Signatures of rapid plasticity in hippocampal CA1 representations during novel experiences.

Neurons in the hippocampus exhibit a striking selectivity for specific combinations of sensory features, forming representations that are thought to subserve episodic memory. Even during completely novel experiences, hippocampal "place cells" are rapidly configured such that the population sparsely encodes visited locations, stabilizing within minutes of the first exposure to a new environment. What mechanisms enable this fast encoding of experience? Using virtual reality and neural population recordings in mice, we dissected the effects of novelty and experience on the dynamics of place field formation. During place field formation, many CA1 neurons immediately modulated the amplitude of their activity and shifted the location of their field, rapid changes in tuning predicted by behavioral timescale synaptic plasticity (BTSP). Signatures of BTSP were particularly enriched during the exploration of a novel context and decayed with experience. Our data suggest that novelty modulates the effective learning rate in CA1, favoring rapid mechanisms of field formation to encode a new experience.

Compartment-specific tuning of dendritic feature selectivity by intracellular Ca2+ release.

Dendritic calcium signaling is central to neural plasticity mechanisms that allow animals to adapt to the environment. Intracellular calcium release (ICR) from the endoplasmic reticulum has long been thought to shape these mechanisms. However, ICR has not been investigated in mammalian neurons in vivo. We combined electroporation of single CA1 pyramidal neurons, simultaneous imaging of dendritic and somatic activity during spatial navigation, optogenetic place field induction, and acute genetic augmentation of ICR cytosolic impact to reveal that ICR supports the establishment of dendritic feature selectivity and shapes integrative properties determining output-level receptive fields. This role for ICR was more prominent in apical than in basal dendrites. Thus, ICR cooperates with circuit-level architecture in vivo to promote the emergence of behaviorally relevant plasticity in a compartment-specific manner.

Reorganization of CA1 dendritic dynamics by hippocampal sharp-wave ripples during learning.

The hippocampus plays a critical role in memory consolidation, mediated by coordinated network activity during sharp-wave ripple (SWR) events. Despite the link between SWRs and hippocampal plasticity, little is known about how network state affects information processing in dendrites, the primary sites of synaptic input integration and plasticity. Here, we monitored somatic and basal dendritic activity in CA1 pyramidal cells in behaving mice using longitudinal two-photon calcium imaging integrated with simultaneous local field potential recordings. We found immobility was associated with an increase in dendritic activity concentrated during SWRs. Coincident dendritic and somatic activity during SWRs predicted increased coupling during subsequent exploration of a novel environment. In contrast, somatic-dendritic coupling and SWR recruitment varied with cells' tuning distance to reward location during a goal-learning task. Our results connect SWRs with the stabilization of information processing within CA1 neurons and suggest that these mechanisms may be dynamically biased by behavioral demands.

Local feedback inhibition tightly controls rapid formation of hippocampal place fields.

Hippocampal place cells underlie spatial navigation and memory. Remarkably, CA1 pyramidal neurons can form new place fields within a single trial by undergoing rapid plasticity. However, local feedback circuits likely restrict the rapid recruitment of individual neurons into ensemble representations. This interaction between circuit dynamics and rapid feature coding remains unexplored. Here, we developed "all-optical" approaches combining novel optogenetic induction of rapidly forming place fields with 2-photon activity imaging during spatial navigation in mice. We find that induction efficacy depends strongly on the density of co-activated neurons. Place fields can be reliably induced in single cells, but induction fails during co-activation of larger subpopulations due to local circuit constraints imposed by recurrent inhibition. Temporary relief of local inhibition permits the simultaneous induction of place fields in larger ensembles. We demonstrate the behavioral implications of these dynamics, showing that our ensemble place field induction protocol can enhance subsequent spatial association learning.

Synaptogenic activity of the axon guidance molecule Robo2 underlies hippocampal circuit function.

Synaptic connectivity within adult circuits exhibits a remarkable degree of cellular and subcellular specificity. We report that the axon guidance receptor Robo2 plays a role in establishing synaptic specificity in hippocampal CA1. In vivo, Robo2 is present and required postsynaptically in CA1 pyramidal neurons (PNs) for the formation of excitatory (E) but not inhibitory (I) synapses, specifically in proximal but not distal dendritic compartments. In vitro approaches show that the synaptogenic activity of Robo2 involves a trans-synaptic interaction with presynaptic Neurexins, as well as binding to its canonical extracellular ligand Slit. In vivo 2-photon Ca2+ imaging of CA1 PNs during spatial navigation in awake behaving mice shows that preventing Robo2-dependent excitatory synapse formation cell autonomously during development alters place cell properties of adult CA1 PNs. Our results identify a trans-synaptic complex linking the establishment of synaptic specificity to circuit function.

Bayesian Word Learning in Multiple Language Environments.

Infant language learners are faced with the difficult inductive problem of determining how new words map to novel or known objects in their environment. Bayesian inference models have been successful at using the sparse information available in natural child-directed speech to build candidate lexicons and infer speakers' referential intentions. We begin by asking how a Bayesian model optimized for monolingual input (the Intentional Model; Frank et al., 2009) generalizes to new monolingual or bilingual corpora and find that, especially in the case of the bilingual input, the model shows a significant decrease in performance. In the next experiment, we propose the ME Model, a modified Bayesian model, which approximates infants' mutual exclusivity bias to support the differential demands of monolingual and bilingual learning situations. The extended model is assessed using the same corpora of real child-directed speech, showing that its performance is more robust against varying input and less dependent than the Intentional Model on optimization of its parsimony parameter. We argue that both monolingual and bilingual demands on word learning are important considerations for a computational model, as they can yield significantly different results than when only one such context is considered.