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.

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.

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.

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

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Apply singular value decomposition to derive a low-dimensional neural response subspace

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Project behavioral templates onto the subspace to derive neuronal templates

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Every neuronal response can be decomposed as a weighted sum of neuronal templates

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The derived weights can be used for clustering the neurons

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

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.

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.

Using a combination of optogenetics, 2-photon imaging, extracellular recordings, and control theoretic models in behaving mice, Adam et al. find that the M2-STN projection sends stop signals to halt visually guided locomotion and potentially controls the MLR/PPN through SNr by differentiating an M2 error signal for the rapid control of locomotion.

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.

The role that the striatum plays in tracking the association between actions and combinations of rewarding and aversive outcomes remains unclear. Here, by using both calcium imaging in mice and reinforcement learning models, the authors find that individual striatal neurons can encode associations between actions and multiple, sometimes conflicting, outcomes.

A Platform for Spatiotemporal "Matrix" Stimulation in Brain Networks Reveals Novel Forms of Circuit Plasticity

Here we demonstrate a facile method by which to deliver complex spatiotemporal stimulation to neural networks in fast patterns, to trigger interesting forms of circuit-level plasticity in cortical areas. We present a complete platform by which patterns of electricity can be arbitrarily defined and distributed across a brain circuit, either simultaneously, asynchronously, or in complex patterns that can be easily designed and orchestrated with precise timing. Interfacing with acute slices of mouse cortex, we show that our system can be used to activate neurons at many locations and drive synaptic transmission in distributed patterns, and that this elicits new forms of plasticity that may not be observable via traditional methods, including interesting measurements of associational and sequence plasticity. Finally, we introduce an automated "network assay" for imaging activation and plasticity across a circuit. Spatiotemporal stimulation opens the door for high-throughput explorations of plasticity at the circuit level, and may provide a basis for new types of adaptive neural prosthetics.

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.

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.

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.

Locus Coeruleus Norepinephrine in Learned Behavior: Anatomical Modularity and Spatiotemporal Integration in Targets

The locus coeruleus (LC), a small brainstem nucleus, is the primary source of the neuromodulator norepinephrine (NE) in the brain. The LC receives input from widespread brain regions, and projects throughout the forebrain, brainstem, cerebellum, and spinal cord. LC neurons release NE to control arousal, but also in the context of a variety of sensory-motor and behavioral functions. Despite its brain-wide effects, much about the role of LC-NE in behavior and the circuits controlling LC activity is unknown. New evidence suggests that the modular input-output organization of the LC could enable transient, task-specific modulation of distinct brain regions. Future work must further assess whether this spatial modularity coincides with functional differences in LC-NE subpopulations acting at specific times, and how such spatiotemporal specificity might influence learned behaviors. Here, we summarize the state of the field and present new ideas on the role of LC-NE in learned behaviors.

Astrocyte glutamate uptake coordinates experience-dependent, eye-specific refinement in developing visual cortex

The uptake of glutamate by astrocytes actively shapes synaptic transmission, however its role in the development and plasticity of neuronal circuits remains poorly understood. The astrocytic glutamate transporter, GLT1 is the predominant source of glutamate clearance in the adult mouse cortex. Here, we examined the structural and functional development of the visual cortex in GLT1 heterozygous (HET) mice using two-photon microscopy, immunohistochemistry and slice electrophysiology. We find that though eye-specific thalamic axonal segregation is intact, binocular refinement in the primary visual cortex is disrupted. Eye-specific responses to visual stimuli in GLT1 HET mice show altered binocular matching, with abnormally high responses to ipsilateral compared to contralateral eye stimulation and a greater mismatch between preferred orientation selectivity of ipsilateral and contralateral eye responses. Furthermore, we observe an increase in dendritic spine density in the basal dendrites of layer 2/3 excitatory neurons suggesting aberrant spine pruning. Monocular deprivation induces atypical ocular dominance plasticity in GLT1 HET mice, with an unusual depression of ipsilateral open eye responses; however, this change in ipsilateral responses correlates well with an upregulation of GLT1 protein following monocular deprivation. These results demonstrate that a key function of astrocytic GLT1 function during development is the experience-dependent refinement of ipsilateral eye inputs relative to contralateral eye inputs in visual cortex.

