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Differences between endogenous attention to spatial locations and sensory modalities


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Vibell et al. (J Cogn Neurosci 19:109–120, 2007) reported that endogenously attending to a sensory modality (vision or touch) modulated perceptual processing, in part, by the relative speeding-up of neural activation (i.e., as a result of prior entry). However, it was unclear whether it was the fine temporal discrimination required by the temporal-order judgment task that was used, or rather, the type of attentional modulation (spatial locations or sensory modalities) that was responsible for the shift in latencies that they observed. The present study used a similar experimental design to evaluate whether spatial attention would also yield similar latency effects suggestive of prior entry in the early visual P1 potentials. Intriguingly, while the results demonstrate similar neural latency shifts attributable to spatial attention, they started at a somewhat later stage than seen in Vibell et al.’s study. These differences are consistent with different neural mechanisms underlying attention to a specific sensory modality versus to a spatial location.
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Exp Brain Res (2017) 235:2983–2996
DOI 10.1007/s00221-017-5030-4
Differences betweenendogenous attention tospatial locations
andsensory modalities
J.Vibell1,2 · C.Klinge1· M.Zampini1· A.C.Nobre1· C.Spence1
Received: 20 December 2016 / Accepted: 9 July 2017 / Published online: 17 July 2017
© The Author(s) 2017. This article is an open access publication
Arguments concerning the law of prior entry, originally
formulated by Titchener a little over a century ago (Titch-
ener 1908), have, over the last 15 years or so, developed
into a debate about whether or not attention speeds-up per-
ceptual processing in comparison to relatively less attended
(or unattended) stimuli. Spence etal. (2001) revived inter-
est in this topic, highlighting a number of inconsistencies
in earlier studies of prior entry. Subsequent behavioural
studies have investigated a number of the finer mechan-
ics of prior entry (e.g., see Lester et al. 2009; Matthews
et al. 2016; McDonald etal. 2005; Miyazaki etal. 2016;
Olivers etal. 2011; Schneider and Bavelier 2003; Spence
and Parise 2010; Vibell et al. 2007; Weiss and Scharlau
2009, 2011, 2012; West etal. 2009; Yates etal. 2009, 2011;
Zampini etal. 2005; Zhuang and Papathomas 2009).
In 2005, McDonald et al. (2005) investigated the neu-
ral underpinnings of the prior-entry effect using electro-
physiological recordings. These researchers were inter-
ested in understanding the physiological mechanisms by
which attention speeds-up perceptual processing. These
researchers had their participants perform a temporal-
order judgment (TOJ) task while event-related potentials
(ERPs) were recorded. The TOJ task has, for many years,
been a favoured method for evaluating prior entry amongst
researchers. The task in the majority of studies typically
involves participants making unspeeded perceptual judg-
ments, thus allowing for the demonstration of genuinely
perceptual modulations by attention. This stands in contrast
to the more commonly reported reaction-time (RT) studies,
in which the contribution of attentional modulations occur-
ring at later cognitive and response-related stages are rather
more difficult to eliminate (e.g., Watt 1991).
Abstract Vibell et al. (J Cogn Neurosci 19:109–120,
2007) reported that endogenously attending to a sensory
modality (vision or touch) modulated perceptual process-
ing, in part, by the relative speeding-up of neural activa-
tion (i.e., as a result of prior entry). However, it was unclear
whether it was the fine temporal discrimination required by
the temporal-order judgment task that was used, or rather,
the type of attentional modulation (spatial locations or sen-
sory modalities) that was responsible for the shift in laten-
cies that they observed. The present study used a similar
experimental design to evaluate whether spatial attention
would also yield similar latency effects suggestive of prior
entry in the early visual P1 potentials. Intriguingly, while
the results demonstrate similar neural latency shifts attrib-
utable to spatial attention, they started at a somewhat later
stage than seen in Vibell etal.’s study. These differences
are consistent with different neural mechanisms underlying
attention to a specific sensory modality versus to a spatial
Keywords Prior entry· Temporal-order judgments·
Event-related potentials· Attention· Crossmodal· Visual·
Tactile· P1· N1· P2· P300
* J. Vibell
1 Department ofExperimental Psychology, University
ofOxford, Oxford, UK
2 Department ofPsychology, University ofHawaii, 2530 Dole
St, Honolulu, HI96822, USA
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2984 Exp Brain Res (2017) 235:2983–2996
1 3
The focus of a participant’s attention was manipulated
in McDonald etal.s (2005) study by means of exogenous
spatial cuing with an auditory noise burst, presented to the
left or right shortly before the presentation of two visual
stimuli, one to either side of central fixation. The visual
stimuli were presented at a variety of stimulus onset asyn-
chronies (SOAs). The results revealed that the point of
subjective simultaneity (PSS) was modulated by spatial
attention. The PSS, calculated from the pattern of perfor-
mance at different SOAs, indicating the interval at which
the left- and right-first responses would be made equally
often. In this case, the left visual stimulus had to be pre-
sented relatively earlier in time when the spatially-non-pre-
dictive auditory cue was presented on the right than when it
was presented on the left. Electrophysiological recordings
revealed that this effect was indeed accompanied by a neu-
ral modulation taking place as early as the early extrastriate
analysis of the visual stimuli, as reflected by the P1 poten-
tial (see also McDonald etal. 2013; Störmer etal. 2009).
The underlying mechanism, however, demonstrated no
significant speeding-up of the latency of the sensory brain
potentials, but rather an increase in the amplitude of the
early visual brain potentials. An enhanced positivity con-
tralateral to the cued visual target starting in the P1 interval
and lasting for ~100ms appeared to lead to the perceived
shifts in temporal order. McDonald et al. did not see a
speeding-up of the neural processes underlying perceptual
processing itself, as might have been inferred from the law
of prior entry. That said, it is uncertain whether McDon-
ald et al.’s results actually reflect an enhancement of per-
ceptual processing by attention or a second-order response
bias [note that the same argument can be applied to Vibell
etal.’s (2007), study too], the early effect suggests that the
effect is attentional as discussed in their study. In second-
order response-biases participants simply use attentional
instruction to guide their selection of appropriate response
once the two stimuli have been presented. Santangelo and
Spence (2008) argued that the TOJ effects that have been
documented to date could be attributable to cue-induced
response bias. However, the crossmodal cuing of visual
stimuli ruled out that these effects could stem from lower
level intramodal processes and suggest they occur by way
of a supramodal attention system, or inter-modal connectiv-
ity, instead (Störmer etal. 2009).
