An analysis of the mean theta phase of population activity in a model of hippocampal region CA1

Abstract

In a recent study, Manns et al. (2006) showed that CA1 population spiking activity differs in mean phase between conditions of exposure to stimuli of varying levels of familiarity. Here we provide an analysis of a computational model of the hippocampus from Hasselmo et al. (2002) to examine how an animal's history of exposures to stimuli affects CA1 population activity. We show how the model can reproduce the major findings from the study by Manns et al. Specifically, we show that differences in direction and magnitude of the mean phase of population activity between two stimuli in the model depend on the order of presentation of the stimuli and the duration of exposure during each presentation. The analyses also reveal that the model's learning rule results in stability and normalization of synaptic weights and show how dysfunction of neuromodulatory systems might lead to epileptic or amnestic type conditions.

On phasic inhibition during hippocampal theta

“…Experimental data and computational modelling, including that presented here, demonstrate that a theta cycle is an ''information processing'' time window (of around 250 ms) during which novel and familiar inputs are ''processed'' in different ways in distinct subwindows within the theta cycle (Hasselmo et al 2002;Hasselmo 2005;Zilli and Hasselmo 2006). However, the exact mix and timing of cellular output and synaptic plasticity may vary between theta cycles for an individual pyramidal cell and across cell populations during active behaviour in an animal.…”

“…The essential characteristics of the effects of theta-modulated excitatory and inhibitory inputs on cell activity can be illustrated using a simple ''sum-ofsinusoids'' (SoS) model (Hasselmo et al 2002;Zilli and Hasselmo 2006). We are specifically interested in the subtractive influence of inhibition on the phasic output of a pyramidal cell.…”

“…The phase of peak output activity as a result of two sinusoidal inputs can be calculated directly from the formula (Zilli and Hasselmo 2006;Chance 2012):…”

“…Experimental and modelling studies suggest that a major role for theta is the separation in time of the processing of novel and familiar inputs (Paulsen and Moser 1998;Hasselmo et al 2002;Zilli and Hasselmo 2006;Manns et al 2007;Cutsuridis et al 2010;Cutsuridis and Hasselmo 2012). In this scenario, one half of a theta cycle is specialised for the encoding of new inputs through synaptic plasticity; whereas recall of previously stored associations is initiated on the alternate half cycle, and plasticity is restricted during this period.…”

“…One simple explanation for this is that it is due to changes in the relative strengths of CA3 and ECIII inputs that have distinct theta-phasic firing and separated, but overlapping place fields (Chance 2012), though a variety of cellular and network causes for phase precession have been proposed (see Chance 2012 for a discussion and references). A conceptually different scenario based upon the same principle is that ECIII input provides direct sensory signals, whereas the CA3 input forms a cue of remembered signals, so that EC input is strongest for novel stimuli, whereas CA3 input dominates for familiar stimuli, with the consequence that the preferred phase of CA1 activity shifts between the peak phases of EC and CA3 input depending on the familiarity of a sensory cue (Zilli and Hasselmo 2006;Manns et al 2007). …”