EAG-SPy: Automated Python Toolkit for Electroantennogram (EAG) and Sensillar Potential (SP) Analysis
Abstract
EAG-SPy is a Python command-line toolkit that automates the quantification of transient, negative-going evoked potentials stored in Axon Binary Format (.abf). It was designed for insect electroantennogram (EAG) and sensillar potential (SP) recordings. Because every metric is derived from the waveform of a single stimulus-locked deflection, it can also be applied to other transient evoked potentials of the same polarity. For every sweep of every selected channel, EAG-SPy (i) restores the recorded amplitude scale from the file header, (ii) applies a zero-phase Gaussian low-pass filter in the frequency domain, (iii) detects response onset with a relative amplitude threshold and computes the latency from stimulus onset, (iv) quantifies the peak voltage, the response amplitude (ΔSP), half-amplitude rise and decay times, the duration at half amplitude, integrated areas, the voltage and percentage of ΔSP at two user-defined times, the linear slope of the rising phase (onset to 50 % and 80 % of ΔSP) the maximal depolarization rate (minimum of dV/dt) and the maximal recovery rate (maximum of dV/dt within a user-defined window of the recovery phase) from the first derivative, and (v) optionally fits one of eight analytical models (linear, exponential, polynomial, logistic) or selects the highest-R² model automatically over a user-defined interval, exporting labelled parameters and R². The toolkit writes annotated figures, fitted and derivative curves as text files, a results table (.csv and .txt) and summary histograms. Every output carries the software version and DOI for provenance. EAG-SPy processes whole folders of recordings without manual trace-by-trace measurement, making the extraction of amplitude and kinetic parameters reproducible and independent of the operator. Scope note. Latency, ΔSP and the derived parameters assume a negative-going deflection (depolarizing in the usual EAG convention) with a single dominant event per analysis window. The tool does not process GC-EAD chromatographic traces.
Fields of Study & Subjects
Neurobiology and Insect Physiology Research
Computational Physics and Python Applications
Undergraduate Neuroscience Education and Research
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 January 2026
- Language
- EN