to learned movement execution and dexterity through mechanisms that include regulation of neurotransmitter transport and calcium signaling.SIGNIFICANCE STATEMENT We demonstrate for the first time that in the M1 of mice, astrocyte function is critical for coordinating neuronal population activity during motor learning. We demonstrate that knockdown of astrocyte glutamate transporter GLT1 affects specific components of learning, such as smooth trajectory formation. Altering astrocyte calcium signaling by activation of Gq-DREADD upregulates GLT1 and affects other components of learning, such as response rates and reaction times as well as trajectory smoothness. In both manipulations, neuronal activity in motor cortex is dysregulated, but in different ways. Thus, astrocytes have a crucial role in motor learning via their influence on motor cortex neurons, and they do so by mechanisms that include regulation of glutamate transport and calcium signals.

Fragile X Syndrome Patient-Derived Neurons Developing in the Mouse Brain Show FMR1-Dependent Phenotypes.

BACKGROUND: Fragile X syndrome (FXS) is characterized by physical abnormalities, anxiety, intellectual disability, hyperactivity, autistic behaviors, and seizures. Abnormal neuronal development in FXS is poorly understood. Data on patients with FXS remain scarce, and FXS animal models have failed to yield successful therapies. In vitro models do not fully recapitulate the morphology and function of human neurons. METHODS: To mimic human neuron development in vivo, we coinjected neural precursor cells derived from FXS patient-derived induced pluripotent stem cells and neural precursor cells derived from corrected isogenic control induced pluripotent stem cells into the brain of neonatal immune-deprived mice. RESULTS: The transplanted cells populated the brain and a proportion differentiated into neurons and glial cells. Immunofluorescence and single and bulk RNA sequencing analyses showed accelerated maturation of FXS neurons after an initial delay. Additionally, we found increased percentages of Arc- and Egr-1-positive FXS neurons and wider dendritic protrusions of mature FXS striatal medium spiny neurons. CONCLUSIONS: This transplantation approach provides new insights into the alterations of neuronal development in FXS by facilitating physiological development of cells in a 3-dimensional context.

Cortical-subcortical interactions in goal-directed behavior.

Flexibly selecting appropriate actions in response to complex, ever-changing environments requires both cortical and subcortical regions, which are typically described as participating in a strict hierarchy. In this traditional view, highly specialized subcortical circuits allow for efficient responses to salient stimuli, at the cost of adaptability and context specificity, which are attributed to the neocortex. Their interactions are often described as the cortex providing top-down command signals for subcortical structures to implement; however, as available technologies develop, studies increasingly demonstrate that behavior is represented by brainwide activity and that even subcortical structures contain early signals of choice, suggesting that behavioral functions emerge as a result of different regions interacting as truly collaborative networks. In this review, we discuss the field's evolving understanding of how cortical and subcortical regions in placental mammals interact cooperatively, not only via top-down cortical-subcortical inputs but through bottom-up interactions, especially via the thalamus. We describe our current understanding of the circuitry of both the cortex and two exemplar subcortical structures, the superior colliculus and striatum, to identify which information is prioritized by which regions. We then describe the functional circuits these regions form with one another, and the thalamus, to create parallel loops and complex networks for brainwide information flow. Finally, we challenge the classic view that functional modules are contained within specific brain regions; instead, we propose that certain regions prioritize specific types of information over others, but the subnetworks they form, defined by their anatomical connections and functional dynamics, are the basis of true specialization.

Algebraic approach for subspace decomposition and clustering of neural activity.

We developed an approach to decompose neuronal signals into disjoint components, corresponding to task- or event-based epochs. This protocol describes how to project behavioral templates onto a low-dimensional subspace of neuronal responses to derive neuronal templates, then how to decompose and cluster neuronal responses using these derived templates. We outline these steps on complementary datasets of calcium imaging and spiking activity. Our approach relies on fundamental, linear algebraic principles and is adaptive to the temporal structure of the neural data. For complete details on the use and execution of this protocol, please refer to Adam et al. (2022).1.

Dynamic control of visually guided locomotion through corticosubthalamic projections.

Goal-directed locomotion requires control signals that propagate from higher order areas to regulate spinal mechanisms. The corticosubthalamic hyperdirect pathway offers a short route for cortical information to reach locomotor centers in the brainstem. We developed a task in which head-fixed mice run to a visual landmark and then stop and wait to collect the reward and examined the role of secondary motor cortex (M2) projections to the subthalamic nucleus (STN) in controlling locomotion. Our behavioral modeling, calcium imaging, and optogenetics manipulation results suggest that the M2-STN pathway can be recruited during visually guided locomotion to rapidly and precisely control the pedunculopontine nucleus (PPN) of the mesencephalic locomotor region through the basal ganglia. By capturing the physiological dynamics through a feedback control model and analyzing neuronal signals in M2, PPN, and STN, we find that the corticosubthalamic projections potentially control PPN activity by differentiating an M2 error signal to ensure fast input-output dynamics.

