NONLINEAR DYNAMICS OF NEURONAL TEMPORAL PROCESSING

点击翻译按钮获取中文摘要

DESCRIPTION (Adapted from Applicant's abstract): It is believed that some neural computations involve cellular and circuit properties that enable encoding and decoding based on precise timing of action potentials. Sound localization in the auditory system offers a compelling example. It serves as the case study for this research that seeks a more qualitative characterization of cellular properties that correlate with precise temporal processing. Many cells in the auditory brain stem contribute to the system's ability to detect coincidence of interaural signals. These neurons have distinctive firing properties. When a steady stimulus is presented they fire only once, at stimulus onset, while neurons of many other types will continue to fire until the stimulus is turned off. This property of phasicness is believed crucial for precise temporal processing. In contrast, tonic cells are assumed to be less capable of tracking rapidly changing signals. The biophysical basis, a special potassium current, IK-LT appears to underlie phasicness in the brain stem neurons. This project will address in a systematic way how the temporal processing ability of a neuron changes as the neuron is transformed from phasic to tonic mode, say by gradually adjusting the strength of IK-LT When a cell is in phasic mode does it track a time-varying signal better, or does it perform better coincidence detection, than when it is in tonic mode? The research will combine both experimental and theoretical approaches. The experiments involve electrical recording from individual neurons in vitro while stimulating them with periodic and other time-varying signals, including random components. From the theoretical side, biophysically-based mathematical models will be developed that mimic the neurons, including a term for IK-LT Various measures will be applied to the computer and cellular models to assess reliability and precision of processing. In addition, concepts from nonlinear dynamical systems will be applied in order to reveal and understand the underlying mathematical structure This understanding will enable us to generalize about the significance of phasicness to other neural systems where the mechanism might not involve IK-LT A related subproject is to develop computational models that will help explain the dynamic effects seen experimentally as interaural phase (or amplitude or frequency) is varied dynamically. A deeper understanding of these surprising effects, as seen in the auditory mid-brain, should contribute to developing a theory for how motion of sound sources are analyzed in the brain.