Organizing memories for generalization in complementary learning systems.

Memorization and generalization are complementary cognitive processes that jointly promote adaptive behavior. For example, animals should memorize safe routes to specific water sources and generalize from these memories to discover environmental features that predict new ones. These functions depend on systems consolidation mechanisms that construct neocortical memory traces from hippocampal precursors, but why systems consolidation only applies to a subset of hippocampal memories is unclear. Here we introduce a new neural network formalization of systems consolidation that reveals an overlooked tension-unregulated neocortical memory transfer can cause overfitting and harm generalization in an unpredictable world. We resolve this tension by postulating that memories only consolidate when it aids generalization. This framework accounts for partial hippocampal-cortical memory transfer and provides a normative principle for reconceptualizing numerous observations in the field. Generalization-optimized systems consolidation thus provides new insight into how adaptive behavior benefits from complementary learning systems specialized for memorization and generalization.

Rapid synaptic plasticity contributes to a learned conjunctive code of position and choice-related information in the hippocampus.

To successfully perform goal-directed navigation, animals must know where they are and what they are doing-e.g., looking for water, bringing food back to the nest, or escaping from a predator. Hippocampal neurons code for these critical variables conjunctively, but little is known about how this "where/what" code is formed or flexibly routed to other brain regions. To address these questions, we performed intracellular whole-cell recordings in mouse CA1 during a cued, two-choice virtual navigation task. We demonstrate that plateau potentials in CA1 pyramidal neurons rapidly strengthen synaptic inputs carrying conjunctive information about position and choice. Plasticity-induced response fields were modulated by cues only in animals previously trained to collect rewards based on available cues. Thus, we reveal that gradual learning is required for the formation of a conjunctive population code, upstream of CA1, while plateau-potential-induced synaptic plasticity in CA1 enables flexible routing of the code to downstream brain regions.

Hippocampal and thalamic afferents form distinct synaptic microcircuits in the mouse infralimbic frontal cortex.

The selection of goal-directed behaviors is supported by neural circuits located within the frontal cortex. Frontal cortical afferents arise from multiple brain areas, yet the cell-type-specific targeting of these inputs is unclear. Here, we use monosynaptic retrograde rabies mapping to examine the distribution of afferent neurons targeting distinct classes of local inhibitory interneurons and excitatory projection neurons in mouse infralimbic frontal cortex. Interneurons expressing parvalbumin, somatostatin, or vasoactive intestinal peptide receive a large proportion of inputs from the hippocampus, while interneurons expressing neuron-derived neurotrophic factor receive a large proportion of inputs from thalamic regions. A similar dichotomy is present among the four different excitatory projection neurons. These results show a prominent bias among long-range hippocampal and thalamic afferent systems in their targeting to specific sets of frontal cortical neurons. Moreover, they suggest the presence of two distinct local microcircuits that control how different inputs govern frontal cortical information processing.

Linking axon morphology to gene expression: a strategy for neuronal cell-type classification.

To study how the brain drives cognition and behavior we need to understand its cellular composition. Advances in single-cell transcriptomics have revolutionized our ability to characterize neuronal diversity. To arrive at meaningful descriptions of cell types, however, gene expression must be linked to structural and functional properties. Axonal projection patterns are an appropriate measure, as they are diverse, change only gradually over time, and they influence and constrain circuit function. Here, we consider how efforts to map transcriptional and morphological diversity in the mouse brain could be linked to generate a modern taxonomy of the mouse brain.

Membrane potential dynamics underlying context-dependent sensory responses in the hippocampus.

As animals navigate, they must identify features within context. In the mammalian brain, the hippocampus has the ability to separately encode different environmental contexts, even when they share some prominent features. To do so, neurons respond to sensory features in a context-dependent manner; however, it is not known how this encoding emerges. To examine this, we performed electrical recordings in the hippocampus as mice navigated in two distinct virtual environments. In CA1, both synaptic input to single neurons and population activity strongly tracked visual cues in one environment, whereas responses were almost completely absent when the same cue was presented in a second environment. A very similar, highly context-dependent pattern of cue-driven spiking was also observed in CA3. These results indicate that CA1 inherits a complex spatial code from upstream regions, including CA3, that have already computed a context-dependent representation of environmental features.

