Is the Binding of Visual Features in Working MemoryResource-Demanding?

Richard J. Allen, Alan D. Baddeley, and Graham J. HitchUniversity of York

The episodic buffer component of working memory is assumed to play a role in the binding of featuresinto chunks. A series of experiments compared memory for arrays of colors or shapes with memory forbound combinations of these features. Demanding concurrent verbal tasks were used to investigate therole of general attentional processes, producing load effects that were no greater on memory for featurecombinations than for the features themselves. However, the binding condition was significantly lessaccurate with sequential rather than simultaneous presentation, especially for items earlier in thesequence. The findings are interpreted as evidence of a relatively automatic but fragile visual featurebinding mechanism in working memory. Implications for the concept of an episodic buffer are discussed.

Keywords: feature binding, working memory, central executive, attention, episodic buffer

Working memory is assumed to be a limited capacity system forthe temporary storage and manipulation of information, a systemthat underpins the capacity for such complex cognitive tasks asreasoning, learning, and comprehension. One widely held view isthat it consists of a number of separate subsystems, as in thethree-component model of working memory proposed by Badde-ley and Hitch (1974). However, it has gradually become clear thatthis model fails to address how different types of informationabout the same stimulus or event are bound together to formintegrated representations. The omission is particularly obviouswhen the relevant information is stored in different subsystems, orwhen binding involves access to long-term memory, but appliesequally well when all the relevant information is stored in a singlesubsystem. In a recent attempt to address this and other shortcom-ings, Baddeley (2000) proposed adding a fourth component (seeFigure 1), a limited capacity episodic buffer that has binding as oneof its principal functions. The present study forms part of a broaderinvestigation into the role of working memory in different aspectsof binding that extends from relatively simple perceptually basedmemory tasks up to the retention of sentences and prose (e.g.,Jefferies, Lambon Ralph, & Baddeley, 2004).

The issue of binding has also arisen independently in the contextof visual short-term memory, where techniques developed to studyvisual attention are being fruitfully applied to understanding themechanisms by which visual stimuli are temporarily maintained(e.g., Luck & Vogel, 1997; Wheeler & Treisman, 2002). Bindingin visual short-term memory refers to grouping together different

features of an object such as color and shape and maintaining themseparately from features belonging to other objects in memory.Given that visual short-term memory is one of the functions servedby the more complex working memory system, the question ariseswhether visual binding calls upon a more general binding systemsuch as the proposed episodic buffer. The experiments that followinvestigate the processes of binding together the features of re-cently perceived visual stimuli in more detail in an attempt toprovide an empirical and theoretical bridge between recent re-search on visual short-term memory and the broader workingmemory system.

Episodic Buffer

The episodic buffer is assumed to be a multimodal temporarystore whose capacity is limited in terms of the number of episodesor chunks (Miller, 1956) that it can hold simultaneously (Badde-ley, 2000). For any type of chunk to be useful, its constituents mustbe sufficiently well bound as to allow the retrieval of one compo-nent to evoke the remainder. The nature of the binding processesthat underpin different forms of chunking is therefore crucial. Weassume that, in general, there are different forms of chunkingdepending, at least in part, on whether the binding involves one ormore subsystems of working memory or long-term memory.

The episodic buffer is separate from, but closely linked to, ahypothetical limited capacity central executive system. This sys-tem resembles the attentional focus within the theory proposed byCowan (in press). It is important to note that the model as illus-trated in Figure 1 assumes that access from the subsystems to theepisodic buffer occurs through the central executive, and thereforeany form of binding that requires encoding, maintenance, or bothwithin the buffer will be particularly dependent on general atten-tional resources provided by the executive. We use the termexecutive processes to refer to the operation of the central execu-tive, defining such processes operationally in terms of a range oftasks that consistently have been found to impair complex perfor-mance regardless of modality of presentation. In this sense, we areusing the concept of the executive at a macro level, while fully

Richard J. Allen, Alan D. Baddeley, and Graham J. Hitch, Departmentof Psychology, University of York.

This research was supported by Medical Research Council GrantG9423916. We thank Akira Miyake and Steve Luck for useful commentson earlier versions of this article and Paul Karlsen and Espen HaukHelskog for assistance with data collection.

Correspondence concerning this article should be addressed to RichardJ. Allen, Department of Psychology, University of York, Heslington, York,United Kingdom, YO10 5DD. Email: r.allen@psych.york.ac.uk

Journal of Experimental Psychology: General Copyright 2006 by the American Psychological Association2006, Vol. 135, No. 2, 298–313 0096-3445/06/$12.00 DOI: 10.1037/0096-3445.135.2.298

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accepting it is likely to reflect a range of separable though linkedprocesses (e.g., Miyake et al., 2000), that typically, though notexclusively, depend heavily on the frontal lobes (Baddeley, 1998).We do, however, distinguish between the central, overarchingexecutive system, and modality-specific aspects of attentional con-trol, such as the visual attention system proposed by Posner andcolleagues (e.g., Posner, Inhoff, Friedrich, & Cohen, 1987; Posner& Peterson, 1990), associated with the parietal rather than thefrontal lobes.

We accept a provisional distinction between a set of relativelypassive, or automatic binding processes, and a more controlled,attention-demanding process of active binding, with the assump-tion that executive processes will be involved in active, but notautomatic, binding. A number of theorists previously identified apotentially important role for attentional resources in at least someforms of information binding (e.g., Baddeley, 2000; Hummel &Holyoak, 1997; O’Reilly, Busby, & Soto, 2003; Treisman &Gelade, 1980). As a working hypothesis, therefore, we assume theepisodic buffer forms a basis for the temporary storage, andretrieval through conscious awareness, of feature bindings in vi-sual short-term memory. These bindings also may be initiallycreated through active, attention-demanding processes. Alterna-tively, the visuospatial subsystem of working memory might sup-port initial feature integration in an automatic manner, withoutrequiring executive processes. The experiments that follow use thedual-task methods that have proved effective in developing thebroad concept of a multicomponent working memory system(Baddeley, 1986; in press), to explore the nature of binding withinvisual short-term memory. The intention is to identify the condi-tions under which an active, resource-demanding binding process

becomes critical for the creation and maintenance of associationsin working memory.

Visual Feature Binding

Visual information rarely consists of single-feature objects, pre-sented without accompanying context. Without encoding and hold-ing in memory the connections between constituent elements ofobjects, or the connections between objects and the context inwhich they were encountered, the visual environment would bedifficult to comprehend. Considerable work has already been per-formed on the perceptual aspect of the binding problem, investi-gating how distributed neural codes representing the visual sceneare integrated to form object percepts (see Treisman, 1996, 1999;Malsburg, 1995).

Luck and Vogel (1997; see also Vogel, Woodman, & Luck,2001) addressed short-term memory for visual features and theirconjunctions in a series of change detection experiments. A visualarray was presented for 100 ms, with accurate retention requiredover a subsequent 900-ms delay. The original array was thenrepresented, either identically or with a single altered feature (suchas a color or orientation). Same–different judgment accuracy be-gan to decline when set size exceeded four, prompting Vogel et al.to place a limited capacity on visual memory of three or four items,in line with other findings (e.g., Cowan, 2001; Irwin & Andrews,1996; Sperling, 1960). This capacity limit was unaffected byvariation in exposure and delay durations, or the addition of asimple verbal memory load. This lack of a verbal load effect hassince been replicated by Morey and Cowan (2004), suggesting thatverbal coding is not important in such experiments.

Luck and Vogel (1997), and later Vogel et al. (2001), observedthat visual working memory capacity appeared to depend on thenumber of objects rather than the number of different features in adisplay. When four objects were presented, each varying in color,size, orientation, and gap (thus involving 16 features in total),performance was as accurate as on four features in isolation. Vogelet al. suggested that features are bound into integrated objects,possibly through a mechanism such as synchronous neural firing,and subsequently encoded into visual working memory.

