Simulations of Extracellular Action Potential

<p>This simulations were done for my PhD thesis. The purpose was to show that different morphologies generate EAP spatial patterns that are stereotypical and can be considered as "fingerprints" which can be used to identify the different types of neurons when doing extracellular recordings with multi electrode arrays (In my experiments I used polytrodes: Poly3-25s from Neuronexus ).</p> <p>This fileset contains simulations of the extracellular signal induced by an action potential. The simulations are done on square grids located parallel to the plane containing the soma of the neuron (using LSA from [1])</p> <p>1-each file corresponds to a particular combination of morphology/electrophysiology.</p> <p>2-each movie contains:</p> <p> - the waveform of the action potential recorded in front of the soma, as recorded by an electrode.</p> <p> - the amplitude of the EAP on a plane, displayed as heatmap. This shows were the signal is stronger: in front of the soma and thick dendrites/axons.</p> <p> - EAP(t), at each time step, displayed also as a heatmap. This allows to see how the dominant sources of current change during the action potential.</p> <p> </p> <p>3- Description per File:</p> <p> - d153_0002_Z30: Simulation of Layer 2/3 pyramidal neuron from mouse cortex ([2], modified from [4]). The plane is 30 um away from the cell.</p> <p> - d154_0002_Z20: NPY interneuron layer not specified ([3], modified from [4]). The plane is 20 um away from the cell.</p> <p> -d151_0003_Z30: CA1 pyramidal neuron (from [1]). The plane is at 30 um from the cell.</p> <p> -d151_0006_Z38: CA1 pyramidal neuron (from [1]). Compare this to d151_0003_Z30 which is more electrotonically compact. On this case the amplitude of the EAP is of similar magnitude to the one recorded in front of the soma on branching points of the dendritic tree.</p> <p> </p> <p>[1] C. Koch, D. Henze, C. Gold, Using extracellular action potential recordings to constrain compartmental models, Journal of Computational Neu- roscience 23 (2007) 39–58.</p> <p>[2] A. Rocher, J. Crimins, M. Amatrudo, M. Kinson, M. Todd-Brown, J. Lewis, J. Luebke, Structural and functional changes in tau mutant mice neurons are not linked to the presence of nfts, Experimental Neu- rology 223 (2010) 385–393.</p> <p>[3] J. Goldberg, JTamas, D. Aronov, R. Yuste, Calcium microdomains in aspiny dendrites., Neuron 13 (2003) 807–821.</p> <p>[4] G. Ascoli, D. Donohue, M. Halavi, Neuromorpho.org: a central resource for neuronal morphologies, Journal of Neuroscience 27 (2007) 9247–51.</p> <p> [5] Localising and classifying neurons from high density MEA recordings. Journal of Neuroscience MEthods 233(2014), 115-128.</p> <p>http://www.sciencedirect.com/science/article/pii/S0165027014002052</p> <p>________________________________________</p> <p>Other relevant references:</p> <p>[5] A. Destexhe, C. Bedard, Do neurons generate monopolar current sources?, Journal of Neurophysiology 108 (2012) 953–955.</p> <p>[6] J. Riera, T. Ogawa, T. Goto, A. Sumiyoshi, H. Nonaka, A. Evans, H. Miyakawa, R. Kawashima, Pitfalls in the dipolar model for the neocortical eeg sources, Journal of Neurophysiology 108 (2012) 956–975.</p> <p>[7] Z. Somogyv'ari, L. Zal ́anyi, I. Ulbert, P. E ́rdi, Model-based source localization of extracellular action potentials, Journal of Neuroscience Methods 147 (2005) 126–137.