scholarly journals Modeling Gravity-Dependent Plasticity of the Angular Vestibuloocular Reflex With a Physiologically Based Neural Network

2006 ◽  
Vol 96 (6) ◽  
pp. 3349-3361 ◽  
Author(s):  
Yongqing Xiang ◽  
Sergei B. Yakushin ◽  
Bernard Cohen ◽  
Theodore Raphan
Keyword(s):  
Neural Network ◽  
Three Dimensional ◽  
Learning Rule ◽  
Three Dimensions ◽  
Head Orientation ◽  
Model Parameters ◽  
Vestibuloocular Reflex ◽  
Model Predictions ◽  
Physiologically Based ◽  
Head Positions

A neural network model was developed to explain the gravity-dependent properties of gain adaptation of the angular vestibuloocular reflex (aVOR). Gain changes are maximal at the head orientation where the gain is adapted and decrease as the head is tilted away from that position and can be described by the sum of gravity-independent and gravity-dependent components. The adaptation process was modeled by modifying the weights and bias values of a three-dimensional physiologically based neural network of canal–otolith-convergent neurons that drive the aVOR. Model parameters were trained using experimental vertical aVOR gain values. The learning rule aimed to reduce the error between eye velocities obtained from experimental gain values and model output in the position of adaptation. Although the model was trained only at specific head positions, the model predicted the experimental data at all head positions in three dimensions. Altering the relative learning rates of the weights and bias improved the model-data fits. Model predictions in three dimensions compared favorably with those of a double-sinusoid function, which is a fit that minimized the mean square error at every head position and served as the standard by which we compared the model predictions. The model supports the hypothesis that gravity-dependent adaptation of the aVOR is realized in three dimensions by a direct otolith input to canal–otolith neurons, whose canal sensitivities are adapted by the visual-vestibular mismatch. The adaptation is tuned by how the weights from otolith input to the canal–otolith-convergent neurons are adapted for a given head orientation.

The three-dimensional stable mandibular landmarks in patients between the ages of 12.5 to 17.1 years

2020 ◽  
Author(s):  
Gui Chen ◽  
Mona Al Awadi ◽  
David William Chambers ◽  
Manuel O Lagravère-Vich ◽  
Tianmin Xu ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Growth Period ◽  
Mandibular Canal ◽  
Mental Foramen ◽  
Three Dimensions ◽  
Head Orientation ◽  
Facial Growth ◽  
Linear Distance ◽  
The Right ◽  
Stable Structures

Abstract Background: With the aid of implants, Björk identified the two-dimensional mandibular stable structures in cephalogram during facial growth. However, we don't know the three-dimensional stable structures exactly. The purpose of this study was to identify the most stable mandibular landmarks in growing patients using three-dimensional images.Methods: The sample was comprised of two cone-beam computed tomography (CBCT) scans taken about 4.6 years apart in 20 growing patients between the ages of 12.5 (T1) to 17.1 years (T2). After head orientation, landmarks were located on the chin (Pog), internal symphysis (Points C, D and E), and mandibular canals, which included the mental foramina (MF and MFA) and mandibular foramina (MdF). The linear distance change between Point C and these landmarks was measured on each CBCT to test stability through time. The reliability of the suggested stable landmarks was also evaluated. Results: The total distance changes between Point C and points D, E, Pog, MF, and MFA were all less than 1.0 mm from T1 to T2. The reliability measures of these landmarks, which were measured by the Cronbach alpha, were above 0.94 in all three dimensions for each landmark. From T1 to T2, distance changes from Point C to the right and left mandibular foramina were respectively 3.39±3.29 mm and 3.03±2.83 mm. Conclusions: During a growth period that averaged 4.6-years, ranging from 11.2 to 19.8 years, the structures that appeared relatively stable and could be used in mandibular regional superimposition included Pog, landmarks on the inferior part of the internal symphysis, and the mental foramen. The centers of the mandibular foramina, the starting points of the mandibular canal, underwent significant changes in the transverse and sagittal dimensions.