Wheeler and Treisman (2002) noted that the Luck and Vogel(1997) experiments did not directly test memory for feature com-binations, but instead examined feature memory with the assump-tion that this would reflect binding processes. Thus, performanceon the conjunction conditions could be accomplished withoutnecessarily testing memory for the bindings themselves. Wheelerand Treisman proposed a model describing separable stores foreach feature dimension (e.g., color, location), with the object-based capacity limits previously reported reinterpreted as arisingfrom competition between the features of different objects thatwere held in the same dimensional store (e.g., color).

Using the change detection paradigm, Wheeler and Treismancompared feature memory with a more direct measure of conjunc-tion memory. On “different” trials in the binding condition, thesame features were represented but with incorrect feature pairingsincluded in the array. For example, an array containing a red circleand a blue triangle might be followed with a test array containinga blue circle and a red triangle. Wheeler and Treisman also testedmemory for arrays using a single probe at test, with a present-absent decision required regarding the probe feature or combina-

Figure 1. The multi-component working memory model. LTM � long-term memory. Reprinted from Trends in Cognitive Sciences, 4, A. D.Baddeley, “The Episodic Buffer: A New Component of Working Mem-ory?” p. 421, copyright 2000, with permission from Elsevier.

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tion of features (with a binding lure probe being an incorrectpairing of two presented features). In both the whole array andsingle probe tests of binding, memory for the features alone wouldnot be sufficient to support performance.

When the whole array was presented at test, accuracy in thebinding condition (in which features were repaired) was reducedrelative to a condition in which an individual feature within thearray was changed. In contrast, equivalent performance in featureand binding conditions was observed with single test probes.Wheeler and Treisman argued that these differences betweenwhole array and single probe tests reflect the possibility that boundobjects disintegrate into their constituent parts if sufficient atten-tional resources are not available. Processing a second complexarray at test requires the reallocation of attentional resources thatwere maintaining the original bindings, thus causing these connec-tions to fall apart. In contrast, single probe tests would not requirethe same degree of attentional resources, and so the originalbindings remain intact.

In line with the possibility that holding visual conjunctioninformation in working memory is effortful and requires additionalattentional resources, Stefurak and Boynton (1986) found thatmemory for previously presented colors or names remained intactafter an attention-demanding filler task, while memory for thecolor–name conjunctions was severely disrupted. Postma and DeHaan (1996) argued that remembering locations and location–object associations involves separable processes. They observedthat backward counting (in ones) had a much larger effect onobject–location associations than on locations themselves, an ef-fect that was also larger than that of a simple articulatory suppres-sion task.

Prabhakaran, Narayanan, Zhao, and Gabrieli (2000) found evi-dence for the importance of frontal activation in feature binding,potentially implying the involvement of the central executive.They used fMRI to examine memory for letters, spatial locations,and both letters and locations. Maintenance of integrated informa-tion resulted in greater activity in the right frontal cortex, includingBA 10, an area also identified by Mitchell, Johnson, Raye, andD’Esposito (2000) as being involved in object–location binding. Incontrast, maintenance of verbal and spatial information that wasnot integrated resulted in greater activity in multiple posteriorbrain areas. In line with Baddeley (2000), Prabhakaran et al.suggested that the frontal cortex might be responsible for a buffercapable of temporarily holding integrated information.

These findings would indicate that the creation, retention, orboth of visual information in the form of integrated representationsis often active and effortful, requiring additional resources notinvolved in memory for simple features. While Wheeler and Treis-man (2002) do not attribute particular attentional demands to theprocesses of encoding into memory, they do argue that the bindingdecrement they observed in whole-test displays reflects an addi-tional requirement for attention in binding maintenance. However,an alternative possibility suggested by Cowan (in press) is that thesimultaneous processing of numerous (and possibly fragile) mul-tifeature items may overload the system and lead to an increase inmistaken recombinations of features (illusory conjunctions), asobjects in memory are unpacked for comparison with each of themultiple test items. A neural firing account of binding (e.g., Vogelet al., 2001) would also predict an increase in illusory conjunctionswith whole display tests, through neurons representing features of

separate objects accidentally firing in synchrony. According tothese accounts, the creation and retention of feature conjunctionswould be no more demanding of general attention than memory forthe features themselves, with specific problems only emerging atretrieval, through access to numerous multifeature representations.

In addition, concurrent task and fMRI studies (e.g., Stefurak &Boynton, 1986; Prabhakaran et al., 2000) have typically usedlonger stimulus presentation and retention durations. The degree towhich binding is achieved automatically or requires additionalcentral resources may be the result of a combination of factors,including object complexity and configuration, exposure duration,and retention interval. Although it is apparent that the workingmemory system is capable of temporarily holding multifeatureobjects in an integrated form (e.g., Vogel et al., 2001; Wheeler &Treisman, 2002), it is not clear whether simple combinations ofvisual features are bound and temporarily maintained over shortexposures and retention intervals through effortful, active process-ing, or if this can be achieved in a relatively automatic manner, atno extra cost to executive resources. The present experimentsinvestigate the processes underlying binding in working memoryusing the short exposure single probe paradigm developed byWheeler and Treisman (2002), in an examination of the accuracy,fragility, and dependence on attentional resources of memory forfeature combinations, relative to memory for the featuresthemselves.

Experiment 1

It is difficult to draw firm conclusions from the Wheeler andTreisman (2002) findings regarding the encoding and retention offeature combinations as the same presentation format was used inall conditions, with items always varying in both shape and color.It was only at test probe presentation that differences in thephysical properties of the conditions emerged and different ele-ments of the stimuli were emphasized. This means that the sameinformation was potentially being encoded and retained in featureand binding conditions, increasing the likelihood of shape–colorbinding regardless of the task demands, particularly if this processoccurs automatically.

The aim of the present experiment was therefore to compare theWheeler and Treisman (2002) measure of binding with morefocused measures of shape and color memory, in which singlefeature arrays vary only in the to-be-tested dimension. Colors wereheld constant when testing memory for shape, and shapes wereheld constant when testing memory for color. In contrast, itemsvarying in both color and shape were presented in the shape–colorcombination condition, with memory for the specific bindingsbeing vital for accurate recognition memory. Finally, the “eithershape or color” condition used by Wheeler and Treisman (2002)was also included, in order to replicate their overall design. In thiscondition participants were presented with different coloredshapes, and did not know which feature dimension was relevantuntil presentation of the test probe.

MethodParticipants

Eight undergraduates (2 men and 6 women) from the University of Yorktook part in return for monetary payment or course credit. All participantsin each of the reported experiments had normal color vision as assessed bythe Ishihara (1966) color-blindness test.

300 ALLEN, BADDELEY, AND HITCH

Materials

Testing was controlled on an iMac with a 15-in. screen, using a Hyper-Card program. All stimuli and probe items were simple shapes subtendinga visual angle of approximately 0.75°, presented on a white background. Apool of eight shapes was used in the “shape-only,” “either,” and “combi-nation” conditions, along with a neutral shape (square) featuring in “color-only” and “either (color)” trials. Eight colors (black, red, blue, green,yellow, gray, turquoise, and violet) were selected for use on the basis ofease of discriminability. Unfilled shapes with three-point black outlineswere used as neutral-colored stimuli in “shape-only” and “either (shape)”trials. Shapes and colors were never repeated within a single trial.

Design and Procedure

Each participant completed four conditions (color-only, shape-only,either shape or color, shape–color combination), performed within separateblocks of 16 practice trials plus 80 test trials, counterbalanced acrossparticipants. A rest was provided after 40 test trials in each block. Trialswere evenly divided in each condition between randomly distributed sameand different probes.

Each trial began with a warning cross, presented for 500 ms in the screencenter. Following a blank screen (250 ms), the initial display was presentedfor 250 ms. This consisted of four items just above center screen, presentedin a row subtending an angle of 7.48° in total, with 1.50° between eachitem. The items presented in each trial were selected at random, with theconstraint that no feature was repeated within a single trial. A blank screendelay of 900 ms followed, before the test probe was presented just belowcenter screen (a neutral, previously unoccupied location). The probe re-mained until participants made their response, via a keypress (using thesame keys for “yes” and “no” in all conditions). The warning crosssignifying the next trial immediately followed. Examples of the presenta-tion and test probe stimuli for each condition are illustrated in Figure 2.

