Exploring pattern recognition: what is the relationship between the recognition of words, faces and other objects?

Debate surrounds processes of visual recognition, with no consensus as to whether recognition of distinct object categories (faces, bodies, cars, and words) is domain specific or subserved by domain-general visual recognition mechanisms. Here, we investigated correlations between the performance of 74 participants on recognition tasks for words, faces and other object categories. Participants completed a counter-balanced test battery of the Cambridge Face, Car and Body Parts Memory tests, as well as a standard four category lexical decision task, with response time and recognition accuracy as dependent variables. Results revealed significant correlations across domains for both recognition accuracy and response time, providing some support for domain-general pattern recognition. Further exploration of the data using principal component analysis (PCA) revealed a two-component model for both the response time and accuracy data. However, how the various word and object recognition tasks fitted these components varied considerably but did hint at familiarity/expertise as a common factor. In sum, we argue a complex relationship exists between domain-specific processing and domain-general processing, but that this is shaped by expertise. To further our understanding of pattern recognition, research investigating the recognition of words, faces and other objects in dyslexic individuals is recommended, as is research exploiting neuroimaging methodologies, with excellent temporal resolution, to chart the temporal specifics of different forms of visual pattern recognition.

Recognition of subtle and universal facial expressions in a community-based sample of adults classified with intellectual disability.

BACKGROUND: Across the USA and UK, schemes now exist to aid the successful integration of adults with mild to moderate intellectual disabilities into general society. One factor that may prove important to the success of such schemes is social competence. Here, understanding the facial expressions of others is critical, as emotion recognition is a prerequisite to empathetic responding and an essential factor in social functioning. Yet research in this area is lacking, especially in community-based samples. METHOD: We investigated the performance of 13 adults with mild to moderate intellectual disability (ID), relative to 13 age-matched controls, on three tasks of emotion recognition (emotion categorisation; recognition of valence; and recognition of arousal), using a number of 'basic' (angry and happy) and more 'subtle' (compassionate and critical) emotional expressions, as well as the posers face in a default relaxed (i.e. 'neutral') state. Importantly, the sample was drawn from a community-based initiative and was therefore representative of populations' government schemes target. RESULTS: Across emotion recognition tasks, the ID adults, as compared with controls, were significantly impaired when labelling the emotions displayed by the poser as well as recognising the associated 'feelings' conveyed by these faces. This was especially true for the neutral, compassionate and angry facial expressions. For example, ID adults demonstrated deficits in categorising neutral and subtle emotional expressions, as well as assessing the valence of such facial expressions. In addition, ID adults also struggled to assess arousal levels; especially those associated with compassionate and angry faces. CONCLUSION: Given both basic and subtle emotions are conveyed in a range of daily situations, errors in interpreting such facial expressions and, relatedly, understanding what potential behaviours such expressions signify could contribute to the social difficulties ID adults face. This is important because current initiatives such as 'personalisation' do not appear to have schemes supporting training in this area, and understanding the facial expressions of others is, after all, one of our most important non-verbal social communication tools.