Dissection of the neuron network in the catfish inner retina. V. Interactions between NA and NB amacrine cells

1990 ◽  
Vol 63 (1) ◽  
pp. 120-130 ◽  
Author(s):  
H. M. Sakai ◽  
K. I. Naka
Keyword(s):  
White Noise ◽  
Small Amplitude ◽  
Amacrine Cell ◽  
Amacrine Cells ◽  
The Other ◽  
First Order ◽  
Membrane Noise ◽  
Current Pulses ◽  
Damped Oscillation ◽  
Order Kernel

1. Simultaneous intracellular recordings were made from two neighboring N amacrine cells, one an ON amacrine (NA) cell and the other an OFF amacrine (NB) cell. Extrinsic current was injected into one amacrine cell, and the resulting intracellular responses were recorded from the other amacrine cell. Test signals included 1) a single-frequency sinusoid, 2) a depolarizing or hyperpolarizing pulse, or 3) a white-noise modulated current. In some cell pairs, membrane noise was measured in the dark as well as under a steady background illumination. 2. Current pulses injected into a NA cell evoked a damped oscillation from a NB cell. The first-order kernel derived by cross-correlating the white-noise current injected into a NA cell against the evoked response from a NB cell was a large depolarization followed by a damped oscillation. The frequency of oscillations varied slightly from pair to pair but averaged 35 Hz. 3. Current pulses injected into a NB cell evoked a sign-inverting response (hyperpolarization) of very small amplitude from a NA cell. Similarly, the first-order kernel was a hyperpolarization of very small amplitude. 4. The power spectrum of the membrane noise recorded from NA and NB cells in the dark or during steady illumination often showed a peak at 35 Hz. Such membrane noise synchronizes synergistically among NA cells and among NB cells in the dark. In addition, the membrane fluctuations seen in NA and NB cells in the dark were out of phase. 5. Transmission between NA and NB cells was largely accounted for by a linear component; however, a very small but significant second- and third-order nonlinearity was also generated. 6. These results show that the interactions occurring between amacrine cells of opposite response polarity are much more complex than those between cells of the same response polarity and that the neural circuitry in the inner retina actively controls interactions between ON and OFF channels in the dark as well as in the presence of light stimuli.

Neural computation of motion in the fly visual system: quadratic nonlinearity of responses induced by picrotoxin in the HS and CH cells

1995 ◽  
Vol 74 (6) ◽  
pp. 2665-2684 ◽  
Author(s):  
Y. Kondoh ◽  
Y. Hasegawa ◽  
J. Okuma ◽  
F. Takahashi
Keyword(s):  
Mean Square Error ◽  
Order Term ◽  
Mirror Image ◽  
Second Order ◽  
The Other ◽  
Linear Component ◽  
Mean Square ◽  
Nonlinear Component ◽  
First Order ◽  
Order Kernel

1. A computational model accounting for motion detection in the fly was examined by comparing responses in motion-sensitive horizontal system (HS) and centrifugal horizontal (CH) cells in the fly's lobula plate with a computer simulation implemented on a motion detector of the correlation type, the Reichardt detector. First-order (linear) and second-order (quadratic nonlinear) Wiener kernels from intracellularly recorded responses to moving patterns were computed by cross correlating with the time-dependent position of the stimulus, and were used to characterize response to motion in those cells. 2. When the fly was stimulated with moving vertical stripes with a spatial wavelength of 5-40 degrees, the HS and CH cells showed basically a biphasic first-order kernel, having an initial depolarization that was followed by hyperpolarization. The linear model matched well with the actual response, with a mean square error of 27% at best, indicating that the linear component comprises a major part of responses in these cells. The second-order nonlinearity was insignificant. When stimulated at a spatial wavelength of 2.5 degrees, the first-order kernel showed a significant decrease in amplitude, and was initially hyperpolarized; the second-order kernel was, on the other hand, well defined, having two hyperpolarizing valleys on the diagonal with two off-diagonal peaks. 3. The blockage of inhibitory interactions in the visual system by application of 10-4 M picrotoxin, however, evoked a nonlinear response that could be decomposed into the sum of the first-order (linear) and second-order (quadratic nonlinear) terms with a mean square error of 30-50%. The first-order term, comprising 10-20% of the picrotoxin-evoked response, is characterized by a differentiating first-order kernel. It thus codes the velocity of motion. The second-order term, comprising 30-40% of the response, is defined by a second-order kernel with two depolarizing peaks on the diagonal and two off-diagonal hyperpolarizing valleys, suggesting that the nonlinear component represents the power of motion. 4. Responses in the Reichardt detector, consisting of two mirror-image subunits with spatiotemporal low-pass filters followed by a multiplication stage, were computer simulated and then analyzed by the Wiener kernel method. The simulated responses were linearly related to the pattern velocity (with a mean square error of 13% for the linear model) and matched well with the observed responses in the HS and CH cells. After the multiplication stage, the linear component comprised 15-25% and the quadratic nonlinear component comprised 60-70% of the simulated response, which was similar to the picrotoxin-induced response in the HS cells. The quadratic nonlinear components were balanced between the right and left sides, and could be eliminated completely by their contralateral counterpart via a subtraction process. On the other hand, the linear component on one side was the mirror image of that on the other side, as expected from the kernel configurations. 5. These results suggest that responses to motion in the HS and CH cells depend on the multiplication process in which both the velocity and power components of motion are computed, and that a putative subtraction process selectively eliminates the nonlinear components but amplifies the linear component. The nonlinear component is directionally insensitive because of its quadratic non-linearity. Therefore the subtraction process allows the subsequent cells integrating motion (such as the HS cells) to tune the direction of motion more sharply.