Shape-only. The stimulus display consisted of four shapes (drawn fromthe pool of eight unfilled shapes), and the test probe was a single shape.Participants were required to judge whether this test shape had been presentin the original display.

Color-only. The stimuli were four colored squares (drawn from thepool of eight colors), and the test probe was a single colored square, withparticipants judging whether this color was present initially.

Either shape or color. Participants were told that either shape or colormemory would be tested, but that they would not know which until theprobe appeared. Four colored shapes (each a different shape and color)were presented, followed by either an unfilled shape or a colored square,with participants responding accordingly. The trials were split evenlybetween shape and color tests and were randomly intermixed.

Combination. Four colored shapes were displayed in each trial, as inthe “either” feature condition. At test, a single colored shape was presented.On target trials, this involved an original color–shape combination, se-lected at random from the original array. On lure trials, color and shapewere combined from two different randomly selected items from theoriginal array. Participants were instructed to judge whether the test com-bination of shape and color was present initially.

Accuracy was emphasized rather than speed. Incorrect responses pro-duced a beep feedback from the computer, and participants were informedof their percentage score at the end of each practice and test block.

Results

Corrected recognition scores for each condition were obtainedby subtracting the number of false alarms from the number of hits.1

The data are displayed in Figure 3, with the either conditiondivided into shape and color trials. A repeated measures ANOVArevealed a significant effect of condition, F(4, 28) � 10.32, MSE� 1.63�02, p � .001. Further examination indicated that color-only performance was better than shape-only, t(7) � 5.73, p � .01,and combination, t(7) � 6.09, p � .001, while the latter twoconditions do not significantly differ, t(7) � .57, ns. Finally,memory for shapes was significantly better when tested in the

1 Detection theory analysis (both d� and A�) was also performed on allreported data. However, response bias significantly varied between condi-tions in some of the experiments, thus rendering A� inaccurate as a measureof sensitivity (McNicol, 1972; Pastore, Crawley, Berens, & Skelly, 2003;Snodgrass & Corwin, 1988). Analysis using d� revealed an identical patternof results to that using corrected recognition in all experiments, so for thesake of clarity only the latter is reported.

Figure 2. Examples of presentation and test probe stimuli from each condition.

301FEATURE BINDING IN WORKING MEMORY

single feature condition than in the either condition, t(7) � 3.64,p � .01, while performance in the color-only and either-colorconditions did not significantly differ, t(7) � 1.66, p � .141, ns.

Hits and False Alarms

Proportional hits and false alarms for each condition are dis-played in Table 1. A repeated measures ANOVA on the hit ratesrevealed that the effect of condition was not significant, F(4, 28) �2.32, MSE � 1.52�02, p � .082. In contrast, condition did have asignificant effect on false alarms, F(4, 28) � 16.23, MSE �9.27�03, p � .001. Fewer false alarms were produced in the colorcondition than in the shape, t(7) � 4.67, p � .01, or combination,t(7) � 4.47, p � .01, conditions, while the latter two conditions didnot significantly differ, t(7) � 1.34, p � .224.

Discussion

The central findings from Wheeler and Treisman (2002, Exper-iment 4B) were replicated, using a method of presentation in whichonly the to-be-tested information was initially displayed. Memorywas more accurate for colors than for shapes or shape-colorcombinations, whereas the latter two conditions did not signifi-cantly differ. As the combination condition involves the processingof both types of feature, accuracy will necessarily have a greaterdependence on the more difficult feature dimension. This mayreflect a binding process that occurs automatically, with the inte-gration of features requiring nothing more than the processing ofthe features themselves. Alternatively, binding may require addi-tional resources to enable this level of accuracy.

Color was the more easily processed and salient feature, al-though this was only significant on lure trials. It is possible thatshape is more complex, with a greater susceptibility to partialinformation loss. Finally, feature memory was less accurate in theeither condition than in the single feature conditions, although thiswas only significant for shape trials. This may imply some sharedprocessing capacity between different feature dimensions, al-though the shift of the nontested feature to a neutral value at testin this condition always produced a change in probe appearance(even during target trials), thus possibly limiting any firm conclu-sions from this condition.

Nontested feature dimensions were held constant in the feature-only conditions, in an attempt to focus these conditions solely ontests of color (or shape) and therefore limit the effects of anyshape–color binding. This procedure leads to variations in stimulibetween conditions, thus introducing the possibility that the patternof results was due to these surface variations rather than underly-ing memory processes. However, the present results replicatedWheeler and Treisman (2002, Experiment 4B) where the sameshape–color stimuli were used in every condition, implying thatsuperficial variations in stimuli between conditions did not influ-ence performance. Thus our adapted methodology for ensuring amore careful control of the focus in each of the conditions isappropriate.

Experiment 2

Is the binding demonstrated in Experiment 1 created and main-tained in working memory automatically, or are executive-based

Figure 3. Corrected recognition (and standard error) for each stimulus condition.

Table 1Proportional Hits and False Alarms (and Standard Deviations) for Each Stimulus Condition inExperiment 1

Color Shape Either-Color Either-Shape Combination

Hits .82 (.10) .74 (.12) .63 (.23) .72 (.17) .71 (.08)False Alarms .15 (.06) .34 (.10) .11 (.08) .45 (.15) .27 (.10)

302 ALLEN, BADDELEY, AND HITCH

attentional resources required? Evidence of concurrent task effectsand frontal lobe involvement in feature binding (e.g., Postma & DeHaan, 1996; Prabhakaran et al., 2000; Stefurak & Boynton, 1986)suggests that the central executive may have an important role atleast under certain conditions. However, variation in presentationduration and applicability of long-term knowledge potentially al-lowed the creation of more complex and elaborated integratedobject representations (Craik & Lockhart, 1972). To address therole of executive process in binding under the short exposureconditions of Experiment 1, we examined the effect of anattention-demanding concurrent task on performance.

It is important that the concurrent task used should load suffi-ciently on the central executive to disrupt attention, while placingminimal demands on visuospatial processing itself. Postma and DeHaan (1996) found significant effects of backward counting inones from 100 on the reconstruction of item-location combina-tions, and suggested that this involved central executive disruption.Backward counting in ones was therefore selected for use in thepresent study.

Although visual memory and backward counting involve differ-ent modalities and forms of information, a secondary task effectwas predicted in all conditions, including the single feature tests(Dell’Acqua & Jolicoeur, 2000; Morey & Cowan, 2004). How-ever, if the encoding of binding information into working memory,and its subsequent maintenance (Wheeler & Treisman, 2002), isparticularly resource demanding, as in the original conception ofthe episodic buffer (Baddeley, 2000), the combination conditionshould show a greater interference effect than the single featureconditions.

Method

Participants

Sixteen undergraduate and postgraduate students (3 men and 13 women)from the University of York took part in the 45-min study for course creditor financial reward.

Materials

Materials from Experiment 1 were used.

Design and Procedure

Participants performed the four conditions from Experiment 1 twice,under control and concurrent task conditions. The 40-min testing sessioninvolved eight blocks of 16 practice trials and 40 trials, with the four testsets (shape, color, either, combination) performed in the same order foreach concurrent task condition. All other testing procedures were identicalto the previous experiment.

In the backward counting condition, participants were presented with athree-digit start number on screen, before the start of the practice session.They were instructed to count aloud in decrements of one from this numberas fast as possible, as they performed the visual memory task. Thisprocedure was repeated with a different start number for the test phase.Any hesitation in counting at any point was discouraged by the experi-menter, who recorded the final number reached by the end of each trialblock, and the number of errors made.

Results

Corrected recognition scores for each of the conditions aredisplayed in Figure 4. A 5 � 2 repeated measures ANOVArevealed significant effects of stimulus condition. F(4, 60) � 5.21,MSE � 3.09�02, p � .01 and concurrent task, F(1, 15) � 15.58,MSE � 6.27�02, p � .01. Significantly, the critical interactionbetween condition and concurrent task was not significant, F(4,60) � .97, MSE � 2.47�02, ns. It is important to make the keycomparison (e.g., whether the concurrent task effect was larger forfeature combinations than for single features) as sensitive as pos-sible. A 2 � 2 ANOVA is perhaps a more rigorous test of criticalinteractions than the omnibus analysis, as it utilizes a single degreeof freedom as the numerator, and does not consider noncriticalvariations in the size of the interaction (e.g., differences in con-current task effect size between color and shape). Therefore,analysis of the shape-combination contrast revealed a significant

Figure 4. Corrected recognition (and standard error) for each stimulus and concurrent task condition. BC1 �backward counting in ones.

