Assessments of dentate gyrus function: discoveries and debates.

There has been considerable speculation regarding the function of the dentate gyrus (DG) - a subregion of the mammalian hippocampus - in learning and memory. In this Perspective article, we compare leading theories of DG function. We note that these theories all critically rely on the generation of distinct patterns of activity in the region to signal differences between experiences and to reduce interference between memories. However, these theories are divided by the roles they attribute to the DG during learning and recall and by the contributions they ascribe to specific inputs or cell types within the DG. These differences influence the information that the DG is thought to impart to downstream structures. We work towards a holistic view of the role of DG in learning and memory by first developing three critical questions to foster a dialogue between the leading theories. We then evaluate the extent to which previous studies address our questions, highlight remaining areas of conflict, and suggest future experiments to bridge these theories.

Stimulation-induced entrainment of hippocampal network activity: Identifying optimal input frequencies.

The hippocampus contains rich oscillatory activity, with continuous ebbs and flows of rhythmic currents that constrain its ability to integrate inputs. During associative learning, the hippocampus must integrate inputs from a range of sources carrying information about events and the contexts in which they occur. Under these circumstances, temporal coordination of activity between sender and receiver is likely essential for successful communication. Previously, it has been shown that the coordination of rhythmic activity between the lateral entorhinal cortex (LEC) and the CA1 region of the hippocampus is tightly correlated with the onset of learning in an associative learning task. We aimed to examine whether rhythmic inputs from the LEC in specific frequency ranges were sufficient to enhance the temporal coordination of activity in downstream CA1. In urethane-anesthetized rats, we applied extracellular low-intensity alternating current stimulation across the length of the LEC. Using this method, we aimed to phase-bias ongoing neuronal activity in LEC at a range of different frequencies (from 1.25 to 55 Hz). Rhythmic stimulation of LEC at both 35 and 50 Hz increased the proportion of CA1 neurons significantly entrained to the phase of the applied stimulation current. A subset of stimulation frequencies modified CA1 spiking relationships to the phase of local ongoing CA1 oscillations, with each stimulation frequency exerting a unique influence upon downstream CA1, often in frequency ranges outside the target stimulation frequency. These results suggest there are optimal frequencies for LEC-CA1 communication, and that different profiles of LEC rhythms likely have distinct outcomes upon CA1 processing.

Modeling relationships between rhythmic processes and neuronal spike timing.

Neurons are embedded in complex networks, where they participate in repetitive, coordinated interactions with other neurons. Neuronal spike timing is thus predictably constrained by a range of ionic currents that shape activity at both short (milliseconds) and longer (tens to hundreds of milliseconds) timescales, but we lack analytical tools to rigorously identify these relationships. Here, we innovate a modeling approach to test the relationship between oscillations in the local field potential (LFP) and neuronal spike timing. We use kernel density estimation to relate single neuron spike timing and the phase of LFP rhythms (in simulated and hippocampal CA1 neuronal spike trains). We then combine phase and short (3 ms) spike history information within a logistic regression framework ("phaseSH models"), and show that models that leverage refractory constraints and oscillatory phase information can effectively test whether-and the degree to which-rhythmic currents (as measured from the LFP) reliably explain variance in neuronal spike trains. This approach allows researchers to systematically test the relationship between oscillatory activity and neuronal spiking dynamics as they unfold over time and as they shift to adapt to distinct behavioral conditions.NEW & NOTEWORTHY Statistical models that incorporate neural spiking history and relationships to the phase of ongoing oscillations in the local field potential robustly capture and predict neuronal engagement in rhythmic processes. These models constitute a powerful tool to systematically test explicit hypotheses regarding the specific rhythmic currents that constrain neural spiking activity over time and during different behaviors.

A flexible likelihood approach for predicting neural spiking activity from oscillatory phase.

