The Neuron Model

Each of the five Atmel AT90S1200 chips in the ring is coded to act as an independent neuron. A Neuron is the basic cellular unit of a nervous system. A biological neuron contains thousands of ion channels and pumps that move ions across the cell membrane for the purpose of signaling. This hardware model simplifies the actual biology down to its aggregate integrate-and-fire behavior. This means that when ion concentrations change within the cell (usually cause by injecting a current, such as an action potential from a previous neuron, as in this 5-cell network) the membrane voltage changes to reflect the new chemical potential difference across the membrane. Should the membrane voltage be above some threshold value, it will fire an all-or-nothing action potential. The action potential has the same shape and duration for any given cell (in this case a square pulse generated by the processor), but in real life the shape can vary from cell to cell. The decision-making ability, through the use of threshold and action potential, is what allows for signal processing and motor control to be possible.
If disconnected from the network, each processor will generate bursting behavior on its own. The program loaded onto each chip solves the following four equations to update the four state variables in real-time.
The four state variables are Vm, Th, Spike, and GK. Vm is the voltage across the neuron’s membrane. Th is the threshold for firing spikes. Spike is the binary value of whether an action potential is being generated or not. And, GK controls the potassium conductance which restores the membrane voltage back to a resting potential.
The output of the chip (on pins 11-19) corresponds to the value of ‘Spike‘. The output of the program for typical parameter values is given below. The program flow is given in the chart to the left. The code was written in the Atmel assembly language. To implement the numerical integration scheme, divide and exponential routines had to be written. The code and an explanation of the exponential is given below.
As an additional experiment, the output of the cell was hooked back up to the input to create a positive feedback loop. The result was the bursting pattern, as shown below. This bursting ability of the cell is what allows for the cyclically inhibitory network to operate.

VmWhen ion concentrations change within the cell (usually cause by injecting a depolarizing current, such as an action potential from a previous neuron) the membrane voltage changes to reflect the new chemical potential difference across the membrane. Should the membrane voltage be above some threshold value, it will fire an all-or-nothing action potential

VmWhen ion concentrations change within the cell (usually cause by injecting a depolarizing current, such as an action potential from a previous neuron) the membrane voltage changes to reflect the new chemical potential difference across the membrane. Should the membrane voltage be above some threshold value, it will fire an all-or-nothing action potential