Article

Network dynamics of encoding and retrieval of behavioural spike sequences during theta and ripples in a CA1 model of the hippocampus

BMC Neuroscience (Impact Factor: 2.67). 07/2010; 11(Suppl 1). DOI: 10.1186/1471-2202-11-S1-P55
Source: DOAJ

ABSTRACT

The hippocampus is known to be involved in spatial learning in rats. Spatial learning involves the encoding and replay of
temporally sequenced spatial information. Temporally sequenced spatial memories are encoded and replayed by the firing rate
and phase of pyramidal cells and inhibitory interneurons with respect to ongoing network oscillations (theta and ripples).
Understanding how the different hippocampal neuronal classes interact during these encoding and replay processes is of great
importance. A computational model of the CA1 microcircuit [3], [4], [5] that uses biophysical representations of the major
cell types, including pyramidal cells and four types of inhibitory interneurons is extended to address: (1) How are the encoding
and replay (forward and reverse) of behavioural place sequences controlled in the CA1 microcircuit during theta and ripples?
and (2) What roles do the various types of inhibitory interneurons play in these processes?

Download full-text

Full-text

Available from: Vassilis Cutsuridis
  • Source
    • "The neuronal diversity, morphology, ionic, and synaptic properties, connectivity , and spatial distribution closely followed known experimental evidence of the hippocampal microcircuitry (Cutsuridis et al., 2010). In a subsequent modeling study, Cutsuridis et al. (2010) extended the model of the CA1 microcircuitry to test its recall performance of new and previously stored static patterns as well as its memory capacity in the presence/absence of various inhibitory interneurons. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Successful spatial exploration requires gating, storage, and retrieval of spatial memories in the correct order. The hippocampus is known to play an important role in the temporal organization of spatial information. Temporally ordered spatial memories are encoded and retrieved by the firing rate and phase of hippocampal pyramidal cells and inhibitory interneurons with respect to ongoing network theta oscillations paced by intra- and extrahippocampal areas. Much is known about the anatomical, physiological, and molecular characteristics as well as the connectivity and synaptic properties of various cell types in the hippocampal microcircuits, but how these detailed properties of individual neurons give rise to temporal organization of spatial memories remains unclear. We present a model of the hippocampal CA1 microcircuit based on observed biophysical properties of pyramidal cells and six types of inhibitory interneurons: axo-axonic, basket, bistratistified, neurogliaform, ivy, and oriens lacunosum-moleculare cells. The model simulates a virtual rat running on a linear track. Excitatory transient inputs come from the entorhinal cortex (EC) and the CA3 Schaffer collaterals and impinge on both the pyramidal cells and inhibitory interneurons, whereas inhibitory inputs from the medial septum impinge only on the inhibitory interneurons. Dopamine operates as a gate-keeper modulating the spatial memory flow to the PC distal dendrites in a frequency-dependent manner. A mechanism for spike-timing-dependent plasticity in distal and proximal PC dendrites consisting of three calcium detectors, which responds to the instantaneous calcium level and its time course in the dendrite, is used to model the plasticity effects. The model simulates the timing of firing of different hippocampal cell types relative to theta oscillations, and proposes functional roles for the different classes of the hippocampal and septal inhibitory interneurons in the correct ordering of spatial memories as well as in the generation and maintenance of theta phase precession of pyramidal cells (place cells) in CA1. The model leads to a number of experimentally testable predictions that may lead to a better understanding of the biophysical computations in the hippocampus and medial septum.
    Full-text · Article · Jul 2012 · Hippocampus
  • Source
    • ", [7]. Active properties of the OLM cell included a fast Na + current, a delayed rectifier K + current, a persistent Na + current, a leakage current and an h-current [7], whereas those of the NGL cell included a fast Na + current, a delayed rectifier K + current and a leakage current. "
    [Show abstract] [Hide abstract]
    ABSTRACT: The hippocampus plays an important role in the encoding and retrieval of spatial and non-spatial memories. Much is known about the anatomical, physiological and molecular characteristics as well as the connectivity and synaptic properties of various cell types in the hippocampal circuits [1], but how these detailed properties of individual neurons give rise to the encoding and retrieval of memories remains unclear. Computational models play an instrumental role in providing clues on how these processes may take place. Here, we present three computational models of the region CA1 of the hippocampus at various levels of detail. Issues such as retrieval of memories as a function of cue loading, presentation frequency and learning paradigm, memory capacity, recall performance, and theta phase precession in the presence of dopamine neuromodulation and various types of inhibitory interneurons are addressed. The models lead to a number of experimentally testable predictions that may lead to a better understanding of the biophysical computations in the hippocampus.
    Full-text · Conference Paper · Jul 2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Coordination of neocortical oscillations has been hypothesized to underlie the "binding" essential to cognitive function. However, the mechanisms that generate neocortical oscillations in physiological frequency bands remain unknown. We hypothesized that interlaminar relations in neocortex would provide multiple intermediate loops that would play particular roles in generating oscillations, adding different dynamics to the network. We simulated networks from sensory neocortex using nine columns of event-driven rule-based neurons wired according to anatomical data and driven with random white-noise synaptic inputs. We tuned the network to achieve realistic cell firing rates and to avoid population spikes. A physiological frequency spectrum appeared as an emergent property, displaying dominant frequencies that were not present in the inputs or in the intrinsic or activated frequencies of any of the cell groups. We monitored spectral changes while using minimal dynamical perturbation as a methodology through gradual introduction of hubs into individual layers. We found that hubs in layer 2/3 excitatory cells had the greatest influence on overall network activity, suggesting that this subpopulation was a primary generator of theta/beta strength in the network. Similarly, layer 2/3 interneurons appeared largely responsible for gamma activation through preferential attenuation of the rest of the spectrum. The network showed evidence of frequency homeostasis: increased activation of supragranular layers increased firing rates in the network without altering the spectral profile, and alteration in synaptic delays did not significantly shift spectral peaks. Direct comparison of the power spectra with experimentally recorded local field potentials from prefrontal cortex of awake rat showed substantial similarities, including comparable patterns of cross-frequency coupling.
    Full-text · Article · Apr 2011 · Frontiers in Computational Neuroscience
Show more