The name is absent

38

2.5 Balanced Truncation Model Reduction Results

We have written a MATLAB suite of functions that loads morphology and channel
kinetics and distributions, constructs the associated quasi-active system and both its
BT and IRKA reductions, and computes and displays the response of the 4 (nonlinear,
quasi-active, ВТ, IRKA) models to random (in space and time) sequences of synaptic
input. These codes are available from the authors upon request. All computations
were performed on a Sun Ultra 20 computer with a 2.2 GHz AMD Opteron processor.

Morphologies, shown in Figure 2.6, were obtained from the Rice-Baylor archive
(Martinez) and from NeuroMorpho.org (http://NeuroMorpho.org) (Ascoli, 2006), and
then imported to our software suite, which lets the user visualize and simulate the neu-
ron via graphical user interfaces. Pyramidal and interneuron ion channel models were
obtained from the literature and from ModelDB (http://senselab.med.yale.edu/modeldb)
(Hines et al., 2004), as detailed in Tables B.l and B.2 of the Appendix. Unless oth-
erwise indicated, g_bs — O.

2.5.1 Dimension Reduction Ratio

Consider a forked neuron as shown in Figure 2.6A. Each of the three branches is
200 μm long and is divided into 2 μm-long segments. The root has radius 2 μm while
the leaves have radius 1 μm. Ion channels with Hodgkin-Huxley kinetics (see Table
B.l) were uniformly distributed. This leads to a quasi-active system of dimension
1204. We computed BT matrices and found that the Hankel singular values decay

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