A low-cost 3D printed microfluidic bioreactor and imaging chamber for live-organoid imaging

Organoids are biological systems grown in vitro and are observed to self-organize into 3D cellular tissues of specific organs. Brain organoids have emerged as valuable models for the study of human brain development in health and disease. Researchers are now in need of improved culturing and imaging tools to capture the in vitro dynamics of development processes in the brain. Here, we describe the design of a microfluidic chip and bioreactor, to enable in situ tracking and imaging of brain organoids on-chip. The low-cost 3D printed microfluidic bioreactor supports organoid growth and provides an optimal imaging chamber for live-organoid imaging, with drug delivery support. This fully isolated design of a live-cell imaging and culturing platform enables long-term live-imaging of the intact live brain organoids as it grows. We can thus analyze their self-organization in a controlled environment with high temporal and spatial resolution.

Signal-to-signal neural networks for improved spike estimation from calcium imaging data

Spiking information of individual neurons is essential for functional and behavioral analysis in neuroscience research. Calcium imaging techniques are generally employed to obtain activities of neuronal populations. However, these techniques result in slowly-varying fluorescence signals with low temporal resolution. Estimating the temporal positions of the neuronal action potentials from these signals is a challenging problem. In the literature, several generative model-based and data-driven algorithms have been studied with varied levels of success. This article proposes a neural network-based signal-to-signal conversion approach, where it takes as input raw-fluorescence signal and learns to estimate the spike information in an end-to-end fashion. Theoretically, the proposed approach formulates the spike estimation as a single channel source separation problem with unknown mixing conditions. The source corresponding to the action potentials at a lower resolution is estimated at the output. Experimental studies on the spikefinder challenge dataset show that the proposed signal-to-signal conversion approach significantly outperforms state-of-the-art-methods in terms of Pearson's correlation coefficient, Spearman's rank correlation coefficient and yields comparable performance for the area under the receiver operating characteristics measure. We also show that the resulting system: (a) has low complexity with respect to existing supervised approaches and is reproducible; (b) is layer-wise interpretable, and (c) has the capability to generalize across different calcium indicators.

Functional parcellation of mouse visual cortex using statistical techniques reveals response-dependent clustering of cortical processing areas

The visual cortex of the mouse brain can be divided into ten or more areas that each contain complete or partial retinotopic maps of the contralateral visual field. It is generally assumed that these areas represent discrete processing regions. In contrast to the conventional input-output characterizations of neuronal responses to standard visual stimuli, here we asked whether six of the core visual areas have responses that are functionally distinct from each other for a given visual stimulus set, by applying machine learning techniques to distinguish the areas based on their activity patterns. Visual areas defined by retinotopic mapping were examined using supervised classifiers applied to responses elicited by a range of stimuli. Using two distinct datasets obtained using wide-field and two-photon imaging, we show that the area labels predicted by the classifiers were highly consistent with the labels obtained using retinotopy. Furthermore, the classifiers were able to model the boundaries of visual areas using resting state cortical responses obtained without any overt stimulus, in both datasets. With the wide-field dataset, clustering neuronal responses using a constrained semi-supervised classifier showed graceful degradation of accuracy. The results suggest that responses from visual cortical areas can be classified effectively using data-driven models. These responses likely reflect unique circuits within each area that give rise to activity with stronger intra-areal than inter-areal correlations, and their responses to controlled visual stimuli across trials drive higher areal classification accuracy than resting state responses.

Distinct prefrontal top-down circuits differentially modulate sensorimotor behavior

Sensorimotor behaviors require processing of behaviorally relevant sensory cues and the ability to select appropriate responses from a vast behavioral repertoire. Modulation by the prefrontal cortex (PFC) is thought to be key for both processes, but the precise role of specific circuits remains unclear. We examined the sensorimotor function of anatomically distinct outputs from a subdivision of the mouse PFC, the anterior cingulate cortex (ACC). Using a visually guided two-choice behavioral paradigm with multiple cue-response mappings, we dissociated the sensory and motor response components of sensorimotor control. Projection-specific two-photon calcium imaging and optogenetic manipulations show that ACC outputs to the superior colliculus, a key midbrain structure for response selection, principally coordinate specific motor responses. Importantly, ACC outputs exert control by reducing the innate response bias of the superior colliculus. In contrast, ACC outputs to the visual cortex facilitate sensory processing of visual cues. Our results ascribe motor and sensory roles to ACC projections to the superior colliculus and the visual cortex and demonstrate for the first time a circuit motif for PFC function wherein anatomically non-overlapping output pathways coordinate complementary but distinct aspects of visual sensorimotor behavior.

