Neural dynamics underlying associative learning in the dorsal and ventral hippocampus.

Animals associate cues with outcomes and update these associations as new information is presented. This requires the hippocampus, yet how hippocampal neurons track changes in cue-outcome associations remains unclear. Using two-photon calcium imaging, we tracked the same dCA1 and vCA1 neurons across days to determine how responses evolve across phases of odor-outcome learning. Initially, odors elicited robust responses in dCA1, whereas, in vCA1, odor responses primarily emerged after learning and embedded information about the paired outcome. Population activity in both regions rapidly reorganized with learning and then stabilized, storing learned odor representations for days, even after extinction or pairing with a different outcome. Additionally, we found stable, robust signals across CA1 when mice anticipated outcomes under behavioral control but not when mice anticipated an inescapable aversive outcome. These results show how the hippocampus encodes, stores and updates learned associations and illuminates the unique contributions of dorsal and ventral hippocampus.

A Distributed Neural Code in the Dentate Gyrus and in CA1.

Neurons are often considered specialized functional units that encode a single variable. However, many neurons are observed to respond to a mix of disparate sensory, cognitive, and behavioral variables. For such representations, information is distributed across multiple neurons. Here we find this distributed code in the dentate gyrus and CA1 subregions of the hippocampus. Using calcium imaging in freely moving mice, we decoded an animal's position, direction of motion, and speed from the activity of hundreds of cells. The response properties of individual neurons were only partially predictive of their importance for encoding position. Non-place cells encoded position and contributed to position encoding when combined with other cells. Indeed, disrupting the correlations between neural activities decreased decoding performance, mostly in CA1. Our analysis indicates that population methods rather than classical analyses based on single-cell response properties may more accurately characterize the neural code in the hippocampus.

The Dentate Gyrus Classifies Cortical Representations of Learned Stimuli.

Animals must discern important stimuli and place them onto their cognitive map of their environment. The neocortex conveys general representations of sensory events to the hippocampus, and the hippocampus is thought to classify and sharpen the distinctions between these events. We recorded populations of dentate gyrus granule cells (DG GCs) and lateral entorhinal cortex (LEC) neurons across days to understand how sensory representations are modified by experience. We found representations of odors in DG GCs that required synaptic input from the LEC. Odor classification accuracy in DG GCs correlated with future behavioral discrimination. In associative learning, DG GCs, more so than LEC neurons, changed their responses to odor stimuli, increasing the distance in neural representations between stimuli, responding more to the conditioned and less to the unconditioned odorant. Thus, with learning, DG GCs amplify the decodability of cortical representations of important stimuli, which may facilitate information storage to guide behavior.

Preferential Targeting of Lateral Entorhinal Inputs onto Newly Integrated Granule Cells.

Mature dentate granule cells in the hippocampus receive input from the entorhinal cortex via the perforant path in precisely arranged lamina, with medial entorhinal axons innervating the middle molecular layer and lateral entorhinal cortex axons innervating the outer molecular layer. Although vastly outnumbered by mature granule cells, adult-generated newborn granule cells play a unique role in hippocampal function, which has largely been attributed to their enhanced excitability and plasticity (Schmidt-Hieber et al., 2004; Ge et al., 2007). Inputs from the medial and lateral entorhinal cortex carry different informational content. Thus, the distribution of inputs onto newly integrated granule cells will affect their function in the circuit. Using retroviral labeling in combination with selective optogenetic activation of medial or lateral entorhinal inputs, we examined the functional innervation and synaptic maturation of newly generated dentate granule cells in the mouse hippocampus. Our results indicate that lateral entorhinal inputs provide the majority of functional innervation of newly integrated granule cells at 21 d postmitosis. Despite preferential functional targeting, the dendritic spine density of immature granule cells was similar in the outer and middle molecular layers, which we speculate could reflect an unequal distribution of shaft synapses. However, chronic blockade of neurotransmitter release of medial entorhinal axons with tetanus toxin disrupted normal synapse development of both medial and lateral entorhinal inputs. Our results support a role for preferential lateral perforant path input onto newly generated neurons in mediating pattern separation, but also indicate that medial perforant path input is necessary for normal synaptic development.SIGNIFICANCE STATEMENT The formation of episodic memories involves the integration of contextual and spatial information. Newly integrated neurons in the dentate gyrus of the hippocampus play a critical role in this process, despite constituting only a minor fraction of the total number of granule cells. Here we demonstrate that these neurons preferentially receive information thought to convey the context of an experience. Each newly integrated granule cell plays this unique role for ∼1 month before reaching maturity.

The Small World of a Fear Memory.

How are fear memories organized? In this issue of Neuron, Vetere et al. (2017) take a network-based approach to demonstrate the importance of highly interconnected hub regions in the consolidation of a fear memory. By doing so, they provide an elegant framework for predicting behavior from functional network properties.