Daniel K. Hartline
PhD Harvard University, 1967
Researcher, Békésy Laboratory of Neurobiology (PBRC)
Békésy Laboratory
University of Hawai'i
1993 East-West Rd, Rm 204
Honolulu, HI 96822
phone: (808) 956-8003
FAX: (808) 956-6984
danh@hawaii.edu
www.pbrc.hawaii.edu/~danh
Neurophysiology
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.
Copepod neuroecology
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 properties of network neurons
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.
Computational studies of space clamp errors in point-clamp experiments
"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.
Representative publications
Copepod neuroecology
Lenz PH, Hartline DK. 1999. Reaction times and force production during
escape behavior of a calanoid copepod, Undinula vulgaris. Mar Biol
133: 249-258.
Davis AD, Weatherby TM, Hartline DK, Lenz PH. 1999. Myelin-like sheaths
in copepod axons. Nature 398: 571.
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 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.
Hartline DK. 1989. Simulation of restricted neural networks with reprogrammable
neurons. IEEE Trans Circuits Systems 36: 653-660.
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