Encoding information that coordinates distributed neural microcircuits

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A major goal of neuroscience is to understand the dynamics of neural circuits. In most cases, ignorance of intrinsic neural properties and the synaptic organization of circuits limit our ability to understand a circuit's function or to cure disorders of the nervous system caused by its malfunction. Modulation by transmitters and hormones can change the properties of neurons and synapses in these circuits dramatically, but leave some features of the circuit's performance strangely unmodified. This project exploits new discoveries of the synaptic organization of a circuit in the crayfish central nervous system (CNS) that coordinates limb movements during locomotion. This coordinating circuit links four pairs of modular local circuits distributed in different parts of the CNS that control individual limbs and are active during locomotion. Periodic motor output from these local circuits is synchronized, but occurs with a stable difference in phase between neighboring circuits. The goal of this research is to understand and explain in cellular terms the encoding of information needed to coordinate these distributed circuits. Electrophysiological experiments and computational analyses will be used to study and model encoding of information by the circuit's key coordinating neurons. How stable phase differences are maintained in the face of neuromodulation is a deep problem. For example, cholinergic modulation of this system changes the period and strength of its motor output, but does not affect the phase differences between neighboring circuits. Electrophysiological and pharmacological experiments will be used to analyze how cholinergic modulation tunes encoding so that phase remains constant when period changes. This research will generate insights and analytical methods that can be applied to similar systems in the brain stem and spinal cord, and to rhythmic neural circuits in the brain. Student participants will be involved in all aspects of the project. The results will also be directly applicable to the development of flexible and adaptive robotic devices.