28
Vb
Wbll
WblF1
Wb21
Wb2F2
WbCl
∖WbCFc /
or, more concisely,
(vb + Kb dbll <⅛12
Φbll ≠frll
Φbl2 Ψbl2
∖ ΦbCFc
dbCFc ∖
ΨbCFc /
( Vb >
Wbii
WfeiFi
W>b21
Wb2F2
WbCl
∖WbCFc∕

∂tzb Qb^,b T ub-
(2.32)
We discretize the neuron in space by dividing each branch into 7ь = ceil(f⅛∕∕ι) com-
partments, where h is some desired step size. The connectivity of the full morphology
is encapsulated in the Hines matrix H, which is the spatial discretization of each T>b
coupled with (2.19) to (2.21) and (2.24) (Hines, 1984). More detail about constructing
this matrix will be given in §A.
Using the Hines matrix imposes an outside-in ordering of branches and compart-
ments, which leads to minimal fill-in for Gaussian Elimination (Hines, 1984). If m
and n denote, respectively, the number of gating variables per compartment and the
total number of compartments, i.e.,
с в
m = and n = 1 + 7ь>
c=l b=l
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