Populations of Tightly Coupled Neurons: The RGC/LGN System

2008 ◽  
Vol 20 (5) ◽  
pp. 1179-1210 ◽  
Author(s):  
Lawrence Sirovich
Keyword(s):  
Cell System ◽  
General Character ◽  
Retinal Ganglion ◽  
Relay Cell ◽  
Transfer Ratio ◽  
Coupled Cells ◽  
Tightly Coupled ◽  
Synaptic Dynamics ◽  
Dynamic Description ◽  
Short Time

A mathematical model, of general character for the dynamic description of coupled neural oscillators is presented. The population approach that is employed applies equally to coupled cells as to populations of such coupled cells. The formulation includes stochasticity and preserves details of precisely firing neurons. Based on the generally accepted view of cortical wiring, this formulation is applied to the retinal ganglion cell (RGC)/lateral geniculate nucleus (LGN) relay cell system, of the early mammalian visual system. The smallness of quantal voltage jumps at the retinal level permits a Fokker-Planck approximation for the RGC contribution; however, the LGN description requires the use of finite jumps, which for fast synaptic dynamics appears as finite jumps in the membrane potential. Analyses of equilibrium spiking behavior for both the deterministic and stochastic cases are presented. Green's function methods form the basis for the asymptotic and exact results that are presented. This determines the spiking ratio (i.e., the number of RGC arrivals per LGN spike), which is the reciprocal of the transfer ratio, under wide circumstances. Criteria for spiking regimes, in terms of the relatively few parameters of the model, are presented. Under reasonable hypotheses, it is shown that the transfer ratio is ≤1/2, in the absence of input from other areas. Thus, the model suggests that the LGN/RGC system may be a relatively unsophisticated spike editor. In the absence of other input, the system is designed to fire an LGN spike only when two or more RGC spikes appear in a relatively short time. Transfer ratios that briefly exceed 1/2 (but are less than 1) have been recorded in the laboratory. Inclusion of brain stem input has been shown to provide a signal that elevates the transfer ratio (Ozaki & Kaplan, 2006). A model that includes this contribution is also presented.

A current-controlled fuel cell system with short-time storage for grid feeding application

2007 ◽  
Author(s):  
H. Mehlich ◽  
S. Jaehnert ◽  
J. Mehlich ◽  
B. Veit ◽  
S. Konig
Keyword(s):  
Fuel Cell ◽  
Cell System ◽  
Fuel Cell System ◽  
Short Time ◽  
A Current

A Development of the Fuel Cell System That the Jet-Pump is Applied

2013 ◽  
Author(s):  
Se Kwon Jung ◽  
Yong Gyu Noh ◽  
Ui Sik Jeon
Keyword(s):  
Fuel Cell ◽  
Stable State ◽  
Cell System ◽  
Performance Limits ◽  
Fuel Cell System ◽  
Jet Pump ◽  
Pump System ◽  
Aerodynamic Performances ◽  
Short Time ◽  
Blower Performance

A fuel cell system is developed by applying a jet-pump system that performs hydrogen supplying and anode recirculation functions. The jet-pump system made up of an ejector and a proportional valve is designed to substitute conventional ejector-blower hydrogen recirculation system. The impulsive fuel feeding applied to overcome the ejector performance limits in low-power conditions. The fuel supply valve moves like injector to operate ejector at a design point in short time and does not works in remain time of each period. Therefore, average performance of ejector is better than continuous fuel feeding condition. The jet-pump compares aerodynamic performances with the blower and installed in the 100kW fuel cell system also. As a result, 25Hz and duty 75% conditions show above 80% of ejector-blower performance under 10kW emulation condition and three conditions demonstrates better performance over 10kW condition. Applicability of Jet-pump is verified at fuel cell system also. The system integrated jet-pump maintains stable state and shows equal level of ejector-blower applied case in Min. cell ratio and voltage decrease test results.

scholarly journals Short-Time Ocular Ischemia Induces Vascular Endothelial Dysfunction and Ganglion Cell Loss in the Pig Retina

2019 ◽  
Vol 20 (19) ◽  
pp. 4685 ◽  
Author(s):  
Jenia Kouchek Zadeh ◽  
Andreas Garcia-Bardon ◽  
Erik Kristoffer Hartmann ◽  
Norbert Pfeiffer ◽  
Wael Omran ◽  
...  
Keyword(s):  
Ganglion Cell ◽  
Messenger Rna ◽  
Structural Changes ◽  
Ganglion Cells ◽  
Ischemia Reperfusion ◽  
Retinal Ganglion ◽  
Retinal Arteriole ◽  
Retinal Arterioles ◽  
Short Time

