I can not comment on pclamp or easy electrophysilogy. The crucial part is usually the reliable detection of the IPSC with sufficient accuracy and low enough false positive and false negative rate.

We use the "Biosig toolbox for Octave and Matlab" [2] for spike and burst detection. For the AP spike and burst analysis, we use [1]. For PSC detection, we use one of the following:

* minidet [3]

* signal_deconvolution [4,5]

* MOD (machine-learning based optimal detection [6,7]

Once the events have been detected, you can do the burst analysis with "spikes2bursts" [8].

Maybe Biosig could be useful to you for your IPSC Burst Analysis.

[1] https://biosig.sourceforge.net/download.html

[2] https://sourceforge.net/p/biosig/code/ci/master/tree/biosig4matlab/t250_ArtifactPreProcessingQualityControl/detect_spikes_bursts.m

[3] https://sourceforge.net/p/biosig/code/ci/master/tree/biosig4matlab/t330_StimFit/minidet.m

[4] Alejandro Javier Pernía-Andrade, Sarit Pati Goswami, Yvonne Stickler, Ulrich Fröbe, Alois Schlögl and Peter Jonas

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

Biophysical Journal, Volume 103, Issue 7, 1429-1439, 3 October 2012

[5] https://sourceforge.net/p/biosig/code/ci/master/tree/biosig4matlab/t300_FeatureExtraction/signal_deconvolution.m

[6] Xiaomin Zhang, Alois Schlögl, David Vandael, and Peter Jonas

MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo.

Journal of Neuroscience Methods, Volume 357, 1 June 2021, 109125.

[7] https://sourceforge.net/p/biosig/code/ci/master/tree/biosig4matlab/t340_MachineLearningOptimalDetection/

[8] https://sourceforge.net/p/biosig/code/ci/master/tree/biosig4matlab/t250_ArtifactPreProcessingQualityControl/spikes2bursts.m