Stimfit: quantifying electrophysiological data with Python

Abstract

Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals.

Substantia nigra dopaminergic neurons and striatal interneurons are engaged in three parallel but interdependent postnatal neurotrophic circuits

“…Currents were low‐pass‐filtered at 3 kHz, digitized at 20 kHz, and acquired using PatchMaster software (HEKA). All miniature postsynaptic currents were analyzed with the program Stimfit (Guzman, Schlögl, & Schmidt‐Hieber, 2014). Recordings were first digitally filtered at 1 kHz.…”

Plasticity-dependent, full detonation at hippocampal mossy fiber–CA3 pyramidal neuron synapses

“…Pulse generation and data acquisition were performed using FPulse version 3.3.3 (U. Fröbe, Physiological Institute, University of Freiburg, Germany). Data were analyzed with Stimfit version 0.13.17 (Guzman et al, 2014) and Igor Pro (Wavemetrics). In a subset of recordings, traces of unitary EPSPs were filtered (low-pass digital filter, cut-off frequency of 1 kHz) for robust analysis of maximal slope of the rising phase of individual EPSPs.…”

The rhodopsin–guanylyl cyclase of the aquatic fungus Blastocladiella emersonii enables fast optical control of cGMP signaling

“…The functionality of the cAMP-sensitive CNG channel (C460W/E583M) was shown through coexpression with bPAC and 3-s illumination with 450-nm light of 0.03 mW mm −2 . Data were analyzed with Stimfit 0.13(15) and Clampfit 10.4 software (Molecular Devices LLC).…”