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4.1.7 Motor Neuron

Update Alert!

I have now finished work on a much more advanced version of the insect simulator named AnimatLab. AnimatLab is a software tool that combines biomechanical simulation and biologically realistic neural networks. You can build the body of an animal, robot, or other machine and place it in a virtual world where the physics of its interaction with the environment are accurate and realistic. You can then design a nervous system that controls the behavior of the body in the environment. The software currently has support for simple firing rate neuron models and leaky integrate and fire spiking neural models. In addition, there a number of different synapse model types that can be used to connect the various neural models to produce your nervous system. On the biomechanics side there is support for a variety of different rigid body types, including custom meshes that can be made to match skeletal structures exactly. The biomechanics system also has hill-based muscle and muscle spindle models. These muscle models allow the nervous system to produce movements around joints. In addition, there are also motorized joints for those interested in controlling robots or other biomimetic machines. This allows the user to generate incredibly complicated artificial lifeforms that are based on real biological systems. Best of all AnimatLab is completely free and it includes free C++ source code!

1. Motor Neuron Functionality

An Animal would not live very long if it could not move its muscles. It would not be able to search for food, flee from predators, find mates or any of the thousands of other things that an active animal needs to be able to do in order to survive in a hostile world. The purpose of the motor neuron is allow the insect to move its muscles. It does this in a very similar manner to how the sensory neuron performs its function. The user is able to associate an item from the sensory motor map with this motor neuron. The motor map item tells which specific data value that this neuron is looking at. For instance, the motor map could use the torque for the first leg as its data value. Unlike the sensory neuron, the data item here is an output and not an input. The motor neuron takes the current firing frequency of the neuron and uses the motor mapping function to calculate a given torque for that frequency. It then adds that torque to the total torque for that leg or jaw. So it is possible to have numerous motor neurons that all add torque to a given leg. This allows the user to set up opposing motor neurons for a single movable element like a leg. So for example, you could have one motor neuron that would apply a positive torque to the leg when it fires, and another motor neuron that would apply a negative torque to the leg when it fires. This is similar to the way that muscle systems really work by having muscles oppose one another and apply torques in opposite directions.

2. Motor Neuron Properties

Motor Neuron Dialog

Figure 1. This is a dialog for setting the properties for a motor neuron.

3. Motor Mapping Function

The motor mapping function is done exactly like the sensory mapping function. It just maps different things is all. The sensory neuron maps a input value to an intrinsic current. The motor neuron maps a firing frequency to an output value. For a more detailed description of the mapping functionality please see section 4.1.6.3 of the sensory neuron.

4. Motor Neuron Analysis

Motor Neuron Analysis

Video 1. This graph shows how the firing frequency of the motor neuron is related the rotation of the leg. Video Size: 5.7 Mb Motor ID: Leg 0 Torque Graph Type: Linear A: 1 B: 35 u C: 0

Video 1 shows how the firing frequency of the motor neurons are related to the torque that is applied to the leg and ultimately to the rotation of that leg. The swing neuron is responsible for causing the leg to rotate in a positive direction, and the stance neuron rotates the leg in a negative direction. When both of the neurons are firing at the same rate it causes no change in the torque. The reason for this is that the torques caused by the two motor neurons are additive. However, if the neurons are firing at different rates then there will be some net torque applied to the legs. How much torque will depend on the differences in the firing rates of the two neurons and the settings of the motor mapping function. One neuron might produce double the torque at the same firing frequency as another neuron would. Another question that might come to mind is why did the leg stop rotating at around 0.6 and -0.6 radians even though torque was still being applied. The reason is that the leg definition has minimum and maximum joint rotation values. These constraints keep the leg from rotating any further even if torque is applied to it. The video associated with the graph shows the insect leg moving and the values of the torque, rotation, and firing frequency in real time.

5. Motor Neuron Overview

The basic thing to remember about the motor neuron is that it converts firing frequency into torque. By using a number of these neurons and setting them up in opposition to each other it is possible to have control over the movement of parts of the insect like its legs and jaw. This provides the basic mechanism that allows the insect to move around in its environment and to eat.