Previous research has suggested that visual short-term memory has a fixed capacity of about four objects. However, we found that capacity varied substantially across the five stimulus classes we examined, ranging from 1.6 for shaded cubes to 4.4 for colors (estimated using a change detection task). We also estimated the information load per item in each class, using visual search rate. The changes we measured in memory capacity across classes were almost exactly mirrored by changes in the opposite direction in visual search rate (r2=.992 between search rate and the reciprocal of memory capacity). The greater the information load of each item in a stimulus class (as indicated by a slower search rate), the fewer items from that class one can hold in memory. Extrapolating this linear relationship reveals that there is also an upper bound on capacity of approximately four or five objects. Thus, both the visual information load and number of objects impose capacity limits on visual short-term memory.

One of the major lessons of memory research has been that human memory is fallible, imprecise, and subject to interference. Thus, although observers can remember thousands of images, it is widely assumed that these memories lack detail. Contrary to this assumption, here we show that long-term memory is capable of storing a massive number of objects with details from the image. Participants viewed pictures of 2,500 objects over the course of 5.5 h. Afterward, they were shown pairs of images and indicated which of the two they had seen. The previously viewed item could be paired with either an object from a novel category, an object of the same basic-level category, or the same object in a different state or pose. Performance in each of these conditions was remarkably high (92%, 88%, and 87%, respectively), suggesting that participants successfully maintained detailed representations of thousands of images. These results have implications for cognitive models, in which capacity limitations impose a primary computational constraint (e.g., models of object recognition), and pose a challenge to neural models of memory storage and retrieval, which must be able to account for such a large and detailed storage capacity.object recognition ͉ gist ͉ fidelity

The visual system can only accurately represent a handful of objects at once. How do we cope with this severe capacity limitation? One possibility is to use selective attention to process only the most relevant incoming information. A complementary strategy is to represent sets of objects as a group or ensemble (e.g. represent the average size of items). Recent studies have established that the visual system computes accurate ensemble representations across a variety of feature domains and current research aims to determine how these representations are computed, why they are computed and where they are coded in the brain. Ensemble representations enhance visual cognition in many ways, making ensemble coding a crucial mechanism for coping with the limitations on visual processing.

Humans have a massive capacity to store detailed information in visual long-term memory. The present studies explored the fidelity of these visual long-term memory representations and examined how conceptual and perceptual features of object categories support this capacity. Observers viewed 2,800 object images with a different number of exemplars presented from each category. At test, observers indicated which of 2 exemplars they had previously studied. Memory performance was high and remained quite high (82% accuracy) with 16 exemplars from a category in memory, demonstrating a large memory capacity for object exemplars. However, memory performance decreased as more exemplars were held in memory, implying systematic categorical interference. Object categories with conceptually distinctive exemplars showed less interference in memory as the number of exemplars increased. Interference in memory was not predicted by the perceptual distinctiveness of exemplars from an object category, though these perceptual measures predicted visual search rates for an object target among exemplars. These data provide evidence that observers’ capacity to remember visual information in long-term memory depends more on conceptual structure than perceptual distinctiveness.

Much of our interaction with the visual world requires us to isolate some currently important objects from other less important objects. This task becomes more difficult when objects move, or when our field of view moves relative to the world, requiring us to track these objects over space and time. Previous experiments have shown that observers can track a maximum of about 4 moving objects. A natural explanation for this capacity limit is that the visual system is architecturally limited to handling a fixed number of objects at once, a so-called magical number 4 on visual attention. In contrast to this view, Experiment 1 shows that tracking capacity is not fixed. At slow speeds it is possible to track up to 8 objects, and yet there are fast speeds at which only a single object can be tracked. Experiment 2 suggests that that the limit on tracking is related to the spatial resolution of attention. These findings suggest that the number of objects that can be tracked is primarily set by a flexibly allocated resource, which has important implications for the mechanisms of object tracking and for the relationship between object tracking and other cognitive processes.

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Working memory is a mental storage system that keeps task-relevant information accessible for a brief span of time, and it is strikingly limited. Its limits differ substantially across people but are assumed to be fixed for a given person. Here we show that there is substantial variability in the quality of working memory representations within an individual. This variability can be explained neither by fluctuations in attention or arousal over time, nor by uneven distribution of a limited mental commodity. Variability of this sort is inconsistent with the assumptions of the standard cognitive models of working memory capacity, including both slot- and resource-based models, and so we propose a new framework for understanding the limitations of working memory: a stochastic process of degradation that plays out independently across memories.

Traditional memory research has focused on identifying separate memory systems and exploring different stages of memory processing. This approach has been valuable for establishing a taxonomy of memory systems and characterizing their function, but has been less informative about the nature of stored memory representations. Recent research on visual memory has shifted towards a representation-based emphasis, focusing on the contents of memory, and attempting to determine the format and structure of remembered information. The main thesis of this review will be that one cannot fully understand memory systems or memory processes without also determining the nature of memory representations. Nowhere is this connection more obvious than in research that attempts to measure the capacity of visual memory. We will review research on the capacity of visual working memory and visual long-term memory, highlighting recent work that emphasizes the contents of memory. This focus impacts not only how we estimate the capacity of the system - going beyond quantifying how many items can be remembered, and moving towards structured representations - but how we model memory systems and memory processes.