Neural Encoding of Dynamic Inputs by Spike Timing

Oscillations are virtually ubiquitous in neural signals and play a wide variety of roles in information coding, signal transmission, coordination of neuronal ensembles, and pathophysiology, including epilepsy. This chapter begins with some general principles about how neurons respond to oscillating input, proceed to selected results from model neurons, and end with some experimental data from neurons in the cerebral cortex and the auditory brainstem. While the chapter focuses on the analysis of

9.1 Basic Principles ............................................................................................226 9.1.1 Subthreshold Voltage Responses ......................................................226 9.1.2 Action Potential Responses ..............................................................228 9.1.3 Phase-Locking ..................................................................................228 9.1.4 Linearization of the AP Response by Noise .....................................228 9.1.5 Gain and Phase Shift of the AP Response ....................................... 229 9.1.6 Gain Estimation Using Noise Stimulation and Correlation

Analysis ............................................................................................230 9.2 Results in Models.......................................................................................... 231

9.2.1 Effects of a Spike Threshold and Voltage Reset: Leaky Integrate-and-Fire Model.................................................................. 231

9.2.2 AP Generation and Sensitivity to High-Frequency Input ................. 232 9.2.3 Models with Subthreshold Resonance ..............................................234