Perceptual differentiation during categorization learning by pigeons.

Aitken, Michael R. F.; Bennett, C. H.; McLaren, Ian A.; Mackintosh, N. J.

doi:10.1037/0097-7403.22.1.43

Cited by 23 publications

(25 citation statements)

References 12 publications

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“…We have previously shown (McLaren, Leevers and Mackintosh, 1994;McLaren, 1997) that exposure to exemplars drawn from a category defined by a prototype leads to perceptual learning, as evidenced by an enhanced ability to discriminate between category exemplars after pre-exposure. And, in pigeons we have been able to show that exposure to the prototype alone can have similar effects as predicted by MKM (Aitken et al, 1996). Now, for the first time, we are able to show that exposure to a single, prototypical stimulus has a similar effect for humans, in that it results in faster acquisition of a discrimination between exemplars drawn from that category (see later in this paper).…”

Section: Problem Domainsupporting

confidence: 54%

“…This paper represents our first attempt at combining a theory of stimulus representation that operates at an elemental level (that due to McLaren, Kaye and Mackintosh, 1989;further elaborated in McLaren and Mackintosh, 2000) with a theory of associative learning and memory that is clearly of a configural nature (APECS, McLaren, 1993, 2011Le Pelley and McLaren, 2001). Whilst the benchmark elemental model of associative learning over the last 40 years has been the Rescorla and Wagner (1972) model, more recently results such as those from retrospective revaluation studies and from experiments on latent inhibition and perceptual learning have suggested that the Rescorla and Wagner (1972) model can no longer accommodate important findings in the human (e.g., Burke, 1996 andLarkin, Aitken, &Dickinson, 1998 on retrospective revaluation;McLaren, Leevers and Mackintosh, 1994;McLaren, 1997 andWills, Suret andMcLaren, 2005 on perceptual learning) and animal (e.g., Matzel, Schactman and Miller, 1985;Matzel, Schuster, & Miller, 1987 on retrospective revaluation;McLaren, Bennett, Plaisted, Aitken and Mackintosh, 1994 on latent inhibition; Aitken, Bennett, McLaren and Mackintosh, 1996 on perceptual learning) literature. Miller and colleagues have taken this further by assessing the Rescorla-Wagner model against what is currently known about associative learning, and, whilst they find it a useful benchmark, note that there are number of phenomena that it cannot accommodate (Miller, Barnet and Grahame, 1995).…”

Section: Introductionmentioning

confidence: 99%

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Elemental representation and configural mappings: Combining elemental and configural theories of associative learning

2012

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In this paper we present our first attempt at combining an elemental theory designed to model representation development in an associative system (e.g., McLaren, Kaye and Mackintosh, 1989), with a configural theory that models associative learning and memory (McLaren, 1993). After considering the possible advantages of such a combination (and some possible pitfalls), we offer a hybrid model that allows both components to produce the phenomena that they are capable of without introducing unwanted interactions. We then successfully apply the model to a range of phenomena including latent inhibition, perceptual learning, the Espinet effect, and first and second order retrospective revaluation. In some cases we present new data for comparison with our model results; in all cases the model replicates the pattern observed in our experimental results. We conclude that this line of development is a promising one for generating truly comprehensive theories of learning and memory. IntroductionOur long-term aim is to produce a general model of associative learning and memory that captures the processes that are common to both humans and infra-humans. This paper investigates the feasibility of combining elemental and configural approaches to associative learning and memory as a stepping stone towards that ultimate goal. In doing so, it also addresses a particular computational problem: of how we can have representation development at an elemental level whilst still learning in a holistic fashion. We start by considering the problem in general, and by motivating the need to find a solution incorporating both elemental (e.g., Estes, 1959;Mclaren, Kaye and Mackintosh, 1989;Brandon, Vogel and Wagner, 2000;Harris, 2006) and configural (e.g., Pearce, 1987, McLaren, 1993Honey, 2000; Honey and WardRobinson, 2002) forms of representation, then move to a specific example of such a combination that attempts to amalgamate the McLaren, Kaye and Mackintosh (1989, henceforth MKM) model of representation development with the APECS (McLaren, 1993;Le Pelley and McLaren, 2001;McLaren, 2011) model of associative learning and memory. To anticipate slightly, the enterprise is a successful one in the sense that the hybrid model is able to reproduce the phenomena that can be simulated using its components (and thus is of wider scope than either of its constituent parts), but this outcome was not achieved without considerable effort and overcoming numerous difficulties. In the course of grappling with this problem we have developed a new respect for the way in which issues multiply as the complexity of the model increases, and we try to pass on our experience of what will and will not work when synthesizing elemental and configural approaches to learning and memory.

