Neural Correlates for Roughness Choice in Monkey Second Somatosensory Cortex (SII)

2001 ◽  
Vol 86 (4) ◽  
pp. 2069-2080 ◽  
Author(s):  
J. R. Pruett ◽  
R. J. Sinclair ◽  
H. Burton
Keyword(s):  
Somatosensory Cortex ◽  
Three Dimensional ◽  
Scanning Speed ◽  
Classification Performance ◽  
Groove Width ◽  
Neural Firing ◽  
Negative Effects ◽  
Firing Rates ◽  
Wide Groove ◽  
Roughness Classification

This experiment explored the relationship between neural firing patterns in second somatosensory cortex (SII) and decisions about roughness of tactile gratings. Neural and behavioral data were acquired while monkeys made dichotomous roughness classifications of pairs of gratings that differed in groove width (1.07 vs. 1.90 and 1.42 vs. 2.53 mm). A computer-controlled device delivered the gratings to a single immobilized finger pad. In one set of experiments, three levels of contact force (30, 60, and 90 g) were assigned to these gratings at random. In another set of experiments, three levels of scanning speed (40, 80, and 120 mm/s) were assigned to these gratings at random. Groove width was the intended variable for roughness. Force variation disrupted the monkeys' groove-width (roughness) classifications more than did speed variation. A sample of 32 SII cells showed correlated changes in firing (positive or negative effects of both variables) when groove width and force increased. While these cells were recorded, the monkeys made roughness classification errors, confusing wide groove-width gratings at low force with narrow groove-width gratings at high force. Three-dimensional plots show how some combinations of groove width and force perturbed the monkeys' trial-wise classifications of grating roughness. Psychometric functions show that errors occurred when firing rates failed to distinguish gratings. A possible interpretation is that when asked to classify grating roughness, the monkeys based classifications on the firing rates of a subset of roughness-sensitive cells in SII. Results support human psychophysical data and extend the roughness range of a model of the effects of groove width and force on roughness. One monkey's SII neural sample (21 cells) showed significant correlation between firing rate response functions for groove width and speed (both correlations either positive or negative). Only that monkey showed a statistically significant interaction between groove width and speed on roughness classification performance. This additional finding adds weight to the argument that SII cell firing rates influenced monkey roughness classifications.

Response Patterns in Second Somatosensory Cortex (SII) of Awake Monkeys to Passively Applied Tactile Gratings

2000 ◽  
Vol 84 (2) ◽  
pp. 780-797 ◽  
Author(s):  
J. R. Pruett ◽  
R. J. Sinclair ◽  
H. Burton
Keyword(s):  
Somatosensory Cortex ◽  
Hand Movement ◽  
Scanning Speed ◽  
Random Force ◽  
Groove Width ◽  
Hand Position ◽  
Sample Population ◽  
Firing Rates ◽  
Passive Touch ◽  
Movement Parameters

This experiment explored the effects of controlled manipulations of three parameters of tactile gratings, groove width (1.07–2.53 mm), contact force (30–90 g), and scanning speed (40–120 mm/s), on the responses of cells in second somatosensory cortex (SII) of awake monkeys that were performing a groove-width classification task with passively presented stimuli. A previous experiment involving an active touch paradigm demonstrated that macaque SII cells code groove-width and hand-movement parameters in their average firing rates. The present study used a passive-touch protocol to remove somatosensory activation related to hand movements that accompany haptic exploration of surfaces. Monkeys maintained a constant hand position while a robotic device delivered stimulation with tactile gratings to a single stabilized finger pad. Single-unit recordings isolated 216 neurons that were retrospectively assigned to SII on histological criteria. Firing patterns for 86 of these SII cells were characterized in detail, while monkeys classified gratings as rough (1.90 and 2.53 mm groove widths) or smooth (1.07 and 1.42 mm groove widths), with trial-wise random, parametric manipulation of force or speed; the monkeys compared 1.07 versus 1.90 mm and 1.42 versus 2.53 mm in alternating blocks of trials. We studied 33 cells with systematic variation of groove width and force, 49 with groove width and speed, and four with all three variables. Sixty-three cells were sensitive to groove width, 43 to force (effects of random force in speed experiments contributed to N), and 34 to speed. Relatively equal numbers of cells changed mean firing rates as positive or negative functions of increasing groove width, force, and/or speed. Cells typically changed mean firing rates for two or three of the independent variables. Effects of groove width, force, and speed were additive or interactive. The variety of response functions was similar to that found in a prior study of primary somatosensory cortex (SI) that used passive touch. The SII sample population showed correlated changes (both positive and negative) in firing rates with increasing groove width and force and to a lesser degree, with increasing groove width and speed. This correlation is consistent with human psychophysical studies that found increasing groove width and force increase perceived roughness magnitude, and it strengthens the argument for SII's direct involvement in roughness perception.

