Mel Goldfinger, PhD
CNS and PNS Processing of Digital and Analog Information
Research in this area addresses two basic mechanisms of electrical information processing in the nervous system. In each case, both experimental and theoretical approaches are used. First, the ability of neuronal circuits to process wide-band random information is studied in peripheral axons and in the CNS Cuneate Nucleus. Random-stimulus probes elicit impulse or population responses, which are analyzed with various stochastic (e.g., interval distributions; autocorrelation functions) and frequency-domain (FFT-based) estimators. To date, this research has found that neuronal elements can efficiently carry wide-band information despite some frequency-limiting components (e.g., chemical synapses; channel inactivation). Second, the ability of branched axons to efficiently spread information is studied with mathematical models (NSF-supported project). To date, this research has found that branched axons have a remarkably high intrinsic ability to propagate impulses within their arborization. This capability is very sensitive to the mathematical methods and physical assumptions used in the simulations. A third research area addresses the role of extracellular neurochemicals in information processing by the Cuneate Nucleus. To date, this work has developed precise measurement of putative amino acid neurotransmitters in CSF, identified amino acids released during synaptic transmission in the cuneate nucleus, and demonstrated amino acid gradients between CSF and extracellular fluid.
Goldfinger MD, Roettger VR, Pearson JC. (1992) Theoretical studies of impulse propagation in serotonergic axons. Biological Cybernetics 66:399-406.
Roettger VR, Goldfinger MD. (1994) Evidence for amino acid concentration gradients between CSF and extracellular fluid. Neuroscience Letters 178:197-200.
Moradmand K, Goldfinger MD. (1995a) Poisson process electrical stimulation: circuit and axonal responses.Journal of Neuroscience Methods 63:113-120.
Moradmand K, Goldfinger MD. (1995b) Computation of long-distance propagation of impulses elicited by poisson process stimulation. Journal of Neurophysiology 74:2415-2426.
Goldfinger MD. (2000) Computation of high safety factor impulse propagation at axonal branch points. Neuroreport11:449-456.
Goldfinger MD. (2005) Highly-efficient propagation of random impulse trains across unmyelinated axonal branch points: modificati periaxonal K+ accumulation and sodium channel kinetics. In: Modeling in the neurosciences, 2nd ed (Reeke GN et al, eds), chapter 17. Boca Raton: CRC Press.
Goldfinger MD. (2005) Rallian "equivalent" cylinders reconsidered: comparisons with literal compartments. Journal of Integrative Neuroscience. 4:227-263.
Goldfinger, MD. (2009). Probability distributions of Markovian Na channel states during propagating axonal impulses with or without recovery supernormality. Journal of Integrative Neuroscience: 8: 203-221