Blinks of the eye predict blinks of the mind.
ABSTRACT The Attentional Blink (AB)--a deficit in reporting the second of two target stimuli presented in close succession in a rapid sequence of distracters--has been related to individual processing limitations of working memory. Given the known role of dopamine (DA) in working memory processes, the present experiment tested the hypothesis that DA, and in particular the DA/D1 subsystem, plays a role in the AB. We present evidence that the spontaneous eyeblink rate (EBR), a functional marker of central dopaminergic function, reliably predicts the size of AB. Thus, in line with our hypothesis, these data point to a modulatory role for DA in the AB.
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ABSTRACT: Increasing evidence suggests that `aromas have distinctive effects on the allocation of attention in space: Arousing olfactory fragrances (e.g., peppermint) are supposed to induce a more focused state, and calming olfactory fragrances (e.g., lavender) a broader attentional state. Here, we investigate whether odors have similar effects on the allocation of attention in time. Participants performed the attentional blink (AB) task, known to produce a deficit in reporting the second of two target stimuli presented in close succession in a rapid sequence of distractors, while being exposed to either a peppermint or a lavender aroma. In two experiments using a between-subjects and a within-subjects design, respectively, we show that the two odors have specific effects on attentional control: As compared with the calming lavender aroma, the arousing peppermint condition yielded a larger AB. Our results demonstrate that attentional control is systematically modulated by factors that induce a more or a less distributed state of mind.Attention Perception & Psychophysics 07/2014; · 2.15 Impact Factor
- Frontiers in Psychology 10/2014; 5:1101. · 2.80 Impact Factor
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ABSTRACT: Goal-directed action in changing environments requires a dynamic balance between complementary control modes, which serve antagonistic adaptive functions (e.g., to shield goals from competing responses and distracting information vs. to flexibly switch between goals and behavioural dispositions in response to significant changes). Too rigid goal shielding promotes stability but incurs a cost in terms of perseveration and reduced flexibility, whereas too weak goal shielding promotes flexibility but incurs a cost in terms of increased distractibility. While research on cognitive control has long been conducted relatively independently from the study of emotion and motivation, it is becoming increasingly clear that positive affect and reward play a central role in modulating cognitive control. In particular, evidence from the past decade suggests that positive affect not only influences the contents of cognitive processes, but also modulates the balance between complementary modes of cognitive control. In this article we review studies from the past decade that examined effects of induced positive affect on the balance between cognitive stability and flexibility with a focus on set switching and working memory maintenance and updating. Moreover, we review recent evidence indicating that task-irrelevant positive affect and performance-contingent rewards exert different and sometimes opposite effects on cognitive control modes, suggesting dissociations between emotional and motivational effects of positive affect. Finally, we critically review evidence for the popular hypothesis that effects of positive affect may be mediated by dopaminergic modulations of neural processing in prefrontal and striatal brain circuits, and we refine this “dopamine hypothesis of positive affect” by specifying distinct mechanisms by which dopamine may mediate effects of positive affect and reward on cognitive control. We conclude with a discussion of limitations of current research, point to central unresolved questions and outline perspective for future research on affective and motivational modulations of cognitive control modes.Neuropsychologia 09/2014; · 3.45 Impact Factor
Neuropsychologia 46 (2008) 3179–3183
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/neuropsychologia
Blinks of the eye predict blinks of the mind
Lorenza S. Colzatoa,∗, Heleen A. Slagterb, Michiel M.A. Spapéa, Bernhard Hommela
aLeiden University, Cognitive Psychology Unit & Leiden Institute for Brain and Cognition, Leiden, The Netherlands
bUniversity of Wisconsin, Laboratory for Brain Imaging and Behavior, Madison, USA
a r t i c l ei n f o
Received 3 March 2008
Received in revised form 3 July 2008
Accepted 9 July 2008
Available online 16 July 2008
Spontaneous eyeblink rate
a b s t r a c t
The Attentional Blink (AB) – a deficit in reporting the second of two target stimuli presented in close
succession in a rapid sequence of distracters – has been related to individual processing limitations of
working memory. Given the known role of dopamine (DA) in working memory processes, the present
present evidence that the spontaneous eyeblink rate (EBR), a functional marker of central dopaminergic
role for DA in the AB.
© 2008 Elsevier Ltd. All rights reserved.
The human brain is severely limited with regard to the num-
ber of events it can process at one time. A particularly convincing
demonstration of this limitation is provided by the so-called Atten-
in close temporal proximity, such as in RSVP (Rapid Serial Visual
Presentation) tasks: Whereas the first target (T1) is commonly easy
to identify and to report, performance on the second target (T2) is
dramatically impaired if it follows T1 within 100–500ms.
