P167 Active NMDARs expand input rate sensitivity into high-conductance states
Movitz Lenninger*1, Pawel Herman1, Mikael Skoglund1, Arvind Kumar1
1 School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden *Email: movitzle@kth.se
Introduction
A single cell has thousands of synapses distributed across the surface, predominantly along the dendritic tree [1]. Thus, in an active state, thousands of inputs can target a single cell leading to what is known as the high conductance state [2]. During such states, both input resistance and the effective membrane time constant are markedly reduced [3]. Paradoxically, high-conductance states can also lead to a reduction of postsynaptic activity [4,5]. Here, we show, using single-cell simulations of thick-tuft layer 5 (TTL5) pyramidal cells, that the voltage dependence of NMDA receptors (NMDARs), a ubiquitous feature in the brain, can increase excitability in high-conductance states – providing sensitivity to a larger range of inputs.
Methods We simulated a previously published reconstructed morphology of a rat TTL5 pyramidal cell [6]. We randomly distribute 5000 excitatory and 2500 inhibitory synapses uniformly according to the membrane surface areas of the dendritic segments (Figure 1a). Inputs are sampled from independent Poisson processes. In all cases, we optimize the inhibitory input rate to keep the somatic potential fluctuating around -60 mV. To study the role of active NMDARs, we consider three scenarios: synapses contain (1) only AMPA receptors (AMPARs), (2) both AMPARs and active NMDARs, and (3) both AMPARs and passive NMDARs. Unless otherwise stated, we use an NMDA-AMPA ratio of 1.6. In all cases, the integrated conductance per input is normalized to ~5.9 nS∙ms.
Results First, we compare the input resistances across three input conditions. The input resistance decreases with increasing inputs for all three synaptic types but is consistently larger with active NMDARs (Figure 1b). Second, we compare the output firing rates (FRs) across a large range of inputs. For low and intermediate inputs, the output FRs are similar across all synaptic types (Figure 1c). However, for high inputs, output gain is only maintained with active NMDARs. Furthermore, the coefficient of variation of the interspike intervals is typically higher for active NMDARs, indicating more irregular firing (Figure 1d). Third, varying the NMDA-AMPA ratio reveals that this is a graded property of active NMDARs (Figure 1e-f).
Discussion A key property of dendrites is to integrate pre-synaptic inputs. Active conductance can significantly alter the summation compared to passive dendrites [1]. Previous studies have, for example, linked active NMDARs to increased sequence discrimination [7] and increased coupling between tuft and soma [8]. Our work suggests active NMDARs might also be crucial for maintaining large postsynaptic activity under high input conditions, expanding the range of input sensitivity. Our work does not exclude the possibility of intrinsic voltage-gated ion channels further contributing to increased excitability under presynaptic activity [9]. It remains to study the possible interaction of such intrinsicconductanceswith active NMDRs.
Figure 1. a) Morphology of cell with 500 randomly distributed synapses. b) Estimated input resistances during three input conditions. c) Input-output transfer function of firing rates (lines). Shaded areas show the standard deviation (across bins of 1 second). d) CVs of the ISIs. Color codes in panels c-d) same as in b). e-f) Output firing rates and CVs for a range of NMDA-AMPA ratios with active NMDARs. AcknowledgementsN/A References [1]https://doi.org/10.1146/annurev.neuro.28.061604.135703 [2]https://doi.org/10.1038/nrn1198 [3]https://doi.org/10.1073/pnas.88.24.11569 [4]https://doi.org/10.1523/JNEUROSCI.3349-03.2004 [5]https://doi.org/10.1103/PhysRevX.12.011044 [6]https://doi.org/10.1371/journal.pcbi.1002107 [7]https://doi.org/10.1126/science.1189664 [8]https://doi.org/10.1038/nn.3646 [9]https://doi.org/10.1016/J.NEURON.2020.04.001
