Short-term memory storage can be divided into separate subsystems for verbal information and visual information, and recent studies have begun to delineate the neural substrates of these working-memory systems. Although the verbal storage system has been well characterized, the storage capacity of visual working memory has not yet been established for simple, suprathreshold features or for conjunctions of features. Here we demonstrate that it is possible to retain information about only four colours or orientations in visual working memory at one time. However, it is also possible to retain both the colour and the orientation of four objects, indicating that visual working memory stores integrated objects rather than individual features. Indeed, objects defined by a conjunction of four features can be retained in working memory just as well as single-feature objects, allowing sixteen individual features to be retained when distributed across four objects. Thus, the capacity of visual working memory must be understood in terms of integrated objects rather than individual features, which places significant constraints on cognitive and neurobiological models of the temporary storage of visual information.

Limits on the storage capacity of working memory significantly affect cognitive abilities in a wide range of domains 1 , but the nature of these capacity limits has been elusive 2 . Some researchers have proposed that working memory stores a limited set of discrete, fixed-resolution representations 3 , whereas others have proposed that working memory consists of a pool of resources that can be allocated flexibly to provide either a small number of highresolution representations or a large number of low-resolution representations 4 . Here we resolve this controversy by providing independent measures of capacity and resolution. We show that, when presented with more than a few simple objects, human observers store a high-resolution representation of a subset of the objects and retain no information about the others. Memory resolution varied over a narrow range that cannot be explained in terms of a general resource pool but can be well explained by a small set of discrete, fixed-resolution representations.To separately measure the number of items stored in working memory and the precision of each representation, we used a shortterm recall paradigm 5,6 in which subjects report the remembered colour of a probed item by clicking on a colour wheel (Fig. 1a). If the probed item has been stored in working memory, the recalled value will tend to be near the original colour. If the probed item has not been stored, then the observer will have no information about the colour, and the responses should be random. These two types of trials are mixed together in the data (Fig. 1b), but the components can be recovered via standard estimation methods. This produces one parameter (P m ) representing the probability that the probed item was present in memory at the time of the probe and another parameter (s.d.) representing the precision of the representation when the cued item was present in memory.Experiment 1 (N 5 8) tested this model using set sizes of 3 or 6 coloured squares (Fig. 1c). s.d. did not vary significantly across set sizes (F , 1), whereas P m was approximately twice as great at set size 3 as at set size 6 (F (1,7) 5 761.26, P , 0.001). Our simple fixed-resolution model provided an excellent quantitative fit to the data, whereas a model in which all items are encoded could not fit the data (see Supplementary Notes). This result rules out the entire class of working memory models in which all items are stored but with a resolution or noise level that depends on the number of items in memory 5 . Control experiments demonstrated that these results cannot be explained by a lack of time to encode the items or by a lack of sensitivity, and additional analyses demonstrated that the observers remembered continuous colour values rather than colour categories (see Supplementary Notes).These results demonstrate that observers store a small number of representations with good precision. However, it is possible that performance is influenced both by a limited number of 'storage slots' and a limited pool of resources 7 . As an an...

Many neurons in extrastriate visual cortex have large receptive fields, and this may lead to significant computational problems whenever multiple stimuli fall within a single field. Previous studies have suggested that when multiple stimuli fall within a cell's receptive field, they compete for the cell's response in a manner that can be biased in favor of attended stimuli. In the present study we examined this role of attention in areas V1, V2, and V4 of macaque monkeys with the use of a behavioral paradigm in which attention was directed to one of two stimulus locations. When two stimuli were presented simultaneously inside the cell's receptive field (which could be accomplished only in areas V2 and V4), we found that the cell's response was strongly influenced by which of the two stimuli was attended. The size of this attention effect was reduced when the attended and ignored stimuli were presented sequentially rather than simultaneously. In addition, the effects became very weak and inconsistent in these areas when only one of the two stimuli was located inside the receptive field. Attention thus modulated sensory responses primarily when two or more simultaneous stimuli competed for access to a neuron's receptive field. As in areas V2 and V4, attention did not modulate sensory responses in area V1 when only a single stimulus was inside the receptive field. In addition, the small receptive fields in this area precluded the simultaneous presentation of attended and ignored stimuli inside the receptive field, making it impossible to determine whether attention effects would be observed under the conditions that led to consistent attention effects in areas V2 and V4. Spontaneous firing rates in areas V2 and V4 were found to be 30-40% higher when attention was directed inside rather than outside the receptive field, even when no stimulus was present in the receptive field. Spontaneous firing rates also varied according to the particular location within the receptive field that was attended. These shifts in spontaneous activity may reflect a top-down signal that biases responses in favor of stimuli at the attended location.

