Imprinting and perceptual learning

Filial responses are first considered by reference to the initial stimulus situations. Findings on variability in responsiveness of chicks are reported and discussed. Facilitated responsiveness subsequent to visual stimulation is reported. The concept of critical period is examined in the light of other workers' and our own findings; it is concluded that imprinting ends as a result of its own action rather than through the effects of fear. Following responses are further considered by reference to the influences of early experiences and the act of following upon the occurrence and strength of subsequent responses. The degree of attachment to a moving object tends to be proportional to the amount of experience. Individual chicks were allowed to spend several hours following a box in a runway and their ability to discriminate between familiar and unfamiliar moving objects and static environments was studied. Strong evidence for imprintability to environment has been found. Imprinting phenomena are discussed in terms of perceptual learning.     

Visual perceptual learning

Perceptual learning refers to the phenomenon that practice or training in perceptual tasks often substantially improves perceptual performance. Often exhibiting stimulus or task specificities, perceptual learning differs from learning in the cognitive or motor domains. Research on perceptual learning reveals important plasticity in adult perceptual systems, and as well as the limitations in the information processing of the human observer. In this article, we review the behavioral results, mechanisms, physiological basis, computational models, and applications of visual perceptual learning.     

Acetylcholine and olfactory perceptual learning

Olfactory perceptual learning is a relatively long-term, learned increase in perceptual acuity, and has been described in both humans and animals. Data from recent electrophysiological studies have indicated that olfactory perceptual learning may be correlated with changes in odorant receptive fields of neurons in the olfactory bulb and piriform cortex. These changes include enhanced representation of the molecular features of familiar odors by mitral cells in the olfactory bulb, and synthetic coding of multiple coincident odorant features into odor objects by cortical neurons. In this paper, data are reviewed that show the critical role of acetylcholine (Ach) in olfactory system function and plasticity, and cholinergic modulation of olfactory perceptual learning at both the behavioral and cortical level.     

Procedural learning in perceptual categorization

In two experiments, observers learned two types of category structures: those in which perfect accuracy could be achieved via some explicit rule-based strategy and those in which perfect accuracy required integrating information from separate perceptual dimensions at some predecisional stage. At the end of training, some observers were required to switch their hands on the response keys, whereas the assignment of categories to response keys was switched for other observers. With the rule-based category structures, neither change in response instructions interfered with categorization accuracy. However, with the information-integration structures, switching response key assignments interfered with categorization performance, but switching hands did not. These results are consistent with the hypothesis that abstract category labels are learned in rule-based categorization, whereas response positions are learned in information-integration categorization. The association to response positions also supports the hypothesis of a procedural-learning-based component to information integration categorization.     

Unconsciously learning task-irrelevant perceptual sequences

We demonstrated unconscious learning of task-irrelevant perceptual regularities in a Serial Reaction Time (SRT) task in both visual and auditory domains. Participants were required to respond to different letters (‘F’ or ‘J’, experiment 1) or syllables (‘can’ or ‘you’, experiment 2) which occurred in random order. Unbeknownst to participants, the color (red, green, blue or yellow) of the two letters or the tone (1–4) of the syllables varied according to certain rules. Reaction times indicated that people indeed learnt both the color and tonal regularities indicating that task-irrelevant sequence structure can be learned perceptually. In a subsequent prediction test of knowledge of the color or tonal cues using subjective measures, we showed that people could acquire task irrelevant knowledge unconsciously.     

Visuospatial perceptual sequence learning and eye movements

We examined perceptual sequence learning by means of an adapted serial reaction time task in which eye movements were unnecessary for performing the sequence learning task. Participants had to respond to the identity of a target letter pair ("OX" or "XO") appearing in one of four locations. On the other locations, similar distractor letter pairs ("QY" or "YQ") were shown. While target identity changed randomly, target location was structured according to a deterministic sequence. To render eye movements superfluous, (1) stimulus letter pairs appeared around a fixation cross with a visual angle of 0.63°, which means that they appeared within the foveal visual area and (2) the letter pairs were presented for only 100 ms, a period too short to allow proper eye movements. Reliable sequence knowledge was acquired under these conditions, as responses were both slower and less accurate when the trained sequence was replaced by an untrained sequence. These results support the notion that perceptual sequence learning can be based on shifts of attention without overt oculomotor movements.     

Attention and the measurement of perceptual learning

Novel and familiar letters were presented to Ss under conditions which controlled momentary attention states. The latencies of letter matching for the novel and familiar letters did not differ when Ss were expecting the particular letters which were presented. However, latencies to the two types of letters differed significantly when Ss were not expecting the particular letters which were presented. Additional exposures significantly reduced this difference, thereby generating a perceptual learning curve in terms of response latency. The main findings were interpreted in terms of a model of perceptual processing which involves mechanisms for hierarchical coding, selective attention, and automatic processing.     

Late maturation of auditory perceptual learning

Adults can improve their performance on many perceptual tasks with training, but when does the response to training become mature? To investigate this question, we trained 11‐year‐olds, 14‐year‐olds and adults on a basic auditory task (temporal‐interval discrimination) using a multiple‐session training regimen known to be effective for adults. The adolescents all began with performance in the adult range. However, while all of the adults improved across sessions, none of the 11‐year‐olds and only half of the 14‐year‐olds did. The adolescents who failed to learn did so even though the 10‐session training regimen provided twice the number of sessions required by adults to reach asymptotic performance. Further, over the course of each session, the performance of the adults was stable but that of the adolescents, including those who learned, deteriorated. These results demonstrate that the processes that underlie perceptual learning can continue to develop well into adolescence.     

Dual-task interference in perceptual category learning

The effect of a working-memory-demanding dual task on perceptual category learning was investigated. In Experiment 1, participants learned unidimensional rule-based or information integration category structures. In Experiment 2, participants learned a conjunctive rule-based category structure. In Experiment 1, unidimensional rule-based category learning was disrupted more by the dual working memory task than was information integration category learning. In addition, rule-based category learning differed qualitatively from information integration category learning in yielding a bimodal, rather than a normal, distribution of scores. Experiment 2 showed that rule-based learning can be disrupted by a dual working memory task even when both dimensions are relevant for optimal categorization. The results support the notion of at least two systems of category learning a hypothesis-testing system that seeks verbalizable rules and relies on working memory and selective attention, and an implicit system that is procedural-learning based and is essentially automatic.