Daily oscillations of neuronal membrane capacitance

Abstract

Capacitance of biological membranes is determined by the properties of the lipid portion of the membrane as well as the morphological features of a cell. In neurons, membrane capacitance is a determining factor of synaptic integration, action potential propagation speed, and firing frequency due to its direct effect on the membrane time constant. Besides slow changes associated with increased morphological complexity during postnatal maturation, neuronal membrane capacitance is considered a stable, non-regulated, and constant magnitude. Here we report that, in two excitatory neuronal cell types, pyramidal cells of the mouse primary visual cortex and granule cells of the hippocampus, the membrane capacitance significantly changes between the start and the end of a daily light-dark cycle. The changes are large, nearly 2-fold in magnitude in pyramidal cells, but are not observed in cortical parvalbumin-expressing inhibitory interneurons. Consistent with daily capacitance fluctuations, the time window for synaptic integration also changes in pyramidal cells.

Keywords: CP: Neuroscience; Circadian; capacitance; cortex; electrophysiology; granule cells; hippocampus; oscillators; pyramidal cells.

Figure 1.. Typical neuronal activity of pyramidal cells, PV⁺ cells, and GCs in response to current pulses

(A–C) Cortical pyramidal neurons (A) and hippocampal GCs (B) display a low frequency of action potential firing compared to cortical PV⁺ cells (C). A range of current pulses was applied, and a subthreshold voltage response (red traces) in each case was fitted with a double exponential function from which membrane capacitance was derived, as described in STAR Methods. (D) Example of a double exponential fit. The vertical lines indicate the limits for the 2-exponential fit (red trace) to a data trace (black). The boxed portion of the trace is shown amplified, with a 2-exponential fit (red trace) and a single exponential fit (blue trace) superimposed to illustrate the improved goodness of the fit with two over one exponential.

Figure 2.. Changes with time of day of Cm,τm, and Rm

(A–C) $C_m$ changes (A), ${\tau }_m$ changes (B), and $R_m$ changes (C) of visual cortex layer 2/3 pyramidal cells (left), hippocampus GCs (center), and visual cortex inhibitory PV⁺ cells (right). $C_m$ of both excitatory neurons (cortical pyramidal and hippocampal GCs) are highest at ZT0 (dark phase, gray area) and lowest at ZT6–ZT12 (light phase, white area). ${\tau }_m$ tracks these changes of $C_m$ and peaks at around ZT0, while $R_m$ does not change significantly with time of day in either GCs or PV⁺ cells. Only pyramidal cells show a significant change of $R_m$ monotonically increasing with time of day. Average ± SD is shown as red squares and connecting lines, slightly displaced from the individual data for clarity. Statistical details are listed in Tables S1–S3, but p values from one-way ANOVAs (pyramidal, PV⁺ cells) and Student’s t tests (GCs) are given here at the top right corners. Horizontal bars with vertical wings represent a post-hoc test (*p < 0.05) for the difference of the indicated pair.

Figure 3.. PNNs surrounding PV⁺ neurons do not regulate daily Cm changes

(A) Confocal image of the V1 region of a mouse cortical slice (region in the white square magnified). All td-tomato expressing, red-stained PV⁺ cells are clearly surrounded around the somata and proximal dendritic regions by a halo of WFA-positive material, indicative of the presence of a PNN. (B) After 45 min of ChABC treatment, the WFA staining is nearly completely eliminated. (C) The membrane capacitance of the individual ChABC-treated cells (black symbols for individual ZT0 and hollow symbols for individual ZT12 cells) and the average ± SD (slightly displaced red squares and whiskers) do not depend on ZT (p = 0.578, Student’s t test). Note that the $C_m$ values are not only indistinguishable between ChABC-treated ZT0 and ZT12 cells but also indistinguishable from the untread controls in Figure 2A.

Figure 4.. Synaptic integration is significantly affected by membrane capacitance changes

(A) Experimental setup. Two 65 × 65 μm squares of 470-nm-wavelength light pulses were sequentially applied (apical dendrite first) on approximately the center of the main apical and basal dendrites. The light intensity of each square pulse was adjusted to evoke a response at 80% of the spike threshold. The time between these pulses (IPI) was modified to be between 5 and 60 ms. The pulses were repeated several times, and the percentage of firing at each IPI was computed for each cell. (B) Example responses of individual cells collected at ZT0 (blue) and ZT12 (orange). Indicated is the fraction of times that each particular cell fired action potentials at each IPI. Stars identify the points in (C). (C) Summary graph of all experiments (9 cells at ZT0, 13 cells at ZT12, 4 mice each), showing that probability of firing decreases as the IPI increases, but more slowly and at higher IPIs in ZT0 cells, which has the largest $C_m$. Faint traces correspond to individual cells; stars label the points for which the voltage traces are shown in (B). Two-way ANOVA, p < 0.0001. Data are means ± SE of the means. (D) Schematic of a simplified model pyramidal cell with activity in response to current pulses (STAR Methods). (E) Examples of model cell runs (5 each) for models with time constants comparable to those in pyramidal cells at ZT0 (24 ms) and ZT12 (12–18 ms) with different IPIs. (F) Graph summarizing the model’s results for three different time constants, showing that cells with the largest $C_m$ and, thus, ${\tau }_m$ integrate the two excitatory postsynaptic potentials over a wider window of IPIs. Data are means ± SE of the means.