Many theoretical accounts of the AB assume that processing
and consolidating T1 in working memory (WM) occupies limited
attentional mechanisms to a degree that leaves too little avail-
able for processing and consolidating T2 if it appears before the
consolidation of T1 is completed (for an overview, see Shapiro,
and Schnitzler (2006) suggest a trade-off between the amount of
resources devoted to T1 processing and the probability of identi-
fying T2: Participants who showed greater attention-related brain
does not reflect a structural bottleneck in information processing
(see Hommel et al., 2006), as studies have shown that T2 per-
formance is usually very good when T2 immediately follows T1,
a phenomenon called “lag-1 sparing” (Visser, Bischof, & Di Lollo,
∗Corresponding author at: Leiden University, Department of Psychology, Cogni-
tive Psychology Unit, Postbus 9555, 2300 RB Leiden, The Netherlands.
E-mail address: firstname.lastname@example.org (L.S. Colzato).
1999). In addition, people can report even more than two targets
when these targets belong to the same category and are presented
in a sequence (Di Lollo, Kawahara, Ghorashi, & Enns, 2005), sug-
gesting that distracter interference plays an important role in the
work of frontal, right-parietal and temporal brain areas involved
in perceptual awareness in the AB (for review, see Hommel et al.,
2006). Yet, little is known about the neurochemical mechanisms
that may modulate the AB. In recent years, a computational theory
has postulated that norepinephrine, given its role in attentional
selection in the temporal domain (Aston-Jones & Cohen, 2005), is
directly involved in the AB phenomenon (Nieuwenhuis, Gilzenrat,
Holmes, & Cohen, 2005). Yet, a pharmacological study showed no
on AB task performance (Nieuwenhuis, Van Nieuwpoort, Veltman,
& Drent, 2007). Consistent with this research, another recent study
(De Martino, Strange, & Dolan, 2007) revealed no effect on T2
detection after the administration of nadolol, a peripherally act-
ing ?-adrenergic antagonist, or after the administration of 20mg of
propanol, a centrally acting ?-adrenergic antagonist. The authors
did report impaired T2 detection after the administration of a
higher dose (40mg) of propanol, but this impairment was equally
in these two studies affected the size of the AB. This series of null
findings is inconsistent with a role for the noradrenergic system in
necessary to fully understand the possible role of norepinephrine
in temporal attention and the AB.
0028-3932/$ – see front matter © 2008 Elsevier Ltd. All rights reserved.
L.S. Colzato et al. / Neuropsychologia 46 (2008) 3179–3183
It is unlikely that any single neuromodulatory mechanism can
ulate the Attentional Blink. However, dopamine (DA) represents a
particularly likely candidate, given its key role in WM processes
(Braver & Barch, 2002; Braver, Barch, & Cohen, 1999; Hazy, Frank,
& O’Reilly, 2006). Specifically, DA projections to the prefrontal cor-
tex (PFC) serve to gate access of context representations into active
memory through simple neuromodulatory effects on processing
units in the PFC (Braver et al., 1999). These effects serve both gating
and learning functions, which enable the system to discover what
regulate when that information is updated. Thus, dopamine plays
obtained evidence that people high in WM operation span show a
smaller AB (Colzato, Spapè, Pannebakker, & Hommel, 2007), indi-
cating that the AB is related to WM in general and attributable to
operational resource limitations in particular (Dehaeane, Sergent,
& Changeux, 2003; Di Lollo et al., 2005; Gross et al., 2004; Hommel
et al., 2006). Schizophrenic patients (Cheung, Chen, Chen, Woo,
& Yee, 2002; Li et al., 2002) have been reported to show a more
pronounced AB, while no differences in AB size were reported
for Parkinson’s patients compared to controls (Vardy, Bradshaw, &
Iansek, 2003). Unfortunately, these studies have major confounds
given that the schizophrenic and Parkinson’s patients were taking
antipsychotic drugs and l-DOPA, respectively (which both act on
the dopaminergic system). The results obtained in these studies
studies should test patients “on” and “off” medication, but for obvi-
ous ethical reasons these kind of studies are difficult to perform.
Importantly for the current study, these links between
dopamine and WM on the one hand and between WM and AB
on the other hand point to a possible modulatory role for DA in
the AB. The major dopaminergic pathways are dominated by D1
and D2 receptors, which appear to play different, separable roles in
are presumably involved in WM processes (Goldman-Rakic, Muly,
& Williams, 2000; Sawaguchi & Goldman-Rakic, 1991), DA/D2-
dominated pathways have been implicated in response inhibition
and cognitive flexibility (Lee, Groman, London, & Jentsch, 2007).
