PLEASE SCROLL DOWN FOR ARTICLE

This article was downloaded by: [Universite Rene Descartes Paris 5]On: 26 February 2010Access details: Access Details: [subscription number 786636382]Publisher Psychology PressInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Visual CognitionPublication details, including instructions for authors and subscription information:http://www.informaworld.com/smpp/title~content=t713683696

Upshifted decision criteria in attentional blink and repetition blindnessFlorent Caetta a; Andrei Gorea a

a Paris Descartes University and CNRS, Paris, France

First published on: 01 July 2009

To cite this Article Caetta, Florent and Gorea, Andrei(2010) 'Upshifted decision criteria in attentional blink and repetitionblindness', Visual Cognition, 18: 3, 413 — 433, First published on: 01 July 2009 (iFirst)To link to this Article: DOI: 10.1080/13506280902884402URL: http://dx.doi.org/10.1080/13506280902884402

Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf

This article may be used for research, teaching and private study purposes. Any substantial orsystematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply ordistribution in any form to anyone is expressly forbidden.

The publisher does not give any warranty express or implied or make any representation that the contentswill be complete or accurate or up to date. The accuracy of any instructions, formulae and drug dosesshould be independently verified with primary sources. The publisher shall not be liable for any loss,actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directlyor indirectly in connection with or arising out of the use of this material.

Upshifted decision criteria in attentional blink

and repetition blindness

Florent Caetta and Andrei Gorea

Paris Descartes University and CNRS, Paris, France

A large number of ‘‘unawareness’’ phenomena have been explained and quantifiedin terms of sensitivity (d?) fluctuations, with very few attempts at addressing analternative putative cause, i.e., fluctuations of subjects’ response criteria (c).Response criteria fluctuations are particularly likely under dual-task paradigmswith unbalanced sensitivities (Gorea & Sagi, 2000) such as those used in evidencingattentional blink (AB) and repetition blindness (RB) phenomena. The present studyinquires into whether AB and RB are indeed prone to a deviant decisionalbehaviour. AB and RB were studied with a yes/no task allowing the assessment of d?and c for the detection (presence/absence) of a target letter T2 as a function of itstemporal lag relative to the presentation of another (AB) or of the same (RB) letter,T1 (Experiment 1). A significant criterion increase was observed in both cases.Additional experiments demonstrate that this criterion effect is typical of thesedual-task AB and RB paradigms as it is not observed in a standard contrastdetection task with mixed contrasts (Experiment 2), in a ‘‘control’’ AB designstripped off its first task T1 (Experiment 3), or in a metacontrast experiment(Experiment 4). We propose that the observed criterion shifts are the consequenceof the inherent dual-task AB and RB designs (where observers have to judge twoevents of unequal saliencies) and that they entail an enhancement of the AB andRB effects as long as these effects are assessed via subjective (yes/no or matching)procedures.

Keywords: Dual task; Decision; Sensitivity; Signal Detection Theory;

Attentional blink.

Among the numerous ‘‘unawareness’’ visual phenomena reported for

otherwise highly salient stimuli (such as binocular rivalry, neglect, blind-

sight, change blindness, invisible priming, etc.), many require an implicit or

explicit dual-task design to be evidenced. This is definitely the case with

attentional blink (AB; Raymond, Shapiro, & Arnell, 1992) and repetition

Please address all correspondence to Florent Caetta, Paris Descartes University and CNRS,

45 rue des Saints Peres, 75006 Paris, France. E-mail: f.caetta@gmail.com

We thank our observers who have patiently spent many hours out of sheer altruism, and

Pedro Cardoso-Leite for useful comments.

VISUAL COGNITION, 2010, 18 (3), 413�433

# 2009 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

http://www.psypress.com/viscog DOI: 10.1080/13506280902884402

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

blindness (RB; Kanwisher, 1987) designs. AB is the phenomenon where, in a

rapid serial visual presentation display, subjects fail to report the second of a

pair of highly salient targets (T1, T2) when it is delayed with respect to the

first by about 200�500 ms. Critically, AB occurs only if subjects are requiredto report both targets, that is, a dual-task design. Likewise, RB is the

phenomenon where, within roughly the same time interval range, subjects

fail to detect the second target in the sequence if it is a repetition of the first

but not otherwise. Although very similar at face value, AB and RB show

rather different sensitivity functions of time-lag (U-shaped and monotonic,

respectively) and have been attributed to distinct (e.g., Chun, 1997) though

debated processes. Globally speaking, these processes have been related to

attentional or short-term memory limitations/bottlenecks or, most fre-quently, a combination of the two (for recent reviews see Bowman & Wyble,

2007; Olivers & Meeter, 2008).

It is not the purpose of this study to disentangle or confront these rather

numerous AB and RB theoretical accounts. Instead, we ask whether such

‘‘unawareness’’ visual phenomena, like many of those mentioned erlier,

might also proceed from other processes than a sensitivity depletion. By

design and by definition, AB and RB are dual-task paradigms where the two

targets to be reported are of unequal saliencies with the second in thesequence much less visible than the first. Here we aim to show that, in

addition to a sensory depletion, the ‘‘invisibility’’ of this second target may

be enhanced by a change in observers’ decision strategy (an upward criterion

shift) entailed by the inherent dual-task nature of these paradigms. Upward

criterion shifts have been positively tested or invoked to account for some

pathological unawareness conditions such as neglect (Klein, 1998; Ricci &

Chatterjee, 2004), extinction (Gorea & Sagi, 2002a), and blindsight

(Azzopardi & Cowey, 1997, 1998; Campion, Latto, & Smith, 1983).Criterion shifts have been recently demonstrated (Caetta, Gorea & Bonneh,

2007) for the case of motion induced blindness (MIB; Bonneh, Cooperman

& Sagi, 2001), but discarded as a putative cause of a response time reduction

due to stimulus repetition in a search task (Sigurdardottir, Kristjansson, &

Driver, 2008).