scholarly journals Three-dimensional multi-source localization of underwater objects using convolutional neural networks for artificial lateral lines

2020 ◽  
Vol 17 (162) ◽  
pp. 20190616 ◽  
Author(s):  
Ben J. Wolf ◽  
Jos van de Wolfshaar ◽  
Sietse M. van Netten
Keyword(s):  
Neural Network ◽  
Source Localization ◽  
Fluid Velocity ◽  
Three Dimensional ◽  
Sensory System ◽  
Three Dimensions ◽  
Hydrodynamic Theory ◽  
Multiple Sources ◽  
Combined System ◽  
Lateral Lines

This research focuses on the signal processing required for a sensory system that can simultaneously localize multiple moving underwater objects in a three-dimensional (3D) volume by simulating the hydrodynamic flow caused by these objects. We propose a method for localization in a simulated setting based on an established hydrodynamic theory founded in fish lateral line organ research. Fish neurally concatenate the information of multiple sensors to localize sources. Similarly, we use the sampled fluid velocity via two parallel lateral lines to perform source localization in three dimensions in two steps. Using a convolutional neural network, we first estimate a two-dimensional image of the probability of a present source. Then we determine the position of each source, via an automated iterative 3D-aware algorithm. We study various neural network architectural designs and different ways of presenting the input to the neural network; multi-level amplified inputs and merged convolutional streams are shown to improve the imaging performance. Results show that the combined system can exhibit adequate 3D localization of multiple sources.

Thermoacoustic Modeling of a Graphene-Based Actuator

2014 ◽  
Author(s):  
Jonghoon Bin ◽  
William S. Oates ◽  
Kunihiko Taira
Keyword(s):  
Three Dimensional ◽  
Three Dimensions ◽  
Model Parameters ◽  
Three Dimensional Model ◽  
Mcmc Algorithms ◽  
Flux Boundary Conditions ◽  
Model Parameter Uncertainty ◽  
The One ◽  
Different Characteristics ◽  
Surface Temperature Variation

A model for two-dimensional graphene-based thermoacoutic membranes is investigated analytically and validated numerically in this study. In one-dimension, the temperature and the pressure variables are analytically determined by decoupling the two variables in the governing equations due to the large disparity between length scales. We further extend the one-dimensional findings to three dimensions. The three-dimensional pressure fluctuation produced by the surface temperature variation is determined with the aid of the acoustic piston model. Through the one and three-dimensional model analysis, the dependence of acoustic pressure as a function of frequency is studied and the acoustic response with respect to the frequency shows different characteristics when assuming Dirichlet (temperature) or Neumann (heat flux) boundary conditions. The general thermoacoustic model is then applied to a graphene-on-paper sound device. Probabilistic Bayesian method coupled with Monte Carlo Markov Chain (MCMC) algorithms is used to optimize model parameters and to analyze model parameter uncertainty. Excellent correlations of thermoacoustic behavior is predicted by the model which provides insight into heat transport mechanisms associated with generating sound from thermally cycling graphene at high frequencies.

scholarly journals Solving Three Dimensions Volterra Integral Equations (TDVIE) via a Neural Network

2019 ◽  
Vol 23 (10) ◽  
pp. 92
Author(s):  
Nahdh S. M. Al-Saif ◽  
Ameen Sh. Ameen ◽  
Ghaith Fadhil Abbas2
Keyword(s):  
Neural Network ◽  
Integral Equations ◽  
Three Dimensional ◽  
Volterra Integral Equations ◽  
Three Dimensions ◽  
Feed Forward Neural Network ◽  
Transform Method ◽  
Linear Transfer Function ◽  
Differential Transform ◽  
Hidden Layer