Given the link between the AB and capacity limitations of working
are involved in the AB. Consistent with this idea, a recent study
(Gibbs, Naudts, Spencer, & David, 2007).
2. Purpose of study
The present experiment aimed to test the hypothesis that DA,
and in particular the DA/D1 subsystem, plays a role in the AB by
driving the WM processes necessary to store and consolidate tar-
was the spontaneous eyeblink rate (EBR), a functional marker of
central dopaminergic function (Blin, Masson, Azulay, Fondarai, &
Serratrice, 1990; Karson, 1983; Kleven & Koek, 1996; Taylor et al.,
1999). This measure has been shown to reliably predict behavioral
performance in several cognitive task that have been associated
with dopaminergic function (e.g., Dreisbach et al., 2005; Colzato,
van Wouwe, & Hommel, 2007; Colzato, van den Wildenberg, &
Hommel, submitted for publication-a). Further evidence that EBR
dopaminergic function. For example, schizophrenic patients, who
show increased dopaminergic activity in the striatum, but reduced
activity in the prefrontal cortex (Davis, Kahn, Ko, & Davidson,
1991), show elevated EBRs (Freed, 1980), while EBR is reduced in
Parkinson’s patients (Deuschel & Goddemeier, 1998). Furthermore,
recreational cocaine users, who suffer from a loss of nigrostra-
tial dopaminergic cells, also display lower EBRs (Colzato, van den
Wildenberg, & Hommel, submitted for publication-b). Together,
these findings indicate that EBR provides a reliable measure of
taneous EBR in healthy individuals. Given the known role of DA/D1
in WM task performance (Goldman-Rakic et al., 2000; Sawaguchi
& Goldman-Rakic, 1991) and based on our previous findings show-
ing a small AB for individuals high in WM operation span (Colzato,
Spapè, et al., 2007), we expected to find a negative correlation
between AB size and EBR. Our specific prediction was that partici-
show a smaller AB.
Twenty young healthy adults (10 women and 10 men, between 18 and 30 years
old) served as participants for partial fulfillment of course credit or a financial
and by word of mouth. Following Colzato, van den Wildenberg, and Hommel (2007)
and Colzato, Kool, and Hommel (2008) participants were selected with the Mini
International Neuropsychiatric Interview (M.I.N.I.; Lecrubier et al., 1997). The fol-
lowing selection criteria were applied: no Axis 1 psychiatric disorder (DSM-IV),
including ‘substance abuse’; no clinically significant medical disease; no use of
medication. Written informed consent was obtained by all participants; the pro-
tocol was approved by the local ethical committee (Leiden University, Institute for
3.2. Apparatus and stimuli
were presented in a resolution of 800 by 600 pixels in 16 bit color on a 17??CRT
refreshing at 100Hz. Participants were seated at a viewing distance of about 50cm.
The fixation mark (“+”), as well as all RSVP items were presented centrally in black
on a gray background (RGB 128, 128, 128). Each item was set in 16 point Times New
Roman font. RSVP items included letters and digits. Letters were drawn randomly
without replacement from the alphabet. Digits were drawn randomly from the set
3.3. Procedure and design
None of the participants needed extra training. The duration of the practice, thus,
did not differ between participants. We formed two groups based on spontaneous
EBR levels using a split mean: a low (10 participants, 2.40–15.16 score) and a high
(10 participants, 15.30–31.80) EBR group.
3.4. Eyeblink rate
A BioSemi ActiveTwo system (BioSemi Inc., Amsterdam, The Netherlands) was
one right) Ag–AgCl electrodes, for 6-min eyes-open segments under resting condi-
tions. The vertical electrooculogram (EOG), which recorded the voltage difference
between two electrodes placed above and below the left eye, was used to detect eye
blinks. The horizontal EOG, which recorded the voltage difference between elec-
trodes placed lateral to the external canthi, was used to measure horizontal eye
movements. Given that spontaneous EBR is supposed to be stable during daytime
but increases in the evening (8:30p.m., as reported by Barbato et al., 2000), data
were never collected after 5p.m. Additionally, we asked participants to avoid alco-
hol and nicotine consumption and to sleep sufficiently the day before the recording.
Participants were comfortably sitting in front of a blank poster with a cross in the
and asked to look at the cross in a relaxed state.
