Automatic guidance of attention fromworking memoryDavid Soto1,2, John Hodsoll2, Pia Rotshtein2 and Glyn W. Humphreys2

1 Imperial College London, Faculty of Medicine, Division of Neuroscience and Mental Health, Charing Cross Campus, St. Dunstan’s

Road, London, W6 8RP, UK2 Behavioural Brain Sciences Centre, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK

Review

Recent research has shown interactions between theprocess of keeping information ‘online’ in working mem-ory, and the processes that select relevant informationfor a response. In particular, our ability to select stimuliin the environment can be modulated by whether thestimuli match the current contents of working memory.Guidance of selection from working memory occursautomatically, even when it is detrimental to perform-ance. Neurophysiological data, from functional brainimaging, indicate that the interaction between workingmemory and attention is based on neuronal mechanismsdistinct from the processes mediating ‘bottom-up’ prim-ing effects from implicit memory. We discuss the import-ance of ‘top-down’ influences from working memory onthe ‘early’ deployment of attention and on the processesthat gate visual information into awareness.

IntroductionTo survive in a complex and dynamically changing world,our attention needs to be guided to select stimuli that arerelevant to our behavioural goals. It has been known forsome time that stimulus-driven factors can guide attentionin a relatively automatic way [1] such as when the suddenappearance of an unexpected object draws attention with-out any intention on the part of the observer. However, ifwe are not at the mercy of such changes, attention needs tobe directed in a ‘top-down’ manner. In many cases, the top-down directing of attention will be based on informationheld in working memory (WM) [2–4]. For example, oursearch for a favourite shirt in the wardrobe might beguided by an on-line memory of the features of the relevantobject (e.g. its texture and colour). This linkage betweenWM and attention might also sometimes have unwantedconsequences – for example, if it turns out that the infor-mation we are holding in WM is irrelevant or even mis-leading for search. Although perhaps disruptive ineveryday life, these unwanted consequences can be scien-tifically useful for studying the automaticity of anycoupling between WM and attention. In this article wereview emerging evidence on this automatic coupling,documenting both the behavioural characteristics of theinteraction and the underlying neural circuits. Our discus-sion is confined to visual selection, although it is an openquestion as to whether a similar coupling exists in othersensory modalities.

Corresponding author: Soto, D. (d.soto@imperial.ac.uk).

342 1364-6613/$ – see front matter � 2008 Elsev

Common resources for WM and visual selectionOne reason for arguing for a close coupling between WMand visual selection is that a common pool of resourcesseems to subserve both processes. For example, Lavie andcolleagues [5] have demonstrated that our ability to filterout irrelevant stimuli during selection depends on theprocessing load inWM. As theWM load increases, so fewerresources seem to be available to support efficient targetselection and distractor rejection. The net result of this isthat interference from distractors increases under con-ditions of high WM load [5]. This contrasts with conditionsin which the perceptual load (e.g. the complexity of a visualdisplay) is increased and distractor interference candecrease [6], indicating the selective linkage of WMresources with a stage of selecting visual information forresponse.

Effects of the contents of WM on the deployment ofattention in searchThe biased competition model of attention proposes thatstimuli compete for selection at multiple levels of repres-entation, with the ‘winner’ gaining control of both percep-tual and response systems [7] (Box 1). Within thisframework, WM acts to bias the competition for attentionto favour objects that fit the goals of the task. Behaviouralstudies are consistent with this, with visual selection beingstrongly modulated by information in WM set up for aparticular search target. For example, if we are lookingfor a red target, inadvertent capture of attention byunexpected salient stimuli can be enhanced when theirrelevant salient item shares the defining properties ofthe target [8–11].