The aim of this paper  is present a new numerical method for solvingThree Dimensions Volterra Integral Equations using artificial neural network by design multilayer feed forward Neural Network. A multi- layers design in our proposed method consist of a hidden layer having seven hidden units. and one linear output unit. Linear Transfer function used as each unit and using Levenberg- Marquardtalgorithmtraining. Moreover, examples on three- dimensional Volterra integral equations carried out to illustrate the accuracy and the efficiency of the presented method. In addition, some comparisons among proposed method and Shifted Chebyshev Polynomials method and Reduced Differential Transform Method are presented.   http://dx.doi.org/10.25130/tjps.23.2018.176

Spatial Distribution of Gravity-Dependent Gain Changes in the Vestibuloocular Reflex

2005 ◽  
Vol 93 (6) ◽  
pp. 3693-3698 ◽  
Author(s):  
Sergei B. Yakushin ◽  
Yongqing Xiang ◽  
Theodore Raphan ◽  
Bernard Cohen
Keyword(s):  
Dimensional Space ◽  
Three Dimensional ◽  
Head Tilt ◽  
Fundamental Property ◽  
Head Position ◽  
Three Dimensions ◽  
Vestibuloocular Reflex ◽  
Gain Adaptation ◽  
The Stability ◽  
Three Dimensional Space

This study determined whether dependence of angular vestibuloocular reflex (aVOR) gain adaptation on gravity is a fundamental property in three dimensions. Horizontal aVOR gains were adaptively increased or decreased in two cynomolgus monkeys in upright, side down, prone, and supine positions, and aVOR gains were tested in darkness by yaw rotation with the head in a wide variety of orientations. Horizontal aVOR gain changes peaked at the head position in which the adaptation took place and gradually decreased as the head moved away from this position in any direction. The gain changes were plotted as a function of head tilt and fit with a sinusoid plus a bias to obtain the gravity-dependent (amplitude) and gravity-independent (bias) components. Peak-to-peak gravity-dependent gain changes in planes containing the position of adaptation and the magnitude of the gravity-independent components were both ∼25%. We assumed that gain changes over three-dimensional space could be described by a sinusoid the amplitude of which also varied sinusoidally. Using gain changes obtained from the head position in which the gains were adapted, a three-dimensional surface was generated that was qualitatively similar to a surface obtained from the experimental data. This extends previous findings on vertical aVOR gain adaptation in one plane and introduces a conceptual framework for understanding plasticity in three dimensions: aVOR gain changes are composed of two components, one of which depends on head position relative to gravity. It is likely that this gravitational dependence optimizes the stability of retinal images during movement in three-dimensional space.

scholarly journals Dynamic triaxial constitutive model for rock subjected to initial stress

Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 149-163
Author(s):  
Junzhe Li ◽  
Guang Zhang ◽  
Mingze Liu ◽  
Shaohua Hu ◽  
Xinlong Zhou
Keyword(s):  
Constitutive Model ◽  
Impact Load ◽  
Three Dimensional ◽  
Estimation Method ◽  
Constant Strain Rate ◽  
Strain Curve ◽  
Initial Pressure ◽  
Expansion Method ◽  
Three Dimensions ◽  
Model Parameters

AbstractBuilding on the existing model, an improved constitutive model for rock is proposed and extended in three dimensions. The model can avoid the defect of non-zero dynamic stress at the beginning of impact loading, and the number of parameters is in a suitable range. The three-dimensional expansion method of the component combination model is similar to that of the Hooke spring, which is easy to operate and understand. For the determination of model parameters, the shared parameter estimation method based on the Levenberg–Marquardt and the Universal Global Optimization algorithm is used, which can be well applied to models with parameters that do not change with confinement and strain rates. According to the established dynamic constitutive equation, the stress–strain curve of rock under the coupling action of the initial hydrostatic pressure load and constant strain-rate impact load can be estimated theoretically. By comparing the theoretical curve with the test data, it is shown that the dynamic constitutive model is suitable for the rock under the initial pressure and impact load.

