scholarly journals The non-linear mixed representations in somatosensory cortex support simple and complex tasks

2021 ◽  
Author(s):  
Ramon Nogueira ◽  
Chris C. Rodgers ◽  
Randy M. Bruno ◽  
Stefano Fusi
Keyword(s):  
Somatosensory Cortex ◽  
Neural Activity ◽  
High Speed ◽  
Barrel Cortex ◽  
Broad Class ◽  
High Dimensional ◽  
Complex Tasks ◽  
Sensory Inputs ◽  
Neural Representations ◽  
Non Linear

Adaptive behavior in humans, rodents, and other animals often requires the integration over time of multiple sensory inputs. Here we studied the behavior and the neural activity of mice trained to actively integrate information from different whiskers to report the curvature of an object. The analysis of high speed videos of the whiskers revealed that the task could be solved by integrating linearly the whisker contacts on the object. However, recordings from the mouse barrel cortex revealed that the neural representations are high dimensional as the inputs from multiple whiskers are mixed non-linearly to produce the observed neural activity. The observed representation enables the animal to perform a broad class of significantly more complex tasks, with minimal disruption of the ability to generalize to novel situations in simpler tasks. Simulated recurrent neural networks trained to perform similar tasks reproduced both the behavioral and neuronal experimental observations. Our work suggests that the somatosensory cortex operates in a regime that represents an efficient compromise between generalization, which typically requires pure and linear mixed selectivity representations, and the ability to perform complex discrimination tasks, which is granted by non-linear mixed representations.

Infrared thermal imaging of rat somatosensory cortex with whisker stimulation

2012 ◽  
Vol 112 (7) ◽  
pp. 1215-1222 ◽  
Author(s):  
Takashi Suzuki ◽  
Yasuhiro Ooi ◽  
Junji Seki
Keyword(s):  
Somatosensory Cortex ◽  
Neural Activity ◽  
Thermal Imaging ◽  
Temperature Increase ◽  
Barrel Cortex ◽  
Brain Temperature ◽  
Local Thermal Equilibrium ◽  
Neural Activation ◽  
Whisker Stimulation ◽  
The Brain

The present study aims to validate the applicability of infrared (IR) thermal imaging for the study of brain function through experiments on the rat barrel cortex. Regional changes in neural activity within the brain produce alterations in local thermal equilibrium via increases in metabolic activity and blood flow. We studied the relationship between temperature change and neural activity in anesthetized rats using IR imaging to visualize stimulus-induced changes in the somatosensory cortex of the brain. Sensory stimulation of the vibrissae (whiskers) was given for 10 s using an oscillating whisker vibrator (5-mm deflection at 10, 5, and 1 Hz). The brain temperature in the observational region continued to increase significantly with whisker stimulation. The mean peak recorded temperature changes were 0.048 ± 0.028, 0.054 ± 0.036, and 0.097 ± 0.015°C at 10, 5, and 1 Hz, respectively. We also observed that the temperature increase occurred in a focal spot, radiating to encompass a larger region within the contralateral barrel cortex region during single-whisker stimulation. Whisker stimulation also produced ipsilateral cortex temperature increases, which were localized in the same region as the pial arterioles. Temperature increase in the barrel cortex was also observed in rats treated with a calcium channel blocker (nimodipine), which acts to suppress the hemodynamic response to neural activity. Thus the location and area of temperature increase were found to change in accordance with the region of neural activation. These results indicate that IR thermal imaging is viable as a functional quantitative neuroimaging technique.

Nearly Exact Bayesian Estimation of Non-linear No-Arbitrage Term-Structure Models*

2021 ◽  
Author(s):  
Marcello Pericoli ◽  
Marco Taboga
Keyword(s):  
Bayesian Estimation ◽  
Term Structure ◽  
Broad Class ◽  
Model Parameters ◽  
State Variables ◽  
Computationally Efficient ◽  
Macroeconomic Factors ◽  
No Arbitrage ◽  
Term Structure Models ◽  
Non Linear

Abstract We propose a general method for the Bayesian estimation of a very broad class of non-linear no-arbitrage term-structure models. The main innovation we introduce is a computationally efficient method, based on deep learning techniques, for approximating no-arbitrage model-implied bond yields to any desired degree of accuracy. Once the pricing function is approximated, the posterior distribution of model parameters and unobservable state variables can be estimated by standard Markov Chain Monte Carlo methods. As an illustrative example, we apply the proposed techniques to the estimation of a shadow-rate model with a time-varying lower bound and unspanned macroeconomic factors.

scholarly journals A Practical Numerical Approach to Characterizing Non-Linear Shrinkage and Optimizing Dimensional Deviation of Injection-Molded Small Module Plastic Gears

Polymers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 2092
Author(s):  
Xiansong He ◽  
Wangqing Wu
Keyword(s):  
Injection Molding ◽  
High Speed ◽  
Numerical Approach ◽  
Linear Shrinkage ◽  
Influential Factor ◽  
Dimensional Deviation ◽  
Non Linear ◽  
Injection Molded ◽  
Plastic Gears ◽  
Circle Diameter

