Changing concepts of working memory

Visual Short-Term Memory Compared in Rhesus Monkeys and Humans

This study is the first to assess lesion-symptom relations for subitizing and counting impairments in a large sample of neuropsychological patients (41 patients) using an observer-independent voxel-based approach. We tested for differential effects of enumerating small versus large numbers of items while controlling for hemianopia and visual attention deficits. Overall impairments in the enumeration of any numbers (small or large) were associated with an extended network, including bilateral occipital and fronto-parietal regions. Within this network, severe impairments in accuracy when enumerating small sets of items (in the subitizing range) were associated with damage to the left posterior occipital cortex, bilateral lateral occipital and right superior frontal cortices. Lesions to the right calcarine extending to the precuneus led to patients serially counting even small numbers of items (indicated by a steep response slope), again demonstrating an impaired subitizing ability. In contrast, impairments in counting large numerosities were associated with damage to the left intraparietal sulcus. The data support the argument for some distinctive processes and neural areas necessary to support subitization and counting with subitizing relying on processes of posterior occipital cortex and with counting associated with processing in the parietal cortex.

A key issue in understanding the evolutionary and developmental emergence of numerical cognition is to learn what mechanism(s) support perception and representation of quantitative information. Two such systems have been proposed, one for dealing with approximate representation of sets of items across an extended numerical range and another for highly precise representation of only small numbers of items. Evidence for the first system is abundant across species and in many tests with human adults and children, whereas the second system is primarily evident in research with children and in some tests with non-human animals. A recent paper (Choo & Franconeri, Psychonomic Bulletin & Review, 21, 93-99, 2014) with adult humans also reported "superprecise" representation of small sets of items in comparison to large sets of items, which would provide more support for the presence of a second system in human adults. We first presented capuchin monkeys with a test similar to that of Choo and Franconeri in which small or large sets with the same ratios had to be discriminated. We then presented the same monkeys with an expanded range of comparisons in the small number range (all comparisons of 1-9 items) and the large number range (all comparisons of 10-90 items in 10-item increments). Capuchin monkeys showed no increased precision for small over large sets in making these discriminations in either experiment. These data indicate a difference in the performance of monkeys to that of adult humans, and specifically that monkeys do not show improved discrimination performance for small sets relative to large sets when the relative numerical differences are held constant.

This study was conducted to assess the National Health Insurance Fund (NHIF) program in Sudan in terms of the expenditure trends over the period of 5 years (2006 and 2010), their value of usage and the pattern of medicines expenditure. The standard tools for analysing aggregate medicine data (ABC and VEN) analysis were used. The total value of consumption was calculated by multiplying quantities by unit cost, and the total values sorted in descending order. The percentage of total value for each item was calculated. Similarly, for Vital, Essential and Non-essential (VEN) analysis, the NHIF medicine lists (2006 and 2007) were classified as vital, essential or non-essential medicines (based on explanatory statement for physician, medical doctors and pharmacists). ABC analysis showed that small number of items (n = 80, 16.98%) in Class A account for large proportion of the fund (70.19%), whereas large number of items (n = 288, 61.15%) of Class C account only for 9.92% of the total fund. Similarly, the VEN analysis showed that small number of items (n = 11, 2.34%) of Class V account for 5.46%, whereas Class N consists of 212 (45.01%) items that account for 26.43% of the total fund. The medicine class that accounted for the highest expenditure were medicines related to general anti-infectives for systemic use (40.37%) and it made the largest contribution to increases in the total medicine expenditure (48.59%). The findings reveal that relatively small number of items accounts for most of the value of the supply fund and non-essential items represent around half of number of NHIF items and account for around quarter of the total fund.

To explore the influence of chunking on the capacity limits of working memory, a model for chunking in sequential working memory is proposed, using hierarchical bidirectional inhibition-connected neural networks with winnerless competition. With the assumption of the existence of an upper bound to the inhibitory weights in neurobiological networks, it is shown that chunking increases the number of memorized items in working memory from the "magical number 7" to 16 items. The optimal number of chunks and the number of the memorized items in each chunk are the "magical number 4".

Human short-term spatial memory: Precision predicts capacity

How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list ABADBD. Comparisons with other models, including TRACE, MERGE, and TISK, are made.