The neural circuit mechanisms for sensorimotor control by the prefrontal cortex (PFC) are unclear. Here, the authors show that PFC outputs to the visual cortex and superior colliculus respectively facilitate sensory processing and action selection, allowing the PFC to independently control complementary but distinct behavioral functions.

Quantitative third-harmonic generation imaging of mouse visual cortex areas reveals correlations between functional maps and structural substrates

The structure of brain regions is assumed to correlate with their function, but there are very few instances in which the relationship has been demonstrated in the live brain. This is due to the difficulty of simultaneously measuring functional and structural properties of brain areas, particularly at cellular resolution. Here, we performed label-free, third-harmonic generation (THG) microscopy to obtain a key structural signature of cortical areas, their effective attenuation lengths (EAL), in the vertical columns of functionally defined primary visual cortex and five adjacent visual areas in awake mice. EALs measured by THG microscopy in the cortex and white matter showed remarkable correspondence with the functional retinotopic sign map of each area. Structural features such as cytoarchitecture, myeloarchitecture and blood vessel architecture were correlated with areal EAL values, suggesting that EAL is a function of these structural features as an optical property of these areas. These results demonstrate for the first time a strong relationship between structural substrates of visual cortical areas and their functional representation maps in vivo. This study may also help in understanding the coupling between structure and function in other animal models as well as in humans.

Level-wise Subject adaptation to improve classification of motor and mental EEG tasks

Classification of various cognitive and motor tasks using electroencephalogram (EEG) signals is necessary for building Brain Computer Interfaces (BCI) that are noninvasive. However, achieving high classification accuracy in a multi-subject multitask scenario is a challenge. A noticeable reduction in accuracy is observed when the subjects between train and test are mismatched. Drawing a similarity from speaker adaptation approaches in speech, we propose a method to perform subject-wise adaptation of EEG in order to improve the task classification performance. A Common Spatial Pattern (CSP) approach is employed for feature extraction. Gaussian Mixture Model (GMM) based subject-specific models are built for each of the tasks. Maximum a-posterior (MAP) adaptation is performed, and an absolute improvement of 1.22-7.26% is observed in the average accuracy.

Subspace techniques for task-independent EEG person identification

There has been a growing interest in studying electroencephalography signals (EEG) as a possible biometric. The brain signals captured by EEG are rich and carry information related to the individual, tasks being performed, mental state, and other channel/measurement noise due to session variability and artifacts. To effectively extract person-specific signatures present in EEG, it is necessary to define a subspace that enhances the biometric information and suppresses other nuisance factors. i-vector and x-vector are state-of-art subspace techniques used in speaker recognition. In this paper, novel modifications are proposed for both frameworks to project person-specific signatures from multi-channel EEG into a subspace. The modified i-vector and x-vector systems outperform baseline i-vector and x-vector systems with an absolute improvement of 10.5% and 15.9%, respectively.

Imprinted Maternally Expressed microRNAs Antagonize Paternally Driven Gene Programs in Neurons

Imprinted genes with parental-biased allelic expression are frequently co-regulated and enriched in common biological pathways. Here, we functionally characterize a large cluster of microRNAs (miRNAs) expressed from the maternally inherited allele ("maternally expressed") to explore the molecular and cellular consequences of imprinted miRNA activity. Using an induced neuron (iN) culture system, we show that maternally expressed miRNAs from the miR-379/410 cluster direct the RNA-induced silencing complex (RISC) to transcriptional and developmental regulators, including paternally expressed transcripts like Plagl1. Maternal deletion of this imprinted miRNA cluster resulted in increased protein levels of several targets and upregulation of a broader transcriptional program regulating synaptic transmission and neuronal function. A subset of the transcriptional changes resulting from miR-379/410 deletion can be attributed to de-repression of Plagl1. These data suggest maternally expressed miRNAs antagonize paternally driven gene programs in neurons.