One may think of such decisional changes as being specific to high-level

processes. Gorea and Sagi (2000, 2001, 2002a, 2002b, 2005) have argued;

however, that they are typical of any testing condition where seen/not seenjudgements bearing on a feebly salient target are implicitly or explicitly made

with reference to a more salient stimulus. According to Signal Detection

Theory (SDT; Green & Swets, 1966), the placement of a decisional crite-

rion by an optimal observer slides along the internal response axis in

proportion with the observer’s sensitivity or, equivalently, with stimulus

salience. Accordingly, two unequally salient targets (like in AB or RB)

should yield, in principle, unequal criteria. Gorea and Sagi have shown that

414 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

this is not the case and that the two criteria tend to ‘‘attract’’ each other to

the point of merging into one. As a consequence, the least salient target will

be reported less and the more salient one more than if either of them were

presented in isolation. As this attraction effect occurs even for sequentially

presented targets (Gorea & Sagi, 2005), it should be also present in AB and

RB paradigms. This is definitely not to say that criterion shifts are the cause

of AB or RB effects, but that they may add to the sensory caused

performance depletion. In fact, criterion shifts entailed by dual-tasks with

unbalanced stimulus saliencies should not contribute at all to these

phenomena when assessed with criterion-free (such as forced-choice)

paradigms. It remains that about 35% of the AB and RB literature we’ve

reviewed (including the pioneering studies of Kanwisher, 1987, and of

Raymond et al., 1992) uses subjective measurements.

In addition to the subjective dual-task paradigms, criterion shifts are

known to occur in any subjective single-task experiment involving the

random presentation (across trials) of different saliency stimuli. In such yes/

no paradigms, false alarms cannot be attributed to a particular stimulus so

that their frequency is computed over the whole saliency range, hence

yielding one single number. In SDT, the z-score of a given false alarm

frequency has been coined by Gorea and Sagi (2000) the ‘‘absolute

criterion’’, c?. It is the decision variable computed along the internal

response axis (or sensory continuum) with respect to the mean of the

internal noise distribution. As explained in the next section (see also Figure 1),

this ‘‘unique’’ c? derived from mixed saliency designs will stand between the

c?-values that would be computed in blocked designs for the lower and the

higher saliency stimuli. As a consequence, the lower and higher saliency

stimuli used in mixed subjective designs will be reported respectively less and

more frequently than when tested in blocked subjective designs. This is the

case for all subjective AB and RB assessments as they have all been made

with randomized T1�T2 lags (hence different T2 saliencies). Under such

experimental conditions the main AB or RB effects (i.e., performance drop

for specific lags) are enhanced by necessity.

The use of a unique c? is not necessarily avoided in either mixed blocks

with ‘‘tagged’’ temporal lags or in experimental designs blocked by lag. This

should be so because humans are poor in tagging temporal delays within the

range effective for AB or RB effects (i.e., 0�200 ms; e.g., Cardoso-Leite,

Gorea, & Mamassian, 2007). Subjects may well report false alarms

originated at arbitrary moments so that these false alarms are erroneously

attributed to the nominal (experimentally tagged or blocked) lag. It follows

that the corresponding c?-values will be smeared (or averaged) across the

different (tagged or blocked) lags the consequence of which is, once again, a

performance undervaluation for the less visible stimuli.

UPSHIFTED DECISION CRITERIA 415

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

In short, the present study is aimed at testing criterion shifts in AB and

RB tasks due both to their dual-task format and to the standard procedure

used in these paradigms of randomizing temporal lags. In relation to this

latter point, the study also addresses the issue of lag uncertainty from the

d’

1.0

2.0

3.0

4.0

0.0

b

AB

Lag

c’

2.0

0 1 2 3 4 5 6 7 8 9

d

AB mixedAB blocked

1.5

1.0

0.5

1.0

0.5

0.0

-0.5

-1.0

c

AB mixedAB blocked

c

p(z)

ad’

c’

SN

c0

Sensory continuum (z)

uc’S1

S2

SN

Figure 1. Noise (N) and signal (S) internal response distributions, sensitivities (d?) and optimal

criteria (c and c?) presented within the SDT framework (a) and derived from hypothetical AB and RB

data (b, c, and d). (a). SDT framework for single and dual-task designs (top and bottom panels,

respectively). Gaussian are the probability density functions of the internal response (represented as z-

scores on the sensory continuum) for noise-alone (N) and for signal-plus-noise (S) events. Sensitivity

corresponds to the separation between the mean of the S and N distributions (top panel). When

measured with respect to the crossing point of the S- and N-distributions (c0), decision criteria are

referred to as relative (c); when measured with respect to the mean of the N-distribution, they are

referred to as absolute (c?). When S and N are equiprobable, an optimal observer places his response

criterion at the crossing point of the N and S distributions, whether tested with one (heavy vertical

solid line in the top panel) or two different signals strengths (S1 and S2; dashed vertical lines in the

bottom panel). In the latter case observers might not be able to keep the S1 and S2 distributions

(dotted Gaussians) apart and merge them into a global S-distribution (heavy Gaussian labelled S in the

bottom panel). If so, they will entertain a unique absolute criterion (uc?; heavy vertical line in the

bottom panel) that is ‘‘optimal’’ with respect to this global S-distribution but suboptimal with respect

to S1 and S2 taken independently. (b) A typical U-shaped d? function of target (T1�T2) lag in an AB

design (c and d). Optimal c- and c?-values in AB for the case where each lag is tested in isolation

(dashed lines) or randomized across trials (solid lines).

416 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

observer’s standpoint, whether these lags are blocked or experimentally

tagged within mixed designs. To make our point, we compare criteria

measured in AB and RB with those assessed in three single-task designs: A

standard contrast detection experiment with mixed contrasts, an AB design

where observers are asked to ignore the first (and easiest) task in the

sequence of two, and a metacontrast task. Metacontrast is the phenomenon

whereby a highly visible target is rendered invisible by a spatially adjacent

suprathreshold mask presented up to a few hundred ms after the target (for a

recent review see Hermens, Luksys, Gerstner, Herzog & Ernst, 2008). The

metacontrast control experiment was chosen for three reasons. First, like AB

and RB, metacontrast is a time dependent invisibility phenomenon. Second,

contrary to AB and RB, it is mostly thought of as due to low-level inhibitory

effects (e.g., Hermens et al., 2008; Ogmen, Breitmeyer, & Melvin, 2003).

