SUMMARY Adaptive behaviors emerge from neuronal networks by dynamically regulating functional connectomes. Based on an underlying anatomical connectome, a functional connectome is the configuration of effective synaptic connections that underlies a pattern of neuronal activity during a specific behavior. Unique combinations of neurons activate specific functional connectomes, thereby generating a behavior (a combinatoric code). By combining neural network and biomechanical modeling, intracellular recording, and newly developed large-scale recording techniques, we will analyze functional connectomes and their combinatoric control of behavior, and how local plasticity and global dynamics mediate feeding behavior, which is controlled by a small brain system. The research will be performed by a multidisciplinary team consisting of Drs. J. Byrne (U. Texas, Houston), C. Chestek (U. Michigan, Ann Arbor), H. Chiel (CWRU), E. Cropper (Mt. Sinai), A. Susswein (Bar Ilan U.), P. Thomas (CWRU) and K. Weiss (Mt. Sinai). The project will: 1) develop a predictive neuromechanical model that incorporates a biomechanical model of the feeding musculature with a computational model of the feeding neural circuitry; 2) use large-scale and intracellular recording techniques to analyze the functional connectome and combinatoric control for choices among different feeding behaviors in response to sensory stimuli; and 3) use these recording techniques to analyze the ways in which the functional connectome and its combinatoric control are reconfigured by modulatory factors, motivation, and learning. We also will examine the ways in which arousal and satiation change the bias of the functional connectome and thus alter behavior, and the ways in which learning may add or remove elements of the functional connectome as an animal modifies behavior to respond to changes in the environment. The results will provide insights into how processes at multiple levels of neural organization contribute to regulation of behavior. Such studies in a small brain model system will provide insights that will help guide future investigations in more complex systems, such as vertebrates and humans.

Project Narrative This research will provide insights into how processes at multiple levels of neural organization contribute to regulation of behavior. Using novel technology that may have broad applications to other nervous systems, we will examine how a combinatoric code of key interneurons generates a range of motor behaviors in response to changing challenges; how arousal and satiation are implemented throughout a complex nervous system, and how a distributed learning system modifies behavior to respond to changes in the environment.