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Calcium imaging using two-photon scanning microscopy has become an essential tool in neuroscience. However, in its typical implementation, the tradeoffs between fields of view, acquisition speeds, and depth restrictions in scattering brain tissue pose severe limitations. Here, using an integrated systems-wide optimization approach combined with multiple technical innovations, we introduce a new design paradigm for optical microscopy based on maximizing biological information while maintaining the fidelity of obtained neuron signals. Our modular design utilizes hybrid multi-photon acquisition and allows volumetric recording of neuroactivity at single-cell resolution within up to 1 × 1 × 1.22 mm volumes at up to 17 Hz in awake behaving mice. We establish the capabilities and potential of the different configurations of our imaging system at depth and across brain regions by applying it to in vivo recording of up to 12,000 neurons in mouse auditory cortex, posterior parietal cortex, and hippocampus.
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Microscopia/métodos , Imagem Molecular/métodos , Neuroimagem/métodos , Animais , Encéfalo/fisiologia , Cálcio/metabolismo , Feminino , Hipocampo/fisiologia , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Neurônios/fisiologia , Análise de Célula Única/métodosRESUMO
The hippocampus is critical for memory and spatial navigation. The ability to map novel environments, as well as more abstract conceptual relationships, is fundamental to the cognitive flexibility that humans and other animals require to survive in a dynamic world. In this review, we survey recent advances in our understanding of how this flexibility is implemented anatomically and functionally by hippocampal circuitry, during both active exploration (online) and rest (offline). We discuss the advantages and limitations of spike timing-dependent plasticity and the more recently discovered behavioral timescale synaptic plasticity in supporting distinct learning modes in the hippocampus. Finally, we suggest complementary roles for these plasticity types in explaining many-shot and single-shot learning in the hippocampus and discuss how these rules could work together to support the learning of cognitive maps.
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Hipocampo , Aprendizagem , Plasticidade Neuronal , Hipocampo/fisiologia , Animais , Aprendizagem/fisiologia , Humanos , Plasticidade Neuronal/fisiologiaRESUMO
Associative memories guide behavioural adaptation by binding together outcome-predictive sensory stimuli1,2. However, in a feature-rich environment, only a subset of stimuli may predict a desired outcome3,4. How neural circuits enable behavioural adaptation by selectively and durably representing subsets of sensory stimuli that are pertinent to a specific outcome is not known. We investigated this feature selection process in the hippocampus during memory acquisition and subsequent consolidation. Two-photon calcium imaging of CA3 axonal projections to CA1 combined with simultaneous local field potential recordings revealed that CA3 projections that encode behaviourally informative sensory stimuli were selectively recruited during the memory replay events that underlie hippocampal memory consolidation5. These axonal projections formed sequential assemblies that conjunctively link sensory features to spatial location and thus reward proximity. By contrast, axons encoding uninformative, peripatetic sensory cues were notably suppressed during memory replay. Thus, while the hippocampus comprehensively encodes the real-time sensory environment, it implements a flexible filtering mechanism to maximize the utility of memories destined for long-term storage. We propose that utility-dependent recruitment of sensory experience during memory consolidation is a general coding principle for associative learning.
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Hipocampo , Consolidação da Memória , Condicionamento Clássico , Memória , RecompensaRESUMO
Local circuit architecture facilitates the emergence of feature selectivity in the cerebral cortex1. In the hippocampus, it remains unknown whether local computations supported by specific connectivity motifs2 regulate the spatial receptive fields of pyramidal cells3. Here we developed an in vivo electroporation method for monosynaptic retrograde tracing4 and optogenetics manipulation at single-cell resolution to interrogate the dynamic interaction of place cells with their microcircuitry during navigation. We found a local circuit mechanism in CA1 whereby the spatial tuning of an individual place cell can propagate to a functionally recurrent subnetwork5 to which it belongs. The emergence of place fields in individual neurons led to the development of inverse selectivity in a subset of their presynaptic interneurons, and recruited functionally coupled place cells at that location. Thus, the spatial selectivity of single CA1 neurons is amplified through local circuit plasticity to enable effective multi-neuronal representations that can flexibly scale environmental features locally without degrading the feedforward input structure.