The effects of WM seem to modulate relatively earlyvisual processing. In visual search, targets can bedetected efficiently if their feature values are categori-cally different from those of the distractors (e.g. thetarget is steep and the distractors are shallow in orien-tation) [12], or if the target is defined at the end of acontinuum of feature values (e.g. if there is a large targetand small and medium distractors). This evidencehas also been used to define the nature of the basicfeatures subserving visual processing (i.e. colour) [13].Interestingly, these effects are contingent on participantsholding the feature values in WM. Hodsoll and Hum-phreys [14] showed that the effects of categorical differ-ences in orientation search were dependent on holdinga memory ‘template’ of the target feature (Figure 1). This

ier Ltd. All rights reserved. doi:10.1016/j.tics.2008.05.007 Available online 5 August 2008

Box 1. The biased competition model of visual selection

According to the model conceived by Desimone and Duncan [7], the

neural representations of different objects in a visual scene compete

against each other in a mutually inhibitory fashion to gain access to

higher level processing and awareness. Visual attention is conceived

of as an emergent property that results from distributed activity in

different brain systems working on the same stimulus. The activation

of relevant object features in WM biases neural activity in specific

brain regions that encode those particular features so that the object

in question ‘wins’ to become the ‘focus’ of attention. Different

mechanisms can help to resolve competition and bias selection,

including purely ‘bottom-up’ stimulus-driven influences and also top-

down sources (i.e. active memory) that identify objects of particular

behavioural significance. Initial neurophysiological evidence for the

model came from single-cell studies in the monkey. Chelazzi et al. [50]

recorded the activity of neurons in the inferior temporal cortex (IT)

while a monkey performed a visual search task. At the beginning of

each trial, a memory cue was displayed at fixation. After a delay

period a search array with several objects appeared, one of them

matching the target. The task was to make an eye movement towards

the location of the target. The firing rate of IT neurons selective to a

particular feature increased when that feature appeared as the

memory cue and it was sustained during the delay before the onset

of the search array, indicating a neural basis for top-down expectan-

cies associated with the crucial target for selection. With the onset of

the search array, the pre-activated cells increased their firing rate to

stimuli in the array for which they were selective (relative to the cells

that were not pre-activated) and before the execution of the saccade to

the target object, the neural responses for irrelevant objects were

suppressed. IT neurons then responded as if the target object was

alone in the search array. According to the biased competition model

of visual selection, top-down control signals from the contents of WM

biased selection in favour of the object whose features were pre-

activated from WM.

Review Trends in Cognitive Sciences Vol.12 No.9

result also holds for search along the size dimension[15,16]. These findings are consonant with the idea of atarget template in WM ‘tuning’ feature values in earlyvision.

Figure 1. Example of search displays for categorically steep and non-categorically stee

the only steep item tilted 108 left with shallow 708 left and 508 right oriented distracto

distractors were shallow lines 808 right and also steep lines 408 left. (c) A word cue be

unknown condition, participants identified the target as the odd-item out in the display.

categorical orientation targets in the known condition. This advantage was eliminated

The automatic influence of WM on searchIn most studies of WM and attention, the WM contentoverlapswith the crucial target of attention so that amatchbetween a stimulus and the contents of WM facilitatesperformance. Under these conditions there is a strategicincentive for participants to use WM to guide visual selec-tion. However, as we have noted, WMmight also influenceselection automatically, even if a match between astimulus and the contents of WM is disruptive for the task.Pashler and Shiu [17] provided initial evidence thatmentalimages seem to be involuntarily detected when they re-appear within a rapid serial visual presentation.

The automatic influence of WM on visual selection insearch can be demonstrated when the contents of WM andthe target for subsequent selection are varied indepen-dently (Figure 2). Downing [18] had participants hold anobject in WM before the appearance of a two-object searchdisplay. The task was to discriminate a target that fell onone of the two objects in the search display, one of whichmatched the item in WM. Discrimination responses werefaster when targets fell on an object matching the stimulusinWM. Because theWM stimulus was not predictive of thelocation of the target, the data indicate that WM can guideattention automatically. Subsequent work by Soto andcolleagues [19,20] has demonstrated that stimuli held inWM can affect the direction of the first saccade in search,the fastest reaction times (RT) and the detection of salient‘pop-out’ targets that generate a flat search slope, evenwhen the WM stimulus never matches the search target.The WM effect does not seem to depend on the timeinterval betweenmemory and search displays, arisingwithasynchronies ranging from 200 ms to 4000 ms [21]. Thislast finding indicates that the effect is not limited to casesin which information is being consolidated in WM, butoccurs even when consolidation in WM has taken place.

