Investigating the Effect of Behavior Modulation in Purkinje Cells Spike Train on the Spectrum of Deep Cerebellar Nuclei Output

Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Neural function depends on the received synapses and the intrinsic properties of the neuron. However, synaptic integration and intrinsic responses can largely depend on the synaptic inputs. In this respect, deep cerebellar nuclei (DCN) neurons which receive inhibitory synapses from Purkinje cells (PCs) are of interest. Transmission of behavior from PC to DCN in awake animal and how this information is coded by the deep cerebellar nuclei remain unknown. To investigate this issue, simultaneous recordings from about 50 Purkinje cells converged to each DCN is required, which is impossible in experiments. Therefore, it is required to use modeling techniques. In this study, to explore the effect of Purkinje cells inputs on the power spectral of DCN output, the transmission of behavioral information from the Purkinje cell to the DCN, and behavior coding by the DCN, artificial spike trains (ASTs) of the Purkinje cell were generated, and behavioral modulation (respiration) was added to them, then, ASTs were applied to the DCN model. Power spectral density analysis of the DCN firing in response to the synaptic inputs from Purkinje cells was made and the frequency bands of the DCN output were analyzed. Results showed that the behavioral modulation frequency is reflected in the DCN spectrum and a peak is visible at low-frequencies at the power spectral of the DCN output in response to the behavioral modulation received from Purkinje cells. On the other hand, the previous study has shown that DCN performs frequency coding in response to the behavioral modulation received from Purkinje cells. Results of the present study coud confirm the frequency coding by the DCN. In addition, a high-frequency peak was observed, which coud be due to the tonic firing of the DCN.
Language:
Persian
Published:
Iranian Journal of Biomedical Engineering, Volume:11 Issue: 2, 2017
Pages:
127 to 135
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