Visual impairment and blindness are often caused by retinal ischemia-reperfusion (I/R) injury. We aimed to characterize a new model of I/R in pigs, in which the intraocular pathways were not manipulated by invasive methods on the ocular system. After 12 min of ischemia followed by 20 h of reperfusion, reactivity of retinal arterioles was measured in vitro by video microscopy. Dihydroethidium (DHE) staining, qPCR, immunohistochemistry, quantification of neurons in the retinal ganglion cell layer, and histological examination was performed. Retinal arterioles of I/R-treated pigs displayed marked attenuation in response to the endothelium-dependent vasodilator, bradykinin, compared to sham-treated pigs. DHE staining intensity and messenger RNA levels for HIF-1α, VEGF-A, NOX2, and iNOS were elevated in retinal arterioles following I/R. Immunoreactivity to HIF-1α, VEGF-A, NOX2, and iNOS was enhanced in retinal arteriole endothelium after I/R. Moreover, I/R evoked a substantial decrease in Brn3a-positive retinal ganglion cells and noticeable retinal thickening. In conclusion, the results of the present study demonstrate that short-time ocular ischemia impairs endothelial function and integrity of retinal blood vessels and induces structural changes in the retina. HIF-1α, VEGF-A, iNOS, and NOX2-derived reactive oxygen species appear to be involved in the pathophysiology.

Spatial summation and center-surround antagonism in the receptive field of single units in the dorsal lateral geniculate nucleus of cat: Comparison with retinal input

2000 ◽  
Vol 17 (6) ◽  
pp. 855-870 ◽  
Author(s):  
O. RUKSENAS ◽  
I.T. FJELD ◽  
P. HEGGELUND
Keyword(s):  
Receptive Field ◽  
Lateral Geniculate Nucleus ◽  
Cell Response ◽  
Spatial Summation ◽  
Dorsal Lateral Geniculate Nucleus ◽  
Relay Cell ◽  
Transfer Ratio ◽  
Retinal Input ◽  
X Cells ◽  
Dorsal Lateral Geniculate

Spatial summation and degree of center-surround antagonism were examined in the receptive field of nonlagged cells in the dorsal lateral geniculate nucleus (dLGN). We recorded responses to stationary light or dark circular spots that were stepwise varied in width. The spots were centered on the receptive field. For a sample of nonlagged X-cells, we made simultaneous recordings of action potentials and S-potentials, and could thereby compare spatial summation in the dLGN cell and in the retinal input to the cell. Plots of response versus spot diameter showed that the response for a dLGN cell was consistently below the response in the retinal input at all spot sizes. There was a marked increase of antagonism at the retinogeniculate relay. The difference between the retinal input and dLGN cell response suggested that the direct retinal input to a relay cell is counteracted in dLGN by an inhibitory field that has an antagonistic center-surround organization. The inhibitory field seems to have the same center sign (ON- or OFF-center), but a wider receptive-field center than the direct retinal input to the relay cell. The broader center of the inhibitory field can explain the increased center-surround antagonism at the retinogeniculate relay. The ratio between the response of a dLGN cell and its retinal input (transfer ratio) varied with spot width. This variation did not necessarily reflect a nonlinearity at the retinogeniculate relay. Plots of dLGN cell response against retinal input were piecewise linear, suggesting that both excitatory and inhibitory transmission in dLGN are close to linear. The variation in transfer ratio could be explained by sustained suppression evoked by the background stimulation, because such suppression has relatively stronger effect on the response to a spot evoking weak response than to a spot evoking a strong response. A simple model for the spatial receptive-field organization of nonlagged X-cells, that is consistent with our findings, is presented.

Surface tension and buoyancy effects in cellular convection

1964 ◽  
Vol 19 (3) ◽  
pp. 341-352 ◽  
Author(s):  
D. A. Nield
Keyword(s):  
Surface Tension ◽  
Order Differential Equation ◽  
Boundary Surface ◽  
Lower Boundary ◽  
Horizontal Layer ◽  
Linear Perturbation ◽  
Perturbation Techniques ◽  
Fourier Series Method ◽  
Coupled Cells ◽  
Tightly Coupled

The cells observed by Bénard (1901) when a horizontal layer of fluid is heated from below were explained by Rayleigh (1916) in terms of buoyancy, and by Pearson (1958) in terms of surface tension. These rival theories are now combined. Linear perturbation techniques are used to derive a sixth-order differential equation subject to six boundary conditions. A Fourier series method has been used to obtain the eigenvalue equation for the case where the lower boundary surface is a rigid conductor and the upper free surface is subject to a general thermal condition. Numerical results are presented. It was found that the two agencies causing instability reinforce one another and are tightly coupled. Cells formed by surface tension are approximately the same size as those formed by buoyancy. Bénard's experiments are briefly discussed.

