Daniel K. Hartline
Researcher and Director, Bekesy Lab
Neurophysiology: Copepod Neurocology, Computational Properties of Network Neurons, Computational Studies of Space Clamp Errors in Point-Clamp Experiments
Three areas of research are currently active in my lab: copepod neuroecology, computational properties of network neurons, and computational studies of space clamp errors in point-clamp experiments.
In this project on the neuroethology and neuroecology of zooplankton, we are examining the relation between physiological and morphological properties of a zooplankter's sensory systems (specifically mechano- and chemoreception in copepods) and the animal's behavior and ecology. The sensory systems reflect unusual adaptations to pelagic life when compared to similar systems in benthic and nektonic forms. We have been finding that the antennules in certain copepod groups have two pairs of giant mechanoreceptor neurons, which are exceptionally sensitive to water-borne disturbances. They have peak sensitivities to vibrations at frequencies well above those of other aquatic invertebrates. Behavioral studies are showing that sensitivities for triggering rapid escape "jumps" parallel those for receptor activation. The evidence suggests that one of the keys to the success of copepods as a group (they are more numerous than insects) is a very rapid mechanically-triggered activation of a swim motor pattern generator tuned to signals produced by predatory attack. We have found that different copepod groups show markedly different reaction times to stimuli mimicking predatory attack. The animals with the more rapid reactions belong to more recently-evolved groups and inhabit a wider range of ecological habitats than do slower animals. In electron microscopic studies, we have discovered that the faster animals have evolved a myelin sheathing that surrounds most of the large axons in their nervous systems. As in vertebrates, we believe that this insulating sheath is responsible for speeding up communication in the copepod nervous system and can explain much of the improvement in reaction times of the more advanced species. We are now testing this hypothesis by examining a range of species from different phyletic groups, extending our analysis of both physiological and behavioral properties of myelinated and non-myelinated copepods and their relations to ecological factors.
Computational approaches are becoming increasingly useful for attacking problems in neuroscience, including problems dealing with the computational properties of the nervous system itself. My lab is currently applying computational approaches to the study of local computation in "dendritic" trees of reidentifiable neurons. Motor neurons in the stomatogastric ganglion (a model motor pattern generator found in decapod crustaceans) are dye-injected, imaged with a confocal microscope and reconstructed in 3D with computer software. Quantitative measurements on the reconstructed dendritic trees are placed in a computer model simulating the spread of signals, active and passive, throughout the tree and along axons. Assessment is made of the effects of inputs placed at various points in the tree on the expected outputs from other regions of the tree. The model predicts that outputs from some regions differ qualitatively and quantitatively from those of others. This has led to the hypothesis that the tree is spatially differentiated in computational properties. We are working to 1) refine physiological measurements made in the cells to improve the reliability of the simulations; 2) investigate the postsynaptic targets for different tree regions to determine the potential ramifications for the neural network of regional computational heterogeneity; 3) extend the modeling studies to other cell types within the ganglion.
"Point clamping" with microelectrodes has become a standard method for identifying and characterizing the various ion channels which are responsible for the computational properties of nerve cells. Unfortunately, the technique is only accurate in spherical cells, which few neurons are. Using computer-simulation approaches, we are studying the properties of the errors that occur when nerve cells are not spherical. The goal of the work is to provide correction factors that can be applied to the flawed measurements made with current technology to determine true values for physiological parameters of ion channels. Specifically, we are working to first establish correction factors for a set of different conditions in nerve cells of simple form having a single active ion channel. We will then extend the work to encompass more complex cells with ramifying dendritic arbors and multiple active channels.
Buskey, E.J. and Hartline, D.K. 2003. High speed video analysis of the escape responses of the copepod Acartia tonsa to shadows. Biol. Bull. 204: 28-37
Buskey, E.J., Lenz, P.H. and Hartline, D.K. 2002. Escape behavior of planktonic copepods to hydrodynamic disturbances: High speed video analysis. Mar. Ecol. Progr. Ser. 235: 135-146
Lenz PH, Hartline DK. 1999. Reaction times and force production during escape behavior of a calanoid copepod, Undinula vulgaris. Mar Biol 133: 249-258.
Hartline DK, Buskey EJ, Lenz PH .1999. Rapid jumps and bioluminescence by controlled hydrodynamic stimuli in a mesopelagic copepod, Pleuromamma xiphias. Biol Bull 197: 132-143.
Computational and Cellular Neuroscience
Hartline, D.K. and Castelfranco, A.M. 2003 Simulations of voltage clamping poorly space-clamped voltage-dependent conductances in a uniform cylindrical neurite. J. comput. Neurosci. 14: 253-269
Hartline DK, Gassie DV, Jones BR. 1993. Effects of soma isolation on outward currents measured under voltage clamp in spiny lobster stomatogastric neurons. J. Neurophysiol 69: 2056-2071.
Hartline DK, Graubard K. 1992. Cellular and synaptic properties in the crustacean stomatogastric nervous system. In: Harris-Warrick R, Marder E, Selverston AI, editors. Dynamic Biological Networks: The Stomatogastric Nervous System. Cambridge: MIT Press. p 31-85.