Online research in philosophy

Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. However, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide variety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity limits will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recoding of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity-limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed. Key Words: attention; enumeration; information chunks; memory capacity; processing capacity; processing channels; serial recall; short-term memory; storage capacity; verbal recall; working memory capacity.

Cowan's concept of a pure short-term memory (STM) capacity limit is equivalent to that of memory subitizing. However, a robust phenomenon well known in the Sternberg paradigm, that is, the linear increase of RT as a function of memory set size is not consistent with this concept. Cowan's STM capacity theory will remain incomplete until it can account for this phenomenon.

Although there are various ways to express actions and behaviors in natural languages, it is found in cognitive informatics that human and system behaviors may be classified into three basic categories: to be , to have , and to do . All mathematical means and forms, in general, are an abstract description of these three categories of system behaviors and their common rules. Taking this view, mathematical logic may be perceived as the abstract means for describing to be, set theory for describing 'to have,' and algebras, particularly the process algebra, for describing to do. This is a fundamental view toward the formal description and modeling of human and system behaviors in general, and software behaviors in particular, because a software system can be perceived as a virtual agent of human beings, and it is created to do something repeatable, to extend human capability, reachability, and/or memory capacity. The author found that both human and software behaviors can be described by a three-dimensional representative model comprising action, time, and space. For software system behaviors, the three dimensions are known as mathematical operations, event/process timing, and memory manipulation. This paper introduces the real-time process algebra (RTPA) that serves as an expressive notation system for describing thoughts and notions of dynamic software behaviors. Experimental case studies on applications of RTPA in describing the equivalent software and human behaviors as a series of actions and cognitive processes are demonstrated with real-world examples.

The limited capacity of immediate memory “rides” on the even more limited capacity of consciousness, which reflects the dynamic activity of the thalamocortical core of the brain. Recent views of the conscious narrow-capacity component of the brain are explored with reference to global workspace theory (Baars 1988; 1993; 1998). The radical limits of immediate memory must be explained in terms of biocognitive brain architecture.

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?

Time and Memory throws new light on fundamental aspects of human cognition and consciousness by bringing together, for the first time, psychological and philosophical approaches dealing with the connection between the capacity to represent and think about time, and the capacity to recollect the past. Fifteen specially written essays offer insights into current theories of memory processes and of the mechanisms and cognitive abilities underlying temporal judgements, and draw out key issues concerning the phenomenology and epistemology of memory and its role in our understanding of time.

A physiological model for short-term memory (STM) based on dual theta (5–10 Hz) and gamma (20–60 Hz) oscillation was proposed by Lisman and Idiart (1995). In this model a memory is represented by groups of neurons that fire in the same gamma cycle. According to this model, capacity is determined by the number of gamma cycles that occur within the slower theta cycle. We will discuss here the implications of recent reports on theta oscillations recorded in humans performing the Sternberg task. Assuming that the oscillatory memory models are correct, these findings can help determine STM capacity.

Although working memory capacity and executive function contribute to human intelligence, we question whether there is an equivalence between them and fluid intelligence. We contend that any satisfactory neurobiological explanation of fluid intelligence needs to include abstraction as an important computational component of brain processing. (Published Online April 5 2006).

Different hypotheses about the mechanisms underlying working memory lead to different predictions about working memory capacity when information is distributed across the two hemispheres. We present preliminary data suggesting that memory scanning time (a parameter often associated with working memory capacity) varies depending on how information is subdivided across hemispheres. The data are consistent with a distributed model of working memory.

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.