p orientation target displays. (a) In the categorically steep condition the target was

rs. (b) For the non-categorical condition the target was a steep 208 right, and the

fore each trial indicated the identity of the target in the known condition. For the

There was only a reaction time (RT) advantage for the categorical targets over non-

for the unknown condition. Reprinted, with permission, from Ref. [14].

343

Figure 2. Example of the display sequences used in studies of inadvertent WM effects on selection. (a) The observers are presented with a cue (to hold in WM or to merely

attend) and, subsequently, the task is to search for a tilted line target. In the valid condition, the target line is surrounded by an object matching the cue. In the invalid

condition, the pre-cued object again re-appears but this time it contains a distracter. In the neutral condition, the memory item does not re-appear in the search display. (b) A

typical pattern of search performance (the data here are taken from a condition in which the search display contained just two items). Search is faster for targets displayed at

the location of the object matching the contents of WM relative to targets presented at the location of a non-matching object. Reproduced, with permission, from Ref. [45].

Copyright � (2007) National Academy of Sciences (www.nasonline.org). (c) Data showing that the WM effect on selection is present even when the cue always contains a

distracter when it re-appears in the search display (search with a display size of four items is illustrated (18). Note that effects are greatly reduced when the cue is merely

attended but not held in WM for a later report. Reproduced, with permission, from Experiments 1 and 3 in Ref. [26]. Copyright � (2007) American Psychological Association

(www.apa.org).

Review Trends in Cognitive Sciences Vol.12 No.9

Importantly, these inadvertent effects ofWM on search areabsent when observers are merely exposed to the cue butdo not have to commit it to memory for later report [18–21].Therefore, the effects cannot be because of an implicitmemory trace arising from the mere repetition of thestimulus, a conclusion supported by imaging studies (seelater). These results indicate that WM exerts an involun-tary influence on visual attention.

Visual or conceptual guidance?Interestingly, attentional guidance does not seem contin-gent on a visual representation being held in WM. Aseminal study by Potter [22] demonstrated that the recog-nition of a visual stimulus in a rapid visual stream pres-entation can be facilitated just as much by advance verbalcueing of its meaning as by visual cueing of its appearance.Additional work showed how spatial orienting and selec-tive processing of targets can be influenced by semanticrelationships between central and peripheral word stimuli[23–25]. The involuntary effects of verbal cueing from WM

344

have also been established. The effect of a WM distractoron search (Figure 2) is effective even when the WMstimulus is encoded verbally [26]. This effect can also bemoderated by the semantic relationship between an itemheld inWMand a distractor in a subsequent search display[27,28]. These studies demonstrate that selection can becaptured through automatic links between visual stimuliand different forms of representation in WM.

Improving visual awareness through the contents ofWMOne by-product of influencing where visual attention isallocated is thatWM canmodulate the entry of informationinto awareness. Parietal patients can suffer visual extinc-tion, in which they are impaired at detecting the presenceof a contralesional stimulus when an ipsilesional itemsappears simultaneously [29]. Such patients can showenhanced awareness for contralesional targets when theymatch the contents of WM [30]. Moreover, research on‘inattentional blindness’ (the failure to notice the presence

Figure 3. Illustration of the effects of cognitive load on the guidance of attention by WM. The paradigm used was identical to that depicted in Figure 2, except that, in this

study [37], an articulatory suppression task was required while the WM stimulus was presented (i.e. verbalising two numbers through the trial). Two aspects of the

results are noteworthy. First, when articulary suppression was required, attentional capture from the memory item was reduced at the shorter inter stimulus intervals (ISIs)

(Figure 2c versus Figure 3a,b). Second, the WM effect even at the longest ISI was abolished when the WM load was increased from one (a) to two (b) items. Reprinted, with

permission, from Ref. [41]. Copyright � (2008) Psychomonics Society (http://www.nasonline.org/).

