Gain control mechanisms mediate neuronal transfer functions, and dynamically adjust a neuron or neural system's output response range to match the range of its input signal. This continuous adjustment of neuronal gain maximizes coding efficiency. Individual neurons regulate their output gain primarily through multiplication of excitatory and inhibitory inputs, with further enhancement by voltage- gated channels. In many sensory nuclei in the CNS, neurons may be part of extensive local circuits, but although spontaneous activity in local circuits has been shown to modulate input-output functions through an effect on tonic excitability, the role of local circuitry in gain control during a changing controlled stimulus remains undefined. Here we propose to examine the role of local circuits in coding auditory stimuli in vivo in awake (unanesthetized) mice using high-divalent cations to block local circuits, thus allowing us to separate the effects of circuit properties from those of extrinsic inputs in coding information in the CNS. Neurons in the inferior colliculus, an auditory midbrain nucleus, are segregated into different excitatory and inhibitory local circuits. These non-linear circuits determine the dynamic range of sound intensity, with different rate-level functions arising in neurons that are parts of different local circuits. We will test the hypothesis that the activation of local circuits in the inferior colliculus is necessary for coding sound intensity, a feature of auditory coding that requires input recruitment, and exhibits symptoms of dynamic gain control, and that sound intensity coding is an emergent property of the IC. More importantly, the successful use of high-divalent cations to separate local circuit effects from extrinsic inputs in vivo will become a very valuable tool for the study of CNS function in systems other than the auditory system and will be a major advance in the study of pathological states in the CNS.
The coding of information in the central nervous system is a complex task that requires the synergistic interaction between the properties of individual nerve cells and the neural networks formed between large populations of nerve cells. It is thus necessary to develop a tool which can be used ubiquitously to separate these two features of neural coding, so that their individual influences on responses in the nervous system can be understood. In this manner, both the normal functioning of the nervous system as well as pathological disease states can be better understood. In this proposal we aim to develop these tools to examine the coding of sound information in the auditory system of mammals. This will help elucidate the mechanism of normal and pathological auditory processing.
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