A METHOD FOR ESTIMATING GAP-FUNCTIONAL CONDUCTANCE BETWEEN CA3 HIPPOCAMPAL PYRAMIDAL NEURONS

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Coupling ratio analysis using dual intracellular recording combined with ultrastructural
examination of particles in plaques corresponding to gap-junctional channels is a quantitative
measure of electrotonic coupling. The difficulty in combining both electrophysiological
and morphological methods in determining the gap-junctional conductance of electrical
synapses is addressed through the use of a passive cable model of two electrotonically
coupled CA3 hippocampal pyramidal cells. Cable estimates of the gap-junctional coupling
conductance based on electrophysiological data are combined with freeze-fracture replicas
of connexin channels (gap-junctions) to confirm strong coupling between the somata of
CA3 pyramidal neurons, based on the assumption that the electrical synapse works as an
ohmic resistor influenced by an ensemble of unitary resistances of gap-junctional channels.

ANALYTICAL SOLUTION OF REACTION-DIFFUSION EQUATIONS FOR CALCIUM WAVE PROPAGATION IN A STARBURST AMACRINE CELL

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A reaction-diffusion model is presented to encapsulate calcium-induced calcium release
(CICR) as a potential mechanism for somatofugal bias of dendritic calcium movement in
starburst amacrine cells. Calcium dynamics involves a simple calcium extrusion (pump)
and a buffering mechanism of calcium binding proteins homogeneously distributed over
the plasma membrane of the endoplasmic reticulum within starburst amacrine cells. The
system of reaction-diffusion equations in the excess buffer (or low calcium concentration)
approximation are reformulated as a nonlinear Volterra integral equation which is solved
analytically via a regular perturbation series expansion in response to calcium feedback
from a continuously and uniformly distributed calcium sources. Calculation of luminal calcium
diffusion in the absence of buffering enables a wave to travel at distances of 120 μm
from the soma to distal tips of a starburst amacrine cell dendrite in 100msec, yet in the
presence of discretely distributed calcium-binding proteins it is unknown whether the propagating
calcium wave-front in the somatofugal direction is further impeded by endogenous
buffers. If so, this would indicate CICR to be an unlikely mechanism of retinal direction
selectivity in starburst amacrine cells.

CELLULAR INHIBITORY BEHAVIOR UNDERLYING  THE FORMATION OF RETINAL DIRECTION SELECTIVITY IN THE STARBUST NETWORK 


		
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Optical imaging of dendritic calcium signals provided evidence of starburst amacrine cells
exhibiting calcium bias to somatofugal motion. In contrast, it has been impractical to use
a dual-patch clamp technique to record membrane potentials from both proximal dendrites
and distal varicosities of starburst amacrine cells in order to unequivocally prove
that they are directionally sensitive to voltage, as was first suggested almost two decades
ago. This paper aims to extend the passive cable model to an active cable model of a starburst
amacrine cell that is intrinsically dependent on the electrical properties of starburst
amacrine cells, whose various macroscopic currents are described quantitatively. The coupling
between voltage and calcium just below the membrane results in a voltage-calcium
system of coupled nonlinear Volterra integral equations whose solutions must be integrated
into a prescribed model for example, for a synaptic couplet of starburst amacrine cells.
Networks of starburst amacrine cells play a fundamental role in the retinal circuitry underlying
directional selectivity. It is suggested that the dendritic plexus of starburst amacrine
cells provides the substrate for the property of directional selectivity, while directional
selectivity is a property of the exclusive layerings and confinement of their interconnections
within the sublaminae of the inner plexiform layer involving cone bipolar cells and
directionally selective ganglion cells.

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TOWARDS AN INTEGRATIVE THEORY OF COGNITION

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A framework is outlined for connecting brain imaging activity with the underlying biophysical
properties of neural networks, and their mechanisms of action and organizing
principles. The main thrust of the framework is a dynamic theory of semantics based on
functional integration of biophysical neural networks. It asserts that higher-brain function
arises from both synaptic and extrasynaptic integration in the neuropil where information
on environmental changes is represented dynamically through a discourse of semantics.
Consequently, integrative neural modeling is shown to be an important methodology for
analyzing the response activities of functional imaging studies in elucidating the relationship
between brain structure, function and behavioral.