Passive models of neurons in the deep cerebellar nuclei: the effect of reconstruction errors

<span title="">2004</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="" style="color: black;">Neurocomputing</a> </i> &nbsp;
The goal of this study was to determine how the ÿt of passive parameters in a compartmental model varies depending on the precise morphological reconstruction of the neuron. We performed whole-cell recordings of deep cerebellar nucleus neurons in brain slices, reconstructed the neuronal morphologies and converted them into detailed compartmental models. A genetic algorithm was used to ÿnd the best ÿt of speciÿc capacitance CM, membrane resistance RM and axial resistivity RA of the model with
more &raquo; ... ordings from the same cell. We then introduced morphological alterations that represented the likely consequence of shrinkage artefacts and reconstruction errors. We found that the optimal ÿts of passive parameters change as much as 173% with such morphological alterations. In addition, dendrites cut during slicing could a ect the value of RM, but not CM or RA.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="">doi:10.1016/s0925-2312(04)00100-6</a> <a target="_blank" rel="external noopener" href="">fatcat:dwl7rdej7bbvrchnkajrg5dd6y</a> </span>
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