A Sparse, Spatially Biased Subtype of Mature Granule Cell Dominates Recruitment in Hippocampal-Associated Behaviors.

Animals can store information about experiences by activating specific neuronal populations, and subsequent reactivation of these neural ensembles can lead to recall of salient experiences. In the hippocampus, granule cells of the dentate gyrus participate in such memory engrams; however, whether there is an underlying logic to granule cell participation has not been examined. Here, we find that a range of novel experiences preferentially activates granule cells of the suprapyramidal blade relative to the infrapyramidal blade. Motivated by this, we identify a suprapyramidal-blade-enriched population of granule cells with distinct spatial, morphological, physiological, and developmental properties. Via transcriptomics, we map these traits onto a sparse and discrete granule cell subtype that is recruited at a 10-fold greater frequency than expected by subtype prevalence, constituting the majority of all recruited granule cells. Thus, in behaviors known to involve hippocampal-dependent memory formation, a rare and spatially localized subtype dominates overall granule cell recruitment.

Transcriptional corepressor SIN3A regulates hippocampal synaptic plasticity via Homer1/mGluR5 signaling.

Long-term memory depends on the control of activity-dependent neuronal gene expression, which is regulated by epigenetic modifications. The epigenetic modification of histones is orchestrated by the opposing activities of 2 classes of regulatory complexes: permissive coactivators and silencing corepressors. Much work has focused on coactivator complexes, but little is known about the corepressor complexes that suppress the expression of plasticity-related genes. Here, we define a critical role for the corepressor SIN3A in memory and synaptic plasticity, showing that postnatal neuronal deletion of Sin3a enhances hippocampal long-term potentiation and long-term contextual fear memory. SIN3A regulates the expression of genes encoding proteins in the postsynaptic density. Loss of SIN3A increases expression of the synaptic scaffold Homer1, alters the metabotropic glutamate receptor 1α (mGluR1α) and mGluR5 dependence of long-term potentiation, and increases activation of ERK in the hippocampus after learning. Our studies define a critical role for corepressors in modulating neural plasticity and memory consolidation and reveal that Homer1/mGluR signaling pathways may be central molecular mechanisms for memory enhancement.

ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology.

Neurons perform computations by integrating inputs from thousands of synapses-mostly in the dendritic tree-to drive action potential firing in the axon. One fruitful approach to studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures of the dendrites, and use the resulting functional and structural data to develop computer models of dendritic integration. Accurately producing quantitative reconstructions of dendrites is typically a tedious process taking many hours of manual inspection and measurement. Here we present ShuTu, a new software package that facilitates accurate and efficient reconstruction of dendrites imaged using bright-field microscopy. The program operates in two steps: (1) automated identification of dendritic processes, and (2) manual correction of errors in the automated reconstruction. This approach allows neurons with complex dendritic morphologies to be reconstructed rapidly and efficiently, thus facilitating the use of computer models to study dendritic structure-function relationships and the computations performed by single neurons.

Functional clustering of dendritic activity during decision-making.

The active properties of dendrites can support local nonlinear operations, but previous imaging and electrophysiological measurements have produced conflicting views regarding the prevalence and selectivity of local nonlinearities in vivo. We imaged calcium signals in pyramidal cell dendrites in the motor cortex of mice performing a tactile decision task. A custom microscope allowed us to image the soma and up to 300 µm of contiguous dendrite at 15 Hz, while resolving individual spines. New analysis methods were used to estimate the frequency and spatial scales of activity in dendritic branches and spines. The majority of dendritic calcium transients were coincident with global events. However, task-associated calcium signals in dendrites and spines were compartmentalized by dendritic branching and clustered within branches over approximately 10 µm. Diverse behavior-related signals were intermingled and distributed throughout the dendritic arbor, potentially supporting a large learning capacity in individual neurons.

Reconstruction of 1,000 Projection Neurons Reveals New Cell Types and Organization of Long-Range Connectivity in the Mouse Brain.