Visual signal processing in the macaque lateral geniculate nucleus

2012 ◽  
Vol 29 (2) ◽  
pp. 105-117 ◽  
Author(s):  
THORSTEIN SEIM ◽  
ARNE VALBERG ◽  
BARRY B. LEE
Keyword(s):  
Receptive Field ◽  
Lateral Geniculate Nucleus ◽  
Visual Information ◽  
Field Size ◽  
Visual Signal ◽  
Test Field ◽  
Retinal Ganglion ◽  
Relay Cell ◽  
Firing Rates ◽  
Lateral Geniculate

AbstractComparisons of S- or prepotential activity, thought to derive from a retinal ganglion cell afferent, with the activity of relay cells of the lateral geniculate nucleus (LGN) have sometimes implied a loss, or leak, of visual information. The idea of the “leaky” relay cell is reconsidered in the present analysis of prepotential firing and LGN responses of color-opponent cells of the macaque LGN to stimuli varying in size, relative luminance, and spectral distribution. Above a threshold prepotential spike frequency, called the signal transfer threshold (STT), there is a range of more than 2 log units of test field luminance that has a 1:1 relationship between prepotential- and LGN-cell firing rates. Consequently, above this threshold, the LGN cell response can be viewed as an extension of prepotential firing (a “nonleaky relay cell”). The STT level decreased when the size of the stimulus increased beyond the classical receptive field center, indicating that the LGN cell is influenced by factors other than the prepotential input. For opponent ON cells, both the excitatory and the inhibitory response decreased similarly when the test field size increased beyond the center of the receptive field. These findings have consequences for the modeling of LGN cell responses and transmission of visual information, particularly for small fields. For instance, for LGN ON cells, information in the prepotential intensity–response curve for firing rates below the STT is left to be discriminated by OFF cells. Consequently, for a given light adaptation, the STT improves the separation of the response range of retinal ganglion cells into “complementary” ON and OFF pathways.

scholarly journals Melanopsin Ganglion Cells Use a Membrane-Associated Rhabdomeric Phototransduction Cascade

2008 ◽  
Vol 99 (5) ◽  
pp. 2522-2532 ◽  
Author(s):  
Dustin M. Graham ◽  
Kwoon Y. Wong ◽  
Peter Shapiro ◽  
Courtney Frederick ◽  
Kartik Pattabiraman ◽  
...  
Keyword(s):  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Striking Similarity ◽  
Retinal Ganglion ◽  
Rt Pcr ◽  
Pupillary Responses ◽  
Tightly Coupled ◽  
Signaling Components ◽  
Inside Out ◽  
Phototransduction Cascade

Intrinsically photosensitive retinal ganglion cells (ipRGCs) are photoreceptors of the mammalian eye that drive pupillary responses, synchronization of circadian rhythms, and other reflexive responses to daylight. Melanopsin is the ipRGC photopigment, but the signaling cascade through which this invertebrate-like opsin triggers the photocurrent in these cells is unknown. Here, using patch-clamp recordings from dissociated ipRGCs in culture, we show that a membrane-associated phosphoinositide cascade lies at the heart of the ipRGC phototransduction mechanism, similar to the cascade in rhabdomeric photoreceptors of invertebrate eyes. When ipRGCs were illuminated, melanopsin activated a G protein of the Gq/11 class, stimulating the effector enzyme phospholipase C. The presence of these signaling components in ipRGCs was confirmed by single-cell RT-PCR and immunofluorescence. The photoresponse was fully functional in excised inside-out patches of ipRGC membrane, indicating that all core signaling components are within or tightly coupled to the plasma membrane. The striking similarity of phototransduction in ipRGCs and invertebrate rhabdomeric photoreceptors reinforces the emerging view that these cells have a common evolutionary origin.

CHAOTIC BEHAVIOR OF A NEURAL NETWORK WITH DYNAMICAL THRESHOLDS

1991 ◽  
Vol 01 (04) ◽  
pp. 327-335 ◽  
Author(s):  
O. Hendin ◽  
D. Horn ◽  
M. Usher
Keyword(s):  
Chaotic Motion ◽  
Chaotic Behavior ◽  
Closed Orbit ◽  
Basin Of Attraction ◽  
Inhibitory Neurons ◽  
General Character ◽  
Closed Loops ◽  
Feedback Network ◽  
Short Time ◽  
Qualitative Changes

Models of neural networks which include dynamical thresholds can display motion in pattern space, the space of all memories. We investigate this motion in a particular model which is based on a feedback network of excitatory and inhibitory neurons. We find that small variations in the parameters of the model can lead to big qualitative changes of its behavior. We display results of closed loops and chaotic motion which turn from one to the other through intermittency. We show that the basin of attraction of a closed orbit has a fractal shape, and find that the dimension of the chaotic motion is slightly bigger than 2. The general character of the dynamics of this model is convergence to centers of attraction on short time scales and divergence on long ones.

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