Functional Brain Network Modularity Captures Inter- and Intra-Individual Variation in Working Memory Capacity

Cognitive abilities, such as working memory, differ among people; however, individuals also vary in their own day-to-day cognitive performance. One potential source of cognitive variability may be fluctuations in the functional organization of neural systems. The degree to which the organization of these functional networks is optimized may relate to the effective cognitive functioning of the individual. Here we specifically examine how changes in the organization of large-scale networks measured via resting state functional connectivity MRI and graph theory track changes in working memory capacity.Twenty-two participants performed a test of working memory capacity and then underwent resting-state fMRI. Seventeen subjects repeated the protocol three weeks later. We applied graph theoretic techniques to measure network organization on 34 brain regions of interest (ROI). Network modularity, which measures the level of integration and segregation across sub-networks, and small-worldness, which measures global network connection efficiency, both predicted individual differences in memory capacity; however, only modularity predicted intra-individual variation across the two sessions. Partial correlations controlling for the component of working memory that was stable across sessions revealed that modularity was almost entirely associated with the variability of working memory at each session. Analyses of specific sub-networks and individual circuits were unable to consistently account for working memory capacity variability.The results suggest that the intrinsic functional organization of an a priori defined cognitive control network measured at rest provides substantial information about actual cognitive performance. The association of network modularity to the variability in an individual's working memory capacity suggests that the organization of this network into high connectivity within modules and sparse connections between modules may reflect effective signaling across brain regions, perhaps through the modulation of signal or the suppression of the propagation of noise

Neural Mechanisms of Interference Control in Working Memory: Effects of Interference Expectancy and Fluid Intelligence

A critical aspect of executive control is the ability to limit the adverse effects of interference. Previous studies have shown activation of left ventrolateral prefrontal cortex after the onset of interference, suggesting that interference may be resolved in a reactive manner. However, we suggest that interference control may also operate in a proactive manner to prevent effects of interference. The current study investigated the temporal dynamics of interference control by varying two factors - interference expectancy and fluid intelligence (gF) - that could influence whether interference control operates proactively versus reactively.A modified version of the recent negatives task was utilized. Interference expectancy was manipulated across task blocks by changing the proportion of recent negative (interference) trials versus recent positive (facilitation) trials. Furthermore, we explored whether gF affected the tendency to utilize specific interference control mechanisms. When interference expectancy was low, activity in lateral prefrontal cortex replicated prior results showing a reactive control pattern (i.e., interference-sensitivity during probe period). In contrast, when interference expectancy was high, bilateral prefrontal cortex activation was more indicative of proactive control mechanisms (interference-related effects prior to the probe period). Additional results suggested that the proactive control pattern was more evident in high gF individuals, whereas the reactive control pattern was more evident in low gF individuals.The results suggest the presence of two neural mechanisms of interference control, with the differential expression of these mechanisms modulated by both experimental (e.g., expectancy effects) and individual difference (e.g., gF) factors

High Visual Working Memory Capacity in Trait Social Anxiety

Working memory capacity is one of the most important cognitive functions influencing individual traits, such as attentional control, fluid intelligence, and also psychopathological traits. Previous research suggests that anxiety is associated with impaired cognitive function, and studies have shown low verbal working memory capacity in individuals with high trait anxiety. However, the relationship between trait anxiety and visual working memory capacity is still unclear. Considering that people allocate visual attention more widely to detect danger under threat, visual working memory capacity might be higher in anxious people. In the present study, we show that visual working memory capacity increases as trait social anxiety increases by using a change detection task. When the demand to inhibit distractors increased, however, high visual working memory capacity diminished in individuals with social anxiety, and instead, impaired filtering of distractors was predicted by trait social anxiety. State anxiety was not correlated with visual working memory capacity. These results indicate that socially anxious people could potentially hold a large amount of information in working memory. However, because of an impaired cognitive function, they could not inhibit goal-irrelevant distractors and their performance decreased under highly demanding conditions

Aging, working memory capacity and the proactive control of recollection:An event-related potential study

The present study investigated the role of working memory capacity (WMC) in the control of recollection in young and older adults. We used electroencephalographic event-related potentials (ERPs) to examine the effects of age and of individual differences in WMC on the ability to prioritize recollection according to current goals. Targets in a recognition exclusion task were words encoded using two alternative decisions. The left parietal ERP old/new effect was used as an electrophysiological index of recollection, and the selectivity of recollection measured in terms of the difference in its magnitude according to whether recognized items were targets or non-targets. Young adults with higher WMC showed greater recollection selectivity than those with lower WMC, while older adults showed nonselective recollection which did not vary with WMC. The data suggest that aging impairs the ability to engage cognitive control effectively to prioritize what will be recollected

Modeling working memory: An interference model of complex span

This article introduces a new computational model for the complex-span task, the most popular task for studying working memory. SOB-CS is a two-layer neural network that associates distributed item representations with distributed, overlapping position markers. Memory capacity limits are explained by interference from a superposition of associations. Concurrent processing interferes with memory through involuntary encoding of distractors. Free time in-between distractors is used to remove irrelevant representations, thereby reducing interference. The model accounts for benchmark findings in four areas: (1) effects of processing pace, processing difficulty, and number of processing steps; (2) effects of serial position and error patterns; (3) effects of different kinds of item-distractor similarity; and (4) correlations between span tasks. The model makes several new predictions in these areas, which were confirmed experimentally

Working Memory Underpins Cognitive Development, Learning, and Education

Working memory is the retention of a small amount of information in a readily accessible form. It facilitates planning, comprehension, reasoning, and problem-solving. I examine the historical roots and conceptual development of the concept and the theoretical and practical implications of current debates about working memory mechanisms. Then I explore the nature of cognitive developmental improvements in working memory, the role of working memory in learning, and some potential implications of working memory and its development for the education of children and adults. The use of working memory is quite ubiquitous in human thought, but the best way to improve education using what we know about working memory is still controversial. I hope to provide some directions for research and educational practice