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The ability to maintain arbitrary sequences of items in the mind contributes to major cognitive faculties, such as language, reasoning, and episodic memory. Previous research suggests that serial order working memory is grounded in the brain's spatial attention system. In the present study, we show that the spatially defined mental organization of novel item sequences is related to literacy and varies as a function of reading/writing direction. Specifically, three groups (left-to-right Western readers, right-to-left Arabic readers, and Arabic-speaking illiterates) were asked to memorize random (and non-spatial) sequences of color patches and determine whether a subsequent probe was part of the memorized sequence (e.g., press left key) or not (e.g., press right key). The results showed that Western readers mentally organized the sequences from left to right, Arabic readers spontaneously used the opposite direction, and Arabic-speaking illiterates showed no systematic spatial organization. This finding suggests that cultural conventions shape one of the most "fluid" aspects of human cognition, namely, the spontaneous mental organization of novel non-spatial information.

This paper attempts to evaluate the capacity of immediate memory to cope with new situations in relation to the compressibility of information likely to allow the formation of chunks. We constructed a task in which untrained participants had to immediately recall sequences of stimuli with possible associations between them. Compressibility of information was used to measure the chunkability of each sequence on a single trial. Compressibility refers to the recoding of information in a more compact representation. Although compressibility has almost exclusively been used to study long-term memory, our theory suggests that a compression process relying on redundancies within the structure of the list materials can occur very rapidly in immediate memory. The results indicated a span of about three items when the list had no structure, but increased linearly as structure was added. The amount of information retained in immediate memory was maximal for the most compressible sequences, particularly when information was ordered in a way that facilitated the compression process. We discuss the role of immediate memory in the rapid formation of chunks made up of new associations that did not already exist in long-term memory, and we conclude that immediate memory is the starting place for the reorganization of information.

A number of studies have investigated whether category learning is influenced by the order in which examples are presented. Elio and Anderson (1981) found that categories are learned faster when training is blocked into groups of mutually similar examples (see also Elio & Anderson, 1984). More recently, Medin and Bettger (1994) demonstrated a strong learning advantage when training objects were presented in an order that tended to maximize similarity between successive examples. Other studies, such as those of Clapper and Bower (1994) and Goldstone (1996), have focused on the effect of alternation of contrasting categories. Presentation order effects are especially interesting in the light of categorization models that emphasize incremental learning from trial to trial. For example, Sakamoto, Jones, and Love (2008) showed that order can affect the incremental update of both category means and variances (see also Love, Medin, & Gureckis, 2004). Incremental-learning models are naturally susceptible to order effects, whereas other models may be less so, so the manipulation of presentation order is a potentially useful tool for studying the mechanisms of learning.However, previous studies of presentation order were limited in that they used orders based on simple similarity-for example, maximizing or minimizing the similarity between adjacent training examples. Here, we explore a type of presentation order that depends in a more structured way on the nature of the category to be learned. We introduce the notion of a rule-based presentation order, which is one that derives from the internal structure of the training examples. In our rule-based order, objects that are within a rule-that is, that obey the same structured subclass within the category-are presented adjacently in the presentation sequence. Training then moves on to another subclass, and so forth until all the objects have been presented. (Negative instances are randomly interspersed among the positives; only the order of the positives is manipulated.) Below, we will compare subjects' performance with such an order with the similarity-based order found to be advantageous in earlier studies. For comparison, we will also include a dissimilarity-based order, previously found to be disadvantageous. We hypothesize that the rulebased order will facilitate learning, particularly in highly structured concepts (i.e., those containing more clusters), by aiding the subject in mentally organizing what would otherwise appear heterogeneous or chaotic. METHOD SubjectsThe subjects were 96 Rutgers University students who received course credit in exchange for their participation. ProcedureTasks were computer-driven. The subjects learned to sort stimulus objects using two keys, with successful learning encouraged by means of a progress bar. Stimulus objects were presented one at a time in the upper part of the computer screen. After each response, feedback indicating a correct or incorrect classification was provided at the bottom of the screen for 2 sec. The subjects learn...

This paper reports a study of a multi-agent model of working memory (WM) in the context of Boolean concept learning. The model aims to assess the compressibility of information processed in WM. Concept complexity is described as a function of communication resources (i.e., the number of agents and the structure of communication between agents) required in WM to learn a target concept. This model has been successfully applied in measuring learning times for three-dimensional (3D) concepts (Mathy and Bradmetz in Curr Psychol Cognit 22(1):41-82, 2004). In this previous study, learning time was found to be a function of compression time. To assess the effect of decompression time, this paper presents an extended intra-conceptual study of response times for two- and 3D concepts. Response times are measured in recognition phases. The model explains why the time required to compress a sample of examples into a rule is directly linked to the time to decompress this rule when categorizing examples. Three experiments were conducted with 65, 49, and 84 undergraduate students who were given Boolean concept learning tasks in two and three dimensions (also called rule-based classification tasks). The results corroborate the metric of decompression given by the multi-agent model, especially when the model is parameterized following static serial processing of information. Also, this static serial model better fits the patterns of response times than an exemplar-based model.

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This study of supervised categorization shows how different kinds of category representations are influenced by the order in which training examples are presented. We used the well-studied 5-4 category structure of Medin and Schaffer (1978) , which allows transfer of category learning to new stimuli to be discriminated as a function of rule-based or similarity-based category knowledge. In the rule-based training condition (thought to facilitate the learning of abstract logical rules and hypothesized to produce rule-based classification), items were grouped by subcategories and randomized within each subcategory. In the similarity-based training condition (thought to facilitate associative learning and hypothesized to produce exemplar classification), transitions between items within the same category were determined by their featural similarity and subcategories were ignored. We found that transfer patterns depended on whether the presentation order was similarity-based, or rule-based, with the participants particularly capitalizing on the rule-based order.

Complex working memory span tasks were designed to engage multiple aspects of working memory and impose interleaved processing demands that limit the use of mnemonic strategies, such as chunking. Consequently, the average span is usually lower (4 ± 1 items) than in simple span tasks (7 ± 2 items). One possible reason for the higher span of simple span tasks is that participants can take advantage of the spare time to chunk multiple items together to form fewer independent units, approximating 4 ± 1 chunks. It follows that the respective spans of these two types of tasks could be equal (at around 4 ± 1) if stimulus lists exclusively used nonchunkable stimulus items. To manipulate the chunkability of the stimulus lists, our method involved a measure of their compressibility, i.e., the extent to which a pattern exists that can be detected and used as a basis of chunk formation. We predicted an interaction between the types of tasks and chunkability/compressibility, supporting a single higher span for the condition in which a simple span task was combined with chunkable items. The three other conditions were predicted to prevent chunking processes, either because the interleaved processing task did not allow any chunking process to occur or because the noncompressible material inherently limited the chunkability of information. The prediction that chunking is important solely in simple spans was not confirmed: Effects of information compression contributed to performance levels to a similar extent in both tasks according to a theoretically-based metric. This result suggests that i ) complex span tasks might overestimate storage capacity in general, and ii ) the difference between simple and complex span performance levels must rest in some mechanism other than prevention of a chunking strategy by the interleaved processing task in complex span tasks.