A Deconvolution-Based Method with High Sensitivity and Temporal Resolution for Detection of Spontaneous Synaptic Currents In Vitro and In Vivo

Abstract

Spontaneous postsynaptic currents (PSCs) provide key information about the mechanisms of synaptic transmission and the activity modes of neuronal networks. However, detecting spontaneous PSCs in vitro and in vivo has been challenging, because of the small amplitude, the variable kinetics, and the undefined time of generation of these events. Here, we describe a, to our knowledge, new method for detecting spontaneous synaptic events by deconvolution, using a template that approximates the average time course of spontaneous PSCs. A recorded PSC trace is deconvolved from the template, resulting in a series of delta-like functions. The maxima of these delta-like events are reliably detected, revealing the precise onset times of the spontaneous PSCs. Among all detection methods, the deconvolution-based method has a unique temporal resolution, allowing the detection of individual events in high-frequency bursts. Furthermore, the deconvolution-based method has a high amplitude resolution, because deconvolution can substantially increase the signal/noise ratio. When tested against previously published methods using experimental data, the deconvolution-based method was superior for spontaneous PSCs recorded in vivo. Using the high-resolution deconvolution-based detection algorithm, we show that the frequency of spontaneous excitatory postsynaptic currents in dentate gyrus granule cells is 4.5 times higher in vivo than in vitro.

Synaptic transmission and plasticity require AMPA receptor anchoring via its N-terminal domain

“…Briefly, events were detected using a template-based search (Pernía-Andrade et al, 2012), aligned by their point of steepest rise and peak scaled to account for differences in synaptic receptor number. Traces were filtered to those with a 10–90% rise time of less than 0.9 ms and subjected to visual inspection to eliminate obvious artifacts, overlapping mEPSCs or insufficient peak alignment.…”

Stimfit: quantifying electrophysiological data with Python

“…A deconvolution-based algorithm was implemented according to Pernía-Andrade et al (2012). The basic idea is to describe the recorded signal r ( t ) as a convolution h ( t ) of the time course of event onsets f ( t ) with the time course of a typical event p ( t ): $h(t)={\displaystyle {\int }_0^{t}f}\text{}\left(t-t^{\prime }\right)p\left(t^{\prime }\right)\text{d}{t}^{\prime },$ where f ( t ) describes event onsets by the Dirac delta function: $f(t)=\delta \text{}\left(t-t_0\right)=\{\begin{array}{ll}left\infty \hfill & \text{for\hspace{0.17em}}t\text{\hspace{0.17em}= }{t}_{\text{0}},\hfill \\ left0\hfill & \text{for\hspace{0.17em}}t\ne t_{\text{0}},\hfill \end{array},$ where t 0 is the time point of the onset of an event.…”

Theta-gamma-modulated synaptic currents in hippocampal granule cells in vivo define a mechanism for network oscillations

“…We therefore examined EPSCs under voltageclamp conditions at a holding potential of -70 mV, close to the reversal potential of GABA A R-mediated IPSCs (Figures 3A-3D; Table 1). EPSC detection (Pernía-Andrade et al, 2012) followed by kinetic analysis revealed that GCs in vivo in both anesthetized and awake rats were exposed to a high-frequency excitatory phasic input ( Figures 3A and 3B). On average, the peak amplitude of individual EPSCs was 8.8 ± 0.7 pA in anesthetized rats and 21.3 ± 2.4 pA in awake rats (15 and 13 cells, respectively; p < 0.0001; Figure 3C).…”

“…EPSCs were detected by a deconvolution-based algorithm (Pernía-Andrade et al, 2012). This procedure is particularly suitable for analysis of synaptic events in vivo, because of its high temporal resolution.…”

“…Temporal resolution was set to 1 ms (1 kHz). The amplitude criterion for detection was set to 4.3 3 SD of baseline noise, corresponding to a false positive rate of 0.17 points per second (Pernía-Andrade et al, 2012). After detection, kinetics and temporal structure of events were analyzed using scripts written in Igor Pro (version 6.22A; Wavemetrics).…”