Third and most critically, it involves a single (here detection) task and should

therefore not be prone to a criterion shift.

A FEW DEFINITIONS

Performance in all the present experiments is assessed in terms of sensitivity,

d?, and of response bias or criterion. Like d?, the criterion (heavy vertical

solid lines in Figure 1a, top panel), is expressed in units of the internal noise,

that is, z-scores. When measured with reference to the value of the sensory

continuum (or internal response) where the noise (N) and signal (S)

distributions cross (noted c0 in the top panel of Figure 1a), it is referred

to as the relative criterion, c��.5(zH�zFA), with zH and zFA the hit and

false alarm z-scores (Green & Swets, 1966; Macmillan & Creelman, 1991).

For equally probable N and S events, the optimal c�c0�0, whatever the d?(dashed horizontal line in Figure 1c). Another way of measuring this same

decision variable is with reference to the mean of the N-distribution in which

case it is referred to as the absolute criterion, c?�zFA (see Gorea & Sagi,

2000). The optimal c (�0) is at the mid-distance between the means of the

N and S distributions, so that an optimal c?�d?/2 (dashed curve in Figure

1d). Although c and c? are directly derivable from each other (provided the

hit rate is known, i.e., c?�2c�zH), c? is a more convenient index for

revealing the use by observers of a unique (internal response) decision

variable (as conceptualized by Gorea & Sagi, 2000) across stimuli yielding

different sensitivities (solid horizontal line in Figure 1d). Under such

conditions, standard SDT predicts different optimal c?-values (given that

the optimal c? equals d?/2; dashed curve in Figure 1d). The assessment of a d?independent c? would be direct evidence of observers using a unique decision

variable, uc?, across different stimulus saliencies. Such behaviour translates

into different c-values (solid curve in Figure 1c) that would hinder its graphic

UPSHIFTED DECISION CRITERIA 417

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

demonstration. For this reason the measured and theoretical criteria

presented in the Results section are given in c?-units. Because c-units are d?independent, they were used in the only case where we compared the

decision variables across distinct experiments yielding different sensitivities.Gorea and Sagi (2000) have shown that when observers cannot ‘‘tag’’ the

internal distributions evoked by two (or more) different saliency stimuli

(dotted Gaussians labelled S1 and S2 in Figure 1a, bottom panel), their

choice of a uc? is compatible with them merging these distributions into a

single one (heavy Gaussian labelled S in Figure 1a, bottom panel) and

picking up their uc? as the internal response point where the N and the

merged S distributions cross. Assuming that observers do indeed comply

with this modelling, their uc? should approximately equal half of the d?averaged over all n different saliency stimuli, i (/�ðan

i d0

i Þ=2n): This should be

also the case when false alarms in a mixed stimuli design cannot be

attributed by the experimenter to a specific stimulus among more than two;

this is so because c?�zFA.

Figure 1b illustrates an idealized (but typical) AB d? function of target

(T2) lag. Figure 1c shows the optimal c�0 to be expected if each lag is tested

in isolation (horizontal dashed line) and the expected c-values for the case

where the lags are mixed and observers use an uc? according to the strategydescribed earlier (/uc

0�ðan

i d0

i Þ=2n; solid curve). Figure 1d displays the

equivalent c?-values when each lag is tested separately (optimal c0

i�d0

i=2;dashed curve) and when they are interleaved and observers use a uc?(horizontal solid line).

GENERAL METHOD

In all experiments, the stimuli were presented on a 19-inch gamma corrected

screen (Philips Brilliance 109P, 1024�768 pixels, 100 Hz refresh rate) and

generated by a PC running Matlab software with the Psychophysics Toolbox

(Brainard, 1997; Pelli, 1997). They were presented on a uniform grey field(35.3 cd/m2). Subjects viewed the display binocularly from a distance of 50

cm in a dark room.

Experiment 1: Attentional blink (AB) andrepetition blindness (RB)

This experiment includes three conditions: ‘‘Mixed’’ AB, ‘‘mixed’’ RB, and

‘‘blocked’’ AB (see Figure 2). As noted in the introduction, the latter

condition is meant to check our conjecture that observers may not relate

their judgements to a specific time lag despite it being blocked and that, as a

consequence, they would use a unique decision criterion across lags. If so,

418 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

their ‘‘not seen’’ rate for lags yielding the largest sensitivity depression should

be enhanced.

Method

Observers. Five volunteers (age range 22�26), naıve to the purpose of

this study and with normal or corrected-to-normal vision, participated in all

three experiments.

Stimuli. Stimuli were Arial font letters (30 points with the largest letters,

‘‘M’’ and ‘‘W’’ subtending 1.158 � 0.808) randomly chosen from the entire

alphabet (with the exception of letter ‘‘X’’ in the AB condition; see the

Procedure section), with the constraint that no letter was presented twice

within a trial. Each trial consisted of a rapid serial visual presentation

(RSVP) of 25 letters displayed foveally, each lasting 20 ms with an interletter

interval of 70 ms (i.e., 11.11 letters/s; see Figure 2). Two letters in the RSVP

sequence were ‘‘targets’’, with the first target (T1) presented in white font

(142.40 cd/m2) and different from all the remaining letters (including the

second target, T2) that were black (0.01 cd/m2). T1 was presented on each

trial, whereas T2 was presented on 50% of the trials only. Fixation before

and after the RSVP sequence was ensured by a black (0.01 cd/m2) fixation

cross (0.48 � 0.48).

+

A

B

X

20 ms

70 ms

500 ms

Time

+

A

B

B

T1

T2

AB RB

70 -..700 ms

450 -..1170 ms

Figure 2. The RSVP sequence used in Experiment 1. In the AB condition, T2 was an ‘‘X’’, whereas

it was the same letter as T1 in the RB condition. The illustration is for T2-lag�1.