Label-free three-photon imaging of intact human cerebral organoids for tracking early events in brain development and deficits in Rett syndrome.

Human cerebral organoids are unique in their development of progenitor-rich zones akin to ventricular zones from which neuronal progenitors differentiate and migrate radially. Analyses of cerebral organoids thus far have been performed in sectioned tissue or in superficial layers due to their high scattering properties. Here, we demonstrate label-free three-photon imaging of whole, uncleared intact organoids (~2 mm depth) to assess early events of early human brain development. Optimizing a custom-made three-photon microscope to image intact cerebral organoids generated from Rett Syndrome patients, we show defects in the ventricular zone volumetric structure of mutant organoids compared to isogenic control organoids. Long-term imaging live organoids reveals that shorter migration distances and slower migration speeds of mutant radially migrating neurons are associated with more tortuous trajectories. Our label-free imaging system constitutes a particularly useful platform for tracking normal and abnormal development in individual organoids, as well as for screening therapeutic molecules via intact organoid imaging.

Spatiotemporal dynamics of noradrenaline during learned behaviour.

Noradrenaline released from the locus coeruleus (LC) is a ubiquitous neuromodulator1-4 that has been linked to multiple functions including arousal5-8, action and sensory gain9-11, and learning12-16. Whether and how activation of noradrenaline-expressing neurons in the LC (LC-NA) facilitates different components of specific behaviours is unknown. Here we show that LC-NA activity displays distinct spatiotemporal dynamics to enable two functions during learned behaviour: facilitating task execution and encoding reinforcement to improve performance accuracy. To examine these functions, we used a behavioural task in mice with graded auditory stimulus detection and task performance. Optogenetic inactivation of the LC demonstrated that LC-NA activity was causal for both task execution and optimization. Targeted recordings of LC-NA neurons using photo-tagging, two-photon micro-endoscopy and two-photon output monitoring showed that transient LC-NA activation preceded behavioural execution and followed reinforcement. These two components of phasic activity were heterogeneously represented in LC-NA cortical outputs, such that the behavioural response signal was higher in the motor cortex and facilitated task execution, whereas the negative reinforcement signal was widely distributed among cortical regions and improved response sensitivity on the subsequent trial. Modular targeting of LC outputs thus enables diverse functions, whereby some noradrenaline signals are segregated among targets, whereas others are broadly distributed.

Molecular Signatures of Response to Mecasermin in Children With Rett Syndrome.

Rett syndrome (RTT) is a devastating neurodevelopmental disorder without effective treatments. Attempts at developing targetted therapies have been relatively unsuccessful, at least in part, because the genotypical and phenotypical variability of the disorder. Therefore, identification of biomarkers of response and patients' stratification are high priorities. Administration of Insulin-like Growth Factor 1 (IGF-1) and related compounds leads to significant reversal of RTT-like symptoms in preclinical mouse models. However, improvements in corresponding clinical trials have not been consistent. A 20-weeks phase I open label trial of mecasermin (recombinant human IGF-1) in children with RTT demonstrated significant improvements in breathing phenotypes. However, a subsequent randomised controlled phase II trial did not show significant improvements in primary outcomes although two secondary clinical endpoints showed positive changes. To identify molecular biomarkers of response and surrogate endpoints, we used RNA sequencing to measure differential gene expression in whole blood samples of participants in the abovementioned phase I mecasermin trial. When all participants (n = 9) were analysed, gene expression was unchanged during the study (baseline vs. end of treatment, T0-T3). However, when participants were subclassified in terms of breathing phenotype improvement, specifically by their plethysmography-based apnoea index, individuals with moderate-severe apnoea and breathing improvement (Responder group) displayed significantly different transcript profiles compared to the other participants in the study (Mecasermin Study Reference group, MSR). Many of the differentially expressed genes are involved in the regulation of cell cycle processes and immune responses, as well as in IGF-1 signalling and breathing regulation. While the Responder group showed limited gene expression changes in response to mecasermin, the MSR group displayed marked differences in the expression of genes associated with inflammatory processes (e.g., neutrophil activation, complement activation) throughout the trial. Our analyses revealed gene expression profiles associated with severe breathing phenotype and its improvement after mecasermin administration in RTT, and suggest that inflammatory/immune pathways and IGF-1 signalling contribute to treatment response. Overall, these data support the notion that transcript profiles have potential as biomarkers of response to IGF-1 and related compounds.