Review Trends in Cognitive Sciences Vol.12 No.9

of unexpected stimuli) has shown that awareness of unex-pected information improves when an unexpectedstimulus is either visually or semantically related to thebehaviourally relevant stimulus in WM [31,32]. Whethersuch effects are best conceptualized in terms of a change inperceptual sensitivity or in the criterion adopted for aresponse is a question that remains open (cf. Refs.[33,34] versus Ref. [35]).

The boundaries of WM guidanceThe evidence reviewed so far demonstrates a strong influ-ence of the contents of WM on selection. However, therealso seem to be boundary conditions on this effect. Forexample, Downing and Dodds [36] failed to findWM effectswhen two items were held in WM. Others have found onlyweak [37] or no effects [38] when the target for searchchanges across trials. When the target for search variesacross trials, more resources might be devoted to thetemplate for this item than when the target is constantacross trials, highlighting this item over other informationheld in WM. Woodman et al. [39] examined general effectsof WM load on search with non-overlapping WM andsearch items. They found minimal effect of WM load whenthe search target was constant across trials, but that highWM load interferedwhen the search target varied. This fitswith the idea that, to maintain good search performancewith a varying target, WM resources have to be devoted tohighlighting the template of the target; search perform-ance suffers when these resources decrease in most cases.Oberauer [40], for example, has argued that although WMmight hold up to four or so items for direct access from theoutside environment, only one can be actively attended at atime. The consequence of actively attending to the searchtemplate might be to ‘compartmentalize’ WM, so thatinformation in WM that is irrelevant to the immediatetask might have less effect over the deployment of visualattention. Soto and Humphreys [41] also found that atten-tional guidance from irrelevant information in WMdecreased as the WM load increased (Figure 3), a manip-

ulation which might also have the effect of reducing theresources devoted to each irrelevant item in WM. Theevidence that memory guidance decreases when thecapacity of WM is stressed is interesting because it alsogoes against any ‘strategic’ account of the data whenattentional guidance does occur. According to this strategicaccount, the WM effects on visual selection are because ofparticipants attending strategically to any re-appearanceof the WM item in the search display to improve their WM.However, such a strategy should come into play particu-larly in cases in which WM is loaded and a higher decay ofthe WM representations is more likely. This is clearly notthe case. Instead the data indicate that WM has an auto-matic influence on selection, but one that remains depend-ent on the availability of resources. Strikingly, somestudies reported that with a heavy load in WM (i.e. articu-latory suppression plus several memory items) observersseem to ignore a WM matching item that re-appears as adistractor during search [36,42] because, in these studies,search was more efficient in the presence of a WM match-ing distracter compared to a neutral baseline. We arguethat high cognitive load might automatically lead to adegradation of the items held in WM, as a result ofincreased inter-item competition for limited resources.When representations are impoverished by competitionin WM (under high load conditions), any strategy to ignoreitems that match stimuli in WM might be helped becausedegraded representations might be more easily inhibited.The net result would be that search might be guided awayfrom stimuli that match theWM contents. Future researchneeds to explore the role of cognitive load on attentionalguidance from WM in more detail (Box 2).

There is evidence that the ability to compartmentalizeWM, to keep separate irrelevant information from anytemplate for search, is dependent on the prefrontal cortex(Box 3). Patients with prefrontal lesions are impairedparticularly when the item they select turns out to bethe memory item rather than the search target [43], indi-cating a failure in prioritizing information matching the

345

Box 2. Questions for future research

� To date, the effects of the contents of WM on attention have been

studied within the visual modality. Future research should

investigate whether similar WM effects happen in different

modalities. Does the maintenance of a sound in WM attract our

attention in auditory space? Additionally, are there cross-modal

links between WM and selection. Does the maintenance of an

auditory stimulus (’the sound of a sea gull’) attract attention to the

equivalent visual stimulus (an image of a gull) or even that of

a related item (i.e. a ship or a fish)? Moreover, are any cross-

modal effects based on a single neuronal mechanism (i.e.

neuronal enhancement to WM matching items), or are any effects

based on different brain systems that are specific to each sensory

modality?