scholarly journals On the regularity of many-particle dynamical systems perturbed by white noise

1996 ◽  
Vol 9 (4) ◽  
pp. 427-437 ◽  
Author(s):  
Anatoli V. Skorokhod
Keyword(s):  
Dynamical Systems ◽  
Finite Number ◽  
White Noise ◽  
Interaction Force ◽  
The Other ◽  
Inertial Particles ◽  
First Order ◽  
Random Forces ◽  
Diffusion Motion ◽  
Number Of Particles

We consider a system of finite number of particles that are moving in Rd under mutual interaction. It is assumed that the particles are subjected to some additional random forces which cause diffusion motion of the particles. The latter is described by a system of stochastic differential equations of the first order for noninertia particles and the second order for inertial particles. The coefficient of the system are unbounded because the interaction force tends to infinity if the distance between two particles tends to zero. The system is called regular if no particle can hit the other. We investigate conditions of regularity.This article is dedicated to the memory of Roland L. Dobrushin.

Processing of Color- and Noncolor-Coded Signals in the Gourami Retina. II. Amacrine Cells

1997 ◽  
Vol 78 (4) ◽  
pp. 2018-2033 ◽  
Author(s):  
Hiroko M. Sakai ◽  
Hildred Machuca ◽  
Ken-Ichi Naka
Keyword(s):  
White Noise ◽  
Amacrine Cell ◽  
Amacrine Cells ◽  
Second Order ◽  
Order Component ◽  
Response Dynamics ◽  
Dendritic Field ◽  
State Response ◽  
Order Components ◽  
Nonlinear Components

Sakai, Hiroko M., Hildred Machuca, and Ken-Ichi Naka. Processing of color- and noncolor-coded signals in the gourami retina. II. Amacrine cells. J. Neurophysiol. 78: 2018–2033, 1997. The same set of stimuli and analytic methods that was used to study the dynamics of horizontal cells ( Sakai et al. 1997a ) was applied to a study of the response dynamics and signal processing in amacrine cells in the retina of the kissing gourami, Helostoma rudolfi. The retina contains two major classes of amacrine cells that could be identified from their morphology: C and N amacrine cells. C amacrine cells had a two-layered dendritic field, whereas N cells had a monolayered dendritic field. Both types of amacrine cell were tracer-coupled but coupling was more extensive in the N amacrine cells. Responses from C amacrine cells lacked a DC component and had a small linear component that was <10% in terms of mean square error (MSE); the second-order component often accounted for >50% of the modulation response. The C amacrine cells did not show any characteristic color coding under any stimulus condition. Most responses of N cells to a pulsatile stimulus consisted of a series of depolarizing transient potentials and steady illumination did not generate any DC potential in these cells. The response to a white-noise modulated input was composed of well-defined first- and second-order components and, possibly, higher-order components. The response evoked by a red or green white-noise–modulated stimulus given alone was not color coded. Modulated red illumination in the presence of a green illumination elicited a color-coded response from >70% of N amacrine cells. Color information was carried not only by the polarity but also by the dynamics of the first-order component. No convincing evidence was obtained to indicate that the second-order component might be involved in color processing. Some N amacrine cells produced a well-defined (second-order) interaction kernel to show that the temporal sequence of red and green stimuli was a parameter to be considered. In a complex cell such as an amacrine cell, responses evoked by a pulsatile stimulus given in darkness and by modulation of a mean luminance could be very different in terms of their characteristics. It was not always possible to predict the response evoked by one stimulus from observing the cell's response to another stimulus. This is because, in N cells, a flash-evoked (nonsteady state) response is composed largely of nonlinear components whereas a modulation (steady state) response is composed of linear as well as nonlinear components.

