PubMed · 6030024
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D K Pumroy, S S Pumroy. 1967. A case study in discrimination learning.. https://doi.org/10.1080/00221325.1967.10533719
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To investigate brain mechanisms involved in identifying the origin of memories, event-related potentials (ERPs) were recorded as participants discriminated previously presented (old) from new items or identified their earlier source (picture, word, or new). Differences in ERPs between old-new recognition and source identification were focused at frontal sites. For source identification, prominent negative deflections at occipital or frontal sites occurred depending on encoding task. These results support a model in which memory attributes are distributed neocortically and the frontal lobes are critical for source monitoring.
A multi-structure neural network (MSNN) classifier consisting of four discriminators followed by a maximum selector was designed and applied to classification of four grades of pistachio nuts. Each discriminator was a multi-layer feed-forward neural network with two hidden layers and a single-neuron output layer. Fourier descriptors of the nuts' boundaries and their area were used as the recognition features. The individual discriminators were trained using a biased technique and a back-propagation algorithm. The MSNN classifier gave an average classification performance of 95.0%. This was an increase of 14.8% over the performance of a multi-layer neural network (MLNN) with similar complexity for classifying the same set of patterns.
Examples of perceptual learning in various visual tasks are briefly reviewed. In spite of the variety of the tasks and stimuli, in most of these examples the effects of learning are specific for stimulus parameters and retinal location and transfer interoccularly. Enduring practice effects can be acquired within a single experimental session and/or progressively from one session to the next one, often continuing to improve until thousands of trials have been performed. The consolidation of learning effects from one session to the next one may occur in the waking state as well as during a normal night sleep, but is strongly dependent on the type of sleep. Improvement in performance does not require that the subject is informed of the correctness of his/her responses, but needs attention to the task: learning does not take place for the stimulus attributes that are not attended to. All this suggests that visual perceptual learning involves plastic changes at early neural processing levels, which are dependent for their induction and consolidation on the general behavioural state of the subject, such as attentiveness and type of sleep.