PubMed Health⌕ Search

Biomedical subjects

D C Plaut

Publications and source records attributed to D C Plaut.

14 recordsLinked to original sources
PubMed2001

The interaction of spatial reference frames and hierarchical object representations: evidence from figure copying in hemispatial neglect.

In copying or drawing a figure, patients with hemispatial neglect following right parietal lobe lesions typically produce an adequate representation of parts on the right of the figure while omitting the corresponding features on the left. The neglect of information occupying contralateral locations is influenced by multiple spatial reference frames and by the hierarchical structure of the object(s) in the figure. The present work presents a computational characterization of the interaction among these influences to account for the way in which neglect manifests in copying. Empirical data are initially collected from brain-damaged and normal control subjects during two figure-copying tasks in which the hierarchical complexity and orientation of the displays to be copied are manipulated. In the context of the model, neglect is simulated by a "lesion" (monotonic drop-off along gradient from right to left) that can affect performance in both object- and viewer-centered reference frames. The effect of neglect in both these frames, coupled with the hierarchical representation of the object(s), provides a coherent account of the copying behavior of the patients and may be extended to account for the copying performance of other patients across a range of objects and scences.

Aged↗
PubMed2000

Attractor dynamics in word recognition: converging evidence from errors by normal subjects, dyslexic patients and a connectionist model.

People 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.

Adult↗
PubMed2000

The task dependence of staged versus cascaded processing: an empirical and computational study of Stroop interference in speech production.

The authors investigated the on-line relationship between overt articulation and the central processes of speech production. In 2 experiments manipulating the timing of Stroop interference in color naming, the authors found that naming behavior can shift between exhibiting a staged or cascaded mode of processing, depending on task demands: An effect of Stroop interference on naming durations arose only when there was increased pressure for speeded responding. In a simple connectionist model of information processing applied to color naming, the authors accounted for the current results by manipulating a single parameter, termed "gain," modulating the rate of information accrual within the network. Results are discussed in relation to mechanisms of strategic control and the link between cognition and action.

Adult↗
PubMed2000

Strategic control in word reading: evidence from speeded responding in the tempo-naming task.

To investigate strategic control over response initiation in word reading, the authors introduce the tempo-naming task. Relative to baseline performance in the standard-naming task, participants were induced to respond with faster latencies, shorter durations, and lower levels of accuracy by instructing them to time response initiation with an experimentally controlled tempo. The tempo response cue attenuated stimulus effects, and as faster tempos reduced latencies, the number of spelling-sound errors remained constant, whereas the number of word, nonword, and articulatory errors increased. To explain these results, the authors propose input gain as a mechanism of control over processing speed. The experimenters sketch how input gain could account for the current results as well as for the results from stimulus-blocking experiments testing the route emphasis and time criterion hypotheses of strategic control.

Adult↗
PubMed2000

Individual and developmental differences in semantic priming: empirical and computational support for a single-mechanism account of lexical processing.

Existing accounts of single-word semantic priming phenomena incorporate multiple mechanisms, such as spreading activation, expectancy-based processes, and postlexical semantic matching. The authors provide empirical and computational support for a single-mechanism distributed network account. Previous studies have found greater semantic priming for low- than for high-frequency target words as well as inhibition following unrelated primes only at long stimulus-onset asynchronies (SOAs). A series of experiments examined the modulation of these effects by individual differences in age or perceptual ability. Third-grade, 6th-grade, and college students performed a lexical-decision task on high- and low-frequency target words preceded by related, unrelated, and nonword primes. Greater priming for low-frequency targets was exhibited only by participants with high perceptual ability. Moreover, unlike the college students, the children showed no inhibition even at the long SOA. The authors provide an account of these results in terms of the properties of distributed network models and support this account with an explicit computational simulation.

Adult↗
PubMed1999

Language acquisition in the absence of explicit negative evidence: how important is starting small?

It is commonly assumed that innate linguistic constraints are necessary to learn a natural language, based on the apparent lack of explicit negative evidence provided to children and on Gold's proof that, under assumptions of virtually arbitrary positive presentation, most interesting classes of languages are not learnable. However, Gold's results do not apply under the rather common assumption that language presentation may be modeled as a stochastic process. Indeed, Elman (Elman, J.L., 1993. Learning and development in neural networks: the importance of starting small. Cognition 48, 71-99) demonstrated that a simple recurrent connectionist network could learn an artificial grammar with some of the complexities of English, including embedded clauses, based on performing a word prediction task within a stochastic environment. However, the network was successful only when either embedded sentences were initially withheld and only later introduced gradually, or when the network itself was given initially limited memory which only gradually improved. This finding has been taken as support for Newport's 'less is more' proposal, that child language acquisition may be aided rather than hindered by limited cognitive resources. The current article reports on connectionist simulations which indicate, to the contrary, that starting with simplified inputs or limited memory is not necessary in training recurrent networks to learn pseudonatural languages; in fact, such restrictions hinder acquisition as the languages are made more English-like by the introduction of semantic as well as syntactic constraints. We suggest that, under a statistical model of the language environment, Gold's theorem and the possible lack of explicit negative evidence do not implicate innate, linguistic-specific mechanisms. Furthermore, our simulations indicate that special teaching methods or maturational constraints may be unnecessary in learning the structure of natural language.

Artificial Intelligence↗
PubMed1996

Relearning after damage in connectionist networks: toward a theory of rehabilitation.

