Motor Outputs in a Multitasking Network: Relative Contributions of Inputs and Experience-Dependent Network States

• Published in: Journal of neurophysiology 2009-12, Vol.102 (6), p.3711-3727
• Main Authors: Friedman, Allyson K, Zhurov, Yuriy, Ludwar, Bjoern Ch, Weiss, Klaudiusz R
• Format: Article
• Language: English
• Subjects: Action Potentials - physiology; Analysis of Variance; Animals; Aplysia - physiology; Electric Stimulation - methods; Feeding Behavior - classification; Feeding Behavior - physiology; Ganglia, Invertebrate - cytology; In Vitro Techniques; Motor Neurons - physiology; Movement - physiology; Nerve Net - physiology; Neural Pathways - physiology; Time Factors
• ISSN: 0022-3077; 1522-1598
• DOI: 10.1152/jn.00844.2009

Department of Neuroscience, Mount Sinai School of Medicine, New York, New York Submitted 15 September 2009; accepted in final form 17 October 2009 ABSTRACT Network outputs elicited by a specific stimulus may differ radically depending on the momentary network state. One class of networks states—experience-dependent states—is known to operate in numerous networks, yet the fundamental question concerning the relative role that inputs and states play in determining the network outputs remains to be investigated in a behaviorally relevant manner. Because previous work indicated that in the isolated nervous system the motor outputs of the Aplysia feeding network are affected by experience-dependent states, we sought to establish the behavioral relevance of these outputs. We analyzed the phasing of firing of radula opening motoneurons (B44 and B48) relative to other previously characterized motoneurons. We found that the overall pattern of motoneuronal firing corresponds to the phasing of movements during feeding behavior, thus indicating a behavioral relevance of network outputs. Previous studies suggested that network inputs act to trigger a response rather than to shape its characteristics, with the latter function being fulfilled by network states. We show this is an oversimplification. In a rested state, different inputs elicited distinct responses, indicating that inputs not only trigger but also shape the responses. However, depending on the combination of inputs and states, responses were either dramatically altered by the network state or were indistinguishable from those observed in the rested state. We suggest that the relative contributions of inputs and states are dynamically regulated and, rather than being fixed, depend on the specifics of states and inputs. Address for reprint requests and other correspondence: K. R. Weiss, Department of Neuroscience, Box 1065, Mount Sinai School of Medicine, New York, NY 10029 (E-mail: klaudiusz.weiss{at}mssm.edu ).