The amount of task-irrelevant information encoded in visual working memory (VWM), referred to as unnecessary storage, has been proposed as a potential mechanism underlying individual differences in VWM capacity. In addition, a number of studies have provided evidence for additional activity that initiates the filtering process originating in the frontal cortex and basal ganglia, and is therefore a crucial step in the link between unnecessary storage and VWM capacity. Here, we re-examine data from two prominent studies that identified unnecessary storage activity as a predictor of VWM capacity by directly testing the implied path model linking filtering-related activity, unnecessary storage, and VWM capacity. Across both studies, we found that unnecessary storage was not a significant predictor of individual differences in VWM capacity once activity associated with filtering was accounted for; instead, activity associated with filtering better explained variation in VWM capacity. These findings suggest that unnecessary storage is not a limiting factor in VWM performance, whereas neural activity associated with filtering may play a more central role in determining VWM performance that goes beyond preventing unnecessary storage.Keywords Working memory . Attention . ERP . Short-term memory . fMRIOver the past few decades, there has been enormous interest in understanding the nature of visual working memory (VWM), which enables the on-line maintenance of a limited amount of visual information over short periods of time. In particular, a number of studies have focused on understanding the origins of individual differences in VWM capacity (Luck & Vogel, 2013). That is, VWM has a limited bandwidth, and as such, the number of items (capacity) and/or the fidelity of information stored in VWM appear to be severely limited, with significant individual differences in this ability.Although the precise origins of individual differences in VWM capacity remains unclear, one mechanism that has been proposed to account for these differences is the ability to efficiently allocate limited capacity resources through the filtering of unnecessary (distractor) information, thereby minimizing the unnecessary storage of task-irrelevant information (Awh & Vogel, 2008;Luck & Vogel, 2013). Specifically, if VWM is characterized as having a limited number of storage Bslots,t hen any item that is encoded into VWM will occupy one of these storage units. According to this model, the more control you have over which information gains access to VWM, the less likely you are to encode task-irrelevant information that will occupy these limited storage slots, thereby freeing up these resources for the task-relevant items. This efficient allocation of capacity-limited resources has been linked to VWM capacity, as shown by a positive correlation between measures of filtering efficiency and VWM capacity (Vogel, Mccollough, & Machizawa, 2005). From this perspective, filtering efficiency can be indexed by the amount of unnecessary activity -that is,...