Connectionist modeling offers a useful computational framework for exploring the nature of normal and impaired cognitive processes. The current work extends the relevance of connectionist modeling in neuropsychology to address issues in cognitive rehabilitation: the degree and speed of recovery through retraining, the extent to which improvement on treated items generalizes to untreated items, and how treated items are selected to maximize this generalization. A network previously used to model impairments in mapping orthography to semantics is retrained after damage. The degree of relearning and generalization varies considerably for different lesion locations, and has interesting implications for understanding the nature and variability of recovery in patients. In a second simulation, retraining on words whose semantics are atypical of their category yields more generalization than retraining on more typical words, suggesting a counterintuitive strategy for selecting items in patient therapy to maximize recovery. In a final simulation, changes in the pattern of errors produced by the network over the course of recovery is used to constrain explanations of the nature of recovery of analogous brain-damaged patients. Taken together, the findings demonstrate that the nature of relearning in damaged connectionist networks can make important contributions to a theory of rehabilitation in patients.

Brain Damage, Chronic↗
PubMed1996

Pseudohomophone effects and models of word recognition.

Two experiments examined factors that influence the processing of pseudohomophones (nonwords such as brone or joap, which sound like words) and nonpseudohomophones (such as brone and joap, which do not sound like words). In Experiment 1, pseudohomophones yielded faster naming latencies and slower lexical-decision latencies than did nonpseudohomophones, replicating results of R. S. McCann and D. Besner (1987) and R. S. McCann, D. Besner, and E. Davelaar (1988). The magnitude of the effect was related to subjects' speed in lexical decision but not naming. In Experiment 2, both immediate and delayed naming conditions were used. There was again a significant pseudohomophone effect that did not change in magnitude across conditions. These results indicate that pseudohomophone effects in the lexical-decision and naming tasks have different bases. In lexical decision, they reflect the pseudohomophone's activation of phonological and semantic information associated with words. In naming, they reflect differences in ease of articulating familiar versus unfamiliar pronunciations. Implications of these results concerning models of word recognition are discussed, focusing on how pseudohomophone effects can arise within models that do not incorporate word-specific representations, such as the M. S. Seidenberg and J. L. McClelland (1989) model.

Humans↗
PubMed1996

Understanding normal and impaired word reading: computational principles in quasi-regular domains.

A connectionist approach to processing in quasi-regular domains, as exemplified by English word reading, is developed. Networks using appropriately structured orthographic and phonological representations were trained to read both regular and exception words, and yet were also able to read pronounceable nonwords as well as skilled readers. A mathematical analysis of a simplified system clarifies the close relationship of word frequency and spelling-sound consistency in influencing naming latencies. These insights were verified in subsequent simulations, including an attractor network that accounted for latency data directly in its time to settle on a response. Further analyses of the ability of networks to reproduce data on acquired surface dyslexia support a view of the reading system that incorporates a graded division of labor between semantic and phonological processes, and contrasts in important ways with the standard dual-route account.

Dyslexia↗
PubMed1995

Double dissociation without modularity: evidence from connectionist neuropsychology.

Many theorists assume that the cognitive system is composed of a collection of encapsulated processing components or modules, each dedicated to performing a particular cognitive function. On this view, selective impairments of cognitive tasks following brain damage, as evidenced by double dissociations, are naturally interpreted in terms of the loss of particular processing components. By contrast, the current investigation examines in detail a double dissociation between concrete and abstract work reading after damage to a connectionist network that pronounces words via meaning and yet has no separable components (Plaut & Shallice, 1993). The functional specialization in the network that gives rise to the double dissociation is not transparently related to the network's structure, as modular theories assume. Furthermore, a consideration of the distribution of effects across quantitatively equivalent individual lesions in the network raises specific concerns about the interpretation of single-case studies. The findings underscore the necessity of relating neuropsychological data to cognitive theories in the context of specific computational assumptions about how the cognitive system operates normally and after damage.

Brain Damage, Chronic↗
PubMed1994

Nonword pronunciation and models of word recognition.

Nonword pronunciation is a form of generalization behavior that has been at the center of debates about models of word recognition, the role of rules in explaining behavior, and the adequacy of the parallel distributed processing approach. An experiment yielded data concerning the pronunciation of a large corpus of nonwords. The data were then used to assess 2 models of naming: a model developed by D. C. Plaut and J. L. McClelland (1993), which is similar to the one described by M. S. Seidenberg and J. L. McClelland (1989) but uses improved orthographic and phonological representations, and the grapheme-phoneme correspondence rules of M. Coltheart, B. Curtis, P. Atkins, and M. Haller's (1993) dual-route model. Both models generate plausible nonword pronunciations and match subjects' responses accurately. The dual-route model does so by using rules that generate correct output for most words but mispronounce a significant number of exceptions. The parallel distributed processing model does so by finding a set of weights that allow it to generate correct output for both "rule-governed" items and exceptions. Some ways in which the two approaches differ and other issues facing them are also discussed.

Humans↗
PubMed1993

Computational approaches to cognition: top-down approaches.

Computational models are useful tools for exploring the nature of human cognitive processes. In particular, connectionist models are providing researchers with new ways of thinking about the basic nature of cognition and its implementation in the brain. They support novel explanations of important aspects of perception, memory, language, thought and cognitive development, and allow cognitive processes to be linked with the underlying physiological mechanisms. The models also aid our understanding of how disorders of brain function lead to disorders of cognition.

Aging↗