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Hipocampo/citologia , Hipocampo/fisiologia , Vias Neurais , Memória Espacial/fisiologia , Navegação Espacial/fisiologia , Animais , Região CA1 Hipocampal/citologia , Região CA1 Hipocampal/fisiologia , Linhagem da Célula , Eletroporação , Feminino , Interneurônios/fisiologia , Masculino , Camundongos , Inibição Neural , Optogenética , Células de Lugar/fisiologia , Terminações Pré-Sinápticas/metabolismo , Células Piramidais/fisiologia , Análise de Célula ÚnicaRESUMO
Genetically encoded voltage indicators (GEVIs) enable optical recording of electrical signals in the brain, providing subthreshold sensitivity and temporal resolution not possible with calcium indicators. However, one- and two-photon voltage imaging over prolonged periods with the same GEVI has not yet been demonstrated. Here, we report engineering of ASAP family GEVIs to enhance photostability by inversion of the fluorescence-voltage relationship. Two of the resulting GEVIs, ASAP4b and ASAP4e, respond to 100-mV depolarizations with ≥180% fluorescence increases, compared with the 50% fluorescence decrease of the parental ASAP3. With standard microscopy equipment, ASAP4e enables single-trial detection of spikes in mice over the course of minutes. Unlike GEVIs previously used for one-photon voltage recordings, ASAP4b and ASAP4e also perform well under two-photon illumination. By imaging voltage and calcium simultaneously, we show that ASAP4b and ASAP4e can identify place cells and detect voltage spikes with better temporal resolution than commonly used calcium indicators. Thus, ASAP4b and ASAP4e extend the capabilities of voltage imaging to standard one- and two-photon microscopes while improving the duration of voltage recordings.
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Encéfalo , Cálcio , Animais , Camundongos , Iluminação , Microscopia , FótonsRESUMO
First-Order, Reduced and Controlled Error (FORCE) learning and its variants are widely used to train chaotic recurrent neural networks (RNNs), and outperform gradient methods on certain tasks. However, there is currently no standard software framework for FORCE learning. We present tension, an object-oriented, open-source Python package that implements a TensorFlow / Keras API for FORCE. We show how rate networks, spiking networks, and networks constrained by biological data can all be trained using a shared, easily extensible high-level API. With the same resources, our implementation outperforms a conventional RNN in loss and published FORCE implementations in runtime. Our work here makes FORCE training chaotic RNNs accessible and simple to iterate, and facilitates modeling of how behaviors of interest emerge from neural dynamics.
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Aprendizagem , Redes Neurais de Computação , SoftwareRESUMO
Although information storage in the central nervous system is thought to be primarily mediated by various forms of synaptic plasticity, other mechanisms, such as modifications in membrane excitability, are available. Local dendritic spikes are nonlinear voltage events that are initiated within dendritic branches by spatially clustered and temporally synchronous synaptic input. That local spikes selectively respond only to appropriately correlated input allows them to function as input feature detectors and potentially as powerful information storage mechanisms. However, it is currently unknown whether any effective form of local dendritic spike plasticity exists. Here we show that the coupling between local dendritic spikes and the soma of rat hippocampal CA1 pyramidal neurons can be modified in a branch-specific manner through an N-methyl-d-aspartate receptor (NMDAR)-dependent regulation of dendritic Kv4.2 potassium channels. These data suggest that compartmentalized changes in branch excitability could store multiple complex features of synaptic input, such as their spatio-temporal correlation. We propose that this 'branch strength potentiation' represents a previously unknown form of information storage that is distinct from that produced by changes in synaptic efficacy both at the mechanistic level and in the type of information stored.
