<p>(<b>A</b>) MDVs for the 8 muscle groups. SFi, inner shoulder flexor (blue); SFo, outer shoulder flexor (light blue); SEi, inner shoulder extensor (orange); SEo, outer shoulder extensor (yellow); EF, elbow flexor (green); EE, elbow extensor (magenta); BiF, biarticular flexor (cyan); and BiE, biarticular extensor (red). (<b>B</b>) Distribution of the MDVs for 1000 neurons. (<b>C</b>) PDs plotted against MDs. (<b>D</b>) PDs of the 8 muscles after learning. (<b>E</b>) Distribution of the PDVs for 1000 neurons after learning. (<b>F</b>) Polar histogram of the neuronal PDs after learning.</p
<p>A: Velocity dependent force fields VF1, VF2, VF4. B: Evolution of correlation between velocity pr...
A. Activity profile of one simulated neuron during its activation period is scaled for the five simu...
<p>Learning directly on a circle (C,D,F,G) or training reaching movements in all directions (B,E,H) ...
<p>(<b>A</b>) Neural network model with a muscle layer. The model consists of an input layer, a 2<su...
<p>(<b>A</b>) The arrows indicate the muscle MDVs in linear acceleration space. DP, posterior part o...
<p>Trial-dependent changes in the magnitude of error (<b>A, B</b>), the norm of the neural activity ...
<p>A) First dimension yields separation between the black cluster (corresponding to the no-movement ...
A computational model is being developed to understand possible mechanisms for the influence of a ne...
<p>Top panel: time evolution of the three joint angles (retraction, red), (levation, black), and ...
We can easily learn and perform a variety of movements that fundamentally require complex neuromuscu...
<div><p>(A) Motor parameters (blue) and their prediction using linear models (red). From top to bott...
We can easily learn and perform a variety of movements that fundamentally require complex neuromuscu...
<p>The average cortical activity of the shoulder flexor (black traces) and the shoulder extensor (re...
This thesis describes computational approaches to modeling and simulating aspects of the neuromuscul...
Introduction: The validation of the involved muscular forces for a computer model of the human body,...
<p>A: Velocity dependent force fields VF1, VF2, VF4. B: Evolution of correlation between velocity pr...
A. Activity profile of one simulated neuron during its activation period is scaled for the five simu...
<p>Learning directly on a circle (C,D,F,G) or training reaching movements in all directions (B,E,H) ...
<p>(<b>A</b>) Neural network model with a muscle layer. The model consists of an input layer, a 2<su...
<p>(<b>A</b>) The arrows indicate the muscle MDVs in linear acceleration space. DP, posterior part o...
<p>Trial-dependent changes in the magnitude of error (<b>A, B</b>), the norm of the neural activity ...
<p>A) First dimension yields separation between the black cluster (corresponding to the no-movement ...
A computational model is being developed to understand possible mechanisms for the influence of a ne...
<p>Top panel: time evolution of the three joint angles (retraction, red), (levation, black), and ...
We can easily learn and perform a variety of movements that fundamentally require complex neuromuscu...
<div><p>(A) Motor parameters (blue) and their prediction using linear models (red). From top to bott...
We can easily learn and perform a variety of movements that fundamentally require complex neuromuscu...
<p>The average cortical activity of the shoulder flexor (black traces) and the shoulder extensor (re...
This thesis describes computational approaches to modeling and simulating aspects of the neuromuscul...
Introduction: The validation of the involved muscular forces for a computer model of the human body,...
<p>A: Velocity dependent force fields VF1, VF2, VF4. B: Evolution of correlation between velocity pr...
A. Activity profile of one simulated neuron during its activation period is scaled for the five simu...
<p>Learning directly on a circle (C,D,F,G) or training reaching movements in all directions (B,E,H) ...