ANNs

1.The Nervous System
The human nervous system can be broken down into three stages that may be represented in block diagram form as:
The receptors collect information from the environment – e.g. photons on the retina.
The effectors generate interactions with the environment – e.g. activate muscles.
The flow of information/activation is represented by arrows – feed forward and feedback.
Naturally, in this module we will be primarily concerned with the neural network in the middle.

2.Basic Components of Biological Neurons
1. The majority of neurons encode their activations or outputs as a series of brief electrical pulses (i.e. spikes or action potentials).
2. The neuron’s cell body (soma) processes the incoming activations and converts them into output activations.

3. Dendrites are fibres which emanate from the cell body and provide the receptive zones that receive activation from other neurons.
4. Axons are fibres acting as transmission lines that send activation to other neurons.
5. The junctions that allow signal transmission between the axons and dendrites are called synapses. The process of transmission is by diffusion of chemicals called neurotransmitters across the synaptic cleft

? Dendrites receive activation from other neurons.
? Soma processes the incoming activations and converts them into output activations.
? Axons act as transmission lines to send activation to other neurons.
? Synapses the junctions allow signal transmission between the axons and dendrites.
? The process of transmission is by diffusion of chemicals called neuro-transmitters.

3. What are Neural Networks ?
1. Neural Networks (NNs) are networks of neurons, for example, as found in real (i.e. biological) brains.
2. Artificial Neurons are crude approximations of the neurons found in
brains. They may be physical devices, or purely mathematical constructs.
3. Artificial Neural Networks (ANNs) are networks of Artificial Neurons,
and hence constitute crude approximations to parts of real brains. They
may be physical devices, or simulated on conventional computers.
4. From a practical point of view, an ANN is just a parallel computational
system consisting of many simple processing elements connected together
in a specific way in order to perform a particular task.
5. One should never lose sight of how crude the approximations are, and
how over-simplified our ANNs are compared to real brains.