L.S. Colzato et al. / Neuropsychologia 46 (2008) 3179–3183
Fig. 1. Example of an RSVP trial. On every trial, 20 items were presented at the center of the screen, preceded by a 2000-ms fixation cross. Most of the items were letters,
presented for 40ms each and followed by a 40-ms blank. Participants had to detect two target numbers (T1 and T2) among the items. T1 and T2 were separated by one, three,
five, or eight nontarget items, defining the lag. T1 was presented at position 7, 8 and 9 of the stimulus stream.
3.5. RSVP task
In the RSVP task adopted from Colzato, Spapè, et al. (2007), participants
had to identify and report two digits (T1 and T2) presented in a rapid stream
of letter distractors. After having read the instructions, which included a slow
demonstration of the RSVP, and indicating to have fully understood the task, par-
ticipants were required to go through 24 trials of training. If more than 50% of
the responses were incorrect during the training, the training part was automat-
ically restarted. A fixation plus sign, which was shown for 2000ms, marked the
beginning of each trial. After a blank interval of 250ms, the RSVP commenced, con-
sisting of 20 items with a duration of 40ms each and an inter-stimulus interval of
7, 8 and 9 in order to reduce the predictability of target onsets. T2 was presented
directly thereafter (Lag 1), or after another 2, 4, or 7 distracters (Lag 3, 5, and 8
successively), see Fig. 1. Both targets were to be reported directly (order of report
was not considered) after the RSVP – the question being “which two targets did
you see?” – by pressing the corresponding digit keys. A full experimental session
lasted 30min and contained one block of 360 trials (3 locations of T1×4 lags×30
3.6. Statistical analysis
(T2|T1). To test our main hypothesis that dopamine modulates the size of the AB,
we ran a Pearson correlation test, which examined the association between EBR and
the maximal AB (measured as T2|T1 at Lag 8 minus the minimum of T2|T1 at Lag
3 and at Lag 5). We also explored the relationship between EBR and Lag-1 sparing
(measured as T2|T1 at Lag 1 minus T2|T1 at Lag 5), and between EBR and mean (i.e.,
averaged across lags) T1 and T2 accuracy. A significance level of p<.05 was adopted
for all statistical tests.
4.1. Eyeblink rate measurement
EOG data were examined using the Brain Vision Analyzer
(Brain ProductsTMGmbH, Munich, Germany; www.brainproducts.
com/products/analyzer/). An eyeblink was defined as a voltage
change of 100?V in a time interval of 500ms (Colzato, van Wouwe,
et al., 2007). Our sample of participants had EBRs ranging from
2.4 to 31.8permin (standard deviation (S.D.)=8.6), and thus rep-
resented a wide range of tonic dopaminergic functioning.
4.2. RSVP task
T1 accuracy is shown in Fig. 2. The ANOVA with lag as within-
participant factor showed a significant lag effect, F(3, 57)=29.49,
p<.001. As Fig. 2 shows, this effect was due to a dip in performance
observed if T1 and T2 belong to the same category (e.g., digits)
and satisfy the same selection criteria, and when the presentation
rate is fast. These conditions are thought to increase the competi-
tion between T1 and T2 representations if they occur close in time,
with T2 outperforming T1 more often (Colzato, Spapè, et al., 2007;
Hommel & Akyürek, 2005; Potter, Staub, & O’Connor, 2002).
The ANOVA of conditional T2 accuracy (T2|T1) revealed a sig-
nificant lag effect, F(3, 57)=33.34, p<.001, indicating a marked AB
with good performance at Lag 1 (Lag-1 sparing, Visser et al., 1999)
and a considerable dip at Lags 3 and 5 (see Fig. 2). Interestingly,
L.S. Colzato et al. / Neuropsychologia 46 (2008) 3179–3183
Fig. 2. T1 (unconditional) performance (left panel) and T2 performance given T1
correct (T2|T1) (right panel), shown separately for each lag and for T2|T1 for high
and low spontaneous eyeblink rate (EBR).
(min) and maximal AB size. Note that those individuals that showed a high EBR
generally showed a smaller AB.
EBR level impacted the blink size, as indicated by a two-way inter-
action between group and lag, F(3, 54)=2.81, p=.048.1Participants
in the high EBR group showed a smaller AB than participants in
the low EBR group, thus confirming our prediction that partici-
show a smaller AB. Also in line with this prediction, EBR nega-
tively correlated with AB size,2r(20)=−.530, p=.016. As it can be
seen in Fig. 3, individuals with relatively high dopaminergic base
activity (as reflected by high EBRs) generally showed a smaller AB.
