1. A method for detecting relevant stimuli using pupillary response as a correlate to cognitive response, comprising: providing a classifier, said classifier trained to detect patterns of spatio-temporal pupil features and generate an output indicative of the occurrence or absence of a relevant stimulus that evokes both a cognitive response and a pupillary response in a subject; using a sensor to measure the pupillary response of a subject subjected to stimuli in an environment, wherein the occurrence of a relevant stimulus is initially unknown to the classifier; deriving data samples d(n) of the pupil diameter from the pupillary response; segmenting the data samples d(n) into a sequence of time-shifted windows, each window including a response period and a baseline period; extracting a plurality of spatio-temporal pupil features from the data samples d(n) in said response and baseline periods in each said window; and for each said window, presenting the extracted pupil features to the classifier to generate an output indicative of the occurrence or absence of a relevant stimulus.
1. A method for detecting relevant stimuli using pupillary response as a correlate to cognitive response, comprising: providing a classifier, said classifier trained to detect patterns of spatio-temporal pupil features and generate an output indicative of the occurrence or absence of a relevant stimulus that evokes both a cognitive response and a pupillary response in a subject; using a sensor to measure the pupillary response of a subject subjected to stimuli in an environment, wherein the occurrence of a relevant stimulus is initially unknown to the classifier; deriving data samples d(n) of the pupil diameter from the pupillary response; segmenting the data samples d(n) into a sequence of time-shifted windows, each window including a response period and a baseline period; extracting a plurality of spatio-temporal pupil features from the data samples d(n) in said response and baseline periods in each said window; and for each said window, presenting the extracted pupil features to the classifier to generate an output indicative of the occurrence or absence of a relevant stimulus. 14. The method of claim 1 , further comprising: providing a training set of spatio-temporal pupil features including absolute diameter, velocity and acceleration features extracted from data samples d(n) in only the response period and comparative diameter, velocity and acceleration features from data samples d(n) in both the response and baseline periods; selecting the plurality of spatio-temporal pupil features from the training set that separate relevant stimuli from non-relevant stimuli; and training the classifier to detect patterns of the selected plurality of spatio-temporal pupil features.