UPSHIFTED DECISION CRITERIA 419

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

Procedure. The RSVP sequence started after a 500 ms presentation of

the fixation cross. At the end of the sequence, subjects were presented with

two letters, one of which was the T1 target and the other chosen randomly

from the alphabet (with the exception of ‘‘X’’ in the AB sessions). Subjects

had to choose the T1 target (a two-alternative forced choice task) and

subsequently decide whether or not T2 (an ‘‘X’’ in AB and a T1 repeat in

RB) was present (a yes/no task). T1 was randomly preceded by 7�15 letters.

Incorrect responses were signalled by a tone. When present (half of the

trials), T2 was pseudorandomly presented at one of eight temporal lags

(‘‘mixed’’ condition), ranging from immediately after T1 (lag 1) to seven

letters after T1 (lag 8).‘‘Mixed’’ AB and RB sessions (50 trials/lag, with no intermixing between

AB and RB trials) were randomized and repeated four times. In case of a T1

identification failure, the whole RSVP sequence was repeated later in the

session so as to reach a constant number of 200 T1-correct trials per T2 lag.

The ‘‘blocked’’ condition was run with the AB paradigm only. The

procedure was the same as in the ‘‘mixed’’ condition except that only one lag

(out of four, i.e., lags 1, 3, 5, and 7) was presented per experimental block (50

trials). Blocks were repeated thrice in a random order (i.e., 150 T1-correct

trials per lag). Note that while the mixed condition compels the measure of a

unique c? shared by all T2-lags, the blocked condition allows for c? measures

specific to each T2-lag.

Results

The overall T1 identification performance was 95% across all three

experiments and subjects. Figure 3 shows T2 group mean sensitivity (Figure

3a) and absolute criteria in the mixed (Figure 3b) and blocked (3c)

conditions as a function of the T1-T2 lag. Squares and circles pertain to

experiments AB and RB, with solid and open symbols showing data for the

mixed and blocked conditions, respectively. For the mixed conditions, c?-sare by necessity unique so that they are represented in Figure 3b as black

(measured) and white (optimal) bars for the AB and RB experiments. For

the blocked AB condition (Figure 3c), c? should, but does not appear to be

lag (and hence d?) dependent (open squares and continuous lines). Instead

the optimal c? computed for each lag independently does show a lag

dependency.

AB and RB exhibit the typical d? functions of the lag: U-shaped for AB

and monotonically increasing for RB (note that the first two d?-values of the

RB function are not statistically different). The maximum AB and RB

effects (in d? units) in the mixed condition are both 1.31 s. The maximum

AB effect in the blocked condition is 0.92 s (but note that lag 8 was absent in

this condition). The measured c?-values are in all cases well above the

420 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

predicted optimal values; the upward shifts for the mixed AB, mixed RB,

and blocked AB conditions are respectively .48, .45 and an average of

.59 s units. Taken together, these d? and c? data clearly establish that AB and

RB are both sensitivity- and decision-related phenomena.A two-factor (condition*AB and RB mixed*and lag) repeated mea-

sures ANOVA on the d? data yields a significant lag effect, F(7, 28)�22.97,

pB.001. Neither the condition factor nor its interaction with the lag factor

yield significant effects. Hence, contrary to previous reports (Chun, 1997),

AB and RB effects are statistically undistinguishable. It should be noted,

however, that partial comparisons of the d?-values for lags 1 and 2 yield a

significant difference in the AB case, F(1, 4)�11.56, pB.05, but not in the

RB case.

Another two factors (condition*AB-mixed and AB-blocked � and lag)

repeated measures ANOVA with the mixed lag d?-values restricted to those

Figure 3. d? (a) and c? (b and c) dependency on the T1�T2 lag for the AB and RB experiments with

mixed (solid symbols and bars; a and b) and blocked (open symbols; a and c). Squares and circles are

for the mixed and blocked conditions, respectively. White bars in (b) and the dashed line in (c) show

optimal c?-values. All datum-points are averages over the five subjects with the vertical lines showing

91SE.

UPSHIFTED DECISION CRITERIA 421

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

used in the blocked condition (i.e., 4) shows both a mixed/blocked, F(1, 4)�7.29, p�.05, and a lag, F(3, 12)�3.62, pB.05, effect with no interaction

between the two. It remains that the lag effect in the AB-blocked condition

appears to be attenuated as it is only marginally significant when tested by

itself, F(3, 12)�2.79, p�.08. Quite likely this attenuation in the blocked

design is due to the global d? increase (presumably entailed by a reduction in

temporal uncertainty) the consequence of which could be a sensitivity ceiling

effect for lags 1 and 7.

The upward c? shift was tested separately for the mixed (AB and RB) and

blocked conditions. In the first case the measured and theoretical (i.e.,

optimal) unique c?s were compared via a two-way ANOVA with condition

(AB, RB) and c? (measured, optimal) as factors. The ANOVA shows a

significant c? effect, F(1, 4)�11.25, pB.05, but no condition or interaction

effects. Another two factors (c?*measured/optimal*and lag) repeated

measures ANOVA was run for the AB blocked condition. It yields a

significant measured/optimal c? effect, F(1, 4)�18.37, pB.05, but no lag

effect and a marginally significant interaction, F(3, 12)�3.26, p�.06.

Because the interaction between measured and optimal c? fails to reach

significance, the issue of whether or not observers use a unique criterion (in

the blocked lag condition) remains undetermined.

Experiment 2: Standard contrast detection (CD)

The possibility exists that the upward criterion shift observed in the previous

AB and RB experiments are accidental and due to a natural conservative

decisional behaviour of the five observers. To settle the issue we run these

same observers in a standard yes/no detection experiment with Gabor

patches yielding one out of four contrasts intermixed within an experimental

block. This experimental format should yield once again a unique c?.

Method

Observers. They were the same as in Experiment 1.

Stimuli. They were 2 c/deg vertical Gabor patches (s�18) with one out

of four contrast levels equally spaced on a log scale in-between 0.25 and 0.45.

When presented (50% of the trials), they were superimposed on an additive

Gaussian noise (s�.75, rms contrast of 59%) and displayed for 20 ms at the

centre of the screen, indicated by a black (0.01 cd/m2) fixation cross (0.48�0.48). ‘‘Noise’’ trials consisted in the Gaussian noise alone. Based on

preliminary experiments, the lowest and highest contrasts of the Gabor

patches were chosen so as to yield a d? difference of at least 1.