The shift in amplitudes at the perceptual stages of
information processing fits well with the extant literature
on both endogenous and exogenous spatial attention. At
these stages, spatial attention is thought to operate by
means of sensory gating or gain modulation (Eimer 1994;
Hillyard et al. 1998; McDonald et al. 2005; Näätänen
1986), whereby the processing of relevant, attended
stimuli is boosted relative to the processing of irrelevant
stimuli starting from early stages of information process-
ing. Both the enhancement of neuronal activity related to
attended stimuli and the attenuation of neuronal activity
associated with ignored stimuli may contribute to sen-
sory gating and gain control (Anllo-Vento et al. 2004;
Eimer 1994; Hillyard etal. 1998; Mangun and Hillyard
1991; Tünnermann et al. 2015). Attentional modulation
through gating or control of the amount of neural activity
has been considered a ubiquitous mechanism, though it
should be noted that support for such a claim has come
primarily from those studies in which attention has been
manipulated in the spatial domain (Hillyard etal. 1998).
Vibell etal. (2007) conducted an ERP study that high-
lighted the possibility that prior entry can be expressed
during early perceptual processing, at least when a par-
ticipant’s attention is endogenously directed to a specific
sensory modality rather than to a particular spatial loca-
tion. Using a crossmodal TOJ paradigm based on earlier
psychophysical studies reported by Spence etal. (2001),
the participants’ attention was directed to either vision or
touch, while they responded orthogonally to which side
stimuli appeared first. Latency shifts of visual potentials
were observed, with processing occurring earlier when
the visual stimuli were attended as compared to when
they were relatively ignored. Latencies were shifted by
3–4ms in terms of the perceptual P1 and N1 potentials
and by 15 ms in the cognitive P3 potential. PSSs have
been shown to correlate with the P1 and N1 latency (e.g.,
Boenke etal. 2012), but the latencies of early potentials
do not appear to shift in line with attention. Comparing
Vibell et al.’s results with those from McDonald et al.
(2005) highlighted the possibility that the neural mech-
anism underlying prior entry might depend on the type
of attention being manipulated (i.e., attention to a spatial
versus attention to a sensory modality). They suggest that
a somewhat different mechanism than sensory gating may
be at work. The results of Vibell etal.’s study, therefore,
raises the intriguing possibility that attention to a sensory
modality and attention to a location in space may involve
different underlying neural mechanisms, at least under
those conditions in which participants have to make fine
temporal discrimination responses, such as those required
in TOJ tasks.
It is important to note, though, that a concern has been
raised about the most appropriate interpretation of Vibell
et al.’s (2007) findings by Keetels and Vroomen (2012,
p. 152) and McDonald etal. (2012, p. 516). Keetels and
Vroomen noted that “the 4-ms shift in the ERP is in a
quite different order of magnitude than the 38-ms shift
of the PSS in the behavioural data, or the 133-ms shift
reported by Spence et al. (2001)”. This concern was a
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2985Exp Brain Res (2017) 235:2983–2996
1 3
common concern addressed in the original paper (Vibell
et al. 2007), where the reasons as to why latencies in
ERP potentials are smaller than correlated shift in behav-
ior were discussed1 (see also Tünnermann and Scharlau
Over the years, several researchers have tried to compare
the effects of attention to spatial locations versus attention
to sensory modalities on neural activity, but differences
in experimental design make direct comparisons difficult
(de Ruiter etal. 1998; Eimer and Schröger 1998; Hotting
et al. 2003; Talsma and Kok 2001, 2002; Teder-Sälejärvi
etal. 1999; Woods etal. 1992, 1993). Several of the experi-
ments mentioned above (De Ruiter etal. 1998; Talsma and
Kok 2001, 2002; Woods etal. 1992, 1993) failed to present
the stimuli from different modalities from the same spatial
location (e.g., auditory stimuli were typically presented
over headphones, while the visual stimuli were presented
on a computer screen). This is an important caveat, because
it may potentially have biased the whole process of spatial
attention between modalities (see Spence and Driver 1997;
Spence etal. 2004, on this point). The different spatial loca-
tions might serve as additional cues for attention, so these
results should be interpreted with some degree of caution.
Meanwhile, the other studies (Hötting etal. 2003; Teder-
Sälejärvi etal. 1999) all required their participants’ atten-
tion to be focused on a specific sensory modality at a spe-
cific location in the same way as in Eimer and Schröger’s
(1998) earlier study.
Those studies that have controlled the locations from
which the stimuli have been presented have not investigated
the effects of attention to a modality in isolation from the
effects of attention to spatial location. Eimer and Schröger
(1998) tried to distinguish spatial from sensory attention by
directing participants’ attention to sensory modalities and
indicating spatial locations by a cue. Similar approaches
have also been adopted by other researchers, where atten-
tion has been directed to non-spatial dimensions such as to
the features and objects (Anllo-Vento and Hillyard 1996;
Eimer 1997; Hillyard and Munte 1984; Hopf etal. 2004;
Valdes-Sosa et al. 1998). Therefore, the possibility that
attention to a sensory modality, if it can be separated from
attention being directed to its intrinsic spatial location,
might involve different neural mechanisms has not yet been
satisfactorily explored. Indeed, McDonald etal. (2012, p.
516) point out that: “it is tempting to speculate that vol-
untary modality-based attentional selection influences the
timing of early visual activity, whereas involuntary loca-
tion-based attentional selection influences the gain of early
visual activity”.
Another possible explanation for the latency shifts in
perceptual potentials observed in the TOJ experiment
reported by Vibell etal. (2007), when the attention of par-
ticipants was directed to a sensory modality, was a com-
bination of two factors. The requirement for participants
to make perceptually difficult temporal discriminations
in combination with a task that was sensitive to specific
attentional manipulations could have caused the latency
shifts. Earlier studies have shown ERP latency shifts when
attention is oriented to a specific point in time using both
peripheral (Griffin et al. 2002) and foveal stimuli (Mini-
ussi etal. 1999). However, none of these previous studies
revealed any effect on early perceptual analysis (P1) as a
function of temporal attention. Instead, the modulation
was of later potentials (P3) thought to be more involved in
decisional and response-related processes. These previous
temporal-orienting studies, however, did not require their
participants to make any fine-grained temporal judgments.
Hence, we thought it possible that it might be the combina-
tion of the strong perceptual demands during the TOJ task,
its reliance on temporal processing, and the fact that atten-
tion was directed to a specific sensory modality that were
together responsible for the early modulations of latencies
observed by Vibell etal.
