Acquiring contextualized concepts: a connectionist approach

Conceptual knowledge is acquired through recurrent experiences, by extracting statistical regularities at different levels of granularity. At a fine level, patterns of feature co-occurrence are categorized into objects. At a coarser level, patterns of concept co-occurrence are categorized into contexts. We present and test CONCAT, a connectionist model that simultaneously learns to categorize objects and contexts. The model contains two hierarchically organized CALM modules (Murre, Phaf, & Wolters, 1992). The first module, the Object Module, forms object representations based on co-occurrences between features. These representations are used as input for the second module, the Context Module, which categorizes contexts based on object co-occurrences. Feedback connections from the Context Module to the Object Module send activation from the active context to those objects that frequently occur within this context. We demonstrate that context feedback contributes to the successful categorization of objects, especially when bottom-up feature information is degraded or ambiguous.     

Accounting for the computational basis of consciousness: a connectionist approach

This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the functional role of consciousness, in the form of the synergy between the conscious and the unconscious. The fit between the model and various cognitive phenomena and data (documented in the psychological literatures) is discussed to accentuate the plausibility of the model and its explanation of consciousness. Comparisons with existing models of consciousness are made in the end.     

Doing without schema hierarchies: a recurrent connectionist approach to normal and impaired routine sequential action

In everyday tasks, selecting actions in the proper sequence requires a continuously updated representation of temporal context. Previous models have addressed this problem by positing a hierarchy of processing units, mirroring the roughly hierarchical structure of naturalistic tasks themselves. The present study considers an alternative framework, in which the representation of context depends on recurrent connections within a network mapping from environmental inputs to actions. The ability of this approach to account for human performance was evaluated by applying it, through simulation, to a specific everyday task. The resulting model learned to deal flexibly with a complex set of sequencing constraints, encoding contextual information at multiple time scales within a single, distributed internal representation. Degrading this representation led to errors resembling those observed both in everyday behavior and in apraxia. Analysis of the model's function yielded numerous predictions relevant to both normal and apraxic performance.     

Neuropsychological dissociations between priming and recognition: a single-system connectionist account

A key claim of current theoretical analyses of the memory impairments associated with amnesia is that certain distinct forms of learning and memory are spared. A compelling example is that amnesic patients and controls are indistinguishable in repetition priming but amnesic patients are impaired at recognizing the study items. The authors show that this pattern of results is predicted by a single-system connectionist model of learning in which amnesia is simulated by a reduced learning rate. They also demonstrate that the model can reproduce the converse pattern in which priming but not recognition is impaired if the input is assumed to be additionally degraded in a priming test. The authors conclude that dissociations between priming and recognition do not require functionally or neurally distinct memory systems.     

Graded semantic and phonological similarity effects in priming: evidence for a distributed connectionist approach to morphology

A considerable body of empirical and theoretical research suggests that morphological structure governs the representation of words in memory and that many words are decomposed into morphological components in processing. The authors investigated an alternative approach in which morphology arises from the interaction of semantic and phonological codes. A series of cross-modal lexical decision experiments shows that the magnitude of priming reflects the degree of semantic and phonological overlap between words. Crucially, moderately similar items produce intermediate facilitation (e.g., lately-late). This pattern is observed for word pairs exhibiting different types of morphological relationships, including suffixed-stem (e.g., teacher-teach), suffixed-suffixed (e.g., saintly-sainthood), and prefixed-stem pairs (preheat-heat). The results can be understood in terms of connectionist models that use distributed representations rather than discrete morphemes.     

Learning to perceive object unity: a connectionist account

To explore questions of how human infants begin to perceive partly occluded objects, we devised two connectionist models of perceptual development. The models were endowed with an existing ability to detect several kinds of visual information that have been found important in infants’ and adults’ perception of object unity (motion, co‐motion, common motion, relatability, parallelism, texture and T‐junctions). They were then presented with stimuli consisting of either one or two objects and an occluding screen. The models’ task was to determine whether the object or objects were joined when such a percept was ambiguous, after specified amounts of training with events in which a subset of possible visual information was provided. The model that was trained in an enriched environment achieved superior levels of performance and was able to generalize veridical percepts to a wide range of novel stimuli. Implications for perceptual development in humans, current theories of development and origins of knowledge are discussed.     

Chaos breeds autonomy: connectionist design between bias and baby-sitting

In connectionism and its offshoots, models acquire functionality through externally controlled learning schedules. This undermines the claim of these models to autonomy. Providing these models with intrinsic biases is not a solution, as it makes their function dependent on design assumptions. Between these two alternatives, there is room for approaches based on spontaneous self-organization. Structural reorganization in adaptation to spontaneous activity is a well-known phenomenon in neural development. It is proposed here as a way to prepare connectionist models for learning and enhance the autonomy of these models.     

A connectionist approach to the organization and continuity of working models of attachment

Most research on adult attachment dynamics has been conducted under the assumption that working models are generalized cognitive-motivational structures that are highly stable and activated in a wide array of circumstances. Recent research, however, suggests that people develop attachment representations that are relationship specific, leading them to hold distinct working models in different kinds of relationships. The objective of this article is to outline a connectionist approach to the working model construct that has the potential to explain how global and relationship-specific working models are organized within the same mental system and how different learning environments can support continuity in those representations over time.     

