pubmed-article:1714549 | rdf:type | pubmed:Citation | lld:pubmed |
pubmed-article:1714549 | lifeskim:mentions | umls-concept:C0019564 | lld:lifeskim |
pubmed-article:1714549 | lifeskim:mentions | umls-concept:C0596630 | lld:lifeskim |
pubmed-article:1714549 | lifeskim:mentions | umls-concept:C0524865 | lld:lifeskim |
pubmed-article:1714549 | lifeskim:mentions | umls-concept:C0009609 | lld:lifeskim |
pubmed-article:1714549 | lifeskim:mentions | umls-concept:C0678837 | lld:lifeskim |
pubmed-article:1714549 | pubmed:issue | 2-3 | lld:pubmed |
pubmed-article:1714549 | pubmed:dateCreated | 1991-9-13 | lld:pubmed |
pubmed-article:1714549 | pubmed:abstractText | A model of the hippocampal granule cells was created that closely approximated most of the measured intracellular responses from a neuron under a variety of stimulus conditions. This model suggests that: (1) A simple, four-conductance model can account for most of the intracellular behavior of these neurons. (2) The repolarization mechanism in granule cells may be different from that in squid axons. A weak potassium conductance may be present in hippocampal granule neurons, which simultaneously give rise to a small, passive depolarizing afterpotential. (3) The strength duration properties may assist in identifying the electronic and sodium channel properties with short stimulus pulse widths. (4) Repetitive firing responses are highly dependent on the cell's recent history of activation and the regulation of the slow potassium conductance and calcium dynamics. (5) The anodic break response is probably not a property of typical granule cells. Through thorough and precise comparison of experimental and model responses, computer simulations can help assembling channel information into verifiable models that accurately reproduce intracellular data. | lld:pubmed |
pubmed-article:1714549 | pubmed:grant | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:1714549 | pubmed:language | eng | lld:pubmed |
pubmed-article:1714549 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:1714549 | pubmed:citationSubset | IM | lld:pubmed |
pubmed-article:1714549 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
pubmed-article:1714549 | pubmed:status | MEDLINE | lld:pubmed |
pubmed-article:1714549 | pubmed:issn | 0306-4522 | lld:pubmed |
pubmed-article:1714549 | pubmed:author | pubmed-author:DurandDD | lld:pubmed |
pubmed-article:1714549 | pubmed:author | pubmed-author:YuenG LGL | lld:pubmed |
pubmed-article:1714549 | pubmed:issnType | Print | lld:pubmed |
pubmed-article:1714549 | pubmed:volume | 41 | lld:pubmed |
pubmed-article:1714549 | pubmed:owner | NLM | lld:pubmed |
pubmed-article:1714549 | pubmed:authorsComplete | Y | lld:pubmed |
pubmed-article:1714549 | pubmed:pagination | 411-23 | lld:pubmed |
pubmed-article:1714549 | pubmed:dateRevised | 2007-11-14 | lld:pubmed |
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pubmed-article:1714549 | pubmed:year | 1991 | lld:pubmed |
pubmed-article:1714549 | pubmed:articleTitle | Reconstruction of hippocampal granule cell electrophysiology by computer simulation. | lld:pubmed |
pubmed-article:1714549 | pubmed:affiliation | School of Medicine, Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106. | lld:pubmed |
pubmed-article:1714549 | pubmed:publicationType | Journal Article | lld:pubmed |
pubmed-article:1714549 | pubmed:publicationType | Research Support, U.S. Gov't, P.H.S. | lld:pubmed |
pubmed-article:1714549 | pubmed:publicationType | Research Support, U.S. Gov't, Non-P.H.S. | lld:pubmed |
pubmed-article:1714549 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
http://linkedlifedata.com/r... | pubmed:referesTo | pubmed-article:1714549 | lld:pubmed |