Activity and Neuromodulatory Input Contribute to the Recovery of Rhythmic Output After Decentralization in a Central Pattern Generator

Abstract

Zhang Y, Khorkova O, Rodriguez R, Golowasch J. Activity and neuromodulatory input contribute to the recovery of rhythmic output after decentralization in a central pattern generator. J Neurophysiol 101: 372-386, 2009. First published July 2, 2008 doi:10.1152/jn.01290.2007. Central pattern generators (CPGs) are neuronal networks that control vitally important rhythmic behaviors including breathing, heartbeat, and digestion. Understanding how CPGs recover activity after their rhythmic activity is disrupted has important theoretical and practical implications. Previous experimental and modeling studies indicated that rhythm recovery after central neuromodulatory input loss (decentralization) could be based entirely on activity-dependent mechanisms, but recent evidence of long-term conductance regulation by neuromodulators suggest that neuromodulator-dependent mechanisms may also be involved. Here we examined the effects of altering activity and the neuromodulatory environment before decentralization of the pyloric CPG in Cancer borealis on the initial phase of rhythmic activity recovery after decentralization. We found that pretreatments altering the network activity through shifting the ionic balance or the membrane potential of pyloric pacemaker neurons reduced the delay of recovery initiation after decentralization, consistent with the recovery process being triggered already during the pretreatment period through an activity-dependent mechanism. However, we observed that pretreatment with neuromodulators GABA and proctolin, acting via metabotropic receptors, also affected the initial phase of the recovery of pyloric activity after decentralization. Their distinct effects appear to result from interactions of their metabotropic effects with their effects on neuronal activity. Thus we show that the initial phase of the recovery process can be accounted for by the existence of distinct activity-and neuromodulator-dependent pathways. We propose a computational model that includes activity-and neuromodulator-dependent mechanisms of the activity recovery process, which successfully explains the experimental observations and predicts the results of key biological experiments.

Modelling the restoration of activity in a biological neural network

“…Previous models of the restoration of the activity in the pyloric network assume that the internal calcium ion release mechanism of the neurons gets altered following decentralisation [7][8][9]. These models capture the change in the calcium ion release mechanism by assuming an activity or neuromodulator sensor and a calcium pump.…”

“…Another model assumes that the calcium and potassium conductances change in an activity-dependent manner [6]. The impact of neuromodulation is implemented in these models by considering a separate neuromodulation-dependent ionic current (I MI ), which gets set to zero following the decentralisation of the STG [6][7][8][9]. Following the modelling the de-centralisation, when the changes to the calcium release mechanism become sufficient the restored levels of calcium ion currents and intracellular Ca 2+ concentration trigger the restart of the activity of individual neurons and of the pyloric rhythm activity.…”

“…Note that our proctolin induced current is the equivalent of the neuromodulation induced current (I MI ) used in previous models [6][7][8][9].…”

“…The recovery of rhythmic activity in the STG pyloric network has been modelled using HH models of STG neurons [6][7][8][9]. These models use some form of alteration of the mechanism of the Calcium ion currents in order to achieve the restarting of the rhythmic activity in the computational model of the STG [6][7][8][9].…”

“…These models use some form of alteration of the mechanism of the Calcium ion currents in order to achieve the restarting of the rhythmic activity in the computational model of the STG [6][7][8][9].…”