Methylene blue induces an analgesic effect by significantly decreasing neural firing rates and improves pain behaviors in rats

2021 ◽  
Vol 541 ◽  
pp. 36-42
Author(s):  
Seung Won Lee ◽  
Sun Wook Moon ◽  
Jin Sung Park ◽  
Hye Rim Suh ◽  
Hee Chul Han
Keyword(s):  
Methylene Blue ◽  
Analgesic Effect ◽  
Neural Firing ◽  
Firing Rates ◽  
Pain Behaviors

On three-dimensional printing of 17-4 precipitation-hardenable stainless steel with direct metal laser sintering in aircraft structural applications

2021 ◽  
pp. 146442072110448
Author(s):  
Rupinder Singh ◽  
Rishab ◽  
Jashanpreet S Sidhu
Keyword(s):  
Stainless Steel ◽  
Structural Engineering ◽  
Three Dimensional ◽  
Surface Hardness ◽  
Dimensional Accuracy ◽  
Scanning Speed ◽  
Laser Sintering ◽  
Structural Components ◽  
Direct Metal Laser Sintering ◽  
Structural Applications

The martensitic 17-4 precipitation-hardenable stainless steel is one of the commercially established materials for structural engineering applications in aircrafts due to its superior mechanical and corrosion resistance properties. The mechanical processing of this alloy through a conventional manufacturing route is critical from the dimensional accuracy (Δ d) viewpoint for development of innovative structural components such as: slat tracks, wing flap tracks, etc. In past two decades, a number of studies have been reported on challenges being faced while conventional processing of 17-4 precipitation-hardenable stainless steel for maintaining uniform thickness of aircraft structural components. However, hitherto little has been reported on direct metal laser sintering of 17-4 precipitation-hardenable stainless steel for development of innovative functional prototypes with uniform surface hardness (HV), Δ d, and surface roughness ( Ra) in aircraft structural engineering. This paper reports the effect of direct metal laser sintering process parameters on HV, Δ d, and Ra for structural components. The results of study suggest that optimized settings of direct metal laser sintering from multifactor optimization viewpoint are laser power 100 W, scanning speed 1400 mm/s, and layer thickness 0.02 mm. The results have been supported with scanning electron microscopy analysis (for metallurgical changes such as porosity (%), HV, grain size, etc.) and international tolerance grades for ensuring assembly fitment.

scholarly journals Development of a Pattern Recognition Tool for the Classification of Electronic Tongue Signals Using Machine Learning

2021 ◽  
Vol 5 (1) ◽  
pp. 21
Author(s):  
Edgar G. Mendez-Lopez ◽  
Jersson X. Leon-Medina ◽  
Diego A. Tibaduiza
Keyword(s):  
Machine Learning ◽  
Dimensionality Reduction ◽  
Performance Measures ◽  
Sensor Array ◽  
Three Dimensional ◽  
Electronic Tongue ◽  
Sensor Arrays ◽  
Classification Performance ◽  
Supervised Machine Learning ◽  
Electrochemical Tests

Electronic tongue type sensor arrays are made of different materials with the property of capturing signals independently by each sensor. The signals captured when conducting electrochemical tests often have high dimensionality, which increases when performing the data unfolding process. This unfolding process consists of arranging the data coming from different experiments, sensors, and sample times, thus the obtained information is arranged in a two-dimensional matrix. In this work, a description of a tool for the analysis of electronic tongue signals is developed. This tool is developed in Matlab® App Designer, to process and classify the data from different substances analyzed by an electronic tongue type sensor array. The data processing is carried out through the execution of the following stages: (1) data unfolding, (2) normalization, (3) dimensionality reduction, (4) classification through a supervised machine learning model, and finally (5) a cross-validation procedure to calculate a set of classification performance measures. Some important characteristics of this tool are the possibility to tune the parameters of the dimensionality reduction and classifier algorithms, and also plot the two and three-dimensional scatter plot of the features after reduced the dimensionality. This to see the data separability between classes and compatibility in each class. This interface is successfully tested with two electronic tongue sensor array datasets with multi-frequency large amplitude pulse voltammetry (MLAPV) signals. The developed graphical user interface allows comparing different methods in each of the mentioned stages to find the best combination of methods and thus obtain the highest values of classification performance measures.