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Dendritos/fisiologia , Plasticidade Neuronal/fisiologia , Células Piramidais/citologia , Células Piramidais/metabolismo , Potenciais de Ação/fisiologia , Animais , Forma Celular , Ativação do Canal Iônico , Masculino , Camundongos , Modelos Neurológicos , Ratos , Ratos Sprague-Dawley , Receptores de N-Metil-D-Aspartato/metabolismo , Canais de Potássio Shal/deficiência , Canais de Potássio Shal/genética , Canais de Potássio Shal/metabolismoRESUMO
Deep learning models perform remarkably well on many classification tasks recently. The superior performance of deep neural networks relies on the large number of training data, which at the same time must have an equal class distribution in order to be efficient. However, in most real-world applications, the labeled data may be limited with high imbalance ratios among the classes, and thus, the learning process of most classification algorithms is adversely affected resulting in unstable predictions and low performance. Three main categories of approaches address the problem of imbalanced learning, i.e., data-level, algorithmic level, and hybrid methods, which combine the two aforementioned approaches. Data generative methods are typically based on generative adversarial networks, which require significant amounts of data, while model-level methods entail extensive domain expert knowledge to craft the learning objectives, thereby being less accessible for users without such knowledge. Moreover, the vast majority of these approaches are designed and applied to imaging applications, less to time series, and extremely rare to both of them. To address the above issues, we introduce GENDA, a generative neighborhood-based deep autoencoder, which is simple yet effective in its design and can be successfully applied to both image and time-series data. GENDA is based on learning latent representations that rely on the neighboring embedding space of the samples. Extensive experiments, conducted on a variety of widely-used real datasets demonstrate the efficacy of the proposed method. Impact Statement: Imbalanced data classification is an actual and important issue in many real-world learning applications hampering most classification tasks. Fraud detection, biomedical imaging categorizing healthy people versus patients, and object detection are some indicative domains with an economic, social and technological impact, which are greatly affected by inherent imbalanced data distribution. However, the majority of the existing algorithms that address the imbalanced classification problem are designed with a particular application in mind, and thus they can be used with specific datasets and even hyperparameters. The generative model introduced in this paper overcomes this limitation and produces improved results for a large class of imaging and time series data even under severe imbalance ratios, making it quite competitive.
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Hippocampal pyramidal neurons support episodic memory by integrating complementary information streams into new 'place fields'. Distal tuft dendrites are widely thought to initiate place field formation by locally generating prolonged, globally-spreading Ca 2+ spikes known as plateau potentials. However, the hitherto experimental inaccessibility of distal tuft dendrites in the hippocampus has rendered their in vivo function entirely unknown. Here we gained direct optical access to this elusive dendritic compartment. We report that distal tuft dendrites do not serve as the point of origin for place field-forming plateau potentials. Instead, the timing and extent of peri-formation distal tuft recruitment is variable and closely predicts multiple properties of resultant place fields. Therefore, distal tuft dendrites play a more powerful role in hippocampal feature selectivity than simply initiating place field formation. Moreover, place field formation is not accompanied by global Ca 2+ influx as previously thought. In addition to shaping new somatic place fields, distal tuft dendrites possess their own local place fields. Tuft place fields are back-shifted relative to that of their soma and appear to maintain somatic place fields via post-formation plateau potentials. Through direct in vivo observation, we provide a revised dendritic basis for hippocampal feature selectivity during navigational learning.
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Investigators conducting behavioral experiments often need precise control over the timing of the delivery of stimuli to subjects and to collect the precise times of the subsequent behavioral responses. Furthermore, investigators want fine-tuned control over how various multi-modal cues are presented. behaviorMate takes an "Intranet of Things" approach, using a networked system of hardware and software components for achieving these goals. The system outputs a file with integrated timestamp-event pairs that investigators can then format and process using their own analysis pipelines. We present an overview of the electronic components and GUI application that make up behaviorMate as well as mechanical designs for compatible experimental rigs to provide the reader with the ability to set up their own system. A wide variety of paradigms are supported, including goal-oriented learning, random foraging, and context switching. We demonstrate behaviorMate's utility and reliability with a range of use cases from several published studies and benchmark tests. Finally, we present experimental validation demonstrating different modalities of hippocampal place field studies. Both treadmill with burlap belt and virtual reality with running wheel paradigms were performed to confirm the efficacy and flexibility of the approach. Previous solutions rely on proprietary systems that may have large upfront costs or present frameworks that require customized software to be developed. behaviorMate uses open-source software and a flexible configuration system to mitigate both concerns. behaviorMate has a proven record for head-fixed imaging experiments and could be easily adopted for task control in a variety of experimental situations.
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Neural circuits are characterized by genetically and functionally diverse cell types. A mechanistic understanding of circuit function is predicated on linking the genetic and physiological properties of individual neurons. However, it remains highly challenging to map the functional properties of transcriptionally heterogeneous neuronal subtypes in mammalian cortical circuits in vivo. Here, we introduce a high-throughput two-photon nuclear phototagging (2P-NucTag) approach optimized for on-demand and indelible labeling of single neurons via a photoactivatable red fluorescent protein following in vivo functional characterization in behaving mice. We demonstrate the utility of this function-forward pipeline by selectively labeling and transcriptionally profiling previously inaccessible 'place' and 'silent' cells in the mouse hippocampus. Our results reveal unexpected differences in gene expression between these hippocampal pyramidal neurons with distinct spatial coding properties. Thus, 2P-NucTag opens a new way to uncover the molecular principles that govern the functional organization of neural circuits.