303FEATURE BINDING IN WORKING MEMORY

effect of concurrent task, F(1, 15) � 11.86, MSE � 3.28�02, p �.01, but not of stimulus condition, F(1, 15) � 1.66, MSE �2.56�02, p � .217, ns, or the interaction, F(1, 15) � .76, MSE �2.28�02, ns. Effect size analysis (Howell, 1997) indicated some-what larger concurrent task effect sizes in the color (d � .79) andcombination conditions (.90) than in the shape condition (.47).2

Collapsing across concurrent task conditions, performance inthe color-only condition was significantly better than in shape-only, t(15) � 2.98, p � .05, or combination, t(15) � 4.21, p � .01.The latter two conditions did not significantly differ, t(15) � 1.29,p � .738, ns. The difference between shape-only and either-shapeconditions was marginally nonsignificant, t(15) � 2.13, p � .051,ns, while the corresponding comparison for color was not signif-icant, t(15) � 1.73, p � 333, ns.

Hits and False Alarms

The proportional rates of hits and false alarms recorded in eachcondition are displayed in Table 2. A repeated measures 5 � 2ANOVA on hit rates revealed a significant effect of concurrent task,F(1, 15) � 7.52, MSE � 3.20�02, p � .05, but not of stimuluscondition, F(4, 60) � 1.80, MSE � 2.65�02, p � .141, ns, or theinteraction, F(4, 60) � .23, MSE � 1.40�02, ns. A 5 � 2 ANOVA onfalse alarms produced significant effects of both concurrent task, F(1,15) � 6.15, MSE � 4.04�02, p � .05, and stimulus condition, F(4,60) � 5.72, MSE � 1.58�02, p � .01. The interaction was again notsignificant, F(4, 60) � .82, MSE � 1.91�02, ns.

Backward Counting

A backward counting score was calculated as the differencebetween the start number and the final number produced, control-ling for errors (e.g., if a participant jumped from 260 to 258, onewas removed from the total counting score). Therefore, if a par-ticipant counted down without error to 230 from a start number of284, the score would be 54 (i.e., the total number of counting stepscorrectly completed).

The mean backward counting scores were 60 (SD � 12) forshape-only trials, 57 (SD � 10) for color-only, 60 (SD � 12) foreither feature, and 58 (SD � 11) for combination trials. A repeatedmeasures ANOVA produced a significant effect of visual memorycondition, F(3, 45) � 3.31, MSE � 14.23, p � .05. Furtheranalysis revealed no differences between shape and combination,t(15) � 1.40, p � .181, ns, color and combination, t(15) � .77, ns,or either and combination, t(15) � 1.90, p � .077, ns, conditions.The only significant difference was between the color-only andeither feature conditions, t(15) � 2.880, p � .05. Thus, although

counting rates did vary, concurrent task performance was equiva-lent during single feature and combination conditions.

Discussion

In line with Experiment 1, memory for combinations of shapeand color was equivalent to memory for the shapes themselves,while accuracy was highest in the test of color memory. Theseexperiments therefore suggest that the binding of different featuresinto integrated objects and subsequent maintenance in visual work-ing memory are accomplished as accurately as the processing ofthe less salient feature dimension.

This experiment aimed to investigate the process of bindingthrough the application of backward counting as a concurrent task.While visual memory showed a substantial detrimental effect ofthis task in every condition, there was no significant task bycondition interaction. The demands placed on the central executiveby simultaneously counting backward did not have a greater effecton shape–color binding than on the individual feature memoryconditions, implying that, in these circumstances, memorial featurebinding is no more demanding of resources than memory for thefeatures themselves.

Experiment 3

It might be argued that counting backward in ones does notplace a sufficient load on the central executive to interact withbinding. In order to examine the robustness of the findings inExperiment 2, it is important to replicate them using a moredemanding concurrent task. In the next experiment, we used aconcurrent near-span length verbal memory task of the type em-ployed frequently in early dual-task studies of working memoryand found to impose a clear load on performance (e.g., Baddeley,Emslie, Kolodny, & Duncan, 1998; Baddeley & Hitch, 1974;Morey & Cowan, 2004). Participants performed recall of digitstrings concurrently with our visual memory task. As with back-ward counting, this task was verbal in nature, thus minimizinginterference effects attributable to peripheral processes, and max-imizing those attributable to a shared reliance on central process-ing resources. For example, Morey and Cowan (2004) demon-strated an effect of digit recall on visual array memory that was notattributable to simple verbal interference.

2 This relatively small effect size in the shape condition was causedentirely by one participant’s near-chance shape baseline performance. Withthis participant excluded, the concurrent task effect size increased to d �.94.

Table 2Proportional Hits and False Alarms (and Standard Deviations) for Each of the Stimulus andConcurrent Task Conditions in Experiment 2

Color Shape Either-Color Either-Shape Combination

Hits Baseline .75 (.11) .73 (.14) .67 (.22) .66 (.20) .67 (.18)Counting .65 (.16) .67 (.12) .58 (.21) .60 (.19) .59 (.14)

FA Baseline .15 (.14) .24 (.12) .12 (.11) .29 (.19) .20 (.10)Counting .21 (.16) .31 (.18) .25 (.24) .31 (.17) .31 (.18)

Note. FA � false alarms.

304 ALLEN, BADDELEY, AND HITCH

A second aim of Experiment 3 was to counter a potentialcriticism of the Wheeler and Treisman (2002) single-probe bindingtest. In the previous experiments, features were sampled withoutreplacement on each trial, with a given feature never repeated inany single array. At test, single probe lures in the combinationcondition involved an incorrect pairing of two features from theoriginal array. This allows the use of a potentially confoundingstrategy. Participants may have used their memory of just a singleobject to reject the lure, if this false test item contained one of thefeatures of the remembered object. For example, if a participantremembers only a red circle from the original array, he would beable to reject a blue-circle test lure on the basis that only one circlecould have been presented, and that was remembered to be red.Using this strategy, accurate responses could be made in thecombination condition at least some of the time on the basis ofpartial knowledge. As the strategy cannot be applied to featuretests, it could differentially support binding performance, possiblyincreasing it to the same level of accuracy as shape memory.

This criticism was addressed by informing participants that featurescould occur more than once on any trial, and by the inclusion of aminority of trials in each condition in which features were repeated inan array (e.g., two circles, or two reds). The retention in memory ofa single item (e.g., red circle) would consequently not allow theconfident rejection of a test lure (e.g., blue circle), as this lure com-bination may have appeared elsewhere in the array.

Finally, the either shape or color condition was not included inthis experiment. It was originally included to replicate the designused by Wheeler and Treisman (2002), and does not form thecentral focus of our studies.

MethodParticipants

Twenty-four undergraduate and postgraduate students (8 men, 16women) with normal color vision from the University of York took part, inreturn for course credit or financial payment.

Materials

Materials from Experiments 1 and 2 were used. In contrast to theprevious experiments, a minority of trials in each condition involved arraysin which a feature was repeated.

Design and Procedure

The three baseline and three concurrent task conditions were performedin counterbalanced blocks. Each condition was preceded by examples ofthe visual arrays the participant would encounter, followed by 10 practicetrials, five of which included one or more repeated features. In the shapeand color repetition trials, two of the four items were identical. In thecombination condition, repetition trials were divided between a repeatedshape, a repeated color, or the repetition of both. This relatively highrepetition rate during practice was used to underline the presence ofrepeated features in some of the arrays. Each subsequent test conditioninvolved 56 trials, 75% (42) of which contained standard presentations and25% (14) repetition trials. The latter was distributed randomly throughoutthe test block. Incorrect responses on the visual memory task resulted in afeedback beep during practice trials but not during test trials.