Noradrenergic signaling in the wakeful state inhibits microglial surveillance and synaptic plasticity in the mouse visual cortex

Microglia are the brain's resident innate immune cells and also have a role in synaptic plasticity. Microglial processes continuously survey the brain parenchyma, interact with synaptic elements and maintain tissue homeostasis. However, the mechanisms that control surveillance and its role in synaptic plasticity are poorly understood. Microglial dynamics in vivo have been primarily studied in anesthetized animals. Here we report that microglial surveillance and injury response are reduced in awake mice as compared to anesthetized mice, suggesting that arousal state modulates microglial function. Pharmacologic stimulation of β₂-adrenergic receptors recapitulated these observations and disrupted experience-dependent plasticity, and these effects required the presence of β₂-adrenergic receptors in microglia. These results indicate that microglial roles in surveillance and synaptic plasticity in the mouse brain are modulated by noradrenergic tone fluctuations between arousal states and emphasize the need to understand the effect of disruptions of adrenergic signaling in neurodevelopment and neuropathology.

Towards a better diagnosis and treatment of Rett syndrome: a model synaptic disorder

With the recent 50th anniversary of the first publication on Rett syndrome, and the almost 20 years since the first report on the link between Rett syndrome and MECP2 mutations, it is important to reflect on the tremendous advances in our understanding and their implications for the diagnosis and treatment of this neurodevelopmental disorder. Rett syndrome features an interesting challenge for biologists and clinicians, as the disorder lies at the intersection of molecular mechanisms of epigenetic regulation and neurophysiological alterations in synapses and circuits that together contribute to severe pathophysiological endophenotypes. Genetic, clinical, and neurobiological evidences support the notion that Rett syndrome is primarily a synaptic disorder, and a disease model for both intellectual disability and autism spectrum disorder. This review examines major developments in both recent neurobiological and preclinical findings of Rett syndrome, and to what extent they are beginning to impact our understanding and management of the disorder. It also discusses potential applications of knowledge on synaptic plasticity abnormalities in Rett syndrome to its diagnosis and treatment.

Pharmacological enhancement of KCC2 gene expression exerts therapeutic effects on human Rett syndrome neurons and Mecp2 mutant mice

Rett syndrome (RTT) is a neurodevelopmental disorder caused by mutations in the methyl CpG binding protein 2 (MECP2) gene. There are currently no approved treatments for RTT. The expression of K+/Cl- cotransporter 2 (KCC2), a neuron-specific protein, has been found to be reduced in human RTT neurons and in RTT mouse models, suggesting that KCC2 might play a role in the pathophysiology of RTT. To develop neuron-based high-throughput screening (HTS) assays to identify chemical compounds that enhance the expression of the KCC2 gene, we report the generation of a robust high-throughput drug screening platform that allows for the rapid assessment of KCC2 gene expression in genome-edited human reporter neurons. From an unbiased screen of more than 900 small-molecule chemicals, we have identified a group of compounds that enhance KCC2 expression termed KCC2 expression-enhancing compounds (KEECs). The identified KEECs include U.S. Food and Drug Administration-approved drugs that are inhibitors of the fms-like tyrosine kinase 3 (FLT3) or glycogen synthase kinase 3β (GSK3β) pathways and activators of the sirtuin 1 (SIRT1) and transient receptor potential cation channel subfamily V member 1 (TRPV1) pathways. Treatment with hit compounds increased KCC2 expression in human wild-type (WT) and isogenic MECP2 mutant RTT neurons, and rescued electrophysiological and morphological abnormalities of RTT neurons. Injection of KEEC KW-2449 or piperine in Mecp2 mutant mice ameliorated disease-associated respiratory and locomotion phenotypes. The small-molecule compounds described in our study may have therapeutic effects not only in RTT but also in other neurological disorders involving dysregulation of KCC2.