� Although there is some evidence that the WM contents can

impinge early stages of perceptual processing [35], more studies

are needed to assess whether, when and how WM influences

perceptual processing (e.g. measuring contrast sensitivity for

targets, orientation sensitivity, spatial frequency discrimination-

thresholds, and temporal order judgments).

� Most research on the interaction between WM and attention has been

carried out with stimuli presented at a supra-threshold level. Future

research will assess whether matches between the contents of WM

and the stimulus array can operate at levels below the perceptual

threshold. Can the WM content enhance the detection of visual

signals which, by themselves, cannot be consciously identified?

� More research is needed to understand the effect of cognitive load

on the interaction between WM and attention. For example, it

remains to be explained why the effects of WM guidance are

reduced or even reversed as the level of cognitive load increases

[41,42]? Are there different effects of items in WM depending on the

time available to consolidate that information in memory? Also,

does altering the perceptual load in a display have the same effect

as varying the cognitive load (cf. Ref. [5])?

� Future studies also need to examine the ecological constraints of

the influence of WM on selection, for example, assessing effects in

more real life environments. Do effects of WM guidance emerge

even as the complexity of the environment increases? Can the

automatic capture of attention by WM lead to some of the action

errors that can occur in everyday situations?

Review Trends in Cognitive Sciences Vol.12 No.9

main task goal (search) over other representations in WM.Neurophysiological studies also show that cells in theprefrontal cortex show selective responses to a stimulusmatching an item in WM under delayed match-to-sampleconditions, but, in contrast to cells in more posteriorregions, prefrontal neurons are insensitive to distractorsappearing during the delay [44]. Thus, prefrontal cells areinvolved in prioritizing the relevant goals for tasks.

Neural substrates of attentional guidance by WMNeurons in prefrontal regions, along with cells in moreposterior neural regions tuned to particular features of

Box 3. A neuropsychological study on the role of the frontal cor

Soto, Humphreys and Heinke [43] tested neuropsychological

patients with lesions to the prefrontal cortex in the combined WM

and attention paradigm depicted in Figure 1 (see main text). The task

required participants to maintain an object in WM for a later report

and to make an eye movement to a tilted line target in the

subsequent search array. Overall, it took longer to make a saccade

to the tilted target when the WM item matched a distracter (on invalid

trials) rather than the tilted target (on valid trials). The prefrontal

patients were particularly impaired at rejecting distracters that

matched items held in WM. Figure I illustrates these findings. The

Figure I. Mean reaction times (RTs) for a fixation to be made to the target for each grou

at fixating the target on invalid than on valid trials, this validity effect was exacerbate

346

stimuli, can both show sustained activity when stimuli areheld inWM [44]. The sustained enhancement of cells tunedto particular features might provide the neural correlate ofexpectancies that influence subsequent selection (Box 1),leading to enhanced responding when the item in memoryis re-presented in a search display.

In the neurophysiological studies, the content of WMhas typically overlapped with the crucial target for thesubsequent selection task. It is possible, then, thatenhanced neuronal responses for the memorized itemreflect the behavioural relevance of the stimulus ratherthan the match between the contents of WM and any

tex

results indicate that, normally, prefrontal brain regions help to keep

separate (at least to some degree) information in WM and informa-

tion about the target for search. The prefrontal patients seemed to

have problems in doing this. As a consequence, the patients had

difficulties in rejecting WM items that were selected. This problem, in

partitioning WM into task relevant and irrelevant components, could

also explain why prefrontal patients might often have problems

under dual-task conditions because such conditions often require

that relevant and irrelevant representations must be kept separate in

WM.

p as a function of the validity of the WM item. Although the normals were slower

d for the prefrontal patients. Reprinted, with permission, from Ref. [43].