Learning to attend: a connectionist model of situated language comprehension

Evidence from numerous studies using the visual world paradigm has revealed both that spoken language can rapidly guide attention in a related visual scene and that scene information can immediately influence comprehension processes. These findings motivated the coordinated interplay account ( Knoeferle & Crocker, 2006 ) of situated comprehension, which claims that utterance-mediated attention crucially underlies this closely coordinated interaction of language and scene processing. We present a recurrent sigma-pi neural network that models the rapid use of scene information, exploiting an utterance-mediated attentional mechanism that directly instantiates the CIA. The model is shown to achieve high levels of performance (both with and without scene contexts), while also exhibiting hallmark behaviors of situated comprehension, such as incremental processing, anticipation of appropriate role fillers, as well as the immediate use, and priority, of depicted event information through the coordinated use of utterance-mediated attention to the scene.     

The relationship between connectionist models and a dynamic data-oriented theory of concept formation

In this paper I shall compare two models of concept formation, both inspired by basic convictions of philosophical empiricism. The first, the connectionist model, will be exemplified by Kohonen maps, and the second will be my own dynamic theory of concept formation. Both can be understood in probabilistic terms, both use a notion of convergence or stabilization in modelling how concepts are built up. Both admit destabilization of concepts and conceptual change. Both do not use a notion of representation in some pregiven language, such as a language of thought or some logical language. Representation in a formal language only plays a role on the meta-level, namely within the theory about concept formation.A short version of this paper was given at the Fachtagung der Gesellschaft für Kognitionswissenschaft. Freiburg, October 12–15th, 1994.     

A healthy dose of trust: The relationship between interpersonal trust and health

The positive effects of trust are manifold. Recent research has shown that trust levels may even influence physical health. The current work explores this issue and aims to shed light on the mechanisms underlying the relationship between trust and health in a 5‐wave longitudinal data set. Results showed that trust was positively related to physical health: Participants report fewer health problems when they trust their partner more, replicating earlier findings. More importantly, symptoms of anxiety and depression mediate the effect of trust on self‐reported health. Finally, results of residual lagged analyses show that earlier levels of trust predict later symptoms of anxiety and depression symptoms, in turn predicting changes in physical health symptoms over time.     

Learning to divide the labor between syntax and semantics: a connectionist account of deficits in light and heavy verb production

In aphasic subjects who demonstrate difficulty producing verbs, a double dissociation has been observed between light verbs (e.g., GO) and heavy verbs (e.g., FLY). A simple connectionist model of sentence production, lesioned to simulate agrammatic- and anomic-like deficits, suggests that this dissociation arises from light verbs learning to rely more on syntactic cues and heavy verbs learning to rely more on semantic cues. Systematic manipulations of the variables which distinguish light and heavy verbs reveal that it is primarily the greater frequency of occurrence of light verbs, and the fact that they are specified by fewer semantic features, which cause them to depend more on syntactic information. Implications are discussed for models of lexical access in both normal and aphasic populations.     

How to build a connectionist idiot (savant)

This paper describes the development of a connectionist model of an idiot savant date calculator using a multi-layer back-propagation network. The model mimics the behaviour of idiot savant date calculators in learning to perform the date calculation task without the need either to develop arithmetical skills or to encode explicit knowledge about regularities in the structure of dates. However, the performance of the model highlights limitations on the use of back-propagation as a general-purpose learning algorithm in complex problem domains. Even with a relatively simple problem like date calculation back-propagation can only succeed when forced to take a highly structured and modular approach to learning.     

An innovative approach to clinical communication in schizophrenia: the approaches to schizophrenia communication checklists

Side effects from antipsychotic medications can have a profound effect on patients' lives and may adversely affect their willingness to comply with treatment. Identification of side effects through improved communication between psychiatrists, other members of the healthcare team, and their patients might increase treatment compliance. The Approaches to Schizophrenia Communication (ASC) Steering Group developed two simple, practical checklists for use in the busy clinical setting. The ASC-Self-Report (ASC-SR) checklist is completed by the patient and comprises a list of the more common or clinically important side effects of antipsychotic treatment. The ASC-Clinic (ASC-C) checklist is completed by both clinician and patient together, being used as the basis for a semi-structured interview. In a multicenter pilot study set up to evaluate the utility of checklists, 86% of patients responding considered the ASC-SR to be useful in communicating their problems to psychiatrists and other members of the healthcare team. All healthcare team respondents found both checklists to be helpful when discussing side effect problems with their patients. Moreover, 41% and 47% of healthcare team respondents reported that the ASC-SR and ASC-C, respectively, had assisted them in identifying side-effect problems not previously acknowledged. Preliminary evaluation of the ASC-SR and ASC-C in this multicenter pilot study suggests that both tools were user-friendly, encouraged communication between patients and healthcare professionals about antipsychotic drug side effects, and could readily integrated into everyday clinical practice.     

Talking normalization: the role of communication in integration

Deinstitutionalization has generally had a positive impact on the lives of people with learning disabilities, although provision of appropriate and individualized support in the community has proved difficult. Communication is often seen in isolation, its role within integration passing unacknowledged. This paper suggests an integrated framework around individual needs. Copyright © 2002 John Wiley & Sons, Ltd.