Brain-wide mapping of inputs to the mouse lateral posterior (LP/Pulvinar) thalamus-anterior cingulate cortex network.

The rodent homolog of the primate pulvinar, the lateral posterior (LP) thalamus, is extensively interconnected with multiple cortical areas. While these cortical interactions can span the entire LP, subdivisions of the LP are characterized by differential connections with specific cortical regions. In particular, the medial LP has reciprocal connections with frontoparietal cortical areas, including the anterior cingulate cortex (ACC). The ACC plays an integral role in top-down sensory processing and attentional regulation, likely exerting some of these functions via the LP. However, little is known about how ACC and LP interact, and about the information potentially integrated in this reciprocal network. Here, we address this gap by employing a projection-specific monosynaptic rabies tracing strategy to delineate brain-wide inputs to bottom-up LP→ACC and top-down ACC→LP neurons. We find that LP→ACC neurons receive inputs from widespread cortical regions, including primary and higher order sensory and motor cortical areas. LP→ACC neurons also receive extensive subcortical inputs, particularly from the intermediate and deep layers of the superior colliculus (SC). Sensory inputs to ACC→LP neurons largely arise from visual cortical areas. In addition, ACC→LP neurons integrate cross-hemispheric prefrontal cortex inputs as well as inputs from higher order medial cortex. Our brain-wide anatomical mapping of inputs to the reciprocal LP-ACC pathways provides a roadmap for understanding how LP and ACC communicate different sources of information to mediate attentional control and visuomotor functions.

Multiplexed action-outcome representation by striatal striosome-matrix compartments detected with a mouse cost-benefit foraging task.

Learning about positive and negative outcomes of actions is crucial for survival and underpinned by conserved circuits including the striatum. How associations between actions and outcomes are formed is not fully understood, particularly when the outcomes have mixed positive and negative features. We developed a novel foraging ('bandit') task requiring mice to maximize rewards while minimizing punishments. By 2-photon Ca++ imaging, we monitored activity of visually identified anterodorsal striatal striosomal and matrix neurons. We found that action-outcome associations for reward and punishment were encoded in parallel in partially overlapping populations. Single neurons could, for one action, encode outcomes of opposing valence. Striosome compartments consistently exhibited stronger representations of reinforcement outcomes than matrix, especially for high reward or punishment prediction errors. These findings demonstrate multiplexing of action-outcome contingencies by single identified striatal neurons and suggest that striosomal neurons are particularly important in action-outcome learning.

Heterosynaptic Plasticity and the Experience-Dependent Refinement of Developing Neuronal Circuits.

Neurons remodel the structure and strength of their synapses during critical periods of development in order to optimize both perception and cognition. Many of these developmental synaptic changes are thought to occur through synapse-specific homosynaptic forms of experience-dependent plasticity. However, homosynaptic plasticity can also induce or contribute to the plasticity of neighboring synapses through heterosynaptic interactions. Decades of research in vitro have uncovered many of the molecular mechanisms of heterosynaptic plasticity that mediate local compensation for homosynaptic plasticity, facilitation of further bouts of plasticity in nearby synapses, and cooperative induction of plasticity by neighboring synapses acting in concert. These discoveries greatly benefited from new tools and technologies that permitted single synapse imaging and manipulation of structure, function, and protein dynamics in living neurons. With the recent advent and application of similar tools for in vivo research, it is now feasible to explore how heterosynaptic plasticity contribute to critical periods and the development of neuronal circuits. In this review, we will first define the forms heterosynaptic plasticity can take and describe our current understanding of their molecular mechanisms. Then, we will outline how heterosynaptic plasticity may lead to meaningful refinement of neuronal responses and observations that suggest such mechanisms are indeed at work in vivo. Finally, we will use a well-studied model of cortical plasticity-ocular dominance plasticity during a critical period of visual cortex development-to highlight the molecular overlap between heterosynaptic and developmental forms of plasticity, and suggest potential avenues of future research.

Hemodynamic molecular imaging of tumor-associated enzyme activity in the living brain.

Molecular imaging could have great utility for detecting, classifying, and guiding treatment of brain disorders, but existing probes offer limited capability for assessing relevant physiological parameters. Here, we describe a potent approach for noninvasive mapping of cancer-associated enzyme activity using a molecular sensor that acts on the vasculature, providing a diagnostic readout via local changes in hemodynamic image contrast. The sensor is targeted at the fibroblast activation protein (FAP), an extracellular dipeptidase and clinically relevant biomarker of brain tumor biology. Optimal FAP sensor variants were identified by screening a series of prototypes for responsiveness in a cell-based bioassay. The best variant was then applied for quantitative neuroimaging of FAP activity in rats, where it reveals nanomolar-scale FAP expression by xenografted cells. The activated probe also induces robust hemodynamic contrast in nonhuman primate brain. This work thus demonstrates a potentially translatable strategy for ultrasensitive functional imaging of molecular targets in neuromedicine.

