Aa. Sharp et al., MECHANISMS OF OSCILLATION IN DYNAMIC CLAMP CONSTRUCTED 2-CELL HALF-CENTER CIRCUITS, Journal of neurophysiology, 76(2), 1996, pp. 867-883
1. The dynamic clamp was used to create reciprocally inhibitory two-ce
ll circuits from pairs of pharmacologically isolated gastric mill neur
ons of the stomatogastric ganglion of the crab, Cancer borealis. 2. We
used this system to study how systematic alterations in intrinsic and
synaptic parameters affected the network behavior. This has previousl
y only been possible in purely computational systems. 3. In the absenc
e of additional hyperpolarization-activated inward current (I-H), stab
le half-center oscillatory behavior was not observed. In the presence
of additional I-H, a variety of circuit dynamics, including stable hal
f-center oscillatory activity, was produced. 4. Stable half-center beh
avior requires that the synaptic threshold lie within the voltage enve
lope of the slow wave oscillation. 5. Changes in the synaptic threshol
d produce dramatic changes in half-center period. As predicted by prev
ious theoretical work, when the synaptic threshold is depolarized, the
period first increases and then decreases in a characteristic inverte
d U-shaped relationship. Analysis of the currents responsible for the
transition between the active and inhibited neurons shows that the mec
hanism of oscillation changes as the synaptic threshold is varied. 6.
Increasing the time constant and the conductance of the inhibitory syn
aptic current increased the period of the half-center oscillater. 7. I
ncreasing the conductance of I-H or changing the voltage dependence of
I-H can either increase or decrease network period, depending on the
initial mode of network oscillation. A depolarization of the activatio
n curve causes the network to respond in a similar fashion as increasi
ng the conductance of I-H. 8. Many neuromodulatory substances are know
n to alter synaptic strength and the conductance and voltage dependenc
e of I-H, parameters we studied with the dynamic clamp. To understand
the response of the network to modulation of a single parameter, it is
necessary to understand the nature of the altered conductance and how
it interacts with the other conductances in the system.