The early latency shifts reported by Vibell etal. (2007)
might be attributable to the paradigm differing in a few
other specific ways from the previous TOJ study reported
by McDonald et al. (2005). First, attention was directed
toward one sensory modality (touch or vision) on both
sides of fixation (i.e., attention was divided spatially, or at
least not focused on a specific spatial location). Directing
attention to one sensory modality irrespective of which side
the cues and target stimuli are presented from could have
the advantage that the main focus of attention is on sensory
perception per se (as opposed to its inherent spatial com-
ponent) and not as much on the location that is inherently
linked with the sensory perception. In McDonald et al.’s
study, attention was directed by a non-predictive auditory
cue, but it was presented at a specific location. In the cur-
rent study and in Vibell etal. (2007), attention was directed
to touch and vision irrespective of location. Second, atten-
tion was oriented in a sustained fashion by presenting a
higher percentage of stimuli in the attended modality and
1 These include increasing latency shifts between cortical poten-
tials and the various stages from perception to response. McDonald
et al. (2012, p. 516) suggested that the results of “a single partici-
pant with an implausibly large latency difference could have biased
results”. However, statistical analysis would not allow a single partici-
pant to create a significant result. This conclusion was verified with
a second analysis using Cartool (Michel Lab, University of Geneva,
Switzerland). Their last concern regarded overlap with tactile poten-
tials: Since, vision was presented an average of 60ms before touch to
account for different rates of perception between the sensory modali-
ties, it is unlikely that tactile potentials would influence the early vis-
ual potentials. Conversely, visual potentials presented 60ms earlier
would most certainly influence tactile potentials and were therefore
not analyzed.
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2986 Exp Brain Res (2017) 235:2983–2996
1 3
by verbal instruction given by the experimenter. Prior work
has shown more effective attentional orienting with sus-
tained rather than transient attention, resulting in both peak
latency shifts (Eimer and Forster 2003) amplitude modula-
tions (see Eimer 1996).
The main aim of the present study was, therefore, to
apply the same design as the study by Vibell etal. (2007) to
test whether equivalent behavioural and neural prior-entry
effects would occur with endogenous spatial attention. To
maintain orthogonal attention and response dimensions,
the participants responded to the modality of the target
stimulus that occurred first, while attention was directed
to spatial locations (either to the left or right). This design
enabled us to compare results to our earlier findings using
exactly the same stimulation parameters, but with spatial
attention being manipulated instead of attention to a spe-
cific sensory modality. Of particular interest, here was the
question of whether sustained spatial attention in the TOJ
task would induce changes in relative latency or amplitude
modulations of early potentials or both. The former would
suggest that the parameters of the study rather than the
dimension along which attention is varied accounts for the
prior-entry effect. The latter would be more consistent with
McDonald etal.’s (2005) findings, and suggest instead that
the behavioural enhancements conferred by spatial atten-
tion and by attention to sensory modalities are brought
about by different underlying modulatory mechanisms
despite giving rise to similar behavioural effects.
Fifteen participants were recruited from the academic com-
munity of students and postdoctoral fellows at the Univer-
sity of Oxford. ERP data from one participant were very
noisy and were, therefore, excluded. Analyses of the behav-
ioural and electrophysiological data were carried out on the
same group of 14 participants (10 males and 4 females, 13
right-handed, and 1 left-handed, ages ranging between 19
and 29years). The participants received £20 remuneration
for their participation in this study. All of the participants
had normal tactile sensitivity and normal or corrected-to-
normal vision by self-report. Each recording sessions lasted
for about 2h including electrode setup and breaks.
Apparatus andmaterials
The experiment took place in a dark, electrically shielded,
and sound-attenuated testing booth. Two tactile and two
visual stimulators were triggered by Presentation 05 (Neu-
robehavioural Systems, Albany, California, version v 0.8)
together with a custom-built interface box that was con-
nected to the parallel port of the task-presentation com-
puter. The visual and tactile stimuli were delivered to the
dorsal medial phalynxes of the index fingers (or in close
proximity). The visual and tactile stimuli both consisted of
very brief 10-ms pulses as measured by a light sensor or
a microphone. The visual stimuli consisted of the illumi-
nation of a red light-emitting diode (LED). Tactile stimu-
lation consisted of taps by small plastic rods that were
moved by means of small solenoids. The tactile stimulators
(Heijo Research Electronics, London, UK) were suspended
by adjustable rods against the participant’s fingertips, and
weights were used to maintain a constant pressure against
the skin surface. The participants’ hands were placed in a
stable position within a specially made hand-shaped cast.
A permanently illuminated central fixation point, con-
sisting of a red LED, was placed 42cm directly in front
of the participant. The participants’ hands, and associated
LEDs and tactile stimulators, were placed one to either side
of the fixation point, at a visual angle of 20° below fixa-
tion. To mask any sounds associated with the operation of
the tactile stimulators, white noise (65 dB) was delivered
centrally and earplugs (LaserLite®, San Diego California;
noise reduction rate 32 dB) were worn. The participants
were instructed to perform the experiment without mov-
ing their eyes. Furthermore, eye movements were moni-
tored with an ISCAN® ETL-400 eye tracker. Participants
responded by lifting their feet off of the footpedals placed
under their left and right foot.
Design andprocedure
Two peripheral stimuli were presented for 10ms, separated
by a variable stimulus onset asynchrony (SOA). The partic-
ipants were instructed to determine whether the first stimu-
lus was visual or tactile, and responded by lifting their toes
off of the footpedal on the specified side (left pedal—touch,
right pedal—vision, and vice versa for counterbalancing).
Two types of trials were presented. Bilateral trials consisted
of one stimulus being presented in each spatial location
(left and right), and unilateral trials consisted of two stimuli
being presented sequentially from the same spatial location
(left or right).
The participants were introduced to the experiment by
means of a written description and a brief practice ses-
sion. They then completed 20 experimental blocks of tri-
als. These were divided into two spatial-attention condi-
tions, where attention was biased to stimuli presented in
the left or right external hemispace. The order of presenta-
tion of the attention conditions was counterbalanced across
participants. A short break was introduced between each
block of trials within each condition, and a longer break
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2987Exp Brain Res (2017) 235:2983–2996
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was allowed between the two attention conditions to ensure
maximal alertness on the part of the participants.
In the two conditions, attention was biased either toward
the left or the right side of space by means of verbal
instruction by the experimenter, and by including a higher
frequency of stimuli at that location. In each condition,
two-thirds of the trials were bilateral, while one-third were
unilateral (i.e., containing only stimuli at the “attended”
location; see Table1 for details). Unilateral trials consisted
of visual flashes and tactile taps separated by one of five
SOAs centered on zero: 0, ±35, and ±150ms in a simi-
lar manner to that reported in an earlier study (Vibell etal.