Figure 4. Illustration of the two networks involved in WM guidance of visual selection (see Figure 2 for an example procedure). (a) A first network was sensitive to the re-

appearance of the WM cue in the search display (activated regions: superior frontal gyrus, parahippocampal gyrus and lingual gyrus). Importantly, there were different

neural responses in the WM condition and in a condition in which the cue was ‘merely repeated’ in the search display. When the task required active maintenance of the cue

in WM, the re-appearance of the cue in the search display enhanced activity in the crucial brain areas. By contrast, when the initial cue had to be attended but not actively

memorized, the same regions showed decreased responses to the re-appearance of the cue in the search display (measured relative to the neutral condition, when the cue

did not re-appear in the search display). (b) A second network involved frontal (BA10, dorsolateral prefrontal cortex), thalamic and earlier visual regions (fusiform gyrus).

Regions in this network show a differential response exclusively linked to WM. Relative to the neutral conditions (cue did not re-appear in the search display), activity

increased when the WM and search goals coincided (valid trials) and decreased when the WM and search target were at different locations (invalid trials). Reproduced, with

permission, from Ref. [45]. Copyright � (2007) National Academy of Sciences (www.nasonline.org).

Review Trends in Cognitive Sciences Vol.12 No.9

search display. To assess automatic attentional guidancefromWM, a recent functional magnetic resonance imaginginvestigation [45] used independent WM and searchstimuli (Figure 1). When the cue held in WM re-appearedin the search display, there was enhanced activity in avariety of brain regions known to be sensitive to the priorhistory of events (the superior frontal gyrus, mid-temporaland occipital areas) [46]. By contrast, when the cue hadonly to be identified but not held in WM, repetition of thecue elicited a suppressed response in the same regions.This repetition suppression effect might reflect enhancedperceptual processing of repeated items. We argue that theenhanced response, under WM conditions, might signalincreased attentional interest to a stimulus that matchesthe content of WM. In addition, a second fronto-thalamicnetwork was uniquely sensitive to the match between thecontents of WM and the goal of the search task, showingincreased activity on valid and decreased activity on inva-lid trials (Figure 4). This network might provide a strongsignal to shift attention when the search goal and the WMstimulus coincide, whereas any attention shift might beinhibited when theWM stimulus and the search target arenon-coincident and compete for selection.

The existence of a fronto-thalamic network involved inselection from WM might complement the role of a fronto-parietal system involved in the control of spatial attentionand spatial workingmemory [47,48], andmight account forthe effects of WM on visual selection in patients showingextinction after parietal lesions [30]. For example, thefronto-thalamic system might provide top-down supportfor earlier visual processes, by-passing any detrimentaleffects of the parietal lesion in these patients.

Concluding remarksThe research reviewed in this article stresses the import-ance of top-down processes from WM in modulating thedeployment of attention and the gating of information intoawareness. Our proposals are consonant with a reversedhierarchy model of visual processing, in which perceptualselection and visual awareness are achieved by re-entrantactivation from higher-order areas (i.e. prefrontal cortex)to early visual areas [49]. Our evidence indicates that thisre-entrant activation occurs automatically but is depend-ent on the availability of processing resources in crucialbrain regions. Although the evidence indicates that WMguidance can sometimes be detrimental to task perform-

347

Review Trends in Cognitive Sciences Vol.12 No.9

ance under most circumstances, this will not always be thecase. Selection of visual information relevant to ourimmediate behavioural goals will benefit from matchesto the contents of WM. The inadvertent effects that arise,when WM mis-cues attention, might reflect the way thesystem is ‘wired’ to gain benefits in the more usual cases inwhich the target for attention is represented in WM.

AcknowledgementsThis work was supported by grants from the British Academy, theBBSRC, the MRC and the ESRC/MRC (UK). We thank Todd Horowitz,Geoff Woodman and one anonymous referee for comments on a prior draftof this paper.