This paper was aimed at finding out the solution to the problem of insufficient dimensional accuracy caused by non-linear shrinkage deformation during injection molding of small module plastic gears. A practical numerical approach was proposed to characterize the non-linear shrinkage and optimize the dimensional deviation of the small module plastic gears. Specifically, Moldflow analysis was applied to visually simulate the shrinkage process of small module plastic gears during injection molding. A 3D shrinkage gear model was obtained and exported to compare with the designed gear model. After analyzing the non-linear shrinkage characteristics, the dimensional deviation of the addendum circle diameter and root circle diameter was investigated by orthogonal experiments. In the end, a high-speed cooling concept for the mold plate and the gear cavity was proposed to optimize the dimensional deviation. It was confirmed that the cooling rate is the most influential factor on the non-linear shrinkage of the injection-molded small module plastic gears. The dimensional deviation of the addendum circle diameter and the root circle diameter can be reduced by 22.79% and 22.99% with the proposed high-speed cooling concept, respectively.

scholarly journals An Improved Lagrangian-Inverse Method for Evaluating the Dynamic Constitutive Parameters of Concrete

Materials ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1871
Author(s):  
Xinlu Yu ◽  
Yingqian Fu ◽  
Xinlong Dong ◽  
Fenghua Zhou ◽  
Jianguo Ning
Keyword(s):  
High Speed ◽  
Inverse Method ◽  
Image Correlation ◽  
Analysis Method ◽  
Stress Strain ◽  
Optical Techniques ◽  
Element Simulation ◽  
Non Linear ◽  
Constitutive Parameters ◽  
Inverse Analysis Method

The dynamic constitutive behaviors of concrete-like materials are of vital importance for structure designing under impact loading conditions. This study proposes a new method to evaluate the constitutive behaviors of ordinary concrete at high strain rates. The proposed method combines the Lagrangian-inverse analysis method with optical techniques (ultra-high-speed camera and digital image correlation techniques). The proposed method is validated against finite-element simulation. Spalling tests were conducted on concretes where optical techniques were employed to obtain the high-frequency spatial and temporal displacement data. We then obtained stress–strain curves of concrete by applying the proposed method on the results of spalling tests. The results show non-linear constitutive behaviors in these stress–strain curves. These non-linear constitutive behaviors can be possibly explained by local heterogeneity of concrete. The proposed method provides an alternative mean to access the dynamic constitutive behaviors which can help future structure designing of concrete-like materials.

scholarly journals Optimal nonlinear eddy viscosity in Galerkin models of turbulent flows

2015 ◽  
Vol 766 ◽  
pp. 337-367 ◽  
Author(s):  
Bartosz Protas ◽  
Bernd R. Noack ◽  
Jan Östh
Keyword(s):  
Turbulent Flows ◽  
High Speed ◽  
Eddy Viscosity ◽  
Broad Class ◽  
Constitutive Relations ◽  
Body Height ◽  
Mixing Layer ◽  
The Body ◽  
Stream Velocity ◽  
Initial Vorticity

AbstractWe propose a variational approach to the identification of an optimal nonlinear eddy viscosity as a subscale turbulence representation for proper orthogonal decomposition (POD) models. The ansatz for the eddy viscosity is given in terms of an arbitrary function of the resolved fluctuation energy. This function is found as a minimizer of a cost functional measuring the difference between the target data coming from a resolved direct or large-eddy simulation of the flow and its reconstruction based on the POD model. The optimization is performed with a data-assimilation approach generalizing the 4D-VAR method. POD models with optimal eddy viscosities are presented for a 2D incompressible mixing layer at $\mathit{Re}=500$ (based on the initial vorticity thickness and the velocity of the high-speed stream) and a 3D Ahmed body wake at $\mathit{Re}=300\,000$ (based on the body height and the free-stream velocity). The variational optimization formulation elucidates a number of interesting physical insights concerning the eddy-viscosity ansatz used. The 20-dimensional model of the mixing-layer reveals a negative eddy-viscosity regime at low fluctuation levels which improves the transient times towards the attractor. The 100-dimensional wake model yields more accurate energy distributions as compared to the nonlinear modal eddy-viscosity benchmark proposed recently by Östh et al. (J. Fluid Mech., vol. 747, 2014, pp. 518–544). Our methodology can be applied to construct quite arbitrary closure relations and, more generally, constitutive relations optimizing statistical properties of a broad class of reduced-order models.

Non-linear parametric modelling of a high-speed rail hydraulic yaw damper with series clearance and stiffness

2010 ◽  
Vol 65 (1-2) ◽  
pp. 13-34 ◽  
Author(s):  
W. L. Wang ◽  
Y. Huang ◽  
X. J. Yang ◽  
G. X. Xu
Keyword(s):  
High Speed ◽  
Parametric Modelling ◽  
High Speed Rail ◽  
Non Linear

Attribute-based Explanation of Non-Linear Embeddings of High-Dimensional Data

2021 ◽  
pp. 1-1
Author(s):  
Jan-Tobias Sohns ◽  
Michaela Schmitt ◽  
Fabian Jirasek ◽  
Hans Hasse ◽  
Heike Leitte
Keyword(s):  
High Dimensional Data ◽  
High Dimensional ◽  
Non Linear
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