An oscillatory model of individual differences in working memory capacity and relational integration

Saturation of auditory short-term memory causes a plateau in the sustained anterior negativity event-related potential

“…It seems, therefore, that the network of regions underpinning VSTM and ASTM at least partially diverges in modality-specific ways. Common activations may be related to the recruitment of executive areas, such as the prefrontal and the parietal cortex, implicated in monitoring of information to reinforce the maintenance and perhaps re-activate representation is the primary memory store (Champod and Petrides, 2007;Edin et al, 2009;Chuderski et al, 2013).…”

Gestalt Effects in Visual Working Memory

“…This differentiated impact of the number of objects versus features on VWM capacity is compatible with the fact that VWM subsystem responsible for maintaining object features is located within the superior parietal lobule, whereas the binding of complete objects from those features most probably takes place within the inferior parietal lobule (Xu & Chun, 2009). In order to explain how single features can be bound into objects, and maintained univocally, oscillatory computational models have been developed (Chuderski, Andrelczyk & Smoleń, 2013;Raffone & Wolters, 2001). …”

From neural oscillations to reasoning ability: Simulating the effect of the theta-to-gamma cycle length ratio on individual scores in a figural analogy test

“…The parameter b controls the strength of that inhibition. Previous simulations (see Chuderski et al, 2013) demonstrated that b is the main factor controlling the capacity of our oscillatory model. An increase in b negatively impacted available capacity, because the higher the values of b, the more elements become eliminated from WM (fall permanently below the threshold arbitrarily set to .2; however the exact value of threshold is not important as long as it is relatively small).…”

“…The previous version of the model, presented by Chuderski, Andrelczyk, and Smoleń (2013), simulated the capacity limits in two WM tasks. The model predicted basic phenomena found in WM tasks (e.g., the recency, context, and capacity-related effects), as well as the distribution of individual capacities in the sample of 168 people.…”

“…The sole manipulated variable was the number of feature transformations per each location transformation (binary, ternary, or quaternary). Moreover, for each participant, four WM tasks (so-called change detection tasks; for the task description see Chuderski, 2014b; for the task model see Chuderski et al, 2013), were applied in order to screen WM capacity. They required the comparison of the memorized pattern of five, seven, or nine stimuli to a target, and used figural, color, letter, and number stimuli.…”