1. In an artificial neural network comprising a plurality of functionally connected neurons, including pre-synaptic neurons and other neurons, a method of producing or generating weight-adjustment factors for said pre-synaptic neurons, comprising: (a) providing a plurality of interconnected artificial neuron means for use as processing unit means, each interconnected artificial neuron means comprising: (1) a plurality of connection means that accept respective input signals from others of said plurality of interconnected artificial neuron means or input signals from external sources, (2) means for storing or supplying respective weight values for each of said plurality of connection means, (3) modulating means for modulating the values of said input signals accepted at said plurality of connection means by said respective weight values, thereby to provide a respective modulation result for each of said plurality of connection means, and (4) an output means for storing or supplying an output signal value derived by summing the results of said modulating means in said plurality of connection means and subjecting the result to a transfer function, (b) calculating a plurality of respective influence values by modulating said respective input signal values by said respective weight values within at least one of said plurality of connection means, and (c) forming an error value for each of said pre-synaptic neurons by accumulating and storing a sum of the respective influence values calculated in said plurality of connection means to which the output signal value of each pre-synaptic neuron connects, whereby said error value will be used as a factor to adjust each of said respective weight values for said plurality of connection means, so that weight values representing connection strengths from pre-synaptic neurons and external sources will tend to be adjusted most when said interconnected artificial neuron means has exercised the greatest influence over the individual modulation results of artificial neuron means to which its output means is connected.