Presurgical Three-Dimensional Magnetic Source Imaging of the Somatosensory Cortex in a Patient with a Peri-Rolandic Lesion

Neurosurgery ◽  
1994 ◽  
Vol 34 (5) ◽  
pp. 930-934 ◽  
Author(s):  
Takato Morioka ◽  
Tomoya Yamamoto ◽  
Toshiro Katsuta ◽  
Kiyotaka Fujii ◽  
Masashi Fukui
Keyword(s):  
Somatosensory Cortex ◽  
Three Dimensional ◽  
Source Imaging ◽  
Magnetic Source Imaging ◽  
Magnetic Source

scholarly journals Coasting in live-bearing fish: the drag penalty of being pregnant

2019 ◽  
Vol 16 (151) ◽  
pp. 20180714 ◽  
Author(s):  
Elsa M. Quicazan-Rubio ◽  
Johan L. van Leeuwen ◽  
Klaas van Manen ◽  
Mike Fleuren ◽  
Bart J. A. Pollux ◽  
...  
Keyword(s):  
Swimming Performance ◽  
Three Dimensional ◽  
Reproductive Investment ◽  
Body Volume ◽  
Negative Effects ◽  
Bending Performance ◽  
Body Drag ◽  
Wetted Area ◽  
Three Dimensional Models ◽  
Different Levels

Swimming performance of pregnant live-bearing fish is presumably constrained by the additional drag associated with the reproductive burden. Yet, it is still unclear how and to what extent the reproductive investment affects body drag of the females. We examined the effect of different levels of reproductive investment on body drag. The biggest measured increase in body volume due to pregnancy was about 43%, linked to a wetted area increase of about 16% and 69% for the frontal area. We printed three-dimensional models of live-bearing fish in a straight body posture representing different reproductive allocation (RA) levels. We measured the drag and visualized the flow around these models in a flow tunnel at different speeds. Drag grew in a power fashion with speed and exponentially with the increase of RA, thus drag penalty for becoming thicker was relatively low for low speeds compared to high ones. We show that the drag increase with increasing RA was most probably due to bigger regions of flow separation behind the enlarged belly. We suggest that the rising drag penalty with an increasing RA, possibly together with pregnancy-related negative effects on muscle- and abdominal bending performance, will reduce the maximum swimming speed.

Experimental Study on Geometric Precision of Microholes Drilling by Picosecond Laser

2019 ◽  
Author(s):  
Zhanfei Zhang ◽  
Wenhu Wang ◽  
Ruisong Jiang ◽  
Chengcheng Jin ◽  
Xiaoxiang Zhu ◽  
...  
Keyword(s):  
Film Cooling ◽  
Three Dimensional ◽  
Great Influence ◽  
Picosecond Laser ◽  
Scanning Speed ◽  
Cooling Efficiency ◽  
Measuring Instrument ◽  
Geometric Precision ◽  
Cooling Hole ◽  
Film Cooling Holes

Abstract The geometric precision of the film cooling hole has a great influence on the cooling efficiency and fatigue life of the turbine blade. In the paper, the processing of film cooling holes on DD6 single crystal superalloy by picosecond laser is investigated. The pulse laser at pulse duration of 2.1ps, the wavelength of 1030 nm and the repetition frequency of 75 kHz are selected to study the pulse energy, scanning speed, defocus and scanning width on the geometric precision of the film cooling hole. After drilling, the three-dimensional coordinates of the entrance and exit plane of the film cooling holes are obtained by using the three-dimensional surface measuring instrument. The diameter, roundness and taper of the film cooling holes are calculated by extracting and processing the coordinate points of the contour around the microholes. The experimental results show that defocusing has the greatest influence on the taper and roundness of film cooling holes. Negative defocusing can produce severe plasma shielding, which makes the exit roundness and taper larger. With larger pulses, positive defocusing and larger scanning width, smaller roundness and taper can be produced.

scholarly journals Effect of Process Parameters and Material Properties on Laser Micromachining of Microchannels

Micromachines ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 123 ◽  
Author(s):  
Matthew Benton ◽  
Mohammad Hossan ◽  
Prashanth Konari ◽  
Sanjeewa Gamagedara
Keyword(s):  
Process Parameters ◽  
Laser System ◽  
Three Dimensional ◽  
Microfluidic Devices ◽  
Scanning Speed ◽  
Transient Heat Conduction ◽  
Laser Micromachining ◽  
Rapid Phase ◽  
Widespread Application ◽  
Optimization Of Process Parameters

