Bursting as an effective relay mode in a minimal thalamic model.
In recent years, accumulating evidence indicates that thalamic bursts are present during wakefulness and participate in information transmission as an effective relay mode with distinctive properties from the tonic activity. Thalamic bursts originate from activation of the low threshold calcium cannels via a local feedback inhibition, exerted by the thalamic reticular neurons upon the relay neurons. This article, examines if this simple mechanism is sufficient to explain the distinctive properties of thalamic bursting as an effective relay mode. A minimal model of thalamic circuit composed of a retinal spike train, a relay neuron and a reticular neuron is simulated to generate the tonic and burst firing modes. The integrate-and-fire-or-burst model is used to simulate the neurons. After discriminating the burst events with criteria based on inter-spike-intervals, statistical indices show that the bursts of the minimal model are stereotypic events. The relation between the rate of bursts and the parameters of the input spike train demonstrates marked nonlinearities. Burst response is shown to be selective to spike-silence-spike sequences in the input spike train. Moreover, burst events represent the input more reliably than the tonic spike in a considerable range of the parameters of the model. In conclusion, many of the distinctive properties of thalamic bursts such as stereotypy, nonlinear dependence on the sensory stimulus, feature selectivity and reliability are reproducible in the minimal model. Furthermore, the minimal model predicts that while the bursts are more frequent in the spike train of the off-center X relay neurons (corresponding to off-center X retinal ganglion cells), they are more reliable when generated by the on-center ones (corresponding to on-center X ganglion cells).
Babadi
Baktash
B
School of Cognitive Sciences (SCS), Institute for Studies in Theoretical Physics and Mathematics (IPM), Niavaran Square, Tehran, PO Box 19395-5746, Iran. baktash@ipm.ir
D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D003198:Computer Simulation; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D011336:Probability; D011963:Receptors, GABA-A / Q000378:metabolism; D012160:Retina / Q000502:physiology; D013569:Synapses / Q000502:physiology; D013788:Thalamus / Q000033:anatomy & histology / Q000502:physiology*; D013997:Time Factors; D014795:Visual Pathways / Q000502:physiology*; D014851:Wakefulness / Q000502:physiology
D011963:Receptors, GABA-A