Spike Estimation from Fluorescence Signals Using High-Resolution Property of Group Delay

Spike estimation from calcium (Ca²⁺) fluorescence signals is a fundamental and challenging problem in neuroscience. Several models and algorithms have been proposed for this task over the past decade. Nevertheless, it is still hard to achieve accurate spike positions from the Ca²⁺ fluorescence signals. While existing methods rely on data-driven methods and the physiology of neurons for modelling the spiking process, this work exploits the nature of the fluorescence responses to spikes using signal processing. We first motivate the problem by a novel analysis of the high-resolution property of minimum-phase group delay (GD) functions for multi-pole resonators. The resonators could be connected either in series or in parallel. The Ca²⁺ indicator responds to a spike with a sudden rise, that is followed by an exponential decay. We interpret the Ca²⁺ signal as the response of an impulse train to the change in Ca²⁺ concentration, where the Ca²⁺ response corresponds to a resonator. We perform minimum-phase group delay-based filtering of the Ca²⁺ signal for resolving spike locations. The performance of the proposed algorithm is evaluated on nine datasets spanning various indicators, sampling rates and, mouse brain regions. The proposed approach: GDspike, is compared with other spike estimation methods including MLspike, Vogelstein de-convolution algorithm, and data-driven Spike Triggered Mixture (STM) model. The performance of GDSpike is superior to that of the Vogelstein algorithm and is comparable to that of MLSpike. It can also be used to post-process the output of MLSpike, which further enhances the performance.

Active control of arousal by a locus coeruleus GABAergic circuit

Arousal responses linked to locus coeruleus noradrenergic (LC-NA) activity affect cognition. However, the mechanisms that control modes of LC-NA activity remain unknown. Here, we reveal a local population of GABAergic neurons (LC-GABA) capable of modulating LC-NA activity and arousal. Retrograde tracing shows that inputs to LC-GABA and LC-NA neurons arise from similar regions, though a few regions provide differential inputs to one subtype over the other. Recordings in the locus coeruleus demonstrate two modes of LC-GABA responses whereby spiking is either correlated or broadly anticorrelated with LC-NA responses, reflecting anatomically similar and functionally coincident inputs, or differential and non-coincident inputs, to LC-NA and LC-GABA neurons. Coincident inputs control the gain of LC-NA-mediated arousal responses, whereas non-coincident inputs, such as from the prefrontal cortex to the locus coeruleus, alter global arousal levels. These findings demonstrate distinct modes by which an inhibitory locus coeruleus circuit regulates arousal in the brain.

Locally coordinated synaptic plasticity of visual cortex neurons in vivo

Plasticity of cortical responses in vivo involves activity-dependent changes at synapses, but the manner in which different forms of synaptic plasticity act together to create functional changes in neurons remains unknown. We found that spike timing-induced receptive field plasticity of visual cortex neurons in mice is anchored by increases in the synaptic strength of identified spines. This is accompanied by a decrease in the strength of adjacent spines on a slower time scale. The locally coordinated potentiation and depression of spines involves prominent AMPA receptor redistribution via targeted expression of the immediate early gene product Arc. Hebbian strengthening of activated synapses and heterosynaptic weakening of adjacent synapses thus cooperatively orchestrate cell-wide plasticity of functional neuronal responses.

Neural mechanisms of sensorimotor transformation and action selection

Ray Guillery made major contributions to our understanding of the development and function of the brain. One of his principal conceptual insights, developed together with Murray Sherman [S.M. Sherman & R.W. Guillery (2001) Exploring the Thalamus. Elsevier, Amstrerdam; S. Sherman & R. Guillery (2006) Exploring the Thalamus and Its Role in Cortical Functioning. Academic Press, New York, NY; S.M. Sherman & R.W. Guillery (2013) Functional Connections of Cortical Areas: A New View from the Thalamus. MIT Press, Cambridge, MA and then in his last book (R. Guillery (2017) The Brain as a Tool: A Neuroscientist's Account. Oxford University Press, Oxford, UK)], was that the brain is a 'tool' to understand the world. In this view, the brain does not passively process sensory information and use the result to inform motor outputs. Rather, sensory and motor signals are widely broadcast and inextricably linked, with ongoing sensorimotor transformations serving as the basis for interaction with the outside world. Here, we describe recent studies from our laboratory and others which demonstrate this astute framing of the link among sensation, perception, and action postulated by Guillery and others [G. Deco & E.T. Rolls (2005) Prog Neurobiol, 76, 236-256; P. Cisek & J.F. Kalaska (2010) Annu Rev Neurosci, 33, 269-298]. Guillery situated his understanding in the deeply intertwined relationship between the thalamus and cortex, and importantly in the feedback from cortex to thalamus which in turn influences feed-forward drive to cortex [S.M. Sherman & R.W. Guillery (2001) Exploring the Thalamus. Elsevier, Amstrerdam; S. Sherman & R. Guillery (2006) Exploring the Thalamus and Its Role in Cortical Functioning. Academic Press, New York, NY]. We extend these observations to argue that brain mechanisms for sensorimotor transformations involve cortical and subcortical circuits that create internal models as a substrate for action, that a key role of sensory inputs is to update such models, and that a major function of sensorimotor processing underlying cognition is to enable action selection and execution.