Reliable Sensory Processing in Mouse Visual Cortex through Cooperative Interactions between Somatostatin and Parvalbumin Interneurons.

Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). However, under certain conditions, neurons can respond reliably with highly precise responses to the same visual stimuli from trial to trial. This suggests that there exists intrinsic neural circuit mechanisms that dynamically modulate the intertrial variability of visual cortical neurons. Here, we sought to elucidate the role of different inhibitory interneurons (INs) in reliable coding in mouse V1. To study the interactions between somatostatin-expressing interneurons (SST-INs) and parvalbumin-expressing interneurons (PV-INs), we used a dual-color calcium imaging technique that allowed us to simultaneously monitor these two neural ensembles while awake mice, of both sexes, passively viewed natural movies. SST neurons were more active during epochs of reliable pyramidal neuron firing, whereas PV neurons were more active during epochs of unreliable firing. SST neuron activity lagged that of PV neurons, consistent with a feedback inhibitory SST→PV circuit. To dissect the role of this circuit in pyramidal neuron activity, we used temporally limited optogenetic activation and inactivation of SST and PV interneurons during periods of reliable and unreliable pyramidal cell firing. Transient firing of SST neurons increased pyramidal neuron reliability by actively suppressing PV neurons, a proposal that was supported by a rate-based model of V1 neurons. These results identify a cooperative functional role for the SST→PV circuit in modulating the reliability of pyramidal neuron activity.SIGNIFICANCE STATEMENT Cortical neurons often respond to identical sensory stimuli with large variability. However, under certain conditions, the same neurons can also respond highly reliably. The circuit mechanisms that contribute to this modulation remain unknown. Here, we used novel dual-wavelength calcium imaging and temporally selective optical perturbation to identify an inhibitory neural circuit in visual cortex that can modulate the reliability of pyramidal neurons to naturalistic visual stimuli. Our results, supported by computational models, suggest that somatostatin interneurons increase pyramidal neuron reliability by suppressing parvalbumin interneurons via the inhibitory SST→PV circuit. These findings reveal a novel role of the SST→PV circuit in modulating the fidelity of neural coding critical for visual perception.

High-content image-based analysis and proteomic profiling identifies Tau phosphorylation inhibitors in a human iPSC-derived glutamatergic neuronal model of tauopathy.

Mutations in MAPT (microtubule-associated protein tau) cause frontotemporal dementia (FTD). MAPT mutations are associated with abnormal tau phosphorylation levels and accumulation of misfolded tau protein that can propagate between neurons ultimately leading to cell death (tauopathy). Recently, a p.A152T tau variant was identified as a risk factor for FTD, Alzheimer's disease, and synucleinopathies. Here we used induced pluripotent stem cells (iPSC) from a patient carrying this p.A152T variant to create a robust, functional cellular assay system for probing pathophysiological tau accumulation and phosphorylation. Using stably transduced iPSC-derived neural progenitor cells engineered to enable inducible expression of the pro-neural transcription factor Neurogenin 2 (Ngn2), we generated disease-relevant, cortical-like glutamatergic neurons in a scalable, high-throughput screening compatible format. Utilizing automated confocal microscopy, and an advanced image-processing pipeline optimized for analysis of morphologically complex human neuronal cultures, we report quantitative, subcellular localization-specific effects of multiple kinase inhibitors on tau, including ones under clinical investigation not previously reported to affect tau phosphorylation. These results demonstrate the potential for using patient iPSC-derived ex vivo models of tauopathy as genetically accurate, disease-relevant systems to probe tau biochemistry and support the discovery of novel therapeutics for tauopathies.

De-scattering with Excitation Patterning enables rapid wide-field imaging through scattering media.

Nonlinear optical microscopy has enabled in vivo deep tissue imaging on the millimeter scale. A key unmet challenge is its limited throughput especially compared to rapid wide-field modalities that are used ubiquitously in thin specimens. Wide-field imaging methods in tissue specimens have found successes in optically cleared tissues and at shallower depths, but the scattering of emission photons in thick turbid samples severely degrades image quality at the camera. To address this challenge, we introduce a novel technique called De-scattering with Excitation Patterning or "DEEP," which uses patterned nonlinear excitation followed by computational imaging-assisted wide-field detection. Multiphoton temporal focusing allows high-resolution excitation patterns to be projected deep inside specimen at multiple scattering lengths due to the use of long wavelength light. Computational reconstruction allows high-resolution structural features to be reconstructed from tens to hundreds of DEEP images instead of millions of point-scanning measurements.