2007). Bilateral trials in the present study SOAs were cen-
tered on the PSSs, which had been established in a separate
behavioural experiment in Vibell etal.’s (2007) study. The
SOAs used were: −90 (tactile precedes visual), 25, 60, 95,
and 210ms. Unilateral and bilateral trials, with visual and
tactile leading stimuli, at each SOA, were randomly inter-
mixed, and appeared in an unpredictable order.
There were ten blocks of trials per condition (attend
left and attend right) with each block lasting for approxi-
mately 2–3min. Each block contained 60 trials giving rise
to a total of 600 trials in each attention condition. There
were 400 bilateral trials, divided equally into left-first and
right-first trials, but with a greater proportion of trials being
presented at the middle three SOAs (100 trials each) as
compared to the two SOAs furthest away from objective
simultaneity (50 trials each). This translated into 50 vision-
first trials and 50 touch-first at the 25-, 60-, and 95-ms
SOAs; and 25 vision-first trials and 25 touch-first trials at
the −90 and 210-ms SOAs. The 200 unilateral trials used a
similarly-proportioned distribution of trials: 50 trials with
simultaneously-delivered visual and tactile stimuli (0-ms
SOA); 100 trials with equally distributed vision-first and
touch-first stimuli at 35-ms SOA; and 50 trials with vision-
first and touch-first stimuli at the 150-ms SOA.
Each trial started with the presentation of two stimuli,
one in each sensory modality. Participants then responded
according to the modality of the stimulus that they thought
occurred first. They were told that the accuracy of their
responses was more important than the speed, but that they
should nevertheless respond as rapidly as they could. The
next trial did not start until a response had been made and
a random intertrial interval between 1500 and 2000ms had
The percentages of bilateral trials in which participants
judged that the left/right stimulus was presented first at
each SOA were computed, and subsequently normalized
into Z-scores (see Spence et al. 2001). The PSS for each
participant was calculated by fitting the best-fitting straight
line through the Z-scores across the five SOAs (−90 to
210 ms), and interpolating the value of 50/50 responses
(see Cohen etal. 1999). These values were analyzed using a
two-way repeated-measures analysis of variance (ANOVA)
with the factors of attention (attend and ignore) and side
of stimulation (left and right) or in the bilateral conditions
with the factors of attention (attend and ignore) and type of
stimulation (unilateral and bilateral).
ERP recordings
EEG was recorded with Ag–AgCl electrodes from 34 scalp
electrodes (Easy Cap, Herrsching-Breitbrunn, Germany;
NuAmps digital amplifiers, Neuroscan, El Paso, Texas).
Additional electrodes served as ground (AFZ), reference,
and electrooculogram (EOG) channels. During recordings,
the right mastoid (A2) was used as the active reference.
Subsequently, the data were re-referenced offline to the
digital average of both mastoids [(A1+A2)/2]. Electrode
impedance was kept below 5 kΩ. The horizontal EOG
(HEOG) was recorded from the outer canthi of both eyes,
and the vertical EOG (VEOG) was recorded from below
and above the right eye. All recordings were sampled with
an A/D rate of 500 Hz and subsequently filtered with a
40-Hz low-pass filter (DC-40Hz).
As in Vibell etal.’s (2007) study, the present experiment
was designed to analyze ERPs elicited by visual stimuli
only. Because of the smaller amplitudes of potentials asso-
ciated with vibrotactile as compared to visual stimuli, and
because of the risk of contamination of the tactile poten-
tials by the potentials evoked by preceding visual stimuli
at most SOAs, analysis of tactile ERPs was not carried out.
Furthermore, only bilateral trials were of interest. Trials
with unilateral stimulation were only included in the exper-
imental design to manipulate spatial attention and hence
were not included in the ERP analysis.
Table 1 Number of trials for the five different SOAs (negative SOAs indicate that the tactile stimulus was presented before the visual), for both
unilateral and bilateral trials separated by attention condition
All values in milliseconds
SOA (ms) Attend left Attend right
−90 25 60 95 210 −90 25 60 95 210
Bilateral VT and TV 50 100 100 100 50 50 100 100 100 50
Unilateral VT and TV 25 50 50 50 25 25 50 50 50 25
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2988 Exp Brain Res (2017) 235:2983–2996
1 3
EEG and EOG analysis was performed offline using
Scan 4.3 (Neuroscan, El Paso). The raw data were epoched
into periods starting 200ms prior to the onset of the visual
stimulus and continuing until 822-ms post-stimulus onset.
The ERPs were measured with the pre-stimulus interval as
a baseline. Trials including eye blinks or large eye move-
ments, measured as large voltage deflections on the HEOG
or VEOG channels (±50µV), were automatically removed.
In addition, epochs containing potentials above ±150µV in
any channel were also removed to avoid large drifts in the
signal. Epochs were also inspected visually to ensure that
all eye movements, drift, or excessive alpha activity had
been eliminated.2 After artifact rejection, ERPs for visual
stimuli in each attention condition, side, and SOA consisted
of an average of 33 trials for the three middle conditions
and 17 trials for the two extreme SOA conditions. When
stimulus side and SOA were collapsed (see below), the
average number of trials was 266, ranging between 172 and
359 across participants.
To test for the effects of spatial attention on brain activ-
ity elicited by visual stimuli in this TOJ task, the potentials
elicited by visual stimuli were analyzed at the electrodes
and time periods, where they were most pronounced.
This approach is the same as that followed by Vibell etal.
(2007), and, therefore, facilitates comparisons across the
two studies. To measure any modulations in the amplitude
of brain activity, mean amplitudes were obtained around
the average time for identifiable potentials to peak across
participants. Mean amplitudes were measured over a nar-
row band around the average peak latency of the poten-
tial to minimize the possible contribution of brain activity
related to other overlapping brain potentials. To measure
the timing of brain activity over successive stages of infor-
mation processing, the peak latencies for identifiable poten-
tials were measured and compared. Peak latencies were
identified by a simple automated computer algorithm,
which defined the absolute maximum or minimum volt-
age value for positive or negative potentials within a tem-
poral window, respectively. The temporal windows used to
identify these peak latencies were enlarged relative to those
used in mean-amplitude measures, to accommodate the
variability in the timing of potential peaks across partici-
pants. The results were subsequently inspected visually to
ensure that the automated algorithm was functioning prop-
erly and that the measurements were not contaminated by
excessive noise or drift.