The testing procedure was the same as in the previous experiments, witha 500-ms warning cue, a 250-ms delay, 250-ms array exposures, and a 900-ms delay before the test probe was presented. However, in this study a 3-sdelay was inserted between each trial. In the digit recall condition, thisdelay was filled with the presentation of the digits 1 to 6 at two per second,in a different randomized order on each trial. The digit sequence wasimmediately followed by the warning cue on screen, signaling the start ofthe visual memory task. On this cue, participants attempted to verballyrecall the six digits in the same order and at the pace (two per second) atwhich they were originally presented. In contrast to Experiment 2, theconcurrent task was only performed during array presentation and thesubsequent retention interval. The timing of the visual memory and digitrecall tasks meant that keypress recognition responses were typically madeafter completion of the digit string.

Following completion of the six conditions, a standard digit span mea-sure was obtained to compare normal verbal memory with performance onthe concurrent task. Digit sequences of increasing length were verballypresented at two digits a second, for immediate repetition in the correctserial order. Participants attempted four sequences at each list length,continuing until they failed to correctly recall two out of four lists.

Results

Data from the repetition trials were excluded, as the number ofdifferent objects in feature and combination trials was not equiv-alent, and hence assumptions about guessing probabilities were notmet. Corrected recognition scores for the standard nonrepetitiontrials are displayed in Figure 5. A 3 � 2 repeated measures

Figure 5. Corrected recognition (and standard error) for each stimulus and concurrent task condition.

305FEATURE BINDING IN WORKING MEMORY

ANOVA produced significant effects of stimulus condition, F(2,46) � 57.60, MSE � 3.50�02, p � .001, and concurrent task, F(1,23) � 16.24, MSE � 2.25�02 p � .01. Notably, the task bycondition interaction was not significant, F(2, 46) � .213, MSE �1.25�02, ns. The 2 � 2 analysis comparing shape and combinationconditions also revealed significant effects of stimulus condition,F(1, 23) � 6.96, MSE � 2.69�02, p � .05, and concurrent task,F(1, 23) � 10.61, MSE � 3.15�02, p � .01, but not the interaction,F(1, 23) � .09, MSE � 1.37�02, ns. Effect size analysis revealeda somewhat larger concurrent task effect in the color condition(d � .82) than in shape (.56) or combination conditions (.56).

Further comparisons between the conditions, collapsed acrossconcurrent tasks, revealed that performance in the color conditionwas significantly better than in the shape test, t(23) � 8.74, p �.001, or in the combination test, t(23) � 10.06, p � .001, withcorrected recognition also higher in the shape condition than in thecombination condition, t(23) � 2.64, p � .05.

Hits and False Alarms

Hits and false alarm rates in each condition are displayed inTable 3. A repeated measures 3 � 2 ANOVA on hit rates revealedsignificant effects of stimulus condition, F(2, 46) � 27.55, MSE �1.50�02, p � .001, and concurrent task, F(1, 23) � 12.07, MSE �1.52�02, p � .01, but not the task by condition interaction, F(2,46) � 2.04, MSE � 9.22�03, p � .141, ns. A repeated measures 3� 2 ANOVA on false alarms also revealed significant effects ofstimulus condition, F(2, 46) � 28.02, MSE � 8.88�03, p � .001,and concurrent task, F(1, 23) � 13.43, MSE � 7.88�03, p � .01,but no task by condition interaction, F(2, 46) � 1.28, MSE �6.09�03, p � .287, ns.

Digit Recall

Participants correctly recalled 71.4% (SD � 19.1) of the listsduring the shape condition, 71.5% (SD � 17.9) during the colorcondition, and 71.7% (SD � 20.8) during the combination condi-tion. A repeated measures ANOVA revealed no differences be-tween conditions in digit recall, F(2, 46) � .01, MSE � 14.62, ns.Although the majority of the six-item lists was recalled correctly ineach condition, these scores contrast with a higher baseline meandigit span of 7.70 (SD � 1.0). Span was calculated as the mean ofthe four longest list lengths correctly recalled. Only 2 of the 24participants achieved a span score of less than 6. A comparison ofconcurrent digit recall (averaged across the different conditions)with performance on the six-digit stage of the span task revealed a

significant difference, t(23) � 6.72, p � .001. Thus, concurrentlyperforming the visual memory task did disrupt digit recall, to anequivalent extent in each condition.

Discussion

While digit recall did disrupt visual memory performance (andvice versa), this effect was equivalent across shape, color, andcombination conditions. This represents further evidence for theautomatic processing of integrated objects in visual working mem-ory, without the requirement for additional executive resources.Memory for combinations was less accurate than memory forshapes or colors. In this third experiment, the potential strategy ofusing the unique relationship between each shape and color toprovide a shortcut to a response in the combination condition wasprevented by the insertion of trials containing feature repetitions.Thus, when participants are required to remember all objects toguarantee accurate recognition, the combination test is more dif-ficult than any of the feature memory tests. This suggests thataccurate measures of memory for feature combinations must in-clude feature repetition trials in order to prevent the shortcutstrategy.

It is important to ensure that our manipulations of centralexecutive resources are powerful enough, if conclusions in re-sponse to the central issue of this study are to be based on nulleffects. While the verbal concurrent tasks used in Experiments 2and 3 did have a significant disruptive effect on performance, it ispossible that an even more demanding task is required to producean interaction with stimulus condition. For example, Engle, Tu-holski, Laughlin, and Conway (1999) suggested that the forwardserial recall of digits places relatively low demands on theexecutive.

Experiment 4

Backward counting in steps of three, performed only duringencoding and retention, was used as the concurrent task in Exper-iment 4. Participants were given a different start number beforeeach trial, subsequently counting backward until presentation ofthe test item. Han and Kim (2004) demonstrated that concurrentlyperforming backward counting in threes from a new start numberon each trial leads to large increases in visual search slopes. Thus,this task should place large demands on the central executiveduring encoding and maintenance of the visual stimuli.

Method

Participants

Twenty-four undergraduate students (10 men and 14 women) from theUniversity of York took part in the 50-min experiment for course credit orfinancial reward.

Materials

Materials from the previous experiments were used.

Design and Procedure

The shape, color, and shape–color combination conditions were eachperformed on their own and with a concurrent task, with order fully

Table 3Proportional Hits and False Alarms (and Standard Deviations)for Each of the Stimulus and Concurrent Task Conditions inExperiment 3

Color Shape Combination

Hits Baseline .90 (.09) .77 (.13) .68 (.12)Digit load .80 (.13) .67 (.16) .65 (.13)

FA Baseline .06 (.07) .17 (.11) .18 (.10)Digit load .10 (.11) .21 (.11) .26 (.15)

Note. FA � false alarms.

306 ALLEN, BADDELEY, AND HITCH

counterbalanced. Each condition was preceded by examples of the visualarrays the participant would encounter, followed by 10 practice trials, 5 ofwhich included one or more repeated features. Each subsequent test con-dition involved 56 trials, 42 (75%) of which contained standard presenta-tions and 14 (25%) repetition trials.

The testing procedure was as in the previous experiments, with theaddition of a 2-s delay between each trial. In the backward countingcondition, this delay was filled with the presentation of a three-digitnumber at the center of the screen, immediately followed by the warningcue on screen, thus signaling the start of the visual memory task. Partici-pants were instructed to read aloud the start number (e.g., “One hundredand seventy-six”) before proceeding to count backward in threes as fast aspossible through array presentation and the retention interval, until thepresentation of the test item. Keypress recognition responses were typicallymade following cessation of the counting task.

Baseline measures of counting performance were obtained before andafter the six visual memory conditions. Participants read aloud a three-digitstart number presented for 2 s, before counting backward in steps of threefor a further 2.5 s. Ten trials were performed in each of the pre- andpostexperimental sessions.

