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Connectionist modelling in cognitive neuropsychology: a case study
No full textComputational models offer tools for exploring the nature of human cognitive processes. In connectionist, neural network, or parallel distributed processing models, information processing takes the form of cooperative and competitive interactions among many simple, neuron-like processing units. These models provide new ways of thinking about the neural basis of cognitive processes, and how disorders of brain function lead to disorders of cognition. This monograph is an expanded version of a recent issue of the journal Cognitive Neuropsychology. It presents the most comprehensive existing "case study" of how the effects of damage in connectionist models can replicate the detailed and diverse patterns of cognitive impairments that can arise in humans as a result of brain damage. It begins with a review of the basic methodology of cognitive neuropsychology and of other attempts at modeling neuropsychological phenomena. It then focuses on a particular form of acquired reading disorder, "deep dyslexia," in which previously literate adults with brain damage exhibit a wide range of symptoms in pronouncing written words, the most striking of which is the production of semantic errors (e.g. reading RIVER as "ocean")
Perseverative and semantic influences on visual object naming errors in optic aphasia: a connectionist account
Full text linkAlthough perseveration - the inappropriate repetition of previous responses is quite common among patients with neurological damage, relatively few detailed computational accounts of its various forms have been put forth. A particularly well-documented variety involves the pattern of errors made by 'optic aphasic' patients, who have a selective deficit in naming visually presented objects. Based on our previous work in modeling impaired reading via meaning in deep dyslexia, we develop a connectionist simulation of visual object naming. The major extension in the present work is the incorporation of short-term correlational weights that bias the network towards reproducing patterns of activity that have occurred on recently preceding trials. Under damage, the network replicates the complex semantic and perseverative effects found in the optic aphasic error pattern. Further analysis reveals that the perseverative effects are strongest when the lesions are near or within semantics, and are relatively mild when the preceding object evokes no response. Like optic aphasics, the network produces predominantly semantic rather than visual errors because, in contrast to reading, there is some structure in the mapping from visual to semantic representations for objects. Viewed together with the dyslexia simulations, the replication of complex empirical phenomena concerning impaired visual comprehension based on a small set of general connectionist principles strongly suggests that these principles provide important insights into the nature of semantic processing of visual information and its breakdown following brain damage
Deep Dyslexia: A Case Study of Connectionist Neuropsychology
Full text linkDeep dyslexia is an acquired reading disorder marked by the occurrence of semantic errors (e.g., reading RIVER as "ocean"). In addition, patients exhibit a number of other symptoms, including visual and morphological effects in their errors, a part-of-speech effect, and an advantage for concrete over abstract words. Deep dyslexia poses a distinct challenge for cognitive neuropsychology because there is little understanding of why such a variety of symptoms should co-occur in virtually all known patients. Hinton and Shallice (1991) replicated the co-occurrence of visual and semantic errors by lesioning a recurrent connectionist network trained to map from orthography to semantics. While the success of their simulations is encouraging, there is little understanding of what underlying principles are responsible for them. In this paper we evaluate and, where possible, improve on the most important design decisions made by Hinton and Shallice, relating to the task, the network architecture,..
Attractor dynamics in word recognition: converging evidence from errors by normal subjects, dyslexic patients and a connectionist model.
No full textPeople make both semantic and visual errors when trying to recognise the meaning of degraded words. This result mirrors the finding that deep dyslexic patients make both semantic and visual errors when reading aloud. We link the results with the demonstration that a recurrent connectionist network which produces the meaning of words in response to their spelling pattern produces this distinctive combination of errors both when its input is degraded and when it is lesioned. The reason why the network can simulate the errors of both normal subjects and patients lies in the nature of the attractors which it develops as it learns to map orthography to semantics. The key role of attractor structure in the successful simulation suggests that the normal adult semantic reading route may involve attractor dynamics
Word Reading in Damaged Connectionist Networks: Computational and Neuropsychological Implications
No full textthis paper were run on a Silicon Graphics Iris-4D/240S using an extended version of the Xerion simulator developed by Tony Plate. This research was supported by grant 87-2-36 from the Alfred P. Sloan Foundation. Word Reading in Damaged Connectionist Networks 2 concern is not just with the development of a network that accomplishes a task, but with understanding how the network accomplishes the task---the nature of its representations and processes. In most connectionist research, the adequacy of a network is evaluated by testing how well its performance generalizes to novel external input drawn from the same distribution as the training examples. In a similar way, damage to a network has the effect of generating unfamiliar activity in the remaining portions of the network . However, damage can affect internal representations in ways that cannot be directly mimicked by manipulations of the external input. Thus, the behavior of the network under damage may provide a more general, and for some purposes, more informative, indication of the nature of the representations and processes the network develops during training. In studying patients with brain damage, the field of cognitive neuropsychology attempts to relate their patterns of impaired and preserved abilities to models of normal cognitive functioning, with the intent both of explaining the behavior of the patients in terms of the effects of damage in the model, and of informing the model based on the observed behavior of patients [Col85, EY88]. In an analogous fashion, this chapter presents an approach that might be called "connectionist neuropsychology," in which analyses of the effects of damage in connectionist networks are used both to provide a comprehensive, detailed account of the cognitive deficits of a par..
Effects of Word Abstractness in a Connectionist Model of Deep Dyslexia
Full text linkness in a Connectionist Model of Deep Dyslexia David C. Plaut School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 [email protected] Tim Shallice Department of Psychology University College London, England WC1E 6BT [email protected] Proceedings of the 13th Annual Meeting of the Cognitive Science Society, Chicago, IL, August 1991, pages 73--78. Abstract Deep dyslexics are patients with neurologicaldamage who exhibit a variety of symptoms in oral reading, including semantic, visual and morphological effects in their errors, a part-of-speech effect, and better performance on concrete than abstract words. Extending work by Hinton & Shallice (1991), we develop a recurrent connectionist network that pronounces both concrete and abstract words via their semantics, defined so that abstract words have fewer semantic features. The behavior of this network under a variety of "lesions" reproduces the main effects of abstractness on deep dyslexic reading: better correct perfor..
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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