Abstract
The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain.
Highlights
The hippocampus and surrounding medial temporal lobe are implicated in declarative memory function in humans and other mammals [1]
A computational theory of this synaptic plasticity was first provided by Donald Hebb within the context of a more general neural coding mechanism, whereby phase sequences of activity directed by ongoing external and internal dynamics propagate in mutually exciting ensembles of neurons
Empirical evidence for this cell assembly model has been obtained in the hippocampus, where neuronal ensembles encoding for spatial location repeatedly fire in sequence at different phases of the ongoing theta oscillation
Summary
The hippocampus and surrounding medial temporal lobe are implicated in declarative memory function in humans and other mammals [1]. It has been demonstrated that the exact timing of place cell discharge, relative to the theta oscillation which dominates the hippocampal EEG during learning, correlates with distance travelled through a place field [2,7,10,11,12] This phase precession mechanism creates a compressed ‘theta coded’ firing pattern in place cells which corresponds to the sequence of place fields being traversed [13]. These findings have led to the hypothesis that the hippocampus operates using a dual rate and temporal coding system [14,15]. We present a spiking neural network model which utilises a dual coding system in order to encode and recall both symmetric (auto-associative) and asymmetric (hetero-associative) connections between neurons that exhibit repeated synchronous and asynchronous firing patterns respectively
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