Are Some Minis Multiquantal?

1997 ◽  
Vol 78 (3) ◽  
pp. 1293-1304 ◽  
Author(s):  
Matthew Frerking ◽  
Salvador Borges ◽  
Martin Wilson
Keyword(s):  
Gaussian Distribution ◽  
Coefficient Of Variation ◽  
Amplitude Distribution ◽  
Postsynaptic Currents ◽  
Central Neurons ◽  
Synchronized Release ◽  
Release Model

Frerking, Matthew, Salvador Borges, and Martin Wilson. Are some minis multiquantal? J. Neurophysiol. 78: 1293–1304, 1997. The amplitude distribution of miniature postsynaptic currents (minis) in many central neurons has a large variance and positive skew, but the sources of this variance and skew are unresolved. Recently it has been proposed that spontaneous Ca2+ influx into a presynaptic bouton with multiple release sites could cause spontaneous multiquantal minis by synchronizing release at all sites in the bouton, accounting for both the large variance and skew of the mini distribution. We tested this hypothesis by evoking minis with internally perfused, buffered Ca2+ and the secretagogue α-latrotoxin, both in the absence of external Ca2+. With these manipulations, the synchronized release model predicts that the mini distribution should collapse to a Gaussian distribution with a reduced coefficient of variation. Contrary to this expectation, we find that mini amplitude distributions under these conditions retain a large variance and positive skew and are indistinguishable from amplitude distributions of depolarization-evoked minis, strongly suggesting that minis are uniquantal.

Ultrasonic Inspection of Composite Materials Using Minimum Entropy Deconvolution

2010 ◽  
Vol 636-637 ◽  
pp. 1555-1561 ◽  
Author(s):  
A. Benammar ◽  
R. Drai ◽  
A. Guessoum
Keyword(s):  
Composite Materials ◽  
Gaussian Distribution ◽  
Ultrasonic Inspection ◽  
Simulated Data ◽  
Amplitude Distribution ◽  
Minimum Phase ◽  
Minimum Entropy ◽  
Ultrasonic Signals ◽  
Non Gaussian ◽  
Deconvolution Techniques

In this work, the Minimum Entropy Deconvolution (MED) method, developed for ultrasonic signals, is used to address the problem of delamination defect detection in Composite Materials. Standard deconvolution techniques suppose that the wavelet is minimum phase but generally make no assumptions about the amplitude distribution of the primary reflection coefficient sequence. For a white reflection sequence the assumption of a Gaussian distribution means that recovery of the true phase of the wavelet is impossible; however, a non-Gaussian distribution in theory allows recovery of the phase. It is generally recognized that primary reflection coefficients typically have a non-Gaussian amplitude distribution. The minimum entropy deconvolution (MED) method supposes whiteness but seek to exploit the non-Gaussianity. This method do not assume minimum phase. The deconvolution filter is defined by the maximization of a function called the objective. The algorithm is tested on simulated data and also tested on real ultrasonic data from multilayered composite materials.

Selective Modulation of Excitatory Transmission by μ-Opioid Receptor Activation in Rat Supraoptic Neurons

1999 ◽  
Vol 82 (6) ◽  
pp. 3000-3005 ◽  
Author(s):  
Qing-Song Liu ◽  
Sheng Han ◽  
You-Sheng Jia ◽  
Gong Ju
Keyword(s):  
Opioid Receptor ◽  
Amplitude Distribution ◽  
Receptor Activation ◽  
Dependent Manner ◽  
Membrane Hyperpolarization ◽  
Postsynaptic Currents ◽  
Cell Recording ◽  
Μ Opioid Receptor ◽  
Neuroendocrine Neurons ◽  
Supraoptic Neurons

Opioid peptides have profound inhibitory effects on the production of oxytocin and vasopressin, but their direct effects on magnocellular neuroendocrine neurons appear to be relatively weak. We tested whether a presynaptic mechanism is involved in this inhibition. The effects of μ-opioid receptor agonist d-Ala2, N-CH3-Phe4, Gly5-ol-enkephalin (DAGO) on excitatory and inhibitory transmission were studied in supraoptic nucleus (SON) neurons from rat hypothalamic slices using whole cell recording. DAGO reduced the amplitude of evoked glutamatergic excitatory postsynaptic currents (EPSCs) in a dose-dependent manner. In the presence of tetrodotoxin (TTX) to block spike activity, DAGO also reduced the frequency of spontaneous miniature EPSCs without altering their amplitude distribution, rising time, or decaying time constant. The above effects of DAGO were reversed by wash out, or by addition of opioid receptor antagonist naloxone or selective μ-antagonist Cys2-Tyr3-Orn5-Pen7-NH2(CTOP). In contrast, DAGO had no significant effect on the evoked and spontaneous miniature GABAergic inhibitory postsynaptic currents (IPSCs) in most SON neurons. A direct membrane hyperpolarization of SON neurons was not detected in the presence of DAGO. These results indicate that μ-opioid receptor activation selectively inhibits excitatory activity in SON neurons via a presynaptic mechanism.

Non‐Gaussian reflectivity, entropy, and deconvolution

Geophysics ◽  
1985 ◽  
Vol 50 (12) ◽  
pp. 2862-2888 ◽  
Author(s):  
A. T. Walden
Keyword(s):  
Gaussian Distribution ◽  
Robust Statistics ◽  
Amplitude Distribution ◽  
Reflection Coefficients ◽  
General Description ◽  
Minimum Phase ◽  
Minimum Entropy ◽  
Highly Nonlinear ◽  
Non Gaussian ◽  
Deconvolution Techniques

Standard deconvolution techniques assume that the wavelet is minimum phase but generally make no assumptions about the amplitude distribution of the primary reflection coefficient sequence. For a white reflection sequence the assumption of a Gaussian distribution means that recovery of the true phase of the wavelet is impossible; however, a non‐Gaussian distribution in theory allows recovery of the phase. It is generally recognized that primary reflection coefficients typically have a non‐Gaussian amplitude distribution. Deconvolution techniques that assume whiteness but seek to exploit the non‐Gaussianity include Wiggins’ minimum entropy deconvolution (MED), Claerbout’s parsimonious deconvolution, and Gray’s variable norm deconvolution. These methods do not assume minimum phase. The deconvolution filter is defined by the maximization of a function called the objective. I examine these and other MED‐type deconvolution techniques. Maximizing the objective by setting derivatives to zero results in most cases in a deconvolution filter which is the solution of a highly nonlinear Toeplitz matrix equation. Wiggins’ original iterative approach to the solution is suitable for some methods, while for other methods straightforward iterative perturbation approaches may be used instead. The likely effects on noise of the nonlinearities involved are demonstrated as extremely varied. When the form of an objective remains constant with iteration, the most general description of the method is likelihood ratio maximization; when the form changes, a method seeks to maximize relative entropy at each iteration. I emphasize simple and useful link between three methods and the use of M-estimators in robust statistics. In attempting to assess the accuracy of the techniques, the choice between different families of distributions for modeling the distribution of reflection coefficients is important. The results provide important insights into methods of constructing and understanding the statistical implications and behavior of a chosen nonlinearity. A new objective is introduced to illustrate this, and a few particular preferences expressed. The methods are compared with the zero‐memory nonlinear deconvolution approach of Godfrey and Rocca (1981); for their approach, two distinctly different yet statistically comparable models for reflection coefficients are seen to give surprisingly similarly shaped nonlinearities. Finally, it is shown that each MED‐type method can be viewed as the minimization of a particular configurational entropy expression, where some suitable ratio plays the role of a probability.

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