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Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions and report an advancing gradient of dendritic theta phase along the basal-tuft axis, then describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.
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Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions, report an advancing gradient of dendritic theta phase along the basal-tuft axis, and describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find that spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.
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Região CA1 Hipocampal , Dendritos , Células Piramidais , Animais , Dendritos/fisiologia , Dendritos/metabolismo , Células Piramidais/fisiologia , Células Piramidais/metabolismo , Camundongos , Região CA1 Hipocampal/fisiologia , Região CA1 Hipocampal/citologia , Potenciais da Membrana/fisiologia , Masculino , Camundongos Endogâmicos C57BL , Hipocampo/fisiologia , Hipocampo/citologia , Navegação Espacial/fisiologia , Locomoção/fisiologiaRESUMO
Neuronal mitochondria play important roles beyond ATP generation, including Ca2+ uptake, and therefore have instructive roles in synaptic function and neuronal response properties. Mitochondrial morphology differs significantly between the axon and dendrites of a given neuronal subtype, but in CA1 pyramidal neurons (PNs) of the hippocampus, mitochondria within the dendritic arbor also display a remarkable degree of subcellular, layer-specific compartmentalization. In the dendrites of these neurons, mitochondria morphology ranges from highly fused and elongated in the apical tuft, to more fragmented in the apical oblique and basal dendritic compartments, and thus occupy a smaller fraction of dendritic volume than in the apical tuft. However, the molecular mechanisms underlying this striking degree of subcellular compartmentalization of mitochondria morphology are unknown, precluding the assessment of its impact on neuronal function. Here, we demonstrate that this compartment-specific morphology of dendritic mitochondria requires activity-dependent, Ca2+ and Camkk2-dependent activation of AMPK and its ability to phosphorylate two direct effectors: the pro-fission Drp1 receptor Mff and the recently identified anti-fusion, Opa1-inhibiting protein, Mtfr1l. Our study uncovers a signaling pathway underlying the subcellular compartmentalization of mitochondrial morphology in dendrites of neurons in vivo through spatially precise and activity-dependent regulation of mitochondria fission/fusion balance.
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Neurônios , Células Piramidais , Neurônios/metabolismo , Células Piramidais/fisiologia , Hipocampo , Axônios/metabolismo , Mitocôndrias/metabolismo , Dendritos/fisiologiaRESUMO
The subregions of the entorhinal cortex (EC) are conventionally thought to compute dichotomous representations for spatial processing, with the medial EC (MEC) providing a global spatial map and the lateral EC (LEC) encoding specific sensory details of experience. Yet, little is known about the specific types of information EC transmits downstream to the hippocampus. Here, we exploit in vivo sub-cellular imaging to record from EC axons in CA1 while mice perform navigational tasks in virtual reality (VR). We uncover distinct yet overlapping representations of task, location, and context in both MEC and LEC axons. MEC transmitted highly location- and context-specific codes; LEC inputs were biased by ongoing navigational goals. However, during tasks with reliable reward locations, the animals' position could be accurately decoded from either subregion. Our results revise the prevailing dogma about EC information processing, revealing novel ways spatial and non-spatial information is routed and combined upstream of the hippocampus.
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Navegação Espacial , Processamento Espacial , Camundongos , Animais , Objetivos , Hipocampo , Córtex Entorrinal , CogniçãoRESUMO
Excitatory-inhibitory interactions structure recurrent network dynamics for efficient cortical computations. In the CA3 area of the hippocampus, recurrent circuit dynamics, including experience-induced plasticity at excitatory synapses, are thought to play a key role in episodic memory encoding and consolidation via rapid generation and flexible selection of neural ensembles. However, in vivo activity of identified inhibitory motifs supporting this recurrent circuitry has remained largely inaccessible, and it is unknown whether CA3 inhibition is also modifiable upon experience. Here we use large-scale, 3-dimensional calcium imaging and retrospective molecular identification in the mouse hippocampus to obtain the first comprehensive description of molecularly-identified CA3 interneuron dynamics during both spatial navigation and sharp-wave ripple (SWR)-associated memory consolidation. Our results uncover subtype-specific dynamics during behaviorally distinct brain-states. Our data also demonstrate predictive, reflective, and experience-driven plastic recruitment of specific inhibitory motifs during SWR-related memory reactivation. Together these results assign active roles for inhibitory circuits in coordinating operations and plasticity in hippocampal recurrent circuits.
