A hemicord locomotor network of excitatory interneurons: a simulation study.
Locomotor burst generation is simulated using a full-scale network model of the unilateral excitatory interneuronal population. Earlier small-scale models predicted that a population of excitatory neurons would be sufficient to produce burst activity, and this has recently been experimentally confirmed. Here we simulate the hemicord activity induced under various experimental conditions, including pharmacological activation by NMDA and AMPA as well as electrical stimulation. The model network comprises a realistic number of cells and synaptic connectivity patterns. Using similar distributions of cellular and synaptic parameters, as have been estimated experimentally, a large variation in dynamic characteristics like firing rates, burst, and cycle durations were seen in single cells. On the network level an overall rhythm was generated because the synaptic interactions cause partial synchronization within the population. This network rhythm not only emerged despite the distributed cellular parameters but relied on this variability, in particular, in reproducing variations of the activity during the cycle and showing recruitment in interneuronal populations. A slow rhythm (0.4-2 Hz) can be induced by tonic activation of NMDA-sensitive channels, which are voltage dependent and generate depolarizing plateaus. The rhythm emerges through a synchronization of bursts of the individual neurons. A fast rhythm (4-12 Hz), induced by AMPA, relies on spike synchronization within the population, and each burst is composed of single spikes produced by different neurons. The dynamic range of the fast rhythm is limited by the ability of the network to synchronize oscillations and depends on the strength of synaptic connections and the duration of the slow after hyperpolarization. The model network also produces prolonged bouts of rhythmic activity in response to brief electrical activations, as seen experimentally. The mutual excitation can sustain long-lasting activity for a realistic set of synaptic parameters. The bout duration depends on the strength of excitatory synaptic connections, the level of persistent depolarization, and the influx of Ca(2+) ions and activation of Ca(2+)-dependent K(+) current.
Kozlov
A K
AK
Computational Biology and Neurocomputing, School of Computer Science and Communication, Royal Institute of Technology, Stockholm 100 44, Sweden. akozlov@csc.kth.se
Lansner
A
A
Grillner
S
S
Kotaleski
J Hellgren
JH
D000200:Action Potentials / Q000187:drug effects / Q000502:physiology / Q000528:radiation effects; D000818:Animals; D003198:Computer Simulation; D004558:Electric Stimulation / Q000379:methods; D018690:Excitatory Amino Acid Agonists / Q000494:pharmacology; D007839:Functional Laterality / Q000502:physiology*; D066298:In Vitro Techniques; D007395:Interneurons / Q000187:drug effects / Q000502:physiology* / Q000528:radiation effects; D007473:Ion Channels / Q000502:physiology; D007798:Lampreys; D008124:Locomotion / Q000187:drug effects / Q000502:physiology* / Q000528:radiation effects; D008959:Models, Neurological; D009415:Nerve Net / Q000187:drug effects / Q000502:physiology* / Q000528:radiation effects; D016571:Neural Networks, Computer; D013116:Spinal Cord / Q000166:cytology
D018690:Excitatory Amino Acid Agonists; D007473:Ion Channels