Neurotransmission of Pain Dr. Wilcox and colleagues are engaged in research into the spinal neurotransmission of pain and mechanisms underlying hyperalgesia, analgesia and analgesic tolerance. Studies of both excitatory and inhibitory neurotransmission in the rodent spinal cord apply behavioral, electrophysiological (both in vivo and in vitro),immunocytochemical and molecular techniques. Behavioral experiments define biologically relevant interactions, which are then examined at the cellular and molecular level using the more reductionist approaches. A key feature of research projects in this laboratory is open collaboration with laboratories located both here and at other universities. One major thrust of these investigations examines neurotransmitters thought to mediate major components of excitatory neurotransmission from primary afferent sensory fibers to secondary projection neurons in spinal cord dorsal horn: the excitatory amino acids (EAAs) like glutamate and the neurokinins like substance P. Intense or prolonged excitatory transmission via both these pathways is thought to evoke long term synaptic plasticity and excitotoxicity, which may underlie the development of some chronic pain states. A second major focus of work in the laboratory is the characterization of several inhibitory neurotransmitters and their receptors which together modulate this excitation. The neurotransmitters, enkephalin, serotonin and noradrenaline, inhibit various components of the incoming excitatory pain message in the dorsal horn via a number of inhibitory receptor subtypes. We are characterizing the interactions between these receptor subtypes and localizing them using transgenic mice, antisense oligonucleotides and immunocytochemical techniques. Finally, Dr. Wilcox facilitates access for Neuroscience students to high performance computing laboratories on campus - The Laboratory for Computational Science & Engineering and The Minnesota Supercomputer Institute (MSI). High performance computers and visualization are now finding applications in biological imaging, macromolecular modeling and neuronal simulation. A recent neuroscience graduate student developed a new method to optimize correspondence between neuronal simulations and experimental structure-function data.