2009/03/09 by K.M. Hynna, K.A. Boahen, Kwabena Boahen · 1 citation
Engineering · Mathematics · Neuroscience · Physics and Astronomy · #Artificial intelligence #Biological system #Biology #Channel (broadcasting) #Computer science #Control theory (sociology) #Electrical engineering #Engineering #Mathematics #Neural dynamics and brain function #Neuroscience and Neural Engineering #Nonlinear system #Physics #Randomness #Relay #Telecommunications #Topology (electrical circuits) #White noise #stochastic dynamics and bifurcation
paper · doi:10.1109/tbme.2009.2015579
openalex publication_date 2009/03/09 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/27
Thalamic relay cells express distinctive response modes based on the state of a low-threshold calcium channel (T-channel). When the channel is fully active (burst mode), the cell responds to inputs with a high-frequency burst of spikes; with the channel inactive ( tonic mode), the cell responds at a rate proportional to the input. Due to the T-channel's dynamics, we expect the cell's response to become more nonlinear as the channel becomes more active. To test this hypothesis, we study the response of an in silico relay cell to Poisson spike trains. We first validate our model cell by comparing its responses with in vitro responses. To characterize the model cell's nonlinearity, we calculate Poisson kernels, an approach akin to white noise analysis but using the randomness of Poisson input spikes instead of Gaussian white noise. We find that a relay cell with active T-channels requires at least a third-order system to achieve a characterization as good as a second-order system for a relay cell without T-channels.