1. An apparatus for the automatic aiding of human cognitive functions during the operation of computerized displays from displayed stimuli, comprising: a digital processor with inputs of recorded human biosignals from analog amplifiers appropriately placed to record the electroencephalogram, electrooculogram, and muscular potentials, that applies filtering to remove the artifacts from the electroencephalogram, that maintains a file of the processed signal, and that outputs a windowed cerebral potential commonly of one second in duration; a digital processor that inputs the type of stimulus being displayed for the task being performed, that maintains a file of cerebral sources for the different stimuli-types, and which outputs the basic waveforms for the corresponding cerebral sources which are evocable by the stimuli-type; a digital processor that inputs the said windowed cerebral potential and the said set of basic waveforms, that computes parameters for an autoregressive model of the cerebral potential which is driven by the summed outputs of parallel attenuators with the basic waveform sources as inputs, and which outputs the computed parametric values of the attenuations and autoregressive coefficients; an expert system processor that consists of a front end spectrum analyzer cascaded in series with an inference engine and production rules, that inputs the said autoregressive coefficients to the said spectrum analyzer, that computes the power spectrum of the autoregressive coefficients as data input to the said inference engine, that estimates the cognitive state and from that a reliability measure by parsing the said production rules, and outputs the measure; a digital processor that inputs the recorded visual responses of the human from a recorder of the head and eye movements, fixations, pupil sizes, and eye blinks; which maintains a file of the visual responses, which computes visual indexes from the file, in particular, the location and duration of the visual fixations and the associated pupil sizes and the number of eye blinks, clutters the fixations into gaze points, determines the gaze durations, and the transitions between the same; and which outputs these indexes; a fuzzy logic processor that consists of a front-end statistical analyzer, a set of fuzzy membership functions, and a set of fuzzy classification rules; that inputs the said visual indexes to the said statistical analyzer, computes gaze statistics from the indexes, and transforms the gaze statistics into normalized scores; that applies the fuzzy membership functions to the scores to form fuzzy logic vector sets comprised of membership class probabilities; that parses the fuzzy classification rules for the membership probability vectors into an estimate of the attention state; and outputs the estimated state; a digital classifier that inputs the said attenuation values, the said cognitive reliability, the said indexes of the visual response, and the said attention state, all to an artificial neural network which with interconnection weights, estimates the probabilities of the occurrences of all possible decisions that can be made in response to the displayed stimulus, and outputs the same; a digital processor with input of the said decision probabilities, that selects the most likely decisions, and outputs the same; and an expert system processor that consists of an inference engine and production rules with input of the said most likely decisions, that determines the decision aiding from rules based on the disparities among the most likely decision estimates and the decisions that are expected from task scripts for the displayed stimulus, and outputs the cognitive aiding to the computer controlling the display driver.