Importantly, EBR did not correlate significantly with Lag-1 sparing
[r(20)=.304, p=.192], or mean T1 and T2 accuracy [respectively:
r(20)=.282; p=.228; r(20)=.150; p=.529], indicating that EBR was
selectively associated with AB size.
1This interaction was even more pronounced when the data from Lag 1 were
dropped from the analysis, F(2, 36)=5.80, p<.01. Separate ANOVAs showed a lag
effect in low blinkers, F(2, 18)=11.35, p<.001, but not in high blinkers, F(2, 18)<1,
with both groups showing equivalent performance at Lag 8, p>.34.
2Other measures of the AB deficit (e.g., T2Lag8|T1–T2Lag3|T1) were also
highly correlated with EBR, r(20)=−.464, p=.039, and even others, atyp-
ical and not of common use (e.g. [T1Lag5–T2Lag5]–[T1Lag8–T2Lag8] and
[T1Lag3–T2Lag3]–[T1Lag8–T2Lag8], showed near significant correlations with EBR,
r(20)=−.425, p=.062 and, r(20)=−.385, p=.094, respectively. These results exclude
the possibility that our data depend on the specific measure of AB size used.
Given that the size of the AB is predicted by individual WM
capacity (Colzato, Spapè, et al., 2007) and the known link between
WM and dopamine (Goldman-Rakic et al., 2000; Sawaguchi &
Goldman-Rakic, 1991), we predicted that AB size varies with the
that spontaneous EBR, a marker of central dopaminergic activity
(Blin et al., 1990; Karson, 1983; Kleven & Koek, 1996; Taylor et al.,
1999), reliably predicts the size of AB, indicating a possible modu-
latory role for DA in the AB.3As our participants were screened for
several psychiatric disorders, we can rule out an account in terms
of pre-existing psychiatric disorders (as schizophrenia, ADHD, and
obsessive compulsive disorder) that have been associated with
dopaminergic abnormalities (Davis et al., 1991; Pooley, Fineberg,
& Harrison, 2007; Tripp & Wickens, 2007).
Even though the correlative nature of our findings does not
directly speak to the underlying causal relations, the idea that DA
plays an important role in the AB is supported by findings from
previous behavioral studies. For example, manipulations that are
1999; Ashby, Valentin, & Turken, 2002), such as viewing pictures of
positive affective content (Olivers & Nieuwenhuis, 2006) and the
induction of happy states (Jefferies, Smilek, Eich, & Enns, 2008),
people high in WM operation span, which is associated with high
basal dopaminergic activity (Braver & Barch, 2002; Braver et al.,
1999; Hazy et al., 2006), show a smaller AB (Colzato, Spapè, et al.,
2007). Taken together, these observations support our hypothesis
that the size of the AB is modulated by dopamine.
This leaves the question of how dopamine might modulate
attentional processes. A major role of WM in general and, presum-
ably, in AB-related tasks in particular is the gating of task-relevant
do not necessarily process or store fewer items than people high in
(Vogel, McCollough, & Machizawa, 2005). In an AB task, this would
imply that individuals with lower capacity are less efficient in dis-
criminating targets from distractors, which means that distractors
are more likely to enter WM and interfere with target information.
Attentional gating is thought to result from phasic increases of DA
activity, which again is a multiplicative function of the individual
tonic DA level (Frank, 2005; O’Reilly & Frank, 2006). Given that EBR
is thought to reflect this individual tonic DA level, it makes sense to
assume that higher EBRs reflected higher tonic levels, which again
more efficient gating.
Taken together, the current observations support the idea that
the AB phenomenon is related to activity of the dopaminergic sys-
tem, presumably that of the DA/D1 subsystem. Clearly, a more
systematic investigation of this issue is necessary. Further inves-
tigations testing acute neuromodulatory effects of highly selective
D1 agonists, such as SKF 38393, on the magnitude of the AB are
necessary to determine the precise role of DA/D1 in the AB and in
temporal attention more generally.
3Given the pattern of T2 performance in high and low blinkers shown in Fig. 2,
one may speculate that high blinkers show a shallower but longer AB, that is, it may
be that at even longer lags low blinkers perform better than high blinkers. On the
one hand, this is an interesting possibility that we cannot rule out and need to leave
for further research. On the other hand, however, the numerical advantage for low
blinkers at Lag 8 was far from significance and matches the inverse advantage on T1
for high blinkers at this lag. This may suggest that performance at Lag 8 effectively
reached asymptote for both groups, who however differ slightly with regard to the
amount of attentional resources devoted to T1 and T2 processing, respectively.
L.S. Colzato et al. / Neuropsychologia 46 (2008) 3179–3183
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