Nonuniform allocation of hippocampal neurons to place fields across all hippocampal subfields

Abstract

The mechanisms governing how the hippocampus selects neurons to exhibit place fields are not well understood. A default assumption in some previous studies was the uniform random draw with replacement (URDWR) model, which, theoretically, maximizes spatial "pattern separation", and predicts a Poisson distribution of the numbers of place fields expressed by a given cell per unit area. The actual distribution of mean firing rates exhibited by a population of hippocampal neurons, however, is approximately exponential or log-normal in a given environment and these rates are somewhat correlated across multiple places, at least under some conditions. The advantage of neural activity-dependent immediate-early gene (IEG) analysis, as a proxy for electrophysiological recording, is the ability to obtain much larger samples of cells, even those whose activity is so sparse that they are overlooked in recording studies. Thus, a more accurate representation of the activation statistics can potentially be achieved. Some previous IEG studies that examined behavior-driven IEG expression in CA1 appear to support URDWR. There was, however, in some of the same studies, an under-recruitment of dentate gyrus granule cells, indicating a highly skewed excitability distribution, which is inconsistent with URDWR. Although it was suggested that this skewness might be related to increased excitability of recently generated granule cells, we show here that CA1, CA3, and subiculum also exhibit cumulative under-recruitment of neurons. Thus, a highly skewed excitability distribution is a general principle common to all major hippocampal subfields. Finally, a more detailed analysis of the frequency distributions of IEG intranuclear transcription foci suggests that a large fraction of hippocampal neurons is virtually silent, even during sleep. Whether the skewing of the excitability distribution is cell-intrinsic or a network phenomenon, and the degree to which this excitability is fixed or possibly time-varying are open questions for future studies. © 2016 Wiley Periodicals, Inc.

Age-related Changes in Lateral Entorhinal and CA3 Neuron Allocation Predict Poor Performance on Object Discrimination

“…Recent data have shown that a subset of cells in a hippocampal neural ensemble activated during an episode of exploration may be used redundantly when the environment changes, such that a greater number of cells have place fields in both environments than would be expected by chance (Alme et al, 2010; Mizuseki and Buzsáki, 2013; Buzsáki and Mizuseki, 2014; Witharana et al, 2016). This is believed to reflect skewed, high firing rate cells that are more likely to remain active across multiple environments (Mizuseki and Buzsáki, 2013; Buzsáki and Mizuseki, 2014; Witharana et al, 2016).…”

“…This is believed to reflect skewed, high firing rate cells that are more likely to remain active across multiple environments (Mizuseki and Buzsáki, 2013; Buzsáki and Mizuseki, 2014; Witharana et al, 2016). One way to examine the extent that neural ensembles follow a skewed excitability distribution rather than adhere to a uniform random draw with replacement (URDWR) model is to compare the expected percent of active cells across multiple epochs of exploration (Px) relative to the observed percent of cells.…”

“…As described previously (Witharana et al, 2016), the conventional theory of how place fields are allocated are a uniform random draw with replacement model in which no cell has more or less of a chance at being active in an environment than any other cell. However, the preconfigured, log-normally distributed firing rates of neurons in the hippocampus and entorhinal cortex (Mizuseki and Buzsáki, 2013; Buzsáki and Mizuseki, 2014) directly challenge traditional theories of memory encoding (namely “orthogonality”; McNaughton, 1998) and uniform random draw with replacement.…”

“…In addition to similarity score, the extent to which activated neural ensembles across regions deviated from a uniform random draw with replacement (URDWR) was quantified (Alme et al, 2010; Witharana et al, 2016). The URDWR model assumes that all cells have the same probability of activation in an environment of a given size, which can be represented by P1.…”

CA1 pyramidal cell diversity enabling parallel information processing in the hippocampus

“…However, the mechanisms that govern the selection of the actual subset of active PCs in a given environment remain unknown. The simplest scenario would be a random allocation of place cells 116 to maximize the separation of neuronal representations in different environments (‘pattern separation’ or remapping 117–119 ). However, recent experiments challenge this model, demonstrating that firing rate distributions of CA1PCs are skewed (log-normally distributed) 120 , the firing activity of each cell is largely preserved across behavioral states 120 , and hippocampal PCs may even be, at least in part, preselected for activation 121,122 .…”