Nonspiking and Spiking Proprioceptors in the Crab: White Noise Analysis of Spiking CB-Chordotonal Organ Afferents

2003 ◽  
Vol 89 (4) ◽  
pp. 1815-1825 ◽  
Author(s):  
E. Rolland Gamble ◽  
Ralph A. DiCaprio
Keyword(s):  
White Noise ◽  
Information Transfer ◽  
Noise Analysis ◽  
Second Order ◽  
Chordotonal Organ ◽  
White Noise Analysis ◽  
Response Component ◽  
First Order ◽  
Wiener Kernels ◽  
Order Kernel

The proprioceptors that signal the position and movement of the first two joints of crustacean legs provide an excellent system for comparison of spiking and nonspiking (graded) information transfer and processing in a simple motor system. The position, velocity, and acceleration of the first two joints of the crab leg are monitored by both nonspiking and spiking proprioceptors. The nonspiking thoracic-coxal muscle receptor organ (TCMRO) spans the TC joint, while the coxo-basal (CB) joint is monitored by the spiking CB chordotonal organ (CBCTO) and by nonspiking afferents arising from levator and depressor elastic strands. The response characteristics and nonlinear models of the input-output relationship for CB chordotonal afferents were determined using white noise analysis (Wiener kernel) methods. The first- and second-order Wiener kernels for each of the four response classes of CB chordotonal afferents (position, position-velocity, velocity, and acceleration) were calculated and the gain function for each receptor determined by taking the Fourier transform of the first-order kernel. In all cases, there was a good correspondence between the response of an afferent to deterministic stimulation (trapezoidal movement) and the best-fitting linear transfer function calculated from the first-order kernel. All afferents also had a nonlinear response component and second-order Wiener kernels were calculated for afferents of each response type. Models of afferent responses based on the first- and second-order kernels were able to predict the response of the afferents with an average accuracy of 86%.

Processing of Color- and Noncolor-Coded Signals in the Gourami Retina. III. Ganglion Cells

1997 ◽  
Vol 78 (4) ◽  
pp. 2034-2047 ◽  
Author(s):  
Hiroko M. Sakai ◽  
Hildred Machuca ◽  
Michael J. Korenberg ◽  
Ken-Ichi Naka
Keyword(s):  
White Noise ◽  
Spike Train ◽  
Ganglion Cells ◽  
Green Light ◽  
Amacrine Cells ◽  
Second Order ◽  
First Order ◽  
Wide Range ◽  
Mean Luminance ◽  
Order Components

Sakai, Hiroko M., Hildred Machuca, Michael J. Korenberg, and Ken-Ichi Naka. Processing of color- and noncolor-coded signals in the gourami retina. III. Ganglion cells. J. Neurophysiol. 78: 2034–2047, 1997. The dynamics of intracellular responses from ganglion cells, as well as that of spike discharges, were studied with the stimulus regimens and analytic procedures identical to those used to study the dynamics of the responses from horizontal and amacrine cells ( Sakai et al. 1997a , b ). The stimuli used were large fields of red and green light given as a pulsatile input or modulation about a mean luminance by a white-noise signal. Spike discharges evoked by a white-noise stimulus were analyzed in exactly the same manner as that used for analysis of analog responses. The canonical nature of kernels allowed us to correlate the first- and second-order components in a spike train with those of the intracellular responses from horizontal, amacrine, and ganglion cells. Both red and green stimuli given alone in darkness produced noncolor-coded responses from all ganglion cells. In the case of some cells, steady red illumination changed the polarity or waveform of the response to green light. Color-coded ganglions responded only to simultaneous color contrast. Nonlinearities recovered from intracellular responses, and spike discharges were similar to those found in responses from amacrine cells and were of two types, one characteristic of the C amacrine cells and the other characteristic of the N amacrine cells. The first-order kernels of most ganglion cells could be divided into two basic types, biphasic and triphasic. The combination of kernels of these two basic types with different polarities can produce a wide range of responses. Addition of two types of second-order nonlinearity could render color coding in this relatively simple retina as an extremely complex process. Color information appeared to be represented by the polarity, as well as the waveform, of the first-order kernel. The response dynamics is a means of transmission of color-coded information. Second-order components carry information about changes around a mean luminance regardless of the color of an input. Some spike discharges produced a well-defined cross-kernel between red and green inputs to show that a particular time sequence of red and green stimuli was detected by the retinal neuron network. The similarity between signatures of second-order kernels for both amacrine and ganglion cells indicates that signals undergo a minimal transformation in the temporal domain when they are transmitted from amacrine to ganglion cells and then transformed into a spike train. Under our experimental conditions, a single spike train carried simultaneously information about red and green inputs, as well as about linear and nonlinear components. In addition, the spike train also carries a cross-talk component. A spike train is a carrier of multiple signals. Conversely, many types of information in a stimulus are independently encoded into a spike train.