Results

Corrected recognition scores for the standard nonrepetition trialsare displayed in Figure 6. A 3 � 2 repeated measures ANOVAproduced significant effects of stimulus condition, F(2, 46) �60.01, MSE � 1.63�02, p � .001, and concurrent task, F(1, 23) �108.26, MSE � 2.63�02, p � .001. Of importance, the task bycondition interaction was not significant, F(2, 46) � .76, MSE �2.5502, ns. A 2 � 2 ANOVA comparing the shape and combina-tion conditions revealed significant effects of concurrent task, F(1,23) � 61.16, MSE � 2.61�02, p � .001, and stimulus condition,F(1, 23) � 4.68, MSE � 1.82�02, p � .05, but not the interaction,F(1, 23) � .01, MSE � 2.49�02, ns. Effect size analysis revealedlarge concurrent task effects in color (d � 1.43), shape (1.10), andcombination (1.19) conditions.

Further comparisons between the conditions, collapsed acrossconcurrent tasks, revealed that performance in the color conditionwas significantly better than in the shape test, t(23) � 9.92, p �.001, or in the combination test, t(23) � 9.46, p � .001. The shape

condition was also generally more accurate than the combinationcondition, t(23) � 2.16, p � .05.

Hits and False Alarms

Hits and false alarm rates in each condition are displayed inTable 4. A repeated measures ANOVA on hit rates revealedsignificant effects of stimulus condition, F(2, 46) � 17.15, MSE �1.45�02, p � .001, and concurrent task, F(1, 23) � 88.97, MSE �1.49�02, p � .001. The task by condition interaction was alsosignificant, F(2, 46) � 8.87, MSE � 8.22�03, p � .01.

A repeated measures 3 � 2 ANOVA on false alarms revealedsignificant effects of stimulus condition, F(2, 46) � 22.75, MSE �1.22�02, p � .001, and concurrent task, F(1, 23) � 19.29, MSE �1.49�02, p � .01. The task by condition interaction was notsignificant for false alarms, F(2, 46) � 1.93, MSE � 1.55�02, p �.156, ns.

Backward Counting

Counting speed was scored as the mean number of correctcounting steps achieved on each trial, following articulation of thestart number. Participants scored a mean of 1.43 (SD � .50)correct responses in the color condition, 1.42 (SD � .50) in theshape condition, and 1.42 (SD � .50) in the combination condi-tion. A repeated measures ANOVA revealed no significant differ-ences in counting speed between stimulus conditions, F(2, 46) �.01, MSE � 3.00�02, ns. A comparison of concurrent task countingspeed (averaged across the different conditions) with baselinecounting speed (M � 2.48, SD � .45) revealed concurrent taskcounting to be significantly slower, t(23) � 16.37, p � .001.

Discussion

A particularly demanding concurrent verbal task performedduring encoding and retention of visual information substantiallyaffected memory for both visual features and combinations ofthese features. However, in a replication of the previous experi-

Figure 6. Corrected recognition (and standard error) for each stimulus and concurrent task condition. BC3 �backward counting in threes.

307FEATURE BINDING IN WORKING MEMORY

ments, this disruption of general attentional resources did not havea larger effect on memory for binding information than on memoryfor individual features. Thus, the absence of a stimulus conditionby concurrent task interaction holds across variations in the degreeof central executive disruption. The findings from Experiment 4further strengthen the notion that shape and color can be boundinto integrated object representations and held in working memorywithout additional support from the central executive.

Experiment 5

The previous experiments have demonstrated that the disruptioncaused by a range of attention-demanding concurrent tasks duringmemory encoding and retention is no larger for the combinationcondition than for any other condition, arguing against a memory-based binding process that is more demanding of central atten-tional resources. Another explanation may therefore be requiredfor the greater whole-array decrement on memory for featurecombinations observed by Wheeler and Treisman (2002). Onepossibility is that this decrement reflects the general fragility offeature bindings, in that the presentation of a subsequent set offeature combinations impinges on and disrupts the original bindingrepresentations, causing them to fall apart. This greater fragilityand susceptibility to interference may be separable from the influ-ence of general attentional resources on the encoding and mainte-nance of feature bindings.

In order to investigate the potential fragility of integrated objectrepresentations, Experiment 5 compared simultaneous presenta-tion of the stimuli with sequential presentation of one item at atime. If representations of feature combinations in working mem-ory are more fragile than those for single features, accuracy in thebinding condition should be low with sequential presentation rel-ative to simultaneous presentation. In contrast, representations ofsingle feature items should be less fragile, showing reduced sus-ceptibility to retroactive interference and a smaller accuracy dec-rement in the sequential condition. At a more detailed level ofanalysis, memory for bindings should be particularly poor for earlyitems in sequential lists, as these items will have suffered mostfrom the presentation of subsequent feature combinations.

Method

Participants

Thirty-six undergraduate and postgraduate students from the Universityof Oslo and the University of York took part in the single 45-min sessionfor course credit or financial reward.

Materials

Materials from the previous experiments were again used.

Design and Procedure

The three simultaneous and three sequential conditions were performedin counterbalanced blocks. Each test block was preceded by 10 practicetrials, 5 of which included the repetition of one or more features. Theserepetition trials were constructed in the same manner as in the previousexperiment. Each subsequent test block contained 80 trials, 64 (80%) ofwhich were nonrepetition trials and 16 (20%) were repetition trials. Thelatter was distributed randomly throughout the test block.

The procedure from the previous experiments was used again in thesimultaneous conditions, with a 500-ms warning cue, a 250-ms delay, a250-ms array exposure, and a 900-ms delay before the test probe waspresented. In the sequential conditions, four items were presented individ-ually for 250 ms each following the 500-ms warning cue and 250-ms delay.Each of the sequential item presentations was separated by a blank screendelay of 250 ms. The 900-ms delay and the test probe followed presenta-tion of the final item. The test item was again always located centrallybelow the four locations.

Items were presented in the same four locations for both the simulta-neous and sequential conditions. For the 32 target trials in each of the testblocks, the probed item was drawn from each of the four locations an equalnumber of times. In addition, the target items in the sequential conditionswere drawn from each of the four serial positions an equal number of times.

As items were presented individually for 250 ms each in the sequentialconditions (as opposed to 250 ms for all four items in the simultaneousconditions), this may increase the opportunity for verbal recoding. In orderto ensure a visually based strategy, participants performed simple articu-latory suppression during the array presentation and delay phases in allconditions (sequential and simultaneous). They were instructed to repeatthe sequence “1–2–3–4” aloud at two digits a second, from the warning cuethrough to presentation of the test probe. Previous studies have indicatedvisual task performance to be insignificantly impaired by a simple verbalload (e.g., Morey & Cowan, 2004; Vogel et al., 2001), while the additionof articulatory suppression to prevent verbal coding is relatively commonin visual memory tasks (e.g., Wheeler & Treisman, 2002).

Results

Corrected recognition scores for the nonrepetition trials in eachcondition are displayed in Figure 7. A 3 � 2 repeated measuresANOVA revealed a significant effect of stimulus condition, F(2,70) � 111.29, MSE � 1.41�02, p � .001, but not of presentationformat, F(1, 35) � 3.10, MSE � 1.18�02, p � .087, ns. Accuracywas higher for color than shape in both the simultaneous, t(35) �5.72, p � .001, and sequential, t(35) � 3.88, p � .001, conditions.Color was also more accurate than the combination condition inthe simultaneous, t(35) � 9.32, p � .001, and sequential, t(35) �13.03, p � .001, conditions. Finally, performance was more ac-curate for shape than for feature combinations, for both the simul-taneous, t(35) � 4.20, p � .001, and sequential, t(35) � 8.19, p �.001, conditions.

The condition by presentation format interaction was signifi-cant, F(2, 70) � 6.85, MSE � 1.08�02, p � .01. Further compar-isons revealed no significant differences between the simultaneousand sequential conditions for color, t(35) � 1.16, p � .252, ns, orfor shape, t(35) � 1.72, p � .095, ns. There were presentationformat effect sizes of d � .19 for color, and .29 (in the oppositedirection) for shape. In contrast, accuracy in the sequential condi-tion was significantly lower than in the simultaneous presentation

Table 4Proportional Hits and False Alarms (and Standard Deviations)for Each of the Stimulus and Concurrent Task Conditions inExperiment 4

Color Shape Combination

Hits Baseline .87 (.09) .71 (.13) .69 (.11)Counting .60 (.20) .60 (.14) .49 (.18)

FA Baseline .08 (.06) .17 (.13) .21 (.16)Counting .14 (.15) .32 (.17) .27 (.13)

Note. FA � false alarms.