Mean amplitudes and peak latencies of the first identifi-
able visual potential P1 were analyzed at electrodes O1/2,
PO3/4, and PO7/8 between 100 and 200ms (latencies) and
140 and 160ms (amplitudes). The later visual N1, P2, and
N2 potentials were analyzed at electrodes O1/2, PO3/4,
PO7/8, P3/4, and P7/8 in the following ranges for latencies:
150–250ms (N1), 200–300ms (P2), and 250–350ms (N2)
and in the following ranges for amplitudes: 180–220 ms
(N1), 240–360ms (P2), and 280–300ms (N2). The late P3
potential was identified and analyzed at electrodes C3/Z/4,
CP3/Z/4, and P3/Z/4; between 300 and 600ms for latencies
and between 350 and 450 ms for amplitudes. The effects
of the attentional manipulation upon the mean amplitude
and latency of the potentials were assessed using repeated-
measures ANOVAs, testing for the factors of attention
(left and right), stimulus side (left and right), SOA (−90,
25, 60, 95, and 210 ms), scalp hemisphere (contralateral,
ipsilateral, and midline where relevant), and electrode loca-
tion. To control for possible violations of sphericity, Green-
house–Geisser adjustments were applied to the degrees of
freedom where necessary.
Main effects and interactions including the attentional
manipulation were the main interest. Latency shifts from
attention were considered as evidence of prior entry. To
center the SOAs on the PSS, vision was presented an aver-
age of 60 ms before touch. Therefore, we only looked at
visual potentials as tactile potentials were too contami-
nated by the earlier presented visual stimulation. To rule
out any influence of possible overlap from tactile potentials
upon the latency measures of visual potentials at any given
SOA, only effects that did not interact with the SOA fac-
tor were considered as indicators of prior entry. Attention
effects that did not interact with the SOA factor were fol-
lowed up by a simpler analysis, which maximized signal to
noise. Since neither side nor SOA interacted with attention,
ERPs elicited by the left and right stimuli at each of the five
SOAs were combined using weighted averaging accord-
ing to the number of trials in each condition. ERPs from
left- and right-side stimulation were combined in a way that
preserved their position relative to the stimulus location
(contralateral versus ipsilateral). Electrodes were renamed
as contralateral or ipsilateral to the stimuli for averaging
(Fig.1). To be consistent with Vibell etal. (2007), the data
were visualized using the Cartool software by Denis Brunet
A two-way repeated-measures ANOVA with attention
and side as factors showed that attending to a location
significantly shifted the PSS [F(1,13) = 28.2, p < 0.001,
η2=2.17]. For visual and tactile stimuli to be perceived as
simultaneous, the visual stimuli would have had to precede
the tactile stimuli by 48ms when the location, where the
visual stimulus was presented, had been attended, and by
2 Because of the subjective nature of TOJs, it was not possible to
remove trials according to behavioral errors.
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2989Exp Brain Res (2017) 235:2983–2996
1 3
76ms when the location of the visual stimulus was ignored/
unattended according to the mean PSSs (see Fig.2). This
constituted a shift in the PSS of 28 ms by attention. This
prior-entry effect was confirmed by post hoc follow-up
analysis using t tests [t(1,13)=−5.3, p<0.001]. Neither a
significant main effect of stimulus side nor any interaction
was observed (all Fs<0.5). Although non-significant, dif-
ferences for attended versus ignored stimuli on the left side
(36ms) were somewhat larger than the differences observed
on the right side (21ms), again in line with Spence etal.’s
(2001, Experiments 3 and 4) previous psychophysical find-
ings. The difference in just noticeable differences (JNDs)
between unimodal and bimodal stimulus pairs when the
location of the visual stimulus was attended as compared
to when it was ignored was not significant, nor were there
any effects for side or interactions (all Fs<0.5). JNDs of
65ms when the location of the stimuli was attended and of
67ms when it was ignored indicated similar difficulties in
the detection of the stimuli.
A follow-up comparison was made between the present
set of data and the results when the attention of participants
was directed to a particular sensory modality (i.e., vision or
touch; see Vibell etal. 2007). The two studies were com-
pared using a mixed-effects ANOVA comparing the PSSs
Fig. 1 Prior-entry effect. Effects of spatial attention on the mean
PSS, the amount of time by which the visual stimulus had to lead the
tactile stimulus in order for the two to be perceived as simultaneous.
Asterisks indicate a significant difference (p< 0.001, two-way t test)
that was observed between the attention conditions. Error bars indi-
cate the standard error of the means
Fig. 2 Early ERP amplitude and latency modulations. Significant amplitude effects were observed for the P1, while the N1, P2, and N2 showed
significant attention effects for both amplitudes and latencies
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2990 Exp Brain Res (2017) 235:2983–2996
1 3
across the between-participants factor of Attended Dimen-
sion (modality versus space), and the within-participants
factors of attention (attended and ignored), and side (left
and right). The ANOVA revealed a significant main effect
of attention [F(1,13)=33.91, p<0.001, η2=2.61], but no
interactions involving the attended dimension factor or any
of the other factors [all F’s<1]. These results demonstrate
that there were no significant differences in the magnitude
of the prior-entry effects reported psychophysically in the
two studies (28 versus 38ms) nor were there any effects of
side of stimulation.
ERP effects
The ERP data from one participant contained an excessive
degree of noise and were excluded from analysis (a total
of 43 trials as compared to between 172 and 359 for the
rest of the participants). For the remaining participants,
visual stimuli within bimodal trials elicited small visual
P1, and clear N1, P2, N2, and late P3 potentials. Visual
potentials had a characteristic lateral posterior distribution,
and because of the dim and very peripheral nature of the
stimulation used (e.g. Störmer et al. 2009; Tünnermann
and Scharlau 2016; Akyürek and de Jong 2017), occurred
relatively late in this task (see Fig. 3). The P1 potential
was largest over PO3/4, PO7/8, and O1/2 electrodes and
showed an unusual ipsilateral predominance. The N1, P2,
and N2 had a slightly broader lateral posterior distribution,
over electrodes O1/2, PO3/4, PO7/8, P3/4, and P7/8. The
P3 potential had a broad distribution, which was maximal
over the central–parietal region of the scalp over electrodes
C3/Z/4, CP3/Z/4, and P3/Z/4.
Peak latencies
Shifts in peak latencies were observed for late potentials
(P2, N2, and P3), but not for the early P1 and N1 poten-
tials. The peak latency of the P1 potential failed to show
any effects of stimulus side or SOA, nor did any of these
factors interact with attention (all p’s>0.11). Accordingly,
the stimulus side and SOA factors were collapsed, and a
simpler P1 analysis confirmed the lack of attentional effects
on the latency of the P1 potential.