Laser micromachining has emerged as a promising technique for mass production of microfluidic devices. However, control and optimization of process parameters, and design of substrate materials are still ongoing challenges for the widespread application of laser micromachining. This article reports a systematic study on the effect of laser system parameters and thermo-physical properties of substrate materials on laser micromachining. Three dimensional transient heat conduction equation with a Gaussian laser heat source was solved using finite element based Multiphysics software COMSOL 5.2a. Large heat convection coefficients were used to consider the rapid phase transition of the material during the laser treatment. The depth of the laser cut was measured by removing material at a pre-set temperature. The grid independent analysis was performed for ensuring the accuracy of the model. The results show that laser power and scanning speed have a strong effect on the channel depth, while the level of focus of the laser beam contributes in determining both the depth and width of the channel. Higher thermal conductivity results deeper in cuts, in contrast the higher specific heat produces shallower channels for a given condition. These findings can help in designing and optimizing process parameters for laser micromachining of microfluidic devices.

Neural correlates of nystagmus in abducens nerve

1979 ◽  
Vol 42 (5) ◽  
pp. 1282-1296 ◽  
Author(s):  
V. Honrubia ◽  
D. B. Reingold ◽  
C. G. Lau ◽  
P. H. Ward
Keyword(s):  
Low Frequency ◽  
Abducens Nerve ◽  
Head Rotation ◽  
Phase Lag ◽  
Neural Firing ◽  
Neural Responses ◽  
Firing Rates ◽  
Viscous Forces ◽  
Phase Angle Difference ◽  
Phase Lead

1. The firing rates of action potentials of abducens nerve single fibers were recorded in the cat's orbit during a variety of vestibular and optokinetic stimulations. 2. Comparison was made of the neural firing rates associated with agonist and antagonist responses during slow and fast components of vestibular and optokinetic nystagmus. It was found that the relationship between the motoneuron firing rates and the eye motion was independent of the reflex with which they were associated--vestibular or optokinetic, or the type of response--agonist or antagonist. No neurons were observed that responded only during the fast or only during the slow nystagmus phase. Motoneuron firing rates were proportional to both velocity and position of the eye in a ratio of 1 (spikes/s)/(deg/s) to 7.2 (spikes/s)/deg. The behavior of the motoneurons was compatible with the hypothesis that thier firing rates are sufficient to overcome both elastic and viscous forces by which the muscles and ligaments hold the eye in the orbit. 3. For low-frequency head rotations, eye displacement and neural responses showed a small phase angle difference. At higher frequencies, however, while the eyes maintained a fixed relationship to the head rotation, the neural responses showed an increasing phase lead. One component of this phase lead compensated for the phase lag introduced by the orbital mechanics. The other was modeled as a constant delay of approximately 70 ms, which may be accounted for by neuromuscular transmission and transduction.

scholarly journals A Developed Siamese CNN with 3D Adaptive Spatial-Spectral Pyramid Pooling for Hyperspectral Image Classification

2020 ◽  
Vol 12 (12) ◽  
pp. 1964 ◽  
Author(s):  
Mengbin Rao ◽  
Ping Tang ◽  
Zheng Zhang
Keyword(s):  
Transfer Learning ◽  
Hyperspectral Image ◽  
Three Dimensional ◽  
Classification Performance ◽  
Generalization Capability ◽  
Training Strategy ◽  
Learning Framework ◽  
Spectral Bands ◽  
Learning Tasks ◽  
3D Information

Since hyperspectral images (HSI) captured by different sensors often contain different number of bands, but most of the convolutional neural networks (CNN) require a fixed-size input, the generalization capability of deep CNNs to use heterogeneous input to achieve better classification performance has become a research focus. For classification tasks with limited labeled samples, the training strategy of feeding CNNs with sample-pairs instead of single sample has proven to be an efficient approach. Following this strategy, we propose a Siamese CNN with three-dimensional (3D) adaptive spatial-spectral pyramid pooling (ASSP) layer, called ASSP-SCNN, that takes as input 3D sample-pair with varying size and can easily be transferred to another HSI dataset regardless of the number of spectral bands. The 3D ASSP layer can also extract different levels of 3D information to improve the classification performance of the equipped CNN. To evaluate the classification and generalization performance of ASSP-SCNN, our experiments consist of two parts: the experiments of ASSP-SCNN without pre-training and the experiments of ASSP-SCNN-based transfer learning framework. Experimental results on three HSI datasets demonstrate that both ASSP-SCNN without pre-training and transfer learning based on ASSP-SCNN achieve higher classification accuracies than several state-of-the-art CNN-based methods. Moreover, we also compare the performance of ASSP-SCNN on different transfer learning tasks, which further verifies that ASSP-SCNN has a strong generalization capability.

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