308 ALLEN, BADDELEY, AND HITCH

condition for combination memory, t(35) � 3.55, p � .01, with aneffect size of d � .59.

Hits and False Alarms

The proportion of hits and false alarms produced in each of theconditions is displayed in Table 5. A repeated measures ANOVAon the proportional hit rates revealed a significant effect of stim-ulus condition, F(2, 70) � 54.35, MSE � 1.06�02, p � .001, butnot of presentation format, F(1, 35) � .49, MSE � 1.15�02, ns, orthe interaction, F(2, 70) � 1.46, MSE � 7.47�03, p � .240, ns.The same analysis on the false alarm rates revealed a significanteffect of stimulus condition, F(2, 70) � 28.67, MSE � 9.41�03,p � .001, but not of presentation format, F(1, 35) � 3.11, MSE �4.36�02, p � .086, ns. The stimulus condition by presentationformat interaction was significant for false alarms, F(2, 70) �6.97, MSE � 4.06�03, p � .01, with further analysis revealingsignificant presentation format effects on the combination condi-tion, t(35) � 2.92, p � .01, but not on color, t(35) � 1.63, p �.113, ns, or shape, t(35) � 1.91, p � .064, ns. Note that thisnonsignificant trend in the shape condition was in the oppositedirection to the other conditions.

Serial Position Analysis on Target Trials

The proportion of hits made in response to target trials in thesequential presentation conditions was analyzed as a function ofthe serial position in which the probe item was initially presented.The results are displayed in Figure 8. A 3 � 4 ANOVA revealedsignificant effects of stimulus condition, F(2, 70) � 42.56, MSE �3.23�02, p � .001, serial position, F(3, 105) � 92.34, MSE �4.14�02, p � .001, and the interaction, F(6, 210) � 4.81, MSE �2.44�02, p � .001. Applying the Bonferroni multiple comparisonsadjustment, further analysis revealed significant differences be-tween shape and combination conditions at Position 1, t(35) �3.50, p � .006, Position 2, t(35) � 5.08, p � .006, and Position 3,t(35) � 3.76, p � .006, but not at the final position, t(35) � 2.50,p � .017, ns. Similarly, there were significant differences amongcolor and combination conditions at Position 1, t(35) � 4.46, p �.006, Position 2, t(35) � 7.28, p � .006, and Position 3, t(35) �5.40, p � .006, but not at the final position, t(35) � 1.19, p �.242, ns.

This inflated and near-ceiling level of performance on the finalitem may account for the absence of a stimulus condition bypresentation format interaction on hit rates generally. A further 3� 2 (stimulus condition by presentation format) ANOVA wascarried out on the hit rates, removing the final item data from thesequential conditions. This revealed significant effects of stimuluscondition, F(2, 70) � 54.82, MSE � 1.35�02, p � .001, presen-tation format, F(1, 35) � 27.94, MSE � 1.72�02, p � .001, andtheir interaction, F(2, 70) � 4.08, MSE � 8.73�02, p � .05.

Discussion

When items were presented sequentially, memory for combina-tions of features was significantly worse than with simultaneouspresentation of items, to a greater degree than shape or colormemory. Although the presentation effect overall is not dramati-cally larger in the combination condition, the stimulus condition by

Figure 7. Corrected recognition (and standard error) for each presentation format and stimulus condition.

Table 5Proportional Hits and False Alarms (and Standard Deviations)for Each of the Stimulus and Presentation Format Conditions inExperiment 5

Color Shape Combination

Hits Simultaneous .74 (.13) .68 (.14) .58 (.13)Sequential .72 (.12) .70 (.12) .54 (.12)

FA Simultaneous .10 (.06) .19 (.10) .20 (.12)Sequential .12 (.07) .17 (.09) .25 (.11)

Note. FA � false alarms.

309FEATURE BINDING IN WORKING MEMORY

presentation format interaction was significant. Furthermore, thisresult is a conservative estimate of the sequential presentationdecrement on binding memory, as hit rates were near ceiling onfinal serial position trials. The sequential presentation decrement inthe combination condition was much larger relative to the featureconditions at the first three serial positions. It may be that, whilefeatures can be integrated and maintained without additional cen-tral executive demands, the connections between them are rela-tively fragile and susceptible to interference from other items, andthus liable to disintegrate. When additional feature combinationsare presented for encoding and retention, they may impinge onthose bindings already held in visual working memory from pre-vious presentations.

General Discussion

Five experiments examined memory for simple visual features(shape and color) and their combinations. Experiment 1 replicatedand extended the findings of Wheeler and Treisman (2002), withperformance in a direct test of binding between shape and color noless accurate than memory for shapes in isolation (although mem-ory for color was superior). This pattern was replicated in Exper-iment 2, in which backward counting in ones was applied as aconcurrent task intended to disrupt attention. Although this taskdid have a substantial negative effect on performance generally,this was no greater in the feature combination condition than inconditions simply requiring memory for the features themselves.Experiment 3 replicated this finding using near-span digit recall asthe concurrent task. In addition, a subset of trials was included inwhich a feature was repeated, with the result that accuracy in thecombination conditions was generally depressed relative to theshape and color conditions, a pattern that was replicated in the finaltwo experiments. Using a more demanding concurrent task ofbackward counting in threes, Experiment 4 replicated the effect ofattentional disruption on visual memory but showed again that theeffect was no greater on memory for shape–color combinationsthan on memory for the individual features themselves. Finally, inExperiment 5 memory for feature combinations was shown to besignificantly less accurate when items were presented sequentially

rather than simultaneously, a manipulation that had a much largereffect on binding than on shape or color memory.

Statistical Power

Before discussing the implications of these findings, it is im-portant to establish whether the absence of a significantly largerconcurrent task effect on the feature combination condition wasmerely due to insufficient statistical power. As Experiments 2through 4 implement near-identical methodologies and address thesame question, it was considered appropriate to pool the data fromall 64 participants in a single analysis. A 2 � 2 � 3 ANOVA (withexperiment as a between-subjects variable) on the shape andcombination conditions revealed significant effects of stimuluscondition, F(1, 61) � 12.54, MSE � 2.46�02, p � .01, andconcurrent task, F(1, 61) � 72.91, MSE � 2.78�02, p � .001, butnot of the interaction, F(1, 61) � .09, MSE � 1.87�02, ns.Similarly, analyzing these effects in terms of a small-scale meta-analysis (Wolf, 1986) in which the individual studies are weightedin proportion to the number of participants, produced one-tailedz � 3.30 ( p � .01) for the stimulus condition effect, 6.48 ( p �.0001) for the concurrent task effect, and 0.72 (ns) for the inter-action. There was a similar absence of significant interaction whencomparing the color and combination conditions. Thus, even whenthe data from the three concurrent task experiments are pooled andanalyzed together, the concurrent task effect is no larger on mem-ory for feature combinations than on memory for the individualfeatures.

Retrospective power calculations were performed on the pooleddata to establish the approximate number of participants requiredfor the concurrent task effect to be significantly larger in thecombination condition, at an alpha level of .05, with statisticalpower of .80 (Cohen, 1988). Using the matched sample t technique(Howell, 2002), we compared the size of the concurrent task effecton the combination and shape conditions. The estimated interac-tion effect size was d � .05, requiring a sample size of 3,854 tobecome significant. A similar analysis of the color and combina-tion conditions found an effect size of d � .12 in the oppositedirection, and a required sample size of 516. Similar power cal-

Figure 8. Proportion correct on target trials in the sequential condition as a function of serial position.

310 ALLEN, BADDELEY, AND HITCH

culations on the individual experiments found similarly smallinteraction effect sizes indicating that unreasonably high numbersof participants would be required for the concurrent task effect tobecome significantly larger in the combination condition. As aresult of these analyses, we can argue that our null findings reflecta genuine absence of a greater disruptive concurrent task effect onmemory for feature combinations.

