000139126 001__ 139126
000139126 005__ 20180913055328.0
000139126 037__ $$aSTUDENT
000139126 245__ $$aSimple Neuron Models and Adaptation
000139126 260__ $$c2008
000139126 269__ $$a2008
000139126 336__ $$aStudent Projects
000139126 500__ $$aLaboratory of Computational Neuroscience, BMI/SV, EPFL, Lausanne
000139126 520__ $$aPredicting activity of single neuron is an important part of the computational neuroscience and a great challenge. Several mathematical models exist, from the simple (one compartment and few parameters, like the SRM or the IF-type models), to the more complex (biophysical model like the Hodgkin-Huxley model). All these models have their own advantages and limitations, but no one is able to reproduce the exact behavior of real neurons. Multiple projects try to simulate complex neural networks, or even the whole brain (i.e. the blue brain project or other big network simulation). To achieve this goal it is very important that simple neuron models simulate, for a low computational cost, the precise activities of all neuron classes. It is well-known that neurons exhibit a lot of different activity patterns (from an electro-physiological point of view). Here we have focused on pyramidal neurons from the layer 5 of the neocortex. They are classified as regular spiking-cells. This cell type shows adaptation and like other neurons, refractoriness. Adaptation and refractoriness are very common neuronal activity in the brain, and so it is important to have a simple model which can reproduce this kind of activity. This project deals with two classical simple neuron models: the adaptive exponential integrate-and-fire model (AdEx) and the spike response model (SRM). We deter- mined the parameters of these two models using data generated with a detailed model, the Destexhe's model which is a HH-like model for cortical pyramidal cells, stimulated with different current injection scenarios. In a second time the model parameters have been set using data from in-vitro recordings of 4 layer 5 pyramidal rat neurons, stimulated with a sinusoid in vivo-like protocol, injected somatically in current-clamp configuration. Then we show that this type of model can capture adaptation and can reproduce the activity of neuron with a high reliability
000139126 6531_ $$aSciences et technologies du vivant
000139126 6531_ $$aLife sciences and technology
000139126 6531_ $$aNervous system
000139126 6531_ $$aDestexhe’s model
000139126 6531_ $$aSpike Response Model (SRM)
000139126 6531_ $$aIntegrate-and-fire model (IF)
000139126 6531_ $$aFSV/SSV
000139126 700__ $$aMensi, Skander
000139126 720_2 $$aGerstner, Wulfram$$edir.
000139126 720_2 $$aNaud, Richard$$edir.
000139126 909C0 $$0252289$$pSSV
000139126 909CO $$ooai:infoscience.tind.io:139126$$pSV
000139126 937__ $$aSSV-STUDENT-2009-018
000139126 973__ $$aEPFL$$sPUBLISHED
000139126 980__ $$aSTUDENT