Task-dependent representations of stimulus and choice in mouse parietal cortex

The posterior parietal cortex (PPC) has been implicated in perceptual decisions, but whether its role is specific to sensory processing or sensorimotor transformation is not well understood. Here, we trained mice to perform a go/no-go visual discrimination task and imaged the activity of neurons in primary visual cortex (V1) and PPC during engaged behavior and passive viewing. Unlike V1 neurons, which respond robustly to stimuli in both conditions, most PPC neurons respond exclusively during task engagement. To test whether signals in PPC primarily encoded the stimulus or the animal's impending choice, we image the same neurons before and after re-training mice with a reversed sensorimotor contingency. Unlike V1 neurons, most PPC neurons reflect the animal's choice of the new target stimulus after re-training. Mouse PPC is therefore strongly task-dependent, reflects choice more than stimulus, and may play a role in the transformation of visual inputs into motor commands.

Calcium-dependent molecular fMRI using a magnetic nanosensor

Calcium ions are ubiquitous signalling molecules in all multicellular organisms, where they mediate diverse aspects of intracellular and extracellular communication over widely varying temporal and spatial scales ¹ . Though techniques to map calcium-related activity at a high resolution by optical means are well established, there is currently no reliable method to measure calcium dynamics over large volumes in intact tissue ² . Here, we address this need by introducing a family of magnetic calcium-responsive nanoparticles (MaCaReNas) that can be detected by magnetic resonance imaging (MRI). MaCaReNas respond within seconds to [Ca²⁺] changes in the 0.1-1.0 mM range, suitable for monitoring extracellular calcium signalling processes in the brain. We show that the probes permit the repeated detection of brain activation in response to diverse stimuli in vivo. MaCaReNas thus provide a tool for calcium-activity mapping in deep tissue and offer a precedent for the development of further nanoparticle-based sensors for dynamic molecular imaging with MRI.

MeCP2-regulated miRNAs control early human neurogenesis through differential effects on ERK and AKT signaling

Rett syndrome (RTT) is an X-linked, neurodevelopmental disorder caused primarily by mutations in the methyl-CpG-binding protein 2 (MECP2) gene, which encodes a multifunctional epigenetic regulator with known links to a wide spectrum of neuropsychiatric disorders. Although postnatal functions of MeCP2 have been thoroughly investigated, its role in prenatal brain development remains poorly understood. Given the well-established importance of microRNAs (miRNAs) in neurogenesis, we employed isogenic human RTT patient-derived induced pluripotent stem cell (iPSC) and MeCP2 short hairpin RNA knockdown approaches to identify novel MeCP2-regulated miRNAs enriched during early human neuronal development. Focusing on the most dysregulated miRNAs, we found miR-199 and miR-214 to be increased during early brain development and to differentially regulate extracellular signal-regulated kinase (ERK)/mitogen-activated protein kinase and protein kinase B (PKB/AKT) signaling. In parallel, we characterized the effects on human neurogenesis and neuronal differentiation brought about by MeCP2 deficiency using both monolayer and three-dimensional (cerebral organoid) patient-derived and MeCP2-deficient neuronal culture models. Inhibiting miR-199 or miR-214 expression in iPSC-derived neural progenitors deficient in MeCP2 restored AKT and ERK activation, respectively, and ameliorated the observed alterations in neuronal differentiation. Moreover, overexpression of miR-199 or miR-214 in the wild-type mouse embryonic brains was sufficient to disturb neurogenesis and neuronal migration in a similar manner to Mecp2 knockdown. Taken together, our data support a novel miRNA-mediated pathway downstream of MeCP2 that influences neurogenesis via interactions with central molecular hubs linked to autism spectrum disorders.

