The overall objective of this research is to use computational models to analyze molecular, cellular and network processes underlying behavior and behavioral plasticity. Models will be based on empirical data from the neural circuitry that mediates feeding behavior of the marine mollusk Aplysia. This behavior is a useful model system for investigating the generation of complex rhythmic movements as well as the neural basis of motivational states and associative learning. Although many elements of the feeding circuitry have been identified an analysis of the mechanisms underlying is overall function has not yet been undertaken. The present proposal outlines studies that will investigate the extent to which the current understanding of the circuitry is sufficient to account for the features of the behavior, examine the contributions of component processes to neuronal and network dynamics, and examine how modulatory inputs and learning-induced changes in cellular properties alter the function of the circuit. In addition, this project will continue the development and distribution of the SNNAP program (Simulator for Neural networks and Action Potentials,) thereby providing a valuable research and educational tool to the scientific and academic community.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Research Project (R01)
Project #
5R01RR011626-06
Application #
6394653
Study Section
Special Emphasis Panel (ZRG1-IFCN-7 (01))
Program Officer
Chang, Michael
Project Start
1995-08-17
Project End
2004-05-31
Budget Start
2001-04-01
Budget End
2004-05-31
Support Year
6
Fiscal Year
2001
Total Cost
$324,180
Indirect Cost
Name
University of Texas Health Science Center Houston
Department
Neurosciences
Type
Schools of Medicine
DUNS #
City
Houston
State
TX
Country
United States
Zip Code
77225
Baxter, Douglas A; Byrne, John H (2007) Short-Term Plasticity in a Computational Model of the Tail-Withdrawal Circuit in Aplysia. Neurocomputing 70:1993-1999
Baxter, Douglas A; Byrne, John H (2007) Simulator for neural networks and action potentials. Methods Mol Biol 401:127-54
Cataldo, Enrico; Brunelli, Marcello; Byrne, John H et al. (2005) Computational model of touch sensory cells (T Cells) of the leech: role of the afterhyperpolarization (AHP) in activity-dependent conduction failure. J Comput Neurosci 18:5-24
Wustenberg, Daniel G; Boytcheva, Milena; Grunewald, Bernd et al. (2004) Current- and voltage-clamp recordings and computer simulations of Kenyon cells in the honeybee. J Neurophysiol 92:2589-603
Luo, Chuan; Clark Jr, John W; Canavier, Carmen C et al. (2004) Multimodal behavior in a four neuron ring circuit: mode switching. IEEE Trans Biomed Eng 51:205-18
Phares, Gregg A; Antzoulatos, Evangelos G; Baxter, Douglas A et al. (2003) Burst-induced synaptic depression and its modulation contribute to information transfer at Aplysia sensorimotor synapses: empirical and computational analyses. J Neurosci 23:8392-401
Susswein, Abraham J; Hurwitz, Itay; Thorne, Richard et al. (2002) Mechanisms underlying fictive feeding in aplysia: coupling between a large neuron with plateau potentials activity and a spiking neuron. J Neurophysiol 87:2307-23
Smolen, P; Baxter, D A; Byrne, J H (2001) Modeling circadian oscillations with interlocking positive and negative feedback loops. J Neurosci 21:6644-56
Smolen, P; Baxter, D A; Byrne, J H (2000) Modeling transcriptional control in gene networks--methods, recent results, and future directions. Bull Math Biol 62:247-92
Smolen, P; Baxter, D A; Byrne, J H (2000) Mathematical modeling of gene networks. Neuron 26:567-80

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