References1 Theeuwes, J. et al. (2003) Attentional and oculomotor capture with

static singletons. Percept. Psychophys. 65, 735–7462 Duncan, J. and Humphreys, G.W. (1989) Visual search and stimulus

similarity. Psychol. Rev. 96, 433–4583 Wolfe, J.M. (1994) Guided search 2.0: a revised model of visual search.

Psychon. Bull. Rev. 1, 202–2384 Bundesen, C. (1990) A theory of visual attention. Psychol. Rev. 97, 523–

5475 Lavie, N. (2005) Distracted and confused?: selective attention under

load. Trends Cogn. Sci. 9, 75–826 Forster, S. and Lavie, N. (2007) High perceptual load makes everybody

equal: eliminating individual differences in distractibility with load.Psychol. Sci. 18, 377–382

7 Desimone, R. and Duncan, J. (1995) Neural mechanisms of selectivevisual attention. Annu. Rev. Neurosci. 18, 193–222

8 Folk, C.L. et al. (1992) Involuntary covert orienting is contingent onattentional control settings. J. Exp. Psychol. Hum. Percept. Perform.18, 1030–1044

9 Bacon, W.F. and Egeth, H.E. (1994) Overriding stimulus drivenattentional capture. Percept. Psychophys. 55, 485–498

10 Leber, A.B. and Egeth, H.E. (2006) It’s under control: top-down searchstrategies can override attentional capture. Psychon. Bull. Rev. 13,132–138

11 Lamy, D. et al. (2004) Effects of stimulus-driven salience within featuresearch mode. J. Exp. Psychol. Hum Percept. Perform. 30, 1019–1031

12 Wolfe, J.M. et al. (1992) The role of categorization in visual search fororientation. J. Exp. Psychol. Hum. Percept. Perform. 18, 34–49

13 Bauer, B. et al. (1996) Visual search for colour targets that are or arenot linearly separable from distractors. Vision Res. 36, 1439–1465

14 Hodsoll, J.P. and Humphreys, G.W. (2005) The effect of targetforeknowledge on visual search for categorically separableorientation targets. Vision Res. 45, 2346–2351

15 Hodsoll, J.P. et al. (2006) Dissociating the effects of similarity, salience,and top-down processes in search for linearly separable size targets.Percept. Psychophys. 68, 558–570

16 Hodsoll, J. and Humphreys, G.W. (2001) Driving attention with the topdown: the relative contribution of target templates to the linearseparability effect in the size dimension. Percept. Psychophys. 63,918–926

17 Pashler, H. and Shiu, L.P. (1999) Do images trigger search? A test ofPillsbury’s hypothesis. Psychon. Bull. Rev. 6, 445–448

18 Downing, P.E. (2000) Interactions between visual working memoryand selective attention. Psychol. Sci. 11, 467–473

19 Soto, D. et al. (2005) Early, involuntary top-down guidance of attentionfrom working memory. J. Exp. Psychol. Hum. Percept. Perform. 31,248–261

20 Soto, D. et al. (2006) Working memory can guide pop-out search. VisionRes. 46, 1010–1018

21 Olivers, C.N. et al. (2006) Feature-based memory-driven attentionalcapture: visual working memory content affects visual attention. J.Exp. Psychol. Hum. Percept. Perform. 32, 1243–1265

22 Potter, M.C. (1975) Meaning in visual search. Science 187, 965–96623 Dark, V.J. et al. (1996) Semantic and spatial components of selective

attention. J. Exp. Psychol. Hum. Percept. Perform. 22, 63–81

348

24 Stolz, J.A. (1996) Exogenous orienting does not reflect an encapsulatedset of processes. J. Exp. Psychol. Hum. Percept. Perform. 22, 187–201

25 Stolz, J.A. (1999) Word recognition and temporal order judgments:semantics turns back the clock. Can. J. Exp. Psychol. 53, 316–322

26 Soto, D. and Humphreys, G.W. (2007) Automatic guidance of visualattention from verbal working memory. J. Exp. Psychol. Hum. Percept.Perform. 33, 730–737