422 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

Procedure. Sensitivity and response criterion were assessed via a yes/no

procedure. Observers had to maintain fixation on the central cross for

500 ms, with its removal signalling the beginning of the trial. Stimuli (noise

or target plus noise) were displayed 500 ms later with the target contrast

pseudorandomly chosen across trials. Subjects had to decide whether a

target was present. Incorrect responses were signalled by a tone. One session

consisted of 200 trials (50 trials/contrast) and was repeated four times so that

d? and criteria were computed out of 200 trials/contrast. Notice again that

this mixed-contrast procedure does not allow for stimulus (here contrast)

specific c? assessments.

Results

Figure 4 shows the group mean sensitivity (d?) as a function of contrast

(Figure 4a), together with the group mean absolute measured (black bar)

and optimal (white bar) criterion (c?, Figure 4b). The major observation is

that the measured and theoretical c?s are very much alike. Repeated

measures ANOVA performed on the d? data show a significant effect of

contrast, F(3, 12)�46.84, pB.0001. A paired t-test comparing the measured

c? and the optimal unique c? failed to reach significance, implying that

observers’ decision behaviour is close to optimal.

Comparison between Experiment 1 and Experiment 2

As noted in the introduction, a comparison of the absolute criteria (c?)across experiments is not warranted as these indices depend on d?, which

cannot be precisely matched across different experimental setups. Instead,

relative criteria (c) are d? independent and do allow for such a comparison.

Remember that the optimal relative criterion is by definition 0. Figure 5 shows

Figure 4. Mean d? (over five observers) as a function of contrast (a) and absolute measured (black

bar) and optimal (white bar) unique criteria (b) in Experiment 2. Vertical bars are 91SE across

observers.

UPSHIFTED DECISION CRITERIA 423

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

the measured c-values averaged across observers and lags in the AB and RB

conditions of Experiment 1 and across observers and contrasts in Experiment

2. AB and RB yield a large upward criterion shift (about 0.45 s, i.e., one-third

of the d? variation observed in those experiments). In the standard contrast

detection experiment these same observers are much less conservative though

not quite optimal (their upward criterion shift is about 0.18, i.e., only one-

eighth of the tested d? range). A repeated measures ANOVA (with condition*AB, RB, and MC*as the only factor) shows that c-values differ significantly

across conditions, F(2, 8)�4.64, pB.05. Planned comparisons do not show a

significant difference between AB and RB, and both AB and RB differ

significantly from MC, AB, and MC, F(1, 4) �7.73, pB.0.5; RB and MC,

F(1, 4)�9.31, pB.05. Overall, the comparison between Experiments 1 and 2

demonstrates that the unique up-shifted criterion observed in Experiment 1 is

not due a natural decisional bias of the observers.

Experiment 3: Attentional blink (AB)*single task

The AB (and also RB) phenomenon is by definition bound to the presence

of an ancillary task, T1, during the RSVP presentation. The exclusion of the

Figure 5. Measured c-values averaged across observers and lags in the AB and RB conditions

(Experiment 1) and across observers and contrasts (Experiment 2). Note that the optimal c equals 0.

Vertical bars are 91SE across observers.

424 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

T1 task (but not stimulus) leaves the RSVP presentation unchanged but

turns the dual-task AB format into a single-task format. Inasmuch as the

criterion shift observed in the standard AB paradigm (Experiment 1) results

from this task involving a dual (T1 and T2) decision, the exclusion of T1

should abolish the criterion shift. The persistence of the criterion shift in the

absence of T1 would exclude this possibility. Unfortunately, the idea of

testing this hypothesis has occurred to us at a late stage in our study so that

not all the observers run in Experiment 1 could be run in the present

experiment. As a consequence, the criteria assessed in these two experiments

cannot be directly compared.

Method

Observers. They were four volunteers*two of whom also participated in

Experiments 1 and 2*naıve to the purpose of the study and the first author.

Their ages ranged from 25 to 29 years. Observers had normal or corrected-

to-normal vision.

Stimuli. They were the same as in Experiment 1 (AB condition) except

that the RSVP sequence was presented on a white Gaussian noise (s�.57,

rms contrast of 29%) to prevent for 100% correct detection. Indeed, the AB

presentation format without the T1 task eliminates the AB effect (Raymond

et al., 1992).

Procedure. The procedure was the same as in the Experiment 1 except

that observers had only to detect the presence of an ‘‘X’’ (T2). This target

was (or was not) presented at four lags (1, 3, 5, and 7) with respect to the

T1 stimulus. Lags were randomly interleaved across trials with 200 trials

per block (50 trials/lag). Blocks were repeated four times yielding 200

trials/lag.

Results

Figure 6 shows the group mean sensitivity (d?, Figure 6a) as a function of

T1�T2 lag, together with the absolute measured and optimal criteria (c?,Figure 6b). As expected for this single-task format, d?s remain constant

across lags (mean d? of 1.25). The measured and optimal criteria are close to

identical indicating that subjects are optimal. A repeated measures ANOVA

did not show a significant d? difference across lags. A paired t-test comparing

the measured and optimal c? also failed to reach significance. Overall, the

present data point to the fact that reducing the dual-task AB format to a

single-task format eliminates both the AB effect and the upward criterion

shift.

UPSHIFTED DECISION CRITERIA 425

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

Experiment 4: Metacontrast (MC)

It remains that the highly conservative behaviour observed with the AB and

RB paradigms might not be exclusively caused by their dual-task design, but

rather be the consequence of them being presumably high-level (attentional?)

phenomena. This possibility was tested in a standard yes/no metacontrast

experiment, which is of the single-task type. MC has been assimilated by

some to a perceptual ‘‘consciousness deficit’’ despite it being modelled in

most cases as low-level lateral inhibition process (see Hermens et al., 2008).

Here the different sensitivities, also mixed within an experimental block, were

obtained by modulating the target�mask stimulus�onset asynchrony (SOA)

so that the experimental format is close to the one used in Experiment 1.