Neuronal cell types are the nodes of neural circuits that determine the flow of information within the brain. Neuronal morphology, especially the shape of the axonal arbor, provides an essential descriptor of cell type and reveals how individual neurons route their output across the brain. Despite the importance of morphology, few projection neurons in the mouse brain have been reconstructed in their entirety. Here we present a robust and efficient platform for imaging and reconstructing complete neuronal morphologies, including axonal arbors that span substantial portions of the brain. We used this platform to reconstruct more than 1,000 projection neurons in the motor cortex, thalamus, subiculum, and hypothalamus. Together, the reconstructed neurons constitute more than 85 meters of axonal length and are available in a searchable online database. Axonal shapes revealed previously unknown subtypes of projection neurons and suggest organizational principles of long-range connectivity.

Mapping the transcriptional diversity of genetically and anatomically defined cell populations in the mouse brain.

Understanding the principles governing neuronal diversity is a fundamental goal for neuroscience. Here, we provide an anatomical and transcriptomic database of nearly 200 genetically identified cell populations. By separately analyzing the robustness and pattern of expression differences across these cell populations, we identify two gene classes contributing distinctly to neuronal diversity. Short homeobox transcription factors distinguish neuronal populations combinatorially, and exhibit extremely low transcriptional noise, enabling highly robust expression differences. Long neuronal effector genes, such as channels and cell adhesion molecules, contribute disproportionately to neuronal diversity, based on their patterns rather than robustness of expression differences. By linking transcriptional identity to genetic strains and anatomical atlases, we provide an extensive resource for further investigation of mouse neuronal cell types.

Heterogeneity within classical cell types is the rule: lessons from hippocampal pyramidal neurons.

The mechanistic operation of brain regions is often interpreted by partitioning constituent neurons into 'cell types'. Historically, such cell types were broadly defined by their correspondence to gross features of the nervous system (such as cytoarchitecture). Modern-day neuroscientific techniques, enabling a more nuanced examination of neuronal properties, have illustrated a wealth of heterogeneity within these classical cell types. Here, we review the extent of this within-cell-type heterogeneity in one of the simplest cortical regions of the mammalian brain, the rodent hippocampus. We focus on the mounting evidence that the classical CA3, CA1 and subiculum pyramidal cell types all exhibit prominent and spatially patterned within-cell-type heterogeneity, and suggest these cell types provide a model system for exploring the organization and function of such heterogeneity. Given that the hippocampus is structurally simple and evolutionarily ancient, within-cell-type heterogeneity is likely to be a general and crucial feature of the mammalian brain.

The subiculum is a patchwork of discrete subregions.

In the hippocampus, the classical pyramidal cell type of the subiculum acts as a primary output, conveying hippocampal signals to a diverse suite of downstream regions. Accumulating evidence suggests that the subiculum pyramidal cell population may actually be comprised of discrete subclasses. Here, we investigated the extent and organizational principles governing pyramidal cell heterogeneity throughout the mouse subiculum. Using single-cell RNA-seq, we find that the subiculum pyramidal cell population can be deconstructed into eight separable subclasses. These subclasses were mapped onto abutting spatial domains, ultimately producing a complex laminar and columnar organization with heterogeneity across classical dorsal-ventral, proximal-distal, and superficial-deep axes. We further show that these transcriptomically defined subclasses correspond to differential protein products and can be associated with specific projection targets. This work deconstructs the complex landscape of subiculum pyramidal cells into spatially segregated subclasses that may be observed, controlled, and interpreted in future experiments.

Astrocytes integrate and drive action potential firing in inhibitory subnetworks.

Many brain functions depend on the ability of neural networks to temporally integrate transient inputs to produce sustained discharges. This can occur through cell-autonomous mechanisms in individual neurons and through reverberating activity in recurrently connected neural networks. We report a third mechanism involving temporal integration of neural activity by a network of astrocytes. Previously, we showed that some types of interneurons can generate long-lasting trains of action potentials (barrage firing) following repeated depolarizing stimuli. Here we show that calcium signaling in an astrocytic network correlates with barrage firing; that active depolarization of astrocyte networks by chemical or optogenetic stimulation enhances; and that chelating internal calcium, inhibiting release from internal stores, or inhibiting GABA transporters or metabotropic glutamate receptors inhibits barrage firing. Thus, networks of astrocytes influence the spatiotemporal dynamics of neural networks by directly integrating neural activity and driving barrages of action potentials in some populations of inhibitory interneurons.