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Section: Problem Domainsupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Elemental representation and configural mappings: Combining elemental and configural theories of associative learning

2012

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“…The second was obtained by measuring the improvement in performance on the discrimination tasks when the stimuli were familiar (i.e., had been seen previously in the categorization phase) compared with when the stimuli were novel (i.e., the preceding categorization had used the irrelevant abstract art stimuli). This is a standard procedure for assessing perceptual learning (Gibson and Walk, 1956;Honey and Hall, 1989;Mackintosh et al, 1991;Aitken et al, 1996), and we predicted that, although there would be evidence for perceptual learning for both types of stimuli in control participants, the patients would only show perceptual learning for faces, the processing of which we presumed to be dependent on perirhinal cortex rather than the hippocampus. Performance was measured with reference to accuracy (percentage correct) and raw reaction time (milliseconds).…”

Section: Measures Of Learningmentioning

confidence: 99%

Abnormal Categorization and Perceptual Learning in Patients with Hippocampal Damage

et al. 2006

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Prevailing theory holds that the medial temporal lobe (MTL) subserves declarative memory exclusively, whereas nondeclarative memory is independent of this brain region. Recent studies in patients with amnesia, however, have shown that performance on declarative memory tasks may not always be dependent on a single MTL memory system, instead highlighting the critical role of anatomically distinct structures in processing different stimulus types. In particular, the hippocampus has been implicated in spatial memory, whereas perirhinal cortex seems critical for object memory. To assess whether stimulus type would also be a key dimension in nondeclarative memory, patients with selective hippocampal lesions were tested on simple categorization and perceptual learning of faces and virtual reality scenes. The patients demonstrated preserved categorization and perceptual learning of faces but abnormal performance when the stimuli to be discriminated were virtual reality scenes. These findings imply that stimulus type may be a more critical predictor of performance on memory tasks (declarative and nondeclarative) than previously thought. They also suggest that reports of good nondeclarative memory after MTL damage may, in some cases, simply reflect the use of stimuli that fail to tap the processes dependent on structures in this region, such as spatial processing in the case of the hippocampus.

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“…This finding, in turn, suggests that categorization training in Experiment 1 increased distinctiveness of the exemplars within categories, to the extent that the pigeons responded to the test stimuli in a "graded" fashion according to the P+ and P-proportions. Such an effect has been known as acquired distinctiveness; there is an increase in perceptual sensitivity to differences that are relevant for a categorization (Corneille & Judd, 1999;Gibson, 1969;Goldstone, 1994; see also Aitken, Bennett, McLaren, & Mackintosh, 1996).…”

Section: Discussionmentioning

confidence: 99%

The learning of basic-level categories by pigeons: The prototype effect, attention, and effects of categorization

2011

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Pigeons were trained to classify composite faces of two categories created by mimicking the structure of basic-level categories, with each face consisting of an itemspecific component and a common component diagnostic for its category. Classification accuracy increased as the proportion of common components increased, regardless of familiar and novel item-specific components, with the best discrimination occurring at untrained original faces used as the common components. A no-categorization control condition suggested that categorization gives rise to equivalence for item-specific components and distinctiveness for degrees of prototypicality. When some item-specific components were shared by exemplars of the contrasting categories, those that were not overlapping between the categories became the effective cues for the pigeons' responses. Implications of these results are discussed in the context of current categorization and associative learning theories.

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Perceptual differentiation during categorization learning by pigeons.

Cited by 23 publications

References 12 publications

Elemental representation and configural mappings: Combining elemental and configural theories of associative learning

Elemental representation and configural mappings: Combining elemental and configural theories of associative learning

Abnormal Categorization and Perceptual Learning in Patients with Hippocampal Damage

The learning of basic-level categories by pigeons: The prototype effect, attention, and effects of categorization

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