The authors present a theory of how relational inference and generalization can be accomplished within a cognitive architecture that is psychologically and neurally realistic. Their proposal is a form of symbolic connectionism: a connectionist system based on distributed representations of concept meanings, using temporal synchrony to bind fillers and roles into relational structures. The authors present a specific instantiation of their theory in the form of a computer simulation model, Learning and Inference with Schemas and Analogies (LISA). By using a kind of self-supervised learning, LISA can make specific inferences and form new relational generalizations and can hence acquire new schemas by induction from examples. The authors demonstrate the sufficiency of the model by using it to simulate a body of empirical phenomena concerning analogical inference and relational generalization. A fundamental aspect of human intelligence is the ability to form and manipulate relational representations. Examples of relational thinking include the ability to appreciate analogies between seemingly different objects or events (Gentner, 1983; Holyoak & Thagard, 1995), the ability to apply abstract rules in novel situations (e.g., Smith, Langston, & Nisbett, 1992), the ability to understand and learn language (e.g., Kim, Pinker, Prince, & Prasada, 1991), and even the ability to appreciate perceptual similarities

Participants memorized briefly presented sets of digits, a subset of which had to be accessed as input for arithmetic tasks (the active set), whereas another subset had to be remembered independently of the concurrent task (the passive set). Latencies for arithmetic operations were a function of the setsize of active but not passive sets. Object-switch costs were observed when successive operations were applied to different digits within an active set. Participants took2stoencode a passive set so that it did not affect processing latencies (Experiment 2). The results support a model distinguishing 3 states of representations in working memory: the activated part of long-term memory, a capacity limited region of direct access, and a focus of attention. Working memory is commonly described as a system for simultaneous storage and processing of information. The relation between “storage ” and “processing, ” however, is rarely specified. Resource models generally posit a common resource (e.g., activation) that must be shared between the two functions (Just & Carpenter, 1992). Evidence from dual task studies, however, casts doubt on the resource-sharing hypothesis: There are numerous examples in the literature of processing that is largely unimpaired by a concurrent short-term memory demand, even when the memory demand is close to the maximum span (e.g., Foos & Wright,

Measures of the speed andacg&U:W ofproc:)gH3fiPW&gcc with nonadjacgH dependencH3 derived from the response -signal speed-acgnalg tradeo#proco#g& were used to examine the nature of the memory system that underlies sentenc ctencesg):WP Three experiments with di#erent sentenc strucg9P demonstrated that theacg))W& of procWPPgH3 dependenc decndenc as more material was interpolated betweennonadjac33 cnadjac33(g However, procer,g):WPWg wasuna#ecUP by the amount of interpolated material,indicl,g39UPfi memory representations for previously procious ciouslygfi9 cfi beac9((fi9 direcfi9g These results suggest that acfi99WgH339fi)gcgc memory system mediates sentenc ctenc&(3:WgH inwhic syntac9g andsemantic information providedirec acec to memory representations without the need tosearc through extraneous representations. Notably,cably,g3Pfi3)gH3&(:&gc appears to underlie the interpretation ofsentenc strucgH9 that also require therec33&U of order information, a type of operation that has been shown tonec:&(gH9fi a slowsearc proc3 in list-learningexperiments(Mct-lea 2001;Mc1;g) & Dosher, 1993).

In the single-store model of memory, the enhanced recall for the last items in a free-recall task (i.e., the recency effect) is understood to reflect a general property of memory rather than a separate short-term store. This interpretation is supported by the finding of a long-term recency effect under conditions that eliminate the contribution from the short-term store. In this article, evidence is reviewed showing that recency effects in the short and long terms have different properties, and it is suggested that 2 memory components are needed to account for the recency effects: an episodic contextual system with changing context and an activation-based short-term memory buffer that drives the encoding of item–context associations. A neurocomputational model based on these 2 components is shown to account for previously observed dissociations and to make novel predictions, which are confirmed in a set of experiments.

The authors investigated the distinctiveness and interrelationships among visuospatial and verbal memory processes in short-term, working, and long-term memories in 345 adults. Beginning in the 20s, a continuous, regular decline occurs for processing-intensive tasks (e.g., speed of processing, working memory, and long-term memory), whereas verbal knowledge increases across the life span. There is little differentiation in the cognitive architecture of memory across the life span. Visuospatial and verbal working memory are distinct but highly interrelated systems with domain-specific short-term memory subsystems. In contrast to recent neuroimaging data, there is little evidence for dedifferentiation of function at the behavioral level in old compared with young adults. The authors conclude that efforts to connect behavioral and brain data yield a more complete understanding of the aging mind. The present study is a life span approach to understanding visuospatial and verbal working memory and its relationship to long-term memory. It is well-documented that measures of overall cognitive resource such as speed of processing and working memory capacity mediate virtually all age-related variance on higher order cognitive tasks, including long-term memory tasks (Hultsch,

Working memory capacity was differentiated along functional and content-related facets. Twentyfour tasks were constructed to operationalize the cells of the proposed taxonomy. We tested 133 university students with the new tasks, together with six working memory marker tasks. With structural equation models, three working memory functions could be distinguished: Simultaneous storage and processing, supervision, and coordination of elements into structures. Each function was further subdivided into distinct components of variance. On the content dimension, evidence for a dissociation between verbal–numerical working memory and spatial working memory was comparatively weak.

Two studies investigated the relationship between working memory capacity (WMC), adult age, and the resolution of conflict between familiarity and recollection in short-term recognition tasks. Experiment 1 showed a specific deficit of young adults with low WMC in rejecting intrusion probes (i.e., highly familiar probes) in a modified Sternberg task, which was similar to the deficit found in old adults in a parallel experiment (K. Oberauer, 2001). Experiment 2 generalized these results to 3 recognition paradigms (modified Sternberg, local recognition, and n back tasks). Old adults showed disproportional performance deficits on intrusion probes only in terms of reaction times, whereas young adults with low WMC showed them only in terms of errors. The generality of the effect across paradigms is more compatible with a deficit in content–context bindings subserving recollection than with a deficit in inhibition of irrelevant information in working memory. Structural equation models showed that WMC is related to the efficiency of recollection but not of familiarity.

Two experiments investigated whether young and old adults can temporarily remove information from

We show that spurious synchronization, as suggested by Luck and Vogel [6], is not sufficient to explain the limited storage capacity of working memory. Instead we argue that the sharp breakdown of error free recall suggests a dynamic mechanism behind working memory. We summarize some suggestions for the dynamic basis of working memory and argue that the reason behind our limited processing capacity lies in the enhanced ability to process highly complex tasks by the collaboration of mental subsystems. 1 Limited storage capacity of working memory Cognitive science has formulated the concept of working memory which seems to be central to a vast amount of higher mental processes such as language comprehension, reasoning, problem solving and consciousness. However, the understanding of underlying functional mechanisms and neural correlates have been rather scattered. One of the long recognized features of working memory is that of the limited capacity of keeping information from seve...

The current review constitutes the first comprehensive look at the possibility that the mismatch negativity (MMN, the deflection of the auditory ERP/ERF elicited by stimulus change) might be generated by so-called fresh-afferent neuronal activity. This possibility has been repeatedly ruled out for the past 30 years, with the prevailing theoretical accounts relying on a memory-based explanation instead. We propose that the MMN is, in essence, a latency- and amplitude-modulated expression of the auditory N1 response, generated by fresh-afferent activity of cortical neurons