A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus.

To support cognitive function, the CA3 region of the hippocampus performs computations involving attractor dynamics. Understanding how cellular and ensemble activities of CA3 neurons enable computation is critical for elucidating the neural correlates of cognition. Here we show that CA3 comprises not only classically described pyramid cells with thorny excrescences, but also includes previously unidentified 'athorny' pyramid cells that lack mossy-fiber input. Moreover, the two neuron types have distinct morphological and physiological phenotypes and are differentially modulated by acetylcholine. To understand the contribution of these athorny pyramid neurons to circuit function, we measured cell-type-specific firing patterns during sharp-wave synchronization events in vivo and recapitulated these dynamics with an attractor network model comprising two principal cell types. Our data and simulations reveal a key role for athorny cell bursting in the initiation of sharp waves: transient network attractor states that signify the execution of pattern completion computations vital to cognitive function.

Persistent Sodium Current Mediates the Steep Voltage Dependence of Spatial Coding in Hippocampal Pyramidal Neurons.

The mammalian hippocampus forms a cognitive map using neurons that fire according to an animal's position ("place cells") and many other behavioral and cognitive variables. The responses of these neurons are shaped by their presynaptic inputs and the nature of their postsynaptic integration. In CA1 pyramidal neurons, spatial responses in vivo exhibit a strikingly supralinear dependence on baseline membrane potential. The biophysical mechanisms underlying this nonlinear cellular computation are unknown. Here, through a combination of in vitro, in vivo, and in silico approaches, we show that persistent sodium current mediates the strong membrane potential dependence of place cell activity. This current operates at membrane potentials below the action potential threshold and over seconds-long timescales, mediating a powerful and rapidly reversible amplification of synaptic responses, which drives place cell firing. Thus, we identify a biophysical mechanism that shapes the coding properties of neurons composing the hippocampal cognitive map.

Dissociable Structural and Functional Hippocampal Outputs via Distinct Subiculum Cell Classes.

The mammalian hippocampus, comprised of serially connected subfields, participates in diverse behavioral and cognitive functions. It has been postulated that parallel circuitry embedded within hippocampal subfields may underlie such functional diversity. We sought to identify, delineate, and manipulate this putatively parallel architecture in the dorsal subiculum, the primary output subfield of the dorsal hippocampus. Population and single-cell RNA-seq revealed that the subiculum can be divided into two spatially adjacent subregions associated with prominent differences in pyramidal cell gene expression. Pyramidal cells occupying these two regions differed in their long-range inputs, local wiring, projection targets, and electrophysiological properties. Leveraging gene-expression differences across these regions, we use genetically restricted neuronal silencing to show that these regions differentially contribute to spatial working memory. This work provides a coherent molecular-, cellular-, circuit-, and behavioral-level demonstration that the hippocampus embeds structurally and functionally dissociable streams within its serial architecture.

Single excitatory axons form clustered synapses onto CA1 pyramidal cell dendrites.

CA1 pyramidal neurons are a major output of the hippocampus and encode features of experience that constitute episodic memories. Feature-selective firing of these neurons results from the dendritic integration of inputs from multiple brain regions. While it is known that synchronous activation of spatially clustered inputs can contribute to firing through the generation of dendritic spikes, there is no established mechanism for spatiotemporal synaptic clustering. Here we show that single presynaptic axons form multiple, spatially clustered inputs onto the distal, but not proximal, dendrites of CA1 pyramidal neurons. These compound connections exhibit ultrastructural features indicative of strong synapses and occur much more commonly in entorhinal than in thalamic afferents. Computational simulations revealed that compound connections depolarize dendrites in a biophysically efficient manner, owing to their inherent spatiotemporal clustering. Our results suggest that distinct afferent projections use different connectivity motifs that differentially contribute to dendritic integration.