Online research in philosophy

Ruchkin et al. use brain-activity data from healthy subjects to assess the physiological validity of a cognitive working memory model and to propose modifications. The conclusions drawn from this data are interesting and plausible, but they have limitations. Much of what is known about the neural mechanisms of working memory comes from single neuron recordings in animals, and it is currently not fully understood how these translate to scalp recordings of EEG.

Working memory span forms an important cornerstone of current accounts of cognition, and cognitive development. We describe data that challenge the conventional interpretation of span as a measure of working memory capacity. We argue that the implications of these data undermine the analysis provided by Caplan & Waters concerning the role of working memory in sentence comprehension.

Single-unit data from the cortex of monkeys performing working-memory tasks support the main point of the target article. Those data, however, also indicate that the activation of long-term memory is essential to the processing of all cognitive functions. The activation of cortical long-term memory networks is a key neural mechanism in attention (working memory is a form thereof), perception, memory acquisition and retrieval, intelligence, and language.

Caplan & Waters propose a dedicated linguistic working memory to handle “interpretive” language comprehension, but there are data suggesting that more general working memory capacity can predict syntactic comprehension difficulty, and their claims depend on the existence of a principled distinction between “interpretive” and “post-interpretive” processes, which seems unlikely. Other conceptions of the source of individual differences also deserve consideration, as more flexible explanations of the phenomena.

Working-memory retention as activated long-term memory fails to capture orchestrated processing and storage, the hallmark of the concept of working memory. The event-related potential (ERP) data are compatible with working memory as a mental workspace that holds and manipulates information on line, which is distinct from long-term memory, and deals with the products of activated traces from stored knowledge.

The metric devised by Halford, Wilson & Phillips may have considerable potential in distinguishing between the working memory demands of different tasks but may be less effective in distinguishing working memory capacity between individuals. Despite the strengths of the metric, determining whether an effect is caused by relational complexity or by differential levels of expertise is currently problematic.

The limited capacity for unrelated things is a fact that needs to be explained by a general theory of memory, rather than being itself used as a means of explaining data. A pure storage capacity is therefore not the right assumption for memory research. Instead an explanation is needed of how capacity limitations arise from the interaction between the environment and the cognitive system. The ACT-R architecture, a theory without working memory but a long-term memory based on activation, may provide such an explanation.

The present commentary agrees with many of the points made by Ruchkin et al., but brings up several important differences in assumptions. These assumptions have to do with the nature of the capacity limit in working memory and the possible bases of working-memory activation.

The target article differentiates a new, syntactic component in verbal working memory. We suggest that several more components could be differentiated to make a model of working memory complete. Next, syntax is not always separable from the subject's verbal memory capacity as measured by standard working memory tasks. Finally, interference between different processes cannot be taken as evidence for the processes sharing the same resources. Interference might be a result of active mutual inhibition.

Ruchkin et al.'s view of working memory as activated long-term memory is more compatible with language processing than models such as Baddeley's, but it raises questions about individual differences in working memory and the validity of domain-general capacity estimates. Does it make sense to refer to someone as having low working memory capacity if capacity depends on particular knowledge structures tapped by the task?