A Three Dimensional Model of Zebrafish Swimming

2016 ◽  
Author(s):  
Violet Mwaffo ◽  
Sachit Butail ◽  
Maurizio Porfiri
Keyword(s):  
Ethical Issues ◽  
Three Dimensional ◽  
Coupled System ◽  
Ease Of Use ◽  
Three Dimensions ◽  
Alternative Methods ◽  
Model Parameters ◽  
Three Dimensional Model ◽  
Modeling Framework ◽  
Speed Modulation

Zebrafish is becoming an important animal model in pre-clinical studies for its genetic similarity to humans and ease of use in the laboratory. In recent years, animal experimentation has faced several ethical issues, calling for alternative methods that capitalize on dynamical systems theory. Here, we propose a computational modeling framework to simulate zebrafish swimming in three dimensions (3D) in the form of a coupled system of stochastic differential equations. The model is capable of reproducing the burst-and-coast swimming style of zebrafish, speed modulation, and avoidance of tank boundaries. Model parameters are calibrated on an experimental dataset of zebrafish swimming in 3D and validated by comparing established behavioral measures obtained from both synthetic and experimental data. We show that the model is capable of accurately predicting fish locomotion in terms of the swimming speed and number of entries in different sections of the tank. The proposed model lays the foundations for in-silico experiments of zebrafish neurobehavioral research.

scholarly journals Elastoplastic Model and Three-Dimensional Method for Unsaturated Soils

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Jinjin Fang ◽  
Yixin Feng
Keyword(s):  
Constitutive Model ◽  
Unsaturated Soils ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Degree Of Saturation ◽  
Triaxial Tests ◽  
Model Parameters ◽  
Elastoplastic Model ◽  
True Triaxial ◽  
Elastoplastic Constitutive Model

This paper proposed a new elastoplastic constitutive model to predict the deformation and strength behaviour of unsaturated soils. Applying the modified Cambridge model as a generalization, the degree of saturation is introduced into the elastoplastic model of unsaturated soil. Under the condition of ensuring that the model parameters are unchanged, the model is transformed into three dimensions based on the SMP criterion transformation stress method. Enhanced modified van Genuchten model under true triaxial conditions is also proposed in this paper to describe hydromechanical behaviours of unsaturated soils. The proposed constitutive model can capture the observed mechanical and hydraulic behaviours. Then, the model is validated via equal p and equal b value true triaxial tests, and the results show that a reasonable agreement can be obtained.

Three Dimensional Eye Movements of Squirrel Monkeys Following Postrotatory Tilt

1993 ◽  
Vol 3 (2) ◽  
pp. 123-139 ◽  
Author(s):  
Daniel M. Merfeld ◽  
Laurence R. Young ◽  
Gary D. Paige ◽  
David L. Tomko
Keyword(s):  
Eye Movements ◽  
Time Course ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Head Orientation ◽  
Ocular Reflex ◽  
Eye Rotation ◽  
Acceleration And Deceleration ◽  
Vestibulo Ocular Reflex ◽  
Vertical Nystagmus

Three-dimensional squirrel monkey eye movements were recorded during and immediately following rotation around an earth-vertical yaw axis (160∘/s steady state, 100∘/s2 acceleration and deceleration). To study interactions between the horizontal angular vestibulo-ocular reflex (VOR) and head orientation, postrotatory VOR alignment was changed relative to gravity by tilting the head out of the horizontal plane (pitch or roll tilt between 15∘ and 90∘) immediately after cessation of motion. Results showed that in addition to post rotatory horizontal nystagmus, vertical nystagmus followed tilts to the left or right (roll), and torsional nystagmus followed forward or backward (pitch) tilts. When the time course and spatial orientation of eye velocity were considered in three dimensions, the axis of eye rotation always shifted toward alignment with gravity, and the postrotatory horizontal VOR decay was accelerated by the tilts. These phenomena may reflect a neural process that resolves the sensory conflict induced by this postrotatory tilt paradigm.

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