27 Huang, L. and Pashler, H. (2007) Working memory and the guidance ofvisual attention: consonance-driven orienting. Psychon. Bull. Rev. 14,148–153

28 Moores, E. et al. (2003) Associative knowledge controls deployment ofvisual selective attention. Nat. Neurosci. 6, 182–189

29 Karnath, H-O. (1988) Deficits of attention in acute and recovered visualhemi-neglect. Neuropsychologia 26, 27–43

30 Soto, D. and Humphreys, G.W. (2006) Seeing the content of the mind:enhanced awareness through working memory in patients with visualextinction. Proc. Natl. Acad. Sci. U. S. A. 103, 4789–4792

31 Koivisto, M. and Revonsuo, A. (2007) How meaning shapes seeing.Psychol. Sci. 18, 845–849

32 Most, S.B. et al. (2005) What you see is what you set: sustainedinattentional blindness and the capture of awareness. Psychol. Rev.112, 217–242

33 Farah, M.J. (1989) Mechanisms of imagery-perception interaction.J. Exp. Psychol. Hum. Percept. Perform. 15, 203–211

34 Theeuwes, J. and Van der Burg, E. (2007) The role of spatial andnonspatial information in visual selection. J. Exp. Psychol. Hum.Percept. Perform. 33, 1335–1351

35 Vierck, E. and Miller, J. (2008) Precuing benefits for color and locationin a visual search task. Percept. Psychophys. 70, 365–373

36 Downing, P.E. and Dodds, C.M. (2004) Competition in visual workingmemory for control of search. Vis. Cogn. 11, 689–703

37 Houtkamp, R. and Roelfsema, P.R. (2006) The effect of Items inworking memory on the deployment of attention and the eyesduring visual search. J. Exp. Psychol. Hum. Percept. Perform. 32,423–442

38 Olivers, C.N. What drives memory-driven attentional capture? Theeffects of memory type, display type, and search type. J. Exp. Psychol.Hum. Percept. Perform. (in press)

39 Woodman, G.F. et al. (2007) The role of working memoryrepresentations in the control of attention. Cereb. Cortex 17, 118–124

40 Oberauer, K. (2002) Access to information in working memory:exploring the focus of attention. J. Exp. Psychol. Learn. Mem. Cogn.28, 411–421

41 Soto, D. and Humphreys, G.W. (2008) Stressing themind: the effect ofverbal suppression and cognitive load on the time course ofattentional guidance from working memory. Percept. Psychophys.70, 924–934

42 Woodman, G.F. and Luck, S.J. (2007) Do the contents of visual workingmemory automatically influence attentional selection during visualsearch? J. Exp. Psychol. Hum. Percept. Perform. 33, 363–377

43 Soto, D. et al. (2006) Dividing themind: the necessary role of the frontallobes in separating memory from search. Neuropsychologia 44, 1282–

128944 Desimone, R. (1996) Neural mechanisms for visual memory and their

role in attention. Proc. Natl. Acad. Sci. U. S. A. 93, 13494–1349945 Soto, D. et al. (2007) Dissociating the neural mechanisms of memory-

based guidance of visual selection. Proc. Natl. Acad. Sci. U. S. A. 104,17186–17191

46 Brown, M.W. and Xiang, J.Z. (1998) Recognition memory: neuronalsubstrates of the judgement of prior occurrence. Prog. Neurobiol. 55,149–189

47 Thiebaut de Schotten, M. et al. (2005) Direct evidence for a parietal-frontal pathway subserving spatial awareness in humans. Science 309,2226–2228

48 Corbetta, M. and Shulman, G.L. (2002) Control of goal-directedand stimulus- driven attention in the brain. Nat. Rev. Neurosci. 3,201–215

49 Ahissar, M. and Hochstein, S. (2004) The reverse hierarchy theory ofvisual perceptual learning. Trends Cogn. Sci. 8, 457–464

50 Chelazzi, L. et al. (1993) A neural basis for visual search in inferiortemporal cortex. Nature 363, 345–347