Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

Abstract

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code.

A computational study on how theta modulated inhibition can account for the long temporal windows in the entorhinal–hippocampal loop

“…For the accurate recall of a memory pattern the dendritic inhibition in all three hippocampal regions (HC in DG, BC in CA3 and BSC in CA1) is instrumental by thresholding the GC and CA3-and CA1-PC firing, respectively. This result is in line with previous experimental results (Winson, 1978) and computational studies at both the single cell level, showing that inhibition is critical for gating and transforming the firing pattern of CA1 PCs (Pissadaki et al, 2010), and the network level (Cutsuridis et al, 2008;Cutsuridis, Cobb, et al, 2010;Cutsuridis et al, 2011;Cutsuridis & Hasselmo, 2012;Cutsuridis & Wenneckers, 2009;Kunec et al, 2005) showing that theta oscillations are implicated in the encoding and retrieval of memories (Cutsuridis & Hasselmo, 2012;Cutsuridis & Wenneckers, 2009;Cutsuridis et al, 2008;Cutsuridis, Cobb, et al, 2010;Hasselmo et al, 2002;Jensen & Lisman, 2005;Kunec et al, 2005) and disruption of them results in behavioral deficits (Winson, 1978).…”

“…Golding et al (2005) suggested that the distal synaptic inputs are likely only to be effective in causing CA1-PCs to fire action potentials when their distal dendrites are highly excitable. One way to increase excitability in these dendrites is by clustering of excitatory synaptic inputs, as previously shown by Poirazi et al (2003b) and Pissadaki, Sidiropoulou, Reczko, & Poirazi (2010).…”

Induction and modulation of persistent activity in a layer V PFC microcircuit model

“…The R-type calcium current, however, has opposite effects, depending on its somatic or dendritic localization: dendritic modifications are proportional while somatic modifications are inversely proportional to the induction probability. The possible explanation for this observation is that R-type calcium channels contribute to bursting when located in the dendrites (Takahashi and Magee, 2009; Pissadaki et al, 2010) and to AHP when located at the soma. Thus, increasing R-type channel currents in the dendrites enhances local depolarization and perhaps contributes to dendritic spike generation, whereas increasing it in the soma does not contribute to dendritic events (Figures 5C,D).…”

Predictive Features of Persistent Activity Emergence in Regular Spiking and Intrinsic Bursting Model Neurons

“…Although the differences in the AP latencies between ‘persistent’ and ‘no persistent’ trials were submillisecond, several studies suggest that they could still be decoded by downstream neurons [49], [50], [51]. This finding adds to the coding capabilities of the AP latency which has also been found to code for differences in spatiotemporal characteristics of the input in CA1 model neurons [48] as well as the location of sound in secondary auditory neurons [52].…”