scholarly journals Thematic Maps for the Variation of Bearing Capacity of Soil Using SPTs and MATLAB

Geosciences ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 329
Author(s):  
Mahdi O. Karkush ◽  
Mahmood D. Ahmed ◽  
Ammar Abdul-Hassan Sheikha ◽  
Ayad Al-Rumaithi
Keyword(s):  
Bearing Capacity ◽  
Mean Squared Error ◽  
Ground Level ◽  
The Other ◽  
Thematic Maps ◽  
First Order ◽  
Squared Error ◽  
Order Polynomial ◽  
Interpolation Polynomials ◽  
Penetration Tests

The current study involves placing 135 boreholes drilled to a depth of 10 m below the existing ground level. Three standard penetration tests (SPT) are performed at depths of 1.5, 6, and 9.5 m for each borehole. To produce thematic maps with coordinates and depths for the bearing capacity variation of the soil, a numerical analysis was conducted using MATLAB software. Despite several-order interpolation polynomials being used to estimate the bearing capacity of soil, the first-order polynomial was the best among the other trials due to its simplicity and fast calculations. Additionally, the root mean squared error (RMSE) was almost the same for the all of the tried models. The results of the study can be summarized by the production of thematic maps showing the variation of the bearing capacity of the soil over the whole area of Al-Basrah city correlated with several depths. The bearing capacity of soil obtained from the suggested first-order polynomial matches well with those calculated from the results of SPTs with a deviation of ±30% at a 95% confidence interval.

Measurement of Wiener kernels

1984 ◽  
Vol 16 (1) ◽  
pp. 11-12
Author(s):  
Yoshifusa Ito
Keyword(s):  
Differential Operator ◽  
Mathematical Models ◽  
White Noise ◽  
Linear Systems ◽  
Main Part ◽  
The Other ◽  
Linear Functionals ◽  
Wiener Kernels ◽  
Non Linear ◽  
Non Linear Systems

Since the late 1960s Wiener's theory on the non-linear functionals of white noise has been widely applied to the construction of mathematical models of non-linear systems, especially in the field of biology. For such applications the main part is the measurement of Wiener's kernels, for which two methods have been proposed: one by Wiener himself and the other by Lee and Schetzen. The aim of this paper is to show that there is another method based on Hida's differential operator.

scholarly journals Ganglioside incorporation and release by the isolated perfused rat liver

1991 ◽  
Vol 274 (2) ◽  
pp. 581-585 ◽  
Author(s):  
S C Kivatinitz ◽  
A Miglio ◽  
R Ghidoni
Keyword(s):  
Rat Liver ◽  
The Other ◽  
Regulatory Role ◽  
Isolated Perfused Rat Liver ◽  
Order Kinetic ◽  
Perfused Rat Liver ◽  
Ganglioside Gm1 ◽  
First Order ◽  
Pseudo First Order

The fate of exogenous ganglioside GM1 labelled in the sphingosine moiety, [Sph-3H]GM1, administered as a pulse, in the isolated perfused rat liver was investigated. When a non-recirculating protocol was employed, the amount of radioactivity in the liver and perfusates was found to be dependent on the presence of BSA in the perfusion liquid and on the time elapsed after the administration of the ganglioside. When BSA was added to the perfusion liquid, less radioactivity was found in the liver and more in the perfusate at each time tested, for up to 1 h. The recovery of radioactivity in the perfusates followed a complex course which can be described by three pseudo-first-order kinetic constants. The constants, in order of decreasing velocity, are interpreted as: (a) the dilution of the labelled GM1 by the constant influx of perfusion liquid; (b) the washing off of GM1 loosely bound to the surface of liver cells; (c) the release of gangliosides from the liver. Process (b) was found to be faster in the presence of BSA, probably owing to the ability of BSA to bind gangliosides. The [Sph-3H]GM1 in the liver underwent metabolism, leading to the appearance of products of anabolic (GD1a, GD1b) and catabolic (GM2, GM3) origin; GD1a appeared before GM2 and GM3 but, at times longer than 10 min, GM2 and GM3 showed more radioactivity than GD1a. At a given time the distribution of the radioactivity in the perfusates was quite different from that of the liver. In fact, after 60 min GD1a was the only metabolite present in any amount, the other being GM3, the quantity of which was small. This indicates that the liver is able to release newly synthesized gangliosides quite specifically. When a recirculating protocol was used, there were more catabolites and less GD1a than with the non-recirculating protocol. A possible regulatory role of ganglioside re-internalization on their own metabolism in the liver is postulated.