We did not see attentional effects for the N1 potential
including between attention, electrode, and hemisphere
[F(4,52) = 2.51, p = 0.053, η2= 0.19]. A main effect
Fig. 3 Late ERP amplitude and latency modulations. Waveforms for the attended stimuli (solid lines) showed significant differences from the
waveforms for ignored stimuli (dashed lines) for amplitudes at P2, N2, and P3 and for latencies at P2 and P3
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2991Exp Brain Res (2017) 235:2983–2996
1 3
for SOA revealed differences between N1 peak latencies
across SOA conditions, with the latencies being gener-
ally longer in the 60-ms SOA condition and becoming
progressively shorter toward the extreme SOA values
[F(2.55,33.12)=10.40, p<0.001, η2=0.80]. A signifi-
cant three-way interaction between SOA, stimulus side,
and hemisphere [F(4,52)=4.38, p<0.05, η2=0.34] fur-
ther qualified these effects by demonstrating earlier peaks
for the earliest SOA contralaterally when the stimuli were
presented on the left side. Since we did not observe inter-
actions between attention and SOA, the stimuli were col-
lapsed over SOA and we performed a post hoc analysis.
The results again failed to show a significant interaction
between attention, electrode, and hemisphere. The inter-
action between attention and stimulus side also failed to
show stronger attentional effects for the right stimulus
side [F(1,13)=3.32, p=0.092, η2=0.26].
Attentional effects on latency became reliable for
the P2 potential, where a main effect of attention was
observed [F(1,13)=6.43, p<0.05, η2=0.49]. Attending
to the relevant spatial location resulted in a shift of the P2
peak 6ms earlier from 259 to 253ms. The latency shifts
were qualified by a complex four-way interaction between
attention, stimulus side, electrode, and hemisphere sug-
gesting that latencies are significantly earlier for attended
stimuli from the left side over the right occipital hemi-
sphere [F(4,52)=3.55, p< 0.05, η2=0.27]. However,
no interaction occurred between the factors of attention
and SOA, thus suggesting that the change in P2 latency
could not be attributed to a differential temporal overlap
between components. A post hoc follow-up analysis sim-
ilar to Vibell etal. (2007) with the data collapsed over
SOA confirmed the main effect of attention, as well as
the four-way interaction between attention, stimulus side,
electrode, and hemisphere.
Significant latency shifts attributable to attention
were also observed in the N2 potentials, but these inter-
acted with the SOA factor and, therefore, could not be
unambiguously attributed to prior entry. An interaction
between attention, SOA, and electrode [F(16,208)=1.73,
p < 0.05, η2 = 0.13] revealed that latency shifts were
particularly pronounced over P3/4 and P7/8 electrodes
for the 60- and 95-ms SOAs (3–11 ms). An additional
significant interaction between attention, stimulus side,
and electrode showed that the strongest latency shifts
occurred when the stimuli were presented on the right
side [F(4,52)=3.36, p<0.05, η2=0.26]. There was also
a four-way interaction between SOA, attention, stimulus
side, and electrode showing that attentional effects were
strongest for the P3/4 and P7/8 electrodes for the 50- and
85-ms SOAs when stimuli were presented on the right
side [F(16,208)=1.96, p<0.05, η2=0.15].
The P3 potential showed longer latencies for attended
stimuli than for ignored stimuli over midline and right-sided
electrodes (12–17ms; see Fig.3), as revealed by the inter-
action between attention and hemisphere [F(2,26)= 9.44,
p=0.001, η2=0.73]. The midline attentional effects were
supported by a four-way interaction between attention,
SOA, hemisphere, and electrode, with these effects being
more pronounced over the central electrodes at the −90-ms
SOA. The interaction over central electrodes at −90ms, on
those trials, where touch was presented before vision, indi-
cated that the attentional effects might also interact with the
tactile stimulation. A statistical trend toward an interaction
between attention, stimulus side, electrode, and hemisphere
revealed a complex pattern of P3 latency modulation, with
ignored stimuli eliciting a slightly earlier P3, particularly
over the contralateral central and centro-parietal regions
[F(4,52)=2.48, p=0.06, η2=0.19].
A Pearson’s correlation analysis tested whether there
was a linear relationship between the early attentional dif-
ferences in the peak latencies and the PSS values obtained
behaviourally. No correlations were observed between the
differences in visual peak latencies and the differences in
PSSs (all r<0.389).
Mean amplitudes
The mean amplitude of the P1 potential was modulated
by attention, but in a way that interacted with the SOA.
A significant interaction between attention and SOA
[F(4,52) = 2.95, p < 0.05, η2 = 0.23] indicated that the
modulations were particularly strong at the more extreme
SOAs. No interactions between SOA, attention, and stim-
ulus side [F(2.19,28.42) = 2.41, p = 0.061, η2 = 0.19];
and between SOA, attention stimulus side, and electrode
[F(2.91,37.82)=4.77, p=0.055, η2=0.37], were observed
when the stimuli came from the left and especially at the
PO7/8 electrodes. Interactions involving SOA revealed
some differences between the intervals with strong activa-
tions in the −90-ms SOA for all electrodes except the O1/2
and PO7/8 electrodes as indicated by a significant interac-
tion between SOA and electrode [F(2.40,31.13) = 3.24,
p < 0.05, η2 = 0.25]. Different effects between SOAs
were further qualified by significant interactions between
SOA, stimulus side, and hemisphere [F(4,52) = 2.95,
p<0.05, η2= 0.23] and SOA, electrode, and hemisphere
[F(5.04,65.46)=5.17, p<0.001, η2=0.40]. This revealed
particularly strong activations for the 25- and 210-ms SOAs
when the stimuli were presented from the left over the PO4
and PO8 electrodes.
Attention effects were also observed for the N1 potential.
A significant interaction between attention and electrode,
indicated that these were differentially distributed over the
lateral posterior electrodes, being more pronounced over
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2992 Exp Brain Res (2017) 235:2983–2996
1 3
PO7/8 and P7/8 [F(1.56,20.22)=2.42, p<0.05, η2=0.19].
The N1 amplitude modulation by attention also interacted
with SOA. The N1 showed attentional interactions between
SOA, attention, and stimulus side [F(3.26,42.35) = 4.52,
p < 0.05, η2 = 0.35], as well as a four-way interaction
between SOA, attention, stimulus side, and electrode
[F(3.51,45.68)=2.74, p<0.05, η2=0.21]. Here, the three
middle SOAs (25, 60, and 95ms) revealed stronger atten-
tional effects particularly for those stimuli presented on the
right side. A main effect of SOA on the mean amplitude
of the N1 was also documented [F(2.14,27.85) = 7.96,
p < 0.001, η2=0.61], with the N1 in the −90-ms SOA
condition differing most from those at the other SOAs.
