Dataset Information

Reverse Replay of Hippocampal Place Cells Is Uniquely Modulated by Changing Reward.

ABSTRACT: Hippocampal replays are episodes of sequential place cell activity during sharp-wave ripple oscillations (SWRs). Conflicting hypotheses implicate awake replay in learning from reward and in memory retrieval for decision making. Further, awake replays can be forward, in the same order as experienced, or reverse, in the opposite order. However, while the presence or absence of reward has been reported to modulate SWR rate, the effect of reward changes on replay, and on replay direction in particular, has not been examined. Here we report divergence in the response of forward and reverse replays to changing reward. While both classes of replays were observed at reward locations, only reverse replays increased their rate at increased reward or decreased their rate at decreased reward, while forward replays were unchanged. These data demonstrate a unique relationship between reverse replay and reward processing and point to a functional distinction between different directions of replay. VIDEO ABSTRACT.

SUBMITTER: Ambrose RE

PROVIDER: S-EPMC6013068 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

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Reverse Replay of Hippocampal Place Cells Is Uniquely Modulated by Changing Reward.

Ambrose R Ellen RE Pfeiffer Brad E BE Foster David J DJ

Neuron 20160825 5

Hippocampal replays are episodes of sequential place cell activity during sharp-wave ripple oscillations (SWRs). Conflicting hypotheses implicate awake replay in learning from reward and in memory retrieval for decision making. Further, awake replays can be forward, in the same order as experienced, or reverse, in the opposite order. However, while the presence or absence of reward has been reported to modulate SWR rate, the effect of reward changes on replay, and on replay direction in particul ...[more]

PMID: 27568518

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Project description:At rest, hippocampal "place cells," neurons with receptive fields corresponding to specific spatial locations, reactivate in a manner that reflects recently traveled trajectories. These "replay" events have been proposed as a mechanism underlying memory consolidation, or the transfer of a memory representation from the hippocampus to neocortical regions associated with the original sensory experience. Accordingly, it has been hypothesized that hippocampal replay of a particular experience should be accompanied by simultaneous reactivation of corresponding representations in the neocortex and in the entorhinal cortex, the primary interface between the hippocampus and the neocortex. Recent studies have reported that coordinated replay may occur between hippocampal place cells and medial entorhinal cortex grid cells, cells with multiple spatial receptive fields. Assessing replay in grid cells is problematic, however, as the cells exhibit regularly spaced spatial receptive fields in all environments and, therefore, coordinated replay between place cells and grid cells may be detected by chance. In the present report, we adapted analytical approaches utilized in recent studies of grid cell and place cell replay to determine the extent to which coordinated replay is spuriously detected between grid cells and place cells recorded from separate rats. For a subset of the employed analytical methods, coordinated replay was detected spuriously in a significant proportion of cases in which place cell replay events were randomly matched with grid cell firing epochs of equal duration. More rigorous replay evaluation procedures and minimum spike count requirements greatly reduced the amount of spurious findings. These results provide insights into aspects of place cell and grid cell activity during rest that contribute to false detection of coordinated replay. The results further emphasize the need for careful controls and rigorous methods when testing the hypothesis that place cells and grid cells exhibit coordinated replay.

Project description:Neural codes have been postulated to build efficient representations of the external world. The hippocampus, an encoding system, employs neuronal firing rates and spike phases to encode external space. Although the biophysical origin of such codes is at a single neuronal level, the role of neural components in efficient coding is not understood. The complexity of this problem lies in the dimensionality of the parametric space encompassing neural components, and is amplified by the enormous biological heterogeneity observed in each parameter. A central question that spans encoding systems therefore is how neurons arrive at efficient codes in the face of widespread biological heterogeneities. To answer this, we developed a conductance-based spiking model for phase precession, a phase code of external space exhibited by hippocampal place cells. Our model accounted for several experimental observations on place cell firing and electrophysiology: the emergence of phase precession from exact spike timings of conductance-based models with neuron-specific ion channels and receptors; biological heterogeneities in neural components and excitability; the emergence of subthreshold voltage ramp, increased firing rate, enhanced theta power within the place field; a signature reduction in extracellular theta frequency compared to its intracellular counterpart; and experience-dependent asymmetry in firing-rate profile. We formulated phase-coding efficiency, using Shannon's information theory, as an information maximization problem with spike phase as the response and external space within a single place field as the stimulus. We employed an unbiased stochastic search spanning an 11-dimensional neural space, involving thousands of iterations that accounted for the biophysical richness and neuron-to-neuron heterogeneities. We found a small subset of models that exhibited efficient spatial information transfer through the phase code, and investigated the distinguishing features of this subpopulation at the parametric and functional scales. At the parametric scale, which spans the molecular components that defined the neuron, several nonunique parametric combinations with weak pairwise correlations yielded models with similar high phase-coding efficiency. Importantly, placing additional constraints on these models in terms of matching other aspects of hippocampal neural responses did not hamper parametric degeneracy. We provide quantitative evidence demonstrating this parametric degeneracy to be a consequence of a many-to-one relationship between the different parameters and phase-coding efficiency. At the functional scale, involving the cellular-scale neural properties, our analyses revealed an important higher-order constraint that was exclusive to models exhibiting efficient phase coding. Specifically, we found a counterbalancing negative correlation between neuronal gain and the strength of external synaptic inputs as a critical functional constraint for the emergence of efficient phase coding. These observations implicate intrinsic neural properties as important contributors in effectuating such counterbalance, which can be achieved by recruiting nonunique parametric combinations. Finally, we show that a change in afferent statistics, manifesting as input asymmetry onto these neuronal models, induced an adaptive shift in the phase code that preserved its efficiency. Together, our analyses unveil parametric degeneracy as a mechanism to harness widespread neuron-to-neuron heterogeneity towards accomplishing stable and efficient encoding, provided specific higher-order functional constraints on the relationship of neural gain to external inputs are satisfied.

Dataset Information

Reverse Replay of Hippocampal Place Cells Is Uniquely Modulated by Changing Reward.

Publications

Reverse Replay of Hippocampal Place Cells Is Uniquely Modulated by Changing Reward.

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