Calcium From Internal Stores Triggers GABA Release From Retinal Amacrine Cells

2005 ◽  
Vol 94 (6) ◽  
pp. 4196-4208 ◽  
Author(s):  
Ajithkumar Warrier ◽  
Salvador Borges ◽  
David Dalcino ◽  
Cameron Walters ◽  
Martin Wilson
Keyword(s):  
Transmitter Release ◽  
Metabotropic Glutamate Receptor ◽  
Amacrine Cell ◽  
Ryanodine Receptors ◽  
Amacrine Cells ◽  
Gaba Release ◽  
Voltage Gated ◽  
Metabotropic Glutamate ◽  
Inositol 1,4,5 Trisphosphate ◽  
Evoked Transmitter Release

The Ca2+ that promotes transmitter release is generally thought to enter presynaptic terminals through voltage-gated Ca2+channels. Using electrophysiology and Ca2+ imaging, we show that, in amacrine cell dendrites, at least some of the Ca2+ that triggers transmitter release comes from endoplasmic reticulum Ca2+ stores. We show that both inositol 1,4,5-trisphosphate receptors (IP3Rs) and ryanodine receptors (RyRs) are present in these dendrites and both participate in the elevation of cytoplasmic [Ca2+] during the brief depolarization of a dendrite. Only the Ca2+ released through IP3Rs, however, seems to promote the release of transmitter. Antagonists for the IP3R reduced transmitter release, whereas RyR blockers had no effect. Application of an agonist for metabotropic glutamate receptor, known to liberate Ca2+ from internal stores, enhanced both spontaneous and evoked transmitter release.

Response dynamics and receptive-field organization of catfish amacrine cells

1992 ◽  
Vol 67 (2) ◽  
pp. 430-442 ◽  
Author(s):  
H. M. Sakai ◽  
K. Naka
Keyword(s):  
Receptive Field ◽  
White Noise ◽  
Amacrine Cells ◽  
Second Order ◽  
Response Dynamics ◽  
Field Center ◽  
Mean Luminance ◽  
Nonlinear Components ◽  
Receptive Field Center ◽  
Dc Potentials

1. We have applied Wiener analysis to a study of response dynamics of N (sustained) and C (transient) amacrine cells. Stimuli were a spot and an annulus of light, the luminance of which was modulated by two independent white-noise signals. First- and second-order Wiener kernels were computed for each spot and annulus input. The analysis allowed us to separate a modulation response into its linear and nonlinear components, and into responses generated by a receptive-field center and its surround. 2. Organization of the receptive field of N amacrine cells consists of both linear and nonlinear components. The receptive field of linear components was center-surround concentric and opposite in polarity, whereas that of second-order nonlinear components was monotonic. 3. In NA (center-depolarizing) amacrine cells, the membrane DC potentials brought about by the mean luminance of a white-noise spot or a steady spot were depolarizations, whereas those brought about by the mean luminance of a white-noise annulus or a steady annulus were hyperpolarizations. In NB (center-hyperpolarizing) amacrine cells, this relationship was reversed. If both receptive-field center and surround were stimulated by a spot and annulus, membrane DC potentials became close to the dark level and the amplitude of modulation responses became larger. 4. The linear responses of a receptive-field center of an N amacrine cell, measured in terms of the first-order Wiener kernel, were facilitated if the surround was stimulated simultaneously. The amplitude of the kernel became larger, and its peak response time became shorter. The same facilitation occurred in the linear responses of a receptive-field surround if the center was stimulated simultaneously. 5. The second-order nonlinear responses were not usually generated in N amacrine cells if the stimulus was either a white-noise spot or a white-noise annulus alone. Significant second-order nonlinearity appeared if the other region of the receptive field was also stimulated. 6. Membrane DC potentials of C amacrine cells remained at the dark level with either a white-noise spot or a white-noise annulus. The cell responded only to modulations. 7. The major characteristics of center and surround responses of C amacrine cells could be approximated by second-order Wiener kernels of the same structure. The receptive field of second-order nonlinear components of C amacrine cells was monotonic.(ABSTRACT TRUNCATED AT 400 WORDS)

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