This was further supported by interactions between SOA
and electrode [F(3.93,51.14)= 7.02, p<0.05, η2 =0.54];
SOA, stimulus side, and electrode [F(4.58,59.51)=1.89,
p< 0.05, η2 =0.15]; SOA, stimulus side, and hemisphere
[F(2.59,33.73) = 2.86, p <0.05, η2=0.22]; SOA, elec-
trode, and hemisphere [F(5.14,66.75) = 5.48, p < 0.001,
η2 =0.42]; and SOA, stimulus side, electrode, and hemi-
sphere [F(3.72,48.34) = 1.91, p<0.05, η2 = 0.15]. The
effects of SOA were particularly pronounced for stimuli
presented on the left over the PO8 electrode.
Just as for the earlier potentials, the mean amplitude
of the P2 was enhanced by attention. This enhancement
was particularly pronounced over the left hemisphere
[F(1,13) =4.84, p< 0.05, η2 =0.37] and was expressed
in all electrode pairs except the P7/8 [F(1.9,24.1)= 3.82,
p < 0.05, η2 = 0.30]. In addition, a three-way inter-
action between attention, electrode, and hemisphere
[F(1.9,24.0) = 2.26, p< 0.05, η2 = 0.18] was observed,
showing that these attentional effects were more pro-
nounced over the right hemisphere. However, the ampli-
tude modulations also interacted with the SOA con-
dition in complex ways. There was a trend toward an
interaction between SOA, attention, and stimulus side
[F(2.5,32.0)=2.29, p=0.072, η2=0.18], and a significant
interaction between SOA, attention, stimulus side, and elec-
trode [F(1,13)=4.87, p<0.05, η2=0.37]. This indicated
that stimuli from the left in the 210-ms SOA over the PO3/4
electrodes elicited particularly strong amplitudes. In addi-
tion, a main effect for SOA indicated that the P2 potentials
were larger over the extreme SOAs [F(1.9,25.0) = 3.91,
p < 0.05, η2=0.30]. The effect of SOA interacted with
several variables other than attention in a complex man-
ner. Interactions were observed between SOA and hemi-
sphere [F(2.61,33.90)=3.40, p < 0.05, η2= 0.26]; SOA
and electrode [F(4.60,59.81)=6.23, p<0.001, η2=0.48];
SOA, stimulus side, and electrode [F(4.82,62.61)=2.00,
p< 0.05, η2=0.15]; and SOA, electrode, and hemisphere
[F(5.31,69.02)=2.65, p=0.001, η2=0.20]. Overall, the
P2 was larger for the 95-ms SOA, particularly over the PO4
Attention once again enhanced the amplitude of the
N2 potential over selected electrodes, but the effects fur-
ther interacted with the SOA condition. An interaction
between attention stimulus side, electrode, and hemisphere
[F(2.4,30.9)=2.58, p<0.05, η2=0.20] revealed enhance-
ments of the N2 by attention, particularly for right visual-
field stimuli, over the PO3/4 and P3/4 electrodes. The influ-
ence of SOA upon the attention effects was highlighted by
significant interactions between SOA, attention, and stimu-
lus side [F(4,52)= 5.85, p=0.001, η2=0.45]; and SOA,
attention, stimulus side, and electrode [F(4.6,60.0)=2.58,
p = 0.001, η2 = 0.20]. Attentional effects on N2 were
largest for right-sided stimuli at the 25-ms SOA, particu-
larly over the P3/4 and PO3/4 electrodes. Effects of SOA
that did not interact with attention were also obtained.
There was, for instance, a significant main effect of SOA
[F(2.1,27.4)=11.33, p<0.001, η2=0.87]; as well as inter-
actions between SOA and electrode [F(2.2,28.5) = 4.28,
p< 0.05, η2 =0.33]; SOA, stimulus side, and hemisphere
[F(2.2,28.5)= 4.28, p<0.05, η2=0.33]; SOA, electrode,
and hemisphere [F(2.2,28.5)= 4.28, p<0.05, η2=0.33];
and SOA, stimulus side, electrode, and hemisphere
[F(2.2,28.5)= 4.28, p<0.05, η2=0.33]. Overall, the N2
potential was largest over the PO3/4 and P3/4 for all SOAs
except the −90 SOA, particularly in the left hemisphere
when stimuli were presented on the right side.
Analysis of the P3 revealed a significant main effect
for attention [F(1,13) = 5.63, p < 0.05, η2 = 0.43].
Attended stimuli elicited a significantly smaller P3 overall
(see Fig. 3). However, the pattern of P3 modulation dif-
fered over the different regions of the scalp. Interactions
between attention and hemisphere [F(1.2,15.7) = 3.51,
p<0.05, η2= 0.27]; and between attention and electrode
[F(1.0,13.5) = 5.87, p<0.05, η2= 0.43], indicated that
the attenuation of the P3 occurred mainly over midline
and right-hemisphere electrodes over parietal regions.
SOA again influenced these attention-related effects.
Interactions occurred between SOA, attention, and stimu-
lus side [F(2.9,37.7) = 3.20, p<0.05, η2 = 0.25]; SOA,
attention, and electrode [F(3.3,42.7) = 4.08, p < 0.001,
η2 = 0.32]; SOA, attention, stimulus side, and electrode
[F(2.1,26.9) = 2.43, p < 0.05, η2 = 0.19]; and SOA,
attention, and hemisphere [F(4.1,53.7) = 2.14, p<0.05,
η2=0.16]. These interactions showed stronger attentional
effects for the −90-, 25-, and 60-ms SOAs, particularly
for midline and parietal electrodes. Effects of SOA that
did not interact with attention were also observed. There
was a main effect of SOA [F(2.2,28.5)= 4.28, p <0.05,
η2=0.33]; as well as interactions between SOA and hemi-
sphere [F(3.9,50.4)=13.80, p < 0.001, η2= 1.07]; SOA
and electrode [F(1.3,23.7)=9.36, p< 0.001, η2=0.51];
SOA, stimulus side, and electrode [F(2.9,38.4) = 2.39,
p< 0.05, η2=0.18]; and SOA, electrode, and hemisphere
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2993Exp Brain Res (2017) 235:2983–2996
1 3
[F(5.4,70.1)=4.64, p<0.001, η2=0.36]. This set of inter-
actions highlighted that the P3 potentials were most pro-
nounced for the −90-, 25-, and 60-ms SOAs for midline-
and left-hemisphere parietal electrodes.
