A Role for Hilar Cells in Pattern Separation in the Dentate Gyrus: A Computational Approach

By Catherine E. Myers, H. Scharfman. 2009

191 citations recorded by the source corpus.

We present a simple computational model of the dentate gyrus to evaluate the hypothesis that pattern separation, defined as the ability to transform a set of similar input patterns into a less‐similar set of output patterns, is dynamically regulated by hilar neurons. Prior models of the dentate gyrus have generally fallen into two categories: simplified models that have focused on a single granule cell layer and its ability to perform pattern separation, and large‐scale and biophysically realistic models of dentate gyrus, which include hilar cells, but which have not specifically addressed pattern separation. The present model begins to bridge this gap. The model includes two of the major subtypes of hilar cells: excitatory hilar mossy cells and inhibitory hilar interneurons that receive input from and project to the perforant path terminal zone (HIPP cells). In the model, mossy cells and HIPP cells provide a mechanism for dynamic regulation of pattern separation, allowing the system to upregulate and downregulate pattern separation in response to environmental and task demands. Specifically, pattern separation in the model can be strongly decreased by decreasing mossy cell function and/or by increasing HIPP cell function; pattern separation can be increased by the opposite manipulations. We propose that hilar cells may similarly mediate dynamic regulation of pattern separation in the dentate gyrus in vivo, not only because of their connectivity within the dentate gyrus, but also because of their modulation by brainstem inputs and by the axons that “backproject” from area CA3 pyramidal cells. © 2008 Wiley‐Liss, Inc.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Developmental Neuroscience

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Citations in the corpus

Pattern separation in the hippocampus through the eyes of computational modeling (2017, methodology): “In their first attempt, Myers and Scharfman used a simple network model of the DG (Myers & Scharfman, 2009), consisting of GCs, mossy cells (MCs), HIPP cells (HCs), and a general type of interneurons that played the role of basket (BCs) and chande-lier cells, all modeled as point neurons.”
Resolving new memories: a critical look at the dentate gyrus, adult neurogenesis, and pattern separation (2011, background): “…some models have assumed the pattern separation function and have sought to reassess the mechanism by which the DG network decorrelates its inputs (Myers and Scharfman, 2009), there are other models that have explored other potential roles for the DG. Relevant to this discussion, there have been…”
Spatial firing correlates of physiologically distinct cell types of the rat dentate gyrus (2012, background): “…input patterns from the entorhinal cortex are distributed across the large granule cell population to decorrelate the patterns to reduce the probability of retrieval errors (McNaughton and Morris, 1987; O’Reilly and McClelland, 1994; Rolls and Kesner, 2006; Rolls, 2007; Myers and Scharfman, 2009).”
Spatial representations of granule cells and mossy cells of the dentate gyrus (2017, background): “…have revealed a more complex circuitry, with the mossy cell occupying a pivotal node mediating both a disynaptic, recurrent processing loop within the DG and a disynaptic feedback loop from the CA3 region back to the DG granule layer (Figure 1A; Scharfman, 1994, 2007; Myers and Scharfman, 2009).”
A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia (2015, background): “The memory eﬃciency of the hippocampus is partially dependent on its capability to encode overlapped sets inputs from the EC as patterns of activated neurons in the DG with minimum overlap between patterns (Myers and Scharfman, 2009).”
Physiological properties and behavioral correlates of hippocampal granule cells and mossy cells (2017, unknown): “Theoretical work, clinical imaging, and lesion experiments suggest that an important computational function of the hippocampal dentate gyrus (DG) is pattern separation (Marr, 1971; McNaughton and Morris, 1987; Treves and Rolls, 1994; Rolls and Kesner, 2006; Yassa and Stark, 2011; Myers and Scharfman”
Dendrites of dentate gyrus granule cells contribute to pattern separation by controlling sparsity (2016, background): “…models (Santhakumar et al., 2005; Yim et al., 2015) and experimental studies (Nitz and McNaughton, 2004; Jinde et al., 2012) have proposed that inhibition controls GC activity which, in turn, mediates pattern separation (Myers and Scharfman, 2009, 2011; Ikrar et al., 2013; Faghihi and…”
Hilar Mossy Cell Degeneration Causes Transient Dentate Granule Cell Hyperexcitability and Impaired Pattern Separation (2012, unknown): “, 1983; Bilkey and Goddard, 1987), it has recently been suggested that under normal conditions, their net effect is excitatory (Ratzliff et al., 2004; Myers and Scharfman, 2009).”
Dynamics of robust pattern separability in the hippocampal dentate gyrus (2015, background): “KEY WORDS: persistence; pattern separation; dentate gyrus; intracellular; slice; variability INTRODUCTION The hippocampal dentate gyrus (DG) is thought to perform pattern separation on the inputs it receives from the entorhinal cortex (Leutgeb et al., 2007; Myers and Scharfman, 2009).”
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation (2020, background): “The Cxcr4+ cells (#99-100) may correspond to the hilar performant path-associated (HIPP) or DG somatostatin-expressing-interneurons (DG-SOMIs) described previously (Hosp et al., 2014; Myers and Scharfman, 2009; Raza et al., 2017; Savanthrapadian et al., 2014).”
Sparse activity of identified dentate granule cells during spatial exploration (2016, background): “Sparse coding in the DG has been postulated to subserve ‘pattern separation’, a key function during memory processing (McNaughton and Morris, 1987; Leutgeb et al., 2007; Myers and Scharfman, 2009; Neunuebel and Knierim, 2014).”
Tracking the Flow of Hippocampal Computation: Pattern Separation, Pattern Completion, and Attractor Dynamics (2015, methodology): “Investigators elaborated Marr's subsequent theory of the hippocampus (Marr, 1971) and ascribed a similar function to the DG granule cell layer (McNaughton & Morris, 1987; McNaughton & Nadel, 1990; Rolls & Treves, 1998; O'Reilly & McClelland, 1994; Myers & Scharfman, 2009; Myers & Scharfman, 2011).”
Modeling new neuron function: a history of using computational neuroscience to study adult neurogenesis (2011, background): “For example, recently a model investigating the role of hilar cells in DG pattern separation was proposed by Myers & Scharfman (2009), and it would be interesting to observe the role of neurogenesis in this context.”