Although humans are the only species to possess language-driven abstract mathematical capacities, we share with many other animals a nonverbal capacity for estimating quantities or numerosity. For some time, researchers have clearly differentiated between small numbers of items--less than about four--referred to as the subitizing range, and larger numbers, where counting or estimation is required. In this review, we examine more recent evidence suggesting a further division, between sets of items greater than the subitizing range, but sparse enough to be individuated as single items; and densely packed stimuli, where they crowd each other into what is better considered as a texture. These two different regimes are psychophysically discriminable in that they follow distinct psychophysical laws and show different dependencies on eccentricity and on luminance levels. But provided the elements are not too crowded (less than about two items per square degree in central vision, less in the periphery), there is little evidence that estimation of numerosity depends on mechanisms responsive to texture. The distinction is important, as the ability to discriminate numerosity, but not texture, correlates with formal maths skills.

The Wechsler Memory Scale-Revised (Wechsler, 1987) was elaborated by adding 20 recognition items for Logical Memory (LM) and by adding recognition, matching, and copy trials for Visual Reproductions (VR). Reliability was very good for VR copy (α = .77, interrater agreement, 100% within 1 point). Reliability was modest for LM recognition (α = .42) and for VR recognition (α = .58), but reasonable given the small number of items on each measure. The reliability coefficient was very weak for VR matching (a = .10), limited considerably by the ease of the task for this healthy sample and by the small number of items. After statistically correcting for imperfect reliability, validity coefficients (correlations with similar tests that are well standardized) were good for all of the new trials (r = .60 to r = 1.00). Age- and education-appropriate reference data are provided using 81 healthy adults. Further validation using theoretically and clinically meaningful patient groups would be very valuable. In the meantime, the new trials should serve the clinician well as screening tools.

Human infants can discriminate between different small numbers of items, and can determine numerical equivalence across perceptual modalities. This may indicate the possession of true numerical concepts. Alternatively, purely perceptual discriminations may underlie these abilities. This debate addresses the nature of subitization, the ability to quantify small numbers of items without conscious counting. Subitization may involve the holistic recognition of canonical perceptual patterns that do not reveal ordinal relationships between the numbers, or may instead be an iterative or 'counting' process that specifies these numerical relationships. Here I show that 5-month-old infants can calculate the results of simple arithmetical operations on small numbers of items. This indicates that infants possess true numerical concepts, and suggests that humans are innately endowed with arithmetical abilities. It also suggests that subitization is a process that encodes ordinal information, not a pattern-recognition process yielding non-numerical percepts.

Discrete forms of repetitive thought (RT), such as worry and reflection, can be characterized along basic dimensions of valence (positive vs. negative) and purpose (searching vs. solving). In addition, people can be characterized as high or low in their tendency to engage in RT. This dimensional model has been demanding to assess, and a smaller number of items that could stand in for a large battery would make measurement more accessible. Using four samples (N = 1,588), eight items that assess RT valence, purpose, and total in a circumplex model were identified. Across these and other samples, the dimensions were adequately reliable and valid with regard to assessment via large RT battery, other measures of RT, and depressive symptoms. The accessibility of dimensional assessment of RT using this smaller number of items should facilitate work on questions about the qualities of RT that predict mental and physical health.

The ability to encode, store, and retrieve visually presented objects is referred to as visual working memory (VWM). Although crucial for many cognitive processes, previous research reveals that VWM strictly capacity limited. This capacity limitation is behaviorally observable in the set size effect: the ability to successfully report items in VWM asymptotes at a small number of items. Research into the neural correlates of set size effects and VWM capacity limits in general largely focus on the maintenance period of VWM. However, we previously reported that neural resources allocated to individual items during VWM encoding correspond to successful VWM performance. Here we expand on those findings by investigating neural correlates of set size during VWM encoding. We hypothesized that neural signatures of encoding-related VWM capacity limitations should be differentiable as a function of set size. We tested our hypothesis using High Density Electroencephalography (HD-EEG) to analyze frequency components evoked by flickering target items in VWM displays of set size 2 or 4. We found that set size modulated the amplitude of the 1st and 2nd harmonic frequencies evoked during successful VWM encoding across frontal and occipital-parietal electrodes. Frontal sites exhibited the most robust effects for the 2nd harmonic (set size 2 > set size 4). Additionally, we found a set-size effect on the induced power of delta-band (1–4 Hz) activity (set size 2 > set size 4). These results are consistent with a capacity limited VWM resource at encoding that is distributed across to-be-remembered items in a VWM display. This resource may work in conjunction with a task-specific selection process that determines which items are to be encoded and which are to be ignored. These neural set size effects support the view that VWM capacity limitations begin with encoding related processes.

[This corrects the article DOI: 10.1371/journal.pone.0167022.].

Some Thoughts Concerning the Recent Shift from Measures with Many Items to Measures with Few Items

Plum take-away