Method

Observers. They were four volunteers naıve to the purpose of the study

and the first author, ranging in age from 25 to 32 years, with normal or

corrected-to-normal vision. One of the volunteers also participated in

Experiments 1 and 2.

Stimuli. The target was a vertical 1 c/deg Gabor patch (s�18) spatially

gated by a circular aperture 2.48 in diameter. It was superimposed on a larger

Gabor mask (s�28) with an identical vertical 1 c/deg carrier in phase with

the target. The target, presented on 50% of the trials, was spatially

overlapping with a horizontal 3 c/deg Gabor patch with the same s as the

target (resulting in a plaid stimulus) also confined by the 2.48 circular

aperture (see Figure 7). This additional stimulus was referred to as the ‘‘tag’’

as it identified the target�mask SOA (0, 20, 40, 60, and 80 ms) whether the

Figure 6. Mean d? (over five observers) as a function of lag (a) and absolute measured (black bar)

and optimal (white bar) unique criteria (b) in Experiment 3. Vertical bars are 91SE across observers.

426 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

target was presented or not. It was added to introduce an additional

transient, hence preventing subjects from basing their detection responses on

the target�mask transient cues that are known to vary with SOA (Kahne-

man, 1968). Target, tag and mask were centred at 78 to the left or right of a

black (0.01 cd/m2) fixation cross (0.48�0.48) and had contrasts of 0.20, 0.25,

and 0.25, respectively. All three were displayed for 20 ms with the mask onset

following the simultaneous target (when present) and tag onsets by 0, 20, 40,

60, or 80 ms. Based on preliminary experiments, the contrasts, spatial

frequencies and orientation of the stimuli were chosen so as to maximize the

masking of the target (when present) and to minimize the masking of the tag

(e.g., Ishikawa, Shimegi, & Sato, 2006), which remained highly visible for all

SOAs. The presence of the tag allowed the attribution of each false alarm to

a specific SOA and hence the assessment of SOA-specific criteria.

Procedure. The beginning of each trial was signalled by a decrease in the

size of the central cross; after a variable delay ranging from 500 to 2000 ms,

the stimuli were flashed for 20 ms with the (target �) tag�mask SOA

randomized across trials. Subjects had to decide whether the target was

Figure 7. Spatial and temporal layout of the stimuli used in the metacontrast experiment. Note that

target (i.e. ‘‘tag’’ or ‘‘tag�target’’) could be presented simultaneously with the ‘‘mask’’; in this the case

both the duration of the second ‘‘blank’’ and the target�mask SOA are null.

UPSHIFTED DECISION CRITERIA 427

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

present. Incorrect responses were signalled by a tone. One session consisted

of 250 trials (50 trials/SOA) and was repeated four times.

Results

Figure 8 shows the mean (over the five observers) d? (Figure 8a) and

absolute criteria (Figure 8b) as a function of SOA. Optimal criteria in Figure

7b are shown as dashed lines. Sensitivity follows a B-type (U-shape) function

of SOA with a minimum at 40 ms. However, with a mean d? maximum drop

of about 0.5 s, the strength of the masking remains relatively weak (despite

all our efforts to enhance it). Repeated measures one-way (lag) ANOVAs

separately performed on the d? and c? data show respectively a significant,

F(4, 16)�3.02, pB.05, and a nonsignificant lag effect with the latter

suggesting the use by observers of a unique c?. However, this conclusion

cannot be sustained in view of a two-way ANOVA comparing the measured

and optimal c?s across SOAs. This analysis fails to show significant effects of

either the c? type (measured vs. theoretical) or SOA factors, or for their

interaction. As the theoretical c?s were independently computed for each

SOA, they necessarily depart from a unique c?. The absence of a theoretical-

measured c? difference together with the absence of a c? � SOA interaction

leaves therefore the issue of whether or not observers use a unique c?undecided. It remains that the main conclusion to be drawn from this

experiment as well as from Experiments 2 and 3 (but not from Experiment 1)

is that, observers use a close to optimal decisional behaviour. The present

experiment also points to the fact that metacontrast, although methodolo-

gically related with the AB and RB paradigms, is not associated with the

large upward criterion shift observed with the latter two.

Figure 8. Mean (over five observers) d? (a) and c? (b) as a function of SOA in Experiment 4

(metacontrast). The dashed line in (b) shows optimal c?-values. Vertical bars are 91SE across

observers.

428 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

GENERAL DISCUSSION

Visual (un)awareness as well as attentional phenomena are typically referred

to and quantified in terms of sensitivity fluctuations. Response biases or

decisional factors may, however, be equally relevant causal factors. On many

occasions the sensitivity and decisional substrates of such phenomena have

been methodologically melded due to the use of subjective measurement

techniques. Under such conditions (about 35% of the AB and RB literature

we’ve reviewed), ignoring the decisional factor entails by necessity an

overestimation of the sensory cause. Building up on previous studies that

illustrated the significant participation of the decisional factor to phenom-

ena such as neglect (Klein, 1998; Ricci & Chatterjee, 2004), extinction

(Gorea & Sagi, 2002), blindsight (Azzopardi & Cowey, 1997, 1998; Campion

et al., 1983), or MIB (Caetta et al., 2007), the present study demonstrates its

involvement in both AB and RB inasmuch as they are assessed via subjective

procedures.

Experiment 1 has shown that, in both AB and RB, the decision criterion

for detecting the second (suppressed) target in the sequence is in average 0.51

s above the criterion expected from SDT. In the AB condition, the upward

criterion shift was observed whether the different time lags were randomly

interleaved or blocked. Experiments 2 and 3 demonstrated that these upward

criterion shifts are not due to observers’ natural conservative behaviour as

their criteria were not significantly different from those predicted by SDT

both in the simple detection task with intermingled contrasts (and hence d?-values; Experiment 2), and in the AB presentation format where observers

had to identify the second target only (thereby eliminating the AB

phenomenon; Experiment 3). Finally, Experiment 4 showed that

metacontrast*a presumably low-level ‘‘disappearance’’ phenomenon*with interleaved but ‘‘tagged’’ SOAs is also immune to the upward criterion

shift.