Relative Accuracy in the Binding Condition

Though the pattern of single feature and combination results thatemerged in the first two experiments replicated the single probefindings observed by Wheeler and Treisman (2002), with colormemory superior to equivalent performance in the shape andshape–color binding conditions, the inclusion of a subset of trialscontaining feature repetition in the final three experiments resultedin combination memory being significantly worse than memoryfor shapes. This demonstrates a potential flaw in the originalbinding test that perhaps enabled participants to achieve an artifi-cially inflated score in that condition. It appears that combinationmemory is less accurate than memory for the individual featureswhen a recognition judgment based on all originally presenteditems is required, and that it is important to include repeated-feature trials when using the Wheeler and Treisman (2002) bindingtest.

While our concurrent task findings suggest that the decrement isunlikely to reflect a greater dependence on general attentionalresources, an alternative possibility is that accurate performance inthe combination condition is particularly reliant on a specializedvisuospatial attention system (e.g., Posner, 1988; Posner & Peter-son, 1990). If this system were to be overstretched by the demandsplaced by the combination condition, performance would deterio-rate to a greater extent than in the feature conditions. However,another possibility is that deciding whether a particular combina-tion of shape and color was initially presented may be a moredifficult judgment than the corresponding decision about a singlefeature. Cowan (in press) has suggested that bound items must beunpacked before recognition judgments can be made, a potentiallyerror-prone process that would not be required for single featureitem judgments.

The Encoding of Feature and Binding Information inVisual Working Memory

Three experiments demonstrated that performing a demandingconcurrent task during presentation of visual arrays does not havea larger disruptive effect on memory for feature combinations thanindividual features. Thus, encoding feature configurations intovisual working memory as integrated object representations is notparticularly demanding of executive resources, at least for thetypes of stimuli studied here. However, each of the concurrenttasks did have a disruptive effect on performance in general,indicating that central attentional resources are required for theencoding of visual features (Dell’Acqua & Jolicouer, 2000; Morey& Cowan, 2004). However, it appears that if sufficient resourcesare available for this process, object integration can occur auto-matically, at no extra cost to executive processes.

Vogel et al. (2001) suggested that the mechanism for featurebinding might involve synchronous firing of neurons correspond-

ing to the features of an object, thus forming a cell assembly(Hebb, 1949) representing each object. This account of binding hasbeen applied to visual object identification (e.g., Gray, Konig,Engle, & Singer, 1989) and to storage in visual working memory(e.g., Raffone & Wolters, 2001; Vogel et al., 2001). It might beregarded as a form of dynamic binding (Hummel & Holyoak,1997) that occurs automatically with the processing of individualfeatures. Provided sufficient attentional resources were available toaccurately process the features, this automatic binding mechanismwould not be dependent on any additional resources

The Retention of Feature and Binding Information inVisual Working Memory

The serial position data from Experiment 5 indicate that mem-ory for features and feature combinations is severely affected bythe presentation of further items. This general effect of presenta-tion format is unlikely to be caused by temporal decay, as Luckand Vogel (1997) and Vogel et al. (2001) observed no effect ofvariations in retention interval, suggesting time-based forgetting isnot a major cause of information loss.

The processing of later items had a greater effect on memory forfeature bindings than for individual features, indicating that thebindings are more fragile than the features themselves. Given thatexecutive resources are required for processing later stimuli in asequence, earlier representations in memory will be neglected, andone might argue that this withdrawal of attention has a greaterimpact on memory for feature combinations. However, the con-current task findings suggest that executive resources are notparticularly required for the maintenance of binding informationover short delays, rendering this account implausible. Alterna-tively, it could be argued that the maintenance of feature bindingsis particularly reliant on a form of visuospatial attention (e.g.,Posner & Peterson, 1990) that is disrupted by processing furtheritems. Although our experiments did not address the role of visuo-spatial attention, we note recent findings by Johnson, Holling-worth, and Luck (2004) that a demanding visuospatial filler taskdid not have a relatively greater effect on memory for featurecombinations. Thus it seems unlikely that feature bindings areespecially dependent upon visuospatial attention for successfulretention.

We suggest instead that automatically bound information isnaturally fragile and more liable to fall apart when further combi-nations require encoding and storage in visual working memory.That is, the processing of further stimuli disrupts and overwritesmemory for feature combinations more than memory for individ-ual features. In other words, bound object representations aredisrupted directly, by the processing of further feature combina-tions, rather than indirectly, through the withdrawal of attentionalsupport.

Automatic and Active Binding

In general, it seems likely that different processes contribute tobinding under different conditions, consistent with a distinctionbetween automatic and active binding processes. Similarly, Mitch-ell, Johnson, Raye, Mather, and D’Esposito (2000) drew a distinc-tion between resource-demanding mechanisms of memorial bind-ing and the perceptual binding involved in the shorter exposures

311FEATURE BINDING IN WORKING MEMORY

and retention intervals used by Luck and Vogel (1997). Longerstimulus exposures or alternative forms of required associationcould allow a more effective application of general attentionalresources to the processing of features and their bindings, perhapsthrough elaboration, redundancy, and the use of reflective strate-gies such as reactivation (e.g., Johnson & Chalfonte, 1994) andrecursive rehearsal (e.g., Johnson, 1992). In addition, factors suchas stimulus complexity, applicability of long-term knowledge, andthe type of associations that require binding may all influence theform of binding applied in a task.

Implications for the Concept of an Episodic Buffer

As explained in the introduction, the episodic buffer forms partof a broader explanatory framework, rather than constituting adetailed model. As such the concept may be evaluated at twolevels. First, it does appear capable of stimulating tractable ques-tions that generate clear answers. Thus, we found that while visualshort-term memory depends upon general attentional capacity, nogreater attention is required to bind features than to encode themseparately. Such a result does not of course uniquely depend on theconcept of an episodic buffer that serves the function of binding.We would suggest, however, that our approach, which led us to usethe well tried techniques of dual-task interference, complementsmethods that have been utilized successfully for the study of visualattention. As such it establishes a potentially fruitful empirical linkbetween work on visual short-term memory and attention and thebroader construct of working memory.

Second, we can consider whether our results have implicationsfor the concept of an episodic buffer. Given that we were unableto demonstrate that encoding and maintaining visual feature bind-ings is especially dependent on executive processes, one couldargue that such a buffer is unnecessary. However, we suggest thatthis would make the mistake of adopting too narrow a perspective.We have already noted our assumption that there are many differ-ent types of binding, depending on what stores are involved, andthat visual feature binding is just one particular type. Indeed, theinitial motivation for assuming an episodic buffer included theneed to explain binding between visual and verbal subsystems ofworking memory and between long-term language knowledge andworking memory (together with other phenomena not directly tiedto the issue of binding; see Baddeley, 2000). It would therefore bepremature to generalize from the present results to binding ingeneral. For these reasons we prefer to consider whether ourfindings imply any revision to the original concept of the episodicbuffer.

The initial account proposed that the flow of information intothe episodic buffer came either directly from LTM or via thecentral executive. Direct links from the visuospatial and phono-logical subsystems were explicitly omitted on the grounds that theevidence at that point did not force such an assumption, leaving thequestion open for further empirical investigation. While we wouldnot regard any single series of experiments as sufficient to radi-cally change the model, we feel that our current results tip thebalance away from the assumption that the executive is all-important for binding. Thus we would tentatively suggest thatbinding the features of simple perceptual objects takes place au-tomatically within the visuospatial subsystem of working memory.If so, it may be the case that object representations are not only

formed but also stored in the visuospatial subsystem. However,another possibility would be that the visuospatial subsystem feedsdirectly into the episodic buffer, and that this process allowsconscious access to recently perceived objects. Such an accountwould involve modifying the original concept, altering the way theepisodic buffer is accessed and its relationship to executive pro-cesses. We are currently exploring the role of general executivecapacities in more demanding visual binding tasks, and to crossmodal and semantic binding conditions. It seems clear that at somepoint executive processes will come into play (e.g., Jefferies et al.,2004) and that the precise degree and nature of these interactionswill have implications for understanding the important processesof chunk formation, regardless of whether, ultimately, we need toinvoke an episodic buffer.

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Received April 20, 2005Revision received December 7, 2005

Accepted December 9, 2005 �

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