Diversity of firing patterns in a two-compartment model neuron: using internal time delay as an independent variable

Title:

Diversity of firing patterns in a two-compartment model neuron: using internal time delay as an independent variable

Creator:

Wang , Lei, Liu, Shenquan, and Zeng , Yanjun

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:ae7d68a8-463a-49ac-bd61-805e074c1281
uuid:ae7d68a8-463a-49ac-bd61-805e074c1281
doi:10.14311/NNW.2013.23.015

Subject:

Compartment neuron model, internal time delay, firing patterns, and Isi diagram

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

Firing properties of single neurons in the nervous system have been recognized to be determined by their intrinsic ion channel dynamics and extrinsic synaptic inputs. Previous studies have suggested that dendritic structures exhibit significant roles in the modulation of somatic firing behavior in neurons. Following these studies, we show that finite information transmission delay between dendrite and soma can also influence the somatic firings in neurons. Our investigation is based on a two-compartment model which can approximately reproduce the firing activity of cortical pyramidal neurons. The obtained simulation results indicate that under subthreshold stimulus, spontaneous fast spiking activity is induced by large values of time delay, while for suprathreshold stimulus, regular bursting, chaotic firing and fast spiking can be observed under different time delays. More importantly, the transition mode between these diverse firing patterns with the variation of delay shows a period-doubling phenomenon under certain stimulus intensity. Consequently, our model results can not only illustrate the influential roles of internal time delay in the generation of a diversity of neuronal firing patterns, but also provide us with frameworks for investigating the impacts of internal time delay on the firing properties of many other neurons in the nervous system.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2013 Volume:23 | Number:3

Harvested from:

CDK

Metadata only:

false