In the process of unveiling the strong criterion modulation under AB and

RB, we also asked the question of whether observers use a unique absolute

criterion (c?; see Figure 1) under conditions where, theoretically, they could

have used distinct c?s for each of the different stimulation conditions (i.e.,

different lags in the blocked AB condition in Experiment 1 and different

‘‘tagged’’ SOAs in Experiment 4). The absence of a lag/SOA effect on the c?measured in the blocked and tagged experiments supports the use of a

unique criterion. In turn, such decisional behaviour enhances the ‘‘not seen’’

reports for the less visible targets and therefore the AB and RB effects.

However, the use of a unique c? cannot be confidently asserted from these

experiments (with temporal tags or blocked lags) as they showed little d? and

therefore, by necessity, c? variability across lags.

UPSHIFTED DECISION CRITERIA 429

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

It remains that the use of a unique c? even under conditions where the

different stimulations are clearly tagged should be expected from Gorea and

Sagi’s work (2000, 2001, 2002a, 2002b) suggesting that subjects cannot

entertain more than one internal distribution at a time. According to these

authors, when multistrength stimuli are tested jointly (be they tagged or not),

subjects merge the corresponding internal distributions and use one single

criterion that is optimal given a unique internal representation but

nonoptimal with respect to the distinct internal representations of each of

the two (or more) stimuli. Specifically, the unique c? is located somewhere in-

between the optimal criteria for each stimulus (but closer to the most salient

stimulus) so that the less and the more salient events are respectively more

and less frequently ignored. As a consequence, the use of subjective methods

in assessing AB or RB deceitfully enhances these effects.

At first sight the account above does not explain the significant elevation

of the unique c? observed in Experiment 1 (0.51 s for both AB and RB), but

not in Experiments 2, 3, and 4. This apparent incongruence disappears if one

considers that AB and RB formats are the only ones in the present series of

four involving an explicit dual-task design. Indeed, the exclusion of the

‘‘secondary’’, T1 task (Experiment 3) not only eradicates the AB and RB

phenomena (as originally shown; Kanwisher, 1987; Raymond et al., 1992),

but it also abolishes the upward c? shift. As the secondary T1 task is designed

to yield a high d? (typically too high to be measured), it also yields a high c?.Our conjecture is that criterion associated with the less salient (T2) stimulus

is ‘‘attracted’’ by the more salient (T1) stimulus as a consequence of

observers’ (at least partly) merging the two underlying internal distributions.

Because T1 performances were measured here via a two-alternative forced

choice procedure, the prediction that the associated c? should be lowered in

the presence of T2 could not be tested.

As noted by Gorea and Sagi (2000), criterion shifts do not follow from

the mere presence of two different saliency targets, but rather from subjects

having to make a decision on each of them. This should explain the absence

of a criterion shift for an AB format where the T1 task (but not stimulus) is

excluded (Experiment 3). So, in addition to the many, yet unresolved

accounts of AB and RB (see introduction), we showed that, when assessed

with subjective methods these phenomena are enhanced by subjects’

‘‘deviant’’ decisional behaviour entailed by the very nature of the dual-task

conditions under which they are obtained.

On the reasonable assumption that a dual-task needs not be explicit to

entail a merged internal representation of two distinct events, the criteria

attraction account may also explain the upward criterion shift (of about

0.7 s) observed by Caetta et al. (2007) in an MIB task. In that experi-

ment, sensitivities to small target-luminance increments were measured in

430 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

independent experimental blocks for the visible and suppressed MIB states.

For this to be feasible, observers must continuously keep track of the MIB

target fading in and out of ‘‘awareness’’. As a consequence, the internal

representations of the two stimulus states may have been merged and a

unique criterion used to both partition the internal states and to perform the

detection task (see Gorea & Sagi, 2001).

Ever since the formulation of SDT (Green & Swets, 1966), the relation-

ship between decision criteria and consciousness has been vigorously

debated. According to Macmillan and Creelman (2005, p. 47), ‘‘the

distinction between consciousness and its lack has nothing to do with either

the existence or location of a criterion’’. The inescapable fact remains that,

inasmuch as consciousness is by definition a strictly subjective construct, its

assessment is necessarily related to subject’s assertion of ‘‘being or not being

conscious’’ and, therefore, to his decisional behaviour. This line of thinking

remains is embraced in a number of recent studies (e.g., Lau, 2008; Lau &

Passingham, 2006; Wilimzig, Tsuchiya, Fahle, Einhauser, & Koch, 2008). We

therefore conclude that, in addition to a pure sensory depletion, AB and RB

also proceed from a significant upward criterion shift presumably caused by

the inherent dual-task format required for their observation.

It is possible that such criterion shifts are also caused by the core

process(es) accounting for the sensory depletion in AB and RB. As noted by

Olivers and Meeter (2008, p 836), ‘‘all currently active theories of the

attentional blink attribute it to a limited-capacity processing stage, or

bottleneck’’. These theories share the notion that processing T1 draws on the

attentional and/or storage resources needed for the encoding of T2. Gorea

and Sagi (2005) and more recently Schneider and Komlos (2008) have

pointed to the fact that, in addition to depleting sensitivity, attentional

limitations may also entail a more conservative decisional behaviour.

Reminiscent of the ‘‘temporary loss of control theory’’ (Di Lollo, Kawahara,

Ghorashi, & Enns, 2005; Kawahara, Kumada, & Di Lollo, 2006), Olivers

and Meeter offered an alternative AB account whereby the ‘‘blink’’ for T2 is

caused by the distractor following T1 (i.e., lags�1). This distractor would

trigger an inhibitory response that blocks its access to visual short term

memory rather than depleting its sensory effect. This proposal does not

match our account of the presently observed criterion shifts being caused by

the AB (or RB) dual-task format with unequally salient stimuli. It remains

that the inhibitory process proposed by Olivers and Meeter may as well

entail a more conservative decisional behaviour bearing on the detection of

T2. Be it as it may, systematic studies assessing the modulation of decision

criteria by transient attentional, mnemonic, and/or selective inhibition

causes remain to be carried out.

