Literature DB >> 226213

Neocortical pyramidal cells: a model with dendritic calcium conductance reproduces repetitive firing and epileptic behavior.

R D Traub.   

Abstract

A computer model of a neocortical pyramidal cell has been constructed using ideas similar to those used for hippocampal pyramidal cells. This model has been applied to the study of (a) repetitive firing, and (b) the paroxysmal depolarizing shift (PDS), an important intracellular event during seizures. Although calcium spikes have not been demonstrated directly in neocortical cells, we have postulated (by analogy with hippocampal pyramidal cells) a dendritic calcium conductance and a 'slow potassium' conductance modulated by intracellular calcium ion. With these dendritic ionic conductances, the model is able to reproduce the following experimental features of neocortical pyramidal cells: the afterdepolarization and succeeding afterhyperpolarization after an antidromic spike, and the f-I (firing rate-injected current) curve. Some of the differences between 'fast' and 'slow' pyramidal tract neurons (PTNs) -- narrower spikes and a steeper f-I curve in the fast PTNs -- may be explained by differences in Hodgkin-Huxley potassium kinetics between the two kinds of cell. The same model which faithfully reproduces repetitive firing behavior also reproduces (given appropriate synaptic inputs) the following intracellular events recording during epileptic seizures: (a) a burst of action potentials superimposed on and followed by a PDS, and (b) rapid repetitive firing succeeded by an IPSP. Thus, a single set of parameters can reporduce both normal physiological behavior and 'epileptic' behavior: the particular behavior seen depending on how the cell is stimulated. This overall result is the same as for our model of the CA1 hippocampal cell. It suggests that certain acutely acting epileptogenic agents, e.g. penicillin, may act by increasing synaptic input (perhaps both excitatory and inhibitory) to pyramidal cells, rather than by altering their membrane properties. As in our CA1 hippocampal cell model, bursting seems to be a phenomenon generated by the apical dendrite.

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Year:  1979        PMID: 226213     DOI: 10.1016/0006-8993(79)90625-5

Source DB:  PubMed          Journal:  Brain Res        ISSN: 0006-8993            Impact factor:   3.252


  7 in total

1.  Thalamic reticular cells firing modes and its dependency on the frequency and amplitude ranges of the current stimulus.

Authors:  Oscar Hernandez; Lilibeth Hernandez; David Vera; Alcides Santander; Eduardo Zurek
Journal:  Med Biol Eng Comput       Date:  2014-10-19       Impact factor: 2.602

2.  Computer modeling of epilepsy: opportunities for drug discovery.

Authors:  William W Lytton
Journal:  Drug Discov Today Dis Models       Date:  2017-06-03

Review 3.  Computational models of epileptic activity: a bridge between observation and pathophysiological interpretation.

Authors:  Fabrice Wendling
Journal:  Expert Rev Neurother       Date:  2008-06       Impact factor: 4.618

4.  A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction.

Authors:  Farzaneh Shayegh; Rasoul Amir Fattahi; Saeid Sadri; Karim Ansari-Asl
Journal:  J Med Signals Sens       Date:  2011-01

5.  Analysis of the behavior of a seizure neural mass model using describing functions.

Authors:  Farzaneh Shayegh; Jean-Jacques Bellanger; Saied Sadri; Rasoul Amirfattahi; Karim Ansari-Asl; Lotfi Senhadji
Journal:  J Med Signals Sens       Date:  2013-01

6.  Large-scale modeling - a tool for conquering the complexity of the brain.

Authors:  Mikael Djurfeldt; Orjan Ekeberg; Anders Lansner
Journal:  Front Neuroinform       Date:  2008-04-02       Impact factor: 4.081

Review 7.  Why are computational neuroscience and systems biology so separate?

Authors:  Erik De Schutter
Journal:  PLoS Comput Biol       Date:  2008-05-30       Impact factor: 4.475

  7 in total

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