This project shows the ionic channel parameter identification algorithm I settled during my computational neuroscientist period. It presents the first part of a study published in Michel CB et al., Eur J Neurosci. 2015 Nov;42(10):2867-77. doi: 10.1111/ejn.13021. Epub 2015 Aug 6. Identification and modelling of fast and slow Ih current components in vestibular ganglion neurons.
Experimental data indicate non-inactivated ionic currents (from nervous system), sometime consist of two components which are impossible to pharmacologically isolate. Also, an algorithm from engineering field has been shown to be efficient in parameters identification of sodium ionic currents.
So, using simulated data I have shown that this algorithm is also able to identify the parameters of two populations of non-inactivated ionic channels more accurately than a classical method. Moreover, a sensitivity analysis demonstrates the algorithm is insensitive to the key identification context variations.