UPSHIFTED DECISION CRITERIA 431

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

REFERENCES

Azzopardi, P., & Cowey, A. (1997). Is blindsight like normal, near-threshold vision? Proceedings

of the National Academy of Sciences of the USA, 94, 14190�14194.

Azzopardi, P., & Cowey, A. (1998). Blindsight and visual awareness. Consciousness and

Cognition, 7, 292�311.

Bonneh, Y. S., Cooperman, A., & Sagi, D. (2001). Motion-induced blindness in normal

observers. Nature, 411, 798�801.

Bowman, H., & Wyble, B. (2007). The simultaneous type, serial token model of temporal

attention and working memory. Psychological Review, 114, 38�70.

Brainard, D. H. (1997). The Psychophysics Toolbox. Spatial Vision, 10, 433�436.

Caetta, F., Gorea, A., & Bonneh, Y. (2007). Sensory and decisional factors in motion-induced

blindness. Journal of Vision, 7(7), 1�12.

Campion, J., Latto, R., & Smith, Y. M. (1983). Is blindsight an effect of scattered light, spared

cortex, and near-threshold vision? Behavioral and Brain Sciences, 6, 423�486.

Cardoso-Leite, P., Gorea, A., & Mamassian, P. (2007). Temporal order judgment and simple

reaction times: Evidence for a common processing system. Journal of Vision, 7(6), 1�14.

Chun, M. M. (1997). Types and tokens in visual processing: A double dissociation between the

attentional blink and repetition blindness. Journal of Experimental Psychology: Human

Perception and Performance, 23, 738�755.

Di Lollo, V., Kawahara, J., Ghorashi, S. M. S., & Enns, J. T. (2005). The attentional blink:

Resource depletion or temporary loss of control? Psychological Research, 69, 191�200.

Gorea, A., & Sagi, D. (2000). Failure to handle more than one internal representation in visual

detection tasks. Proceedings of the National Academy of Sciences of the USA, 97, 12380�12384.

Gorea, A., & Sagi, D. (2001). Disentangling signal from noise in visual contrast discrimination.

Nature Neuroscience, 4, 1146�1150.

Gorea, A., & Sagi, D. (2002a). Natural extinction: A criterion shift phenomenon. Visual

Cognition, 9, 913�936.

Gorea, A., & Sagi, D. (2002b). The unique criterion constraint: A false alarm? (response to

Kontsevich et al.). Nature Neuroscience, 5, 707�708.

Gorea, A., & Sagi, D. (2005). On decision and attention. In L. Itti, G. Rees, & J. K. Tsotsos

(Eds.), Neurobiology of attention (pp. 152�159). San Diego, CA: Elsevier.

Green, D. M., & Swets, J. A. (1966). Signal detection theory. New York: Wiley.

Hermens, F., Luksys, G., Gerstner, W., Herzog, M. H., & Ernst, U. (2008). Modelling spatial

and temporal aspects of visual backward masking. Psychological Review, 115, 83�100.

Ishikawa, A., Shimegi, S., & Sato, H. (2006). Metacontrast masking suggests interaction

between visual pathways with different spatial and temporal properties. Vision Research,

46(13), 2130�2136.

Kahneman, D. (1968). Method, findings, and theory in studies of visual masking. Psychological

Bulletin, 70, 404�425.

Kanwisher, N. (1987). Repetition blindness: Type recognition without token individuation.

Cognition, 27, 117�143.

Kawahara, J., Kumada, T., & Di Lollo, V. (2006). The attentional blink is governed by a

temporary loss of control. Psychonomic Bulletin and Review, 13, 886�890.

Klein, S. A. (1998). Double-judgment psychophysics for research on consciousness: Application

to blindsight. In S. A. Hemeroff, A. W. Kaszniak, & A. C. Scott (Eds.), Toward a science of

consciousness: II. The second Tucson discussions and debates (pp. 361�369). Cambridge, MA:

MIT Press.

432 CAETTA AND GOREA

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010

Lau, H. C. (2008). A higher-order Bayesian decision theory of perceptual consciousness.

Progress in Brain Research, 168, 35�48.

Lau, H. C., & Passingham, R. E. (2006). Relative blindsight in normal observers and the neural

correlate of visual consciousness. Proceedings of the National Academy of Sciences, 103(49),

18763�18768.

Macmillan, N. A., & Creelman, C. D. (1991). Detection theory: A user’s guide. New York:

Cambridge University Press.

Macmillan, N. A., & Creelman, C. D. (2005). Detection theory: A user’s guide (2nd ed.).

Mahwah, NJ: Lawrence Erlbaum Associates.

Ogmen, H., Breitmeyer, B. G., & Melvin, R. (2003). The what and where in visual masking.

Vision Research, 43, 1337�1350.

Olivers, C. N. L., & Meeter, M. (2008). A boost and bounce theory of temporal attention.

Psychological Review, 115(4), 836�863.

Pelli, D. G. (1997). The VideoToolbox software for visual psychophysics: Transforming numbers

into movies. Spatial Vision, 10, 437�442.

Raymond, J. E., Shapiro, K. L., & Arnell, K. M. (1992). Temporary suppression of visual

processing in an RSVP task: An attentional blink? Journal of Experimental Psychology:

Human Perception and Performance, 18, 849�860.

Ricci, R., & Chatterjee, A. (2004). Sensory and response contributions to visual awareness in

extinction. Experimental Brain Research, 157, 85�93.

Schneider, K. A., & Komlos, M. (2008). Attention biases decisions but does not alter

appearance. Journal of Vision, 8(15): 3, 1�10.

Sigurdardottir, H. M., Kristjansson, A., & Driver, J. (2008). Repetition streaks increase

perceptual sensitivity in visual search of brief displays. Visual Cognition, 16, 643�658.

Wilimzig, C., Tsuchiya, N., Fahle, M., Einhauser, W., & Koch, C. (2008). Spatial attention

increases performance but not subjective confidence in a discrimination task. Journal of

Vision, 8(5), 1�10.

Manuscript received September 2008

Manuscript accepted March 2009

First published online July 2009

UPSHIFTED DECISION CRITERIA 433

Downloaded By: [Universite Rene Descartes Paris 5] At: 11:57 26 February 2010