Working memory can be divided into separate subsystems for verbal and visual information. Although the verbal system has been well characterized, the storage capacity of visual working memory has not yet been established for simple features or for conjunctions of features. The authors demonstrate that it is possible to retain information about only 3-4 colors or orientations in visual working memory at one time. Observers are also able to retain both the color and the orientation of 3-4 objects, indicating that visual working memory stores integrated objects rather than individual features. Indeed, objects defined by a conjunction of four features can be retained in working memory just as well as single-feature objects, allowing many individual features to be retained when distributed across a small number of objects. Thus, the capacity of visual working memory must be understood in terms of integrated objects rather than individual features.

ERPLAB toolbox is a freely available, open-source toolbox for processing and analyzing event-related potential (ERP) data in the MATLAB environment. ERPLAB is closely integrated with EEGLAB, a popular open-source toolbox that provides many EEG preprocessing steps and an excellent user interface design. ERPLAB adds to EEGLAB’s EEG processing functions, providing additional tools for filtering, artifact detection, re-referencing, and sorting of events, among others. ERPLAB also provides robust tools for averaging EEG segments together to create averaged ERPs, for creating difference waves and other recombinations of ERP waveforms through algebraic expressions, for filtering and re-referencing the averaged ERPs, for plotting ERP waveforms and scalp maps, and for quantifying several types of amplitudes and latencies. ERPLAB’s tools can be accessed either from an easy-to-learn graphical user interface or from MATLAB scripts, and a command history function makes it easy for users with no programming experience to write scripts. Consequently, ERPLAB provides both ease of use and virtually unlimited power and flexibility, making it appropriate for the analysis of both simple and complex ERP experiments. Several forms of documentation are available, including a detailed user’s guide, a step-by-step tutorial, a scripting guide, and a set of video-based demonstrations.

Event-related brain potentials (ERPs) were recorded from normal young adults during visual search tasks in which the stimulus arrays contained either eight identical items (homogeneous arrays) or seven identical items and one deviant item (pop-out arrays). Four experiments were conducted in which different classes of stimulus arrays were designated targets and the remaining stimulus arrays were designated nontargets. In Experiments 1 and 2, both target and nontarget pop-out stimuli elicited an enhanced anterior N2 wave and a contralaterally larger posterior P1 wave, but Experiments 3 and 4 demonstrated that these components do not reflect fully automatic pop-out detection processes. In all four experiments, target pop-outs elicited enlarged anterior P2, posterior N2, occipital P3, and parietal P3 waves. The target-elicited posterior N2 wave contained a contralateral subcomponent (N2pc) that exhibited a focus over occipital cortex in maps of current source density. The overall pattern of results was consistent with guided search models in which preattentive stimulus information is used to guide attention to task-relevant stimuli.

The identification of targets in visual search arrays may be improved by suppressing competing information from the surrounding distractor items. The present study provided evidence that this hypothetical filtering process has a neural correlate, the "N2pc" component of the event-related potential waveform. The N2pc was observed when a target item was surrounded by competing distractor items but was absent when the array could be rejected as a nontarget on the basis of simple feature information. In addition, the N2pc was eliminated when filtering was discouraged by removing the distractor items, making the distractors relevant, or making all items within an array identical. Combined with previous topographic analyses, these results suggest that attentional filtering occurs in occipital cortex under the control of feedback from higher cortical regions after a preliminary feature-based analysis of the stimulus array.

nisms may be used for space-based attention that are not available for time-based attention. In this study we addressed this issue by comparing the nature of attentional selection in a time-based attention task with previous findings from space-based attention tasks.