The present study was designed to evaluate whether the
particular dimension in which endogenous attention was
oriented was responsible for the latency shifts in early per-
ceptual processing observed by Vibell et al. (2007). The
experiment reported here was identical to our previous
study, except for the fact that the participants here had to
focus their attention endogenously on a particular spatial
location and decide on the modality of the stimulus that
occurred first (to maintain orthogonality of the experi-
mental design; cf. Spence etal. 2001). The results provide
support for the claim that the dimension along which atten-
tion is oriented plays an important role in determining the
neural mechanisms underlying any behavioural facilitation
effects that are observed.
Behaviourally, the results of the present study were simi-
lar to those reported by Vibell etal. (2007), even though
space and modality were transposed. Visual and tactile
stimuli occurring at the attended spatial location were
reported as occurring significantly earlier in time than
those appearing at the ignored spatial location. The behav-
ioural data from the present study, therefore, confirm the
results from the paper by Vibell et al., as well as those
from other earlier studies (see Spence and Parise 2010, for
a review). The behavioural data were in line with earlier
work (Spence etal. 2001, Experiments 3 and 4) in showing
that spatial attention shifted the PSS toward the attended
modality. This study used a simple PSS-based method
for comparability with Vibell et al. (2007), but see also
Alcalá-Quintana and García-Pérez (2013), García-Pérez
and Alcalá-Quintana (2015), Krüger etal. (2016) for more
detailed analysis approaches. (We will publish the data for
further assessment by the modeling community.)
The pattern of behavioural prior-entry effects was simi-
lar to that observed in previous endogenous cuing studies.
A behavioural prior-entry effect of 28 ms was observed
here as compared to a shift of 38ms in the study by Vibell
etal. (2007). A between-studies comparison of the shift in
PSS values, however, revealed that these effects were not
significantly different. Despite showing a smaller prior-
entry effect for spatial attention than in Spence etal. (2001)
previous study (121ms), the slightly smaller (though non-
significant) difference between the present study and the
study by Vibell etal. concurs with Spence and colleagues’
findings in suggesting a smaller effect in the spatial
dimension than in the modality dimension. Further studies
are needed, however, to confirm this.
The ERP results show both similarities and differences
to those observed by Vibell etal. (2007). Spatial attention,
within the context of the TOJ task, influenced the latency
of potentials elicited by visual stimuli. The effects started
later than those reported for modality-based attention by
Vibell et al. with the P2 potential showing significantly
earlier latencies in the attended as compared to the ignored
stimulus conditions. The latency shifts occurred indepen-
dently of the SOA, thus providing evidence in support of
the occurrence of post-perceptual latency effects, and argu-
ing against the effects being caused by artifacts or by an
interaction between the visual and tactile evoked potentials.
Latency modulations continued to be observed for even
later potentials, but in this case, the effects of spatial atten-
tion interacted with the SOA conditions, making it difficult
to rule out contamination of potential overlap from the suc-
cessive stimuli as a possible explanation.
The ERP results from the present endogenous spatial-
attention TOJ study highlight both similarities and differ-
ences with the findings reported by McDonald etal. (2005)
using exogenous spatial attention directed to audio-visual
TOJs. In their study, spatial attention did not significantly
shift the latency of the earlier perceptual potentials (P1 and
N1) as in Vibell etal. (2007). Instead, they found latency
modulations only from post-perceptual stages of infor-
mation processing (P2 and onwards). The present study
showed similar shifts to McDonald etal. occurring in the
P2 potential. We found a 6-ms shift for the P2 potential,
which is very similar to the 5-ms difference observed by
McDonald and colleagues. We did not, however, see the
enhanced contralateral positivity reported by McDonald
etal. (2005; also Störmer etal. 2009; and McDonald etal.
By comparing the results in the present experiment to
those reported by Vibell etal. (2007), it can be concluded
that the dimension along which attention is oriented can
influence the ability to detect shifts in the latency of early
visual potentials. However, additional experimental factors,
other than the dimension of attention (e.g. response bias),
may also influence the ability to observe perceptual prior-
entry effects in TOJ experiments. Vibell et al.’s (2007)
study refutes such claims with quite early attentional mod-
ulations (P1), which are unlikely to have stemmed from
response bias which is thought to occur at later cognitive
processing stages. This leaves open, however, the question
of whether later components are influenced by response
The P3 (not analyzed in McDonald etal.’s 2005, study)
exhibited a reverse latency effect. This has been observed
in other studies using spatial attention, though it is never-
theless still somewhat unusual (Eimer 1994; Griffin et al.
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2994 Exp Brain Res (2017) 235:2983–2996
1 3
2002). One of the interactions suggested that attentional
effects were the strongest when touch is presented 90ms
before vision and particularly over somatosensory areas,
suggesting that the tactile stimuli might interact with the
effect of the later potentials. Since touch is perceived on
average 60ms earlier than vision, it is likely that the tac-
tile stimulation can interfere with the later visual potentials
causing the interactions by SOA that we observed. In addi-
tion, several studies have demonstrated that the amplitude
of the P3 depends on target probability (e.g., Duncan-John-
son and Donchin 1977; Kutas etal. 1977). The P3 increases
as a function of decreasing the probability of occurrence of
the relevant stimulus. Therefore, it is perhaps not so sur-
prising that in the present study, using an increased num-
ber of stimuli in the attended location induced a decreased
P3, canceling out any potential attention effects. Using the
same type of paradigm, the study by Vibell etal. (2007)
showed P3 amplitudes that just failed to reach significance
for attention. In that study, the effects were stronger for the
P3 when stimuli were attended, but might have been even
stronger with another attentional manipulation, where
attention was not directed based on increasing the fre-
quency of stimuli.
The waveforms observed in the present study were very
similar to those observed by Vibell et al. (2007), where
attention was oriented to a specific sensory modality. How-
ever, compared to their effects of modality-based atten-
tion during the performance of a TOJ task, more ampli-
tude modulation of the visual potentials was observed in
the present study. These effects consistently interacted
with the SOA conditions, thus making their interpretation
in this context somewhat problematic. Nevertheless, their
occurrence, combined with the later-emerging effects on
the peak latency of visual potentials, clearly shows that the
mechanisms of neural modulation by spatial attention differ
from those by modality-based attention (see also Störmer
etal. 2009; Grabot and van Wassenhove 2017).
Research comparing dimensions of attention (e.g., atten-
tion to spatial locations or sensory modalities) have shown
that slightly different mechanisms can underlie similar
behavioural effects, as in the case of attention to spatial
locations and temporal intervals (see Nobre and Silvert
2008). Despite using similar paradigms, mostly based on
Posner and Rothbart (1980) influential attentional orient-
ing task, these studies showed different stages of attentional
modulation and even latency changes in later potentials
for the case of temporal attention (