Two-photon imaging in mice shows striosomes and matrix have overlapping but differential reinforcement-related responses

Striosomes were discovered several decades ago as neurochemically identified zones in the striatum, yet technical hurdles have hampered the study of the functions of these striatal compartments. Here we used 2-photon calcium imaging in neuronal birthdate-labeled Mash1-CreER;Ai14 mice to image simultaneously the activity of striosomal and matrix neurons as mice performed an auditory conditioning task. With this method, we identified circumscribed zones of tdTomato-labeled neuropil that correspond to striosomes as verified immunohistochemically. Neurons in both striosomes and matrix responded to reward-predicting cues and were active during or after consummatory licking. However, we found quantitative differences in response strength: striosomal neurons fired more to reward-predicting cues and encoded more information about expected outcome as mice learned the task, whereas matrix neurons were more strongly modulated by recent reward history. These findings open the possibility of harnessing in vivo imaging to determine the contributions of striosomes and matrix to striatal circuit function.

The influence of astrocytes on the width of orientation hypercolumns in visual cortex: A computational perspective

Orientation preference maps (OPMs) are present in carnivores (such as cats and ferrets) and primates but are absent in rodents. In this study we investigate the possible link between astrocyte arbors and presence of OPMs. We simulate the development of orientation maps with varying hypercolumn widths using a variant of the Laterally Interconnected Synergetically Self-Organizing Map (LISSOM) model, the Gain Control Adaptive Laterally connected (GCAL) model, with an additional layer simulating astrocytic activation. The synaptic activity of V1 neurons is given as input to the astrocyte layer. The activity of this astrocyte layer is now used to modulate bidirectional plasticity of lateral excitatory connections in the V1 layer. By simply varying the radius of the astrocytes, the extent of lateral excitatory neuronal connections can be manipulated. An increase in the radius of lateral excitatory connections subsequently increases the size of a single hypercolumn in the OPM. When these lateral excitatory connections become small enough the OPM disappears and a salt-and-pepper organization emerges.

Columns of neurons in the primary visual cortex (V1) are known to be tuned to visual stimuli containing edges of a particular orientation. The arrangement of these cortical columns varies across species. In many species such as in ferrets, cats, and monkeys a topology preserving map is observed, wherein similarly tuned columns are observed in close proximity to each other, resulting in the formation of Orientation Preference Maps (OPMs). The width of the hypercolumns, the fundamental unit of an OPM, also varies across species. However, such an arrangement is not observed in rodents, wherein a more random arrangement of these cortical columns is reported. We explore the role of astrocytes in the arrangement of these cortical columns using a self-organizing computational model. Invoking evidence that astrocytes could influence bidirectional plasticity among effective lateral excitatory connections in V1, we introduce a mechanism by which astrocytic inputs can influence map formation in the neuronal network. In the resulting model-generated OPMs the radius of the hypercolumns is found to be correlated with that of astrocytic arbors, a feature that finds support in experimental studies.

Photomarking Relocalization Technique for Correlated Two-Photon and Electron Microcopy Imaging of Single Stimulated Synapses

Synapses learn and remember by persistent modifications of their internal structures and composition but, due to their small size, it is difficult to observe these changes at the ultrastructural level in real time. Two-photon fluorescence microscopy (2PM) allows time-course live imaging of individual synapses but lacks ultrastructural resolution. Electron microscopy (EM) allows the ultrastructural imaging of subcellular components but cannot detect fluorescence and lacks temporal resolution. Here, we describe a combination of procedures designed to achieve the correlated imaging of the same individual synapse under both 2PM and EM. This technique permits the selective stimulation and live imaging of a single dendritic spine and the subsequent localization of the same spine in EM ultrathin serial sections. Landmarks created through a photomarking method based on the 2-photon-induced precipitation of an electrodense compound are used to unequivocally localize the stimulated synapse. This technique was developed to image, for the first time, the ultrastructure of the postsynaptic density in which long-term potentiation was selectively induced just seconds or minutes before, but it can be applied for the study of any biological process that requires the precise relocalization of micron-wide structures for their correlated imaging with 2PM and EM.

Induction of Expansion and Folding in Human Cerebral Organoids

An expansion of the cerebral neocortex is thought to be the foundation for the unique intellectual abilities of humans. It has been suggested that an increase in the proliferative potential of neural progenitors (NPs) underlies the expansion of the cortex and its convoluted appearance. Here we show that increasing NP proliferation induces expansion and folding in an in vitro model of human corticogenesis. Deletion of PTEN stimulates proliferation and generates significantly larger and substantially folded cerebral organoids. This genetic modification allows sustained cell cycle re-entry, expansion of the progenitor population, and delayed neuronal differentiation, all key features of the developing human cortex. In contrast, Pten deletion in mouse organoids does not lead to folding. Finally, we utilized the expanded cerebral organoids to show that infection with Zika virus impairs cortical growth and folding. Our study provides new insights into the mechanisms regulating the structure and organization of the human cortex.

Cell-specific modulation of plasticity and cortical state by cholinergic inputs to the visual cortex

Acetylcholine (ACh) modulates diverse vital brain functions. Cholinergic neurons from the basal forebrain innervate a wide range of cortical areas, including the primary visual cortex (V1), and multiple cortical cell types have been found to be responsive to ACh. Here we review how different cell types contribute to different cortical functions modulated by ACh. We specifically focus on two major cortical functions: plasticity and cortical state. In layer II/III of V1, ACh acting on astrocytes and somatostatin-expressing inhibitory neurons plays critical roles in these functions. Cell type specificity of cholinergic modulation points towards the growing understanding that even diffuse neurotransmitter systems can mediate specific functions through specific cell classes and receptors.

Direct modulation of GFAP-expressing glia in the arcuate nucleus bi-directionally regulates feeding

Multiple hypothalamic neuronal populations that regulate energy balance have been identified. Although hypothalamic glia exist in abundance and form intimate structural connections with neurons, their roles in energy homeostasis are less known. Here we show that selective Ca²⁺ activation of glia in the mouse arcuate nucleus (ARC) reversibly induces increased food intake while disruption of Ca²⁺ signaling pathway in ARC glia reduces food intake. The specific activation of ARC glia enhances the activity of agouti-related protein/neuropeptide Y (AgRP/NPY)-expressing neurons but induces no net response in pro-opiomelanocortin (POMC)-expressing neurons. ARC glial activation non-specifically depolarizes both AgRP/NPY and POMC neurons but a strong inhibitory input to POMC neurons balances the excitation. When AgRP/NPY neurons are inactivated, ARC glial activation fails to evoke any significant changes in food intake. Collectively, these results reveal an important role of ARC glia in the regulation of energy homeostasis through its interaction with distinct neuronal subtype-specific pathways.

Distinct roles of visual, parietal, and frontal motor cortices in memory-guided sensorimotor decisions

Mapping specific sensory features to future motor actions is a crucial capability of mammalian nervous systems. We investigated the role of visual (V1), posterior parietal (PPC), and frontal motor (fMC) cortices for sensorimotor mapping in mice during performance of a memory-guided visual discrimination task. Large-scale calcium imaging revealed that V1, PPC, and fMC neurons exhibited heterogeneous responses spanning all task epochs (stimulus, delay, response). Population analyses demonstrated unique encoding of stimulus identity and behavioral choice information across regions, with V1 encoding stimulus, fMC encoding choice even early in the trial, and PPC multiplexing the two variables. Optogenetic inhibition during behavior revealed that all regions were necessary during the stimulus epoch, but only fMC was required during the delay and response epochs. Stimulus identity can thus be rapidly transformed into behavioral choice, requiring V1, PPC, and fMC during the transformation period, but only fMC for maintaining the choice in memory prior to execution.

DOI:http://dx.doi.org/10.7554/eLife.13764.001

Genes, circuits, and precision therapies for autism and related neurodevelopmental disorders

Research in the genetics of neurodevelopmental disorders such as autism suggests that several hundred genes are likely risk factors for these disorders. This heterogeneity presents a challenge and an opportunity at the same time. Although the exact identity of many of the genes remains to be discovered, genes identified to date encode proteins that play roles in certain conserved pathways: protein synthesis, transcriptional and epigenetic regulation, and synaptic signaling. The next generation of research in neurodevelopmental disorders must address the neural circuitry underlying the behavioral symptoms and comorbidities, the cell types playing critical roles in these circuits, and common intercellular signaling pathways that link diverse genes. Results from clinical trials have been mixed so far. Only when we can leverage the heterogeneity of neurodevelopmental disorders into precision medicine will the mechanism-based therapeutics for these disorders start to unlock success.