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The hippocampus is a multi-stage neural circuit that is critical for memory formation. Its distinct anatomy has long inspired theories that rely on local interactions between neurons within each subregion in order to perform serial operations important for memory encoding and storage. These local computations have received less attention in CA1 area, the primary output node of the hippocampus, where excitatory neurons are thought to be only very sparsely interconnected. However, recent findings have demonstrated the power of local circuitry in CA1, with evidence for strong functional interactions among excitatory neurons, regulation by diverse inhibitory microcircuits, and novel plasticity rules that can profoundly reshape the hippocampal ensemble code. Here we review how these properties expand the dynamical repertoire of CA1 beyond the confines of feedforward processing, and what implications they have for hippocampo-cortical functions in memory formation.
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Região CA1 Hipocampal , Navegação Espacial , Região CA1 Hipocampal/fisiologia , Hipocampo/fisiologia , Memória/fisiologia , Neurônios/fisiologiaRESUMO
Recurrent excitatory connections in hippocampal regions CA3 and CA2 are thought to play a key role in the generation of sharp-wave ripples (SWRs), electrophysiological oscillations tightly linked with learning and memory consolidation. However, it remains unknown how defined populations of inhibitory interneurons regulate these events during behavior. Here, we use large-scale, three-dimensional calcium imaging and retrospective molecular identification in the mouse hippocampus to characterize molecularly identified CA3 and CA2 interneuron activity during SWR-associated memory consolidation and spatial navigation. We describe subtype- and region-specific responses during behaviorally distinct brain states and find that SWRs are preceded by decreased cholecystokinin-expressing interneuron activity and followed by increased parvalbumin-expressing basket cell activity. The magnitude of these dynamics correlates with both SWR duration and behavior during hippocampal-dependent learning. Together these results assign subtype- and region-specific roles for inhibitory circuits in coordinating operations and learning-related plasticity in hippocampal recurrent circuits.
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Hipocampo , Consolidação da Memória , Camundongos , Animais , Estudos Retrospectivos , Hipocampo/fisiologia , Transmissão Sináptica/fisiologia , Interneurônios/fisiologia , Consolidação da Memória/fisiologiaRESUMO
Multimodal microscopy experiments that image the same population of cells under different experimental conditions have become a widely used approach in systems and molecular neuroscience. The main obstacle is to align the different imaging modalities to obtain complementary information about the observed cell population (e.g., gene expression and calcium signal). Traditional image registration methods perform poorly when only a small subset of cells are present in both images, as is common in multimodal experiments. We cast multimodal microscopy alignment as a cell subset matching problem. To solve this non-convex problem, we introduce an efficient and globally optimal branch-and-bound algorithm to find subsets of point clouds that are in rotational alignment with each other. In addition, we use complementary information about cell shape and location to compute the matching likelihood of cell pairs in two imaging modalities to further prune the optimization search tree. Finally, we use the maximal set of cells in rigid rotational alignment to seed image deformation fields to obtain a final registration result. Our framework performs better than the state-of-the-art histology alignment approaches regarding matching quality and is faster than manual alignment, providing a viable solution to improve the throughput of multimodal microscopy experiments.
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Adult-born granule cells (abGCs) have been implicated in memory discrimination through a neural computation known as pattern separation. Here, using in vivo Ca2+ imaging, we examined how chronic ablation or acute chemogenetic silencing of abGCs affects the activity of mature granule cells (mGCs). In both cases, we observed altered remapping of mGCs. Rather than broadly modulating the activity of all mGCs, abGCs promote the remapping of place cells' firing fields while increasing rate remapping of mGCs that represent sensory cues. In turn, these remapping deficits are associated with behavioral impairments in animals' ability to correctly identify new goal locations. Thus, abGCs facilitate pattern separation through the formation of non-overlapping representations for identical sensory cues encountered in different locations. In the absence of abGCs, the dentate gyrus shifts to a state that is dominated by cue information, a situation that is consistent with the overgeneralization often observed in anxiety or age-related disorders.