BACKGROUND: The synchronous ionic currents that give rise to neural oscillations have complex influences on neuronal spiking activity that are challenging to characterize. NEW METHOD: Here we present a method to estimate probabilistic relationships between neural spiking activity and the phase of field oscillations using a generalized linear model (GLM) with an overcomplete basis of circular functions. We first use an L1-regularized maximum likelihood procedure to select an active set of regressors from the overcomplete set and perform model fitting using standard maximum likelihood estimation. An information theoretic model selection procedure is then used to identify an optimal subset of regressors and associated coefficients that minimize overfitting. To assess goodness of fit, we apply the time-rescaling theorem and compare model predictions to original data using quantile-quantile plots. RESULTS: Spike-phase relationships in synthetic data were robustly characterized. When applied to in vivo hippocampal data from an awake behaving rat, our method captured a multimodal relationship between the spiking activity of a CA1 interneuron, a theta (5-10 Hz) rhythm, and a nested high gamma (65-135 Hz) rhythm. COMPARISON WITH EXISTING METHODS: Previous methods for characterizing spike-phase relationships are often only suitable for unimodal relationships, impose specific relationship shapes, or have limited ability to assess the accuracy or fit of their characterizations. CONCLUSIONS: This method advances the way spike-phase relationships are visualized and quantified, and captures multimodal spike-phase relationships, including relationships with multiple nested rhythms. Overall, our method is a powerful tool for revealing a wide range of neural circuit interactions.

Neurophysiological signatures of temporal coordination between retrosplenial cortex and the hippocampal formation.

Retrosplenial cortex (RSC) is heavily interconnected with a multitude of cortical regions and is directly connected with the hippocampal formation. As such, it is a likely coordinator of information transfer between the hippocampus (HPC) and cortex in the service of spatial cognition and episodic memory. The current work examined three potential temporal frameworks for retrosplenial-hippocampal communication, namely, theta frequency oscillations (6-12 Hz), sharp-wave/ripple events, and repeating, theta phase-locked shifts from low (30-65 Hz) to high (120-160 Hz) gamma frequency oscillations. From simultaneous recordings of single units and local field potentials (LFPs) in RSC and HPC, we report the presence of prominent theta, low-gamma, and high-gamma oscillations in the retrosplenial LFP. Retrosplenial and hippocampal theta rhythms were strongly coherent and subgroups of retrosplenial neurons exhibited either spiking at theta frequencies and/or spike-phase-locking to theta. Retrosplenial neurons were also phase-locked to local low- and high-gamma rhythms, and power in these frequency bands was coupled in a sequential fashion to specific phases of hippocampal and retrosplenial theta rhythms. Coordinated activity between the two regions also occurred during hippocampal sharp-wave/ripple events, where retrosplenial neuron populations were modulated in their spiking and retrosplenial LFPs exhibited sharp-wave-like events that co-occurred with those observed in HPC. These results identify several temporal windows of synchronization between RSC and HPC that may mediate cortico-hippocampal processes related to learning, memory, and spatial representation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Young adult born neurons enhance hippocampal dependent performance via influences on bilateral networks.

Adult neurogenesis supports performance in many hippocampal dependent tasks. Considering the small number of adult-born neurons generated at any given time, it is surprising that this sparse population of cells can substantially influence behavior. Recent studies have demonstrated that heightened excitability and plasticity may be critical for the contribution of young adult-born cells for certain tasks. What is not well understood is how these unique biophysical and synaptic properties may translate to networks that support behavioral function. Here we employed a location discrimination task in mice while using optogenetics to transiently silence adult-born neurons at different ages. We discovered that adult-born neurons promote location discrimination during early stages of development but only if they undergo maturation during task acquisition. Silencing of young adult-born neurons also produced changes extending to the contralateral hippocampus, detectable by both electrophysiology and fMRI measurements, suggesting young neurons may modulate location discrimination through influences on bilateral hippocampal networks.

Rhythmic coordination of hippocampal neurons during associative memory processing.

Hippocampal oscillations are dynamic, with unique oscillatory frequencies present during different behavioral states. To examine the extent to which these oscillations reflect neuron engagement in distinct local circuit processes that are important for memory, we recorded single cell and local field potential activity from the CA1 region of the hippocampus as rats performed a context-guided odor-reward association task. We found that theta (4-12 Hz), beta (15-35 Hz), low gamma (35-55 Hz), and high gamma (65-90 Hz) frequencies exhibited dynamic amplitude profiles as rats sampled odor cues. Interneurons and principal cells exhibited unique engagement in each of the four rhythmic circuits in a manner that related to successful performance of the task. Moreover, principal cells coherent to each rhythm differentially represented task dimensions. These results demonstrate that distinct processing states arise from the engagement of rhythmically identifiable circuits, which have unique roles in organizing task-relevant processing in the hippocampus.

Transient optogenetic inactivation of the medial entorhinal cortex biases the active population of hippocampal neurons.

The mechanisms that enable the hippocampal network to express the appropriate spatial representation for a particular circumstance are not well understood. Previous studies suggest that the medial entorhinal cortex (MEC) may have a role in reproducibly selecting the hippocampal representation of an environment. To examine how ongoing MEC activity is continually integrated by the hippocampus, we performed transient unilateral optogenetic inactivations of the MEC while simultaneously recording place cell activity in CA1. Inactivation of the MEC caused a partial remapping in the CA1 population without diminishing the degree of spatial tuning across the active cell assembly. These changes remained stable irrespective of intermittent disruption of MEC input, indicating that while MEC input is integrated over long time scales to bias the active population, there are mechanisms for stabilizing the population of active neurons independent of the MEC. We find that MEC inputs to the hippocampus shape its ongoing activity by biasing the participation of the neurons in the active network, thereby influencing how the hippocampus selectively represents information.

Theta and beta oscillatory dynamics in the dentate gyrus reveal a shift in network processing state during cue encounters.

The hippocampus is an important structure for learning and memory processes, and has strong rhythmic activity. Although a large amount of research has been dedicated toward understanding the rhythmic activity in the hippocampus during exploratory behaviors, specifically in the theta (5-10 Hz) frequency range, few studies have examined the temporal interplay of theta and other frequencies during the presentation of meaningful cues. We obtained in vivo electrophysiological recordings of local field potentials (LFP) in the dentate gyrus (DG) of the hippocampus as rats performed three different associative learning tasks. In each task, cue presentations elicited pronounced decrements in theta amplitude in conjunction with increases in beta (15-30 Hz) amplitude. These changes were often transient but were sustained from the onset of cue encounters until the occurrence of a reward outcome. This oscillatory profile shifted in time to precede cue encounters over the course of the session, and was not present during similar behaviors in the absence of task relevant stimuli. The observed decreases in theta amplitude and increases in beta amplitude in the DG may thus reflect a shift in processing state that occurs when encountering meaningful cues.

A hypothesis for temporal coding of young and mature granule cells.

While it has been hypothesized that adult neurogenesis (NG) plays a role in the encoding of temporal information at long time-scales, the temporal relationship of immature cells to the highly rhythmic network activity of the hippocampus has been largely unexplored. Here, we present a theory for how the activity of immature adult-born granule cells relates to hippocampal oscillations. Our hypothesis is that theta rhythmic (5-10 Hz) excitatory and inhibitory inputs into the hippocampus could differentially affect young and mature granule cells due to differences in intrinsic physiology and synaptic inhibition between the two cell populations. Consequently, immature cell activity may occur at broader ranges of theta phase than the activity of their mature counterparts. We describe how this differential influence on young and mature granule cells could separate the activity of differently aged neurons in a temporal coding regime. Notably, this process could have considerable implications on how the downstream CA3 region interprets the information conveyed by young and mature granule cells. To begin to investigate the phasic behavior of granule cells, we analyzed in vivo recordings of the rat dentate gyrus (DG), observing that the temporal behavior of granule cells with respect to the theta rhythm is different between rats with normal and impaired levels of NG. Specifically, in control animals, granule cells exhibit both strong and weak coupling to the phase of the theta rhythm. In contrast, the distribution of phase relationships in NG-impaired rats is shifted such that they are significantly stronger. These preliminary data support our hypothesis that immature neurons could distinctly affect the temporal dynamics of hippocampal encoding.

What's new is older.

Distinct populations of active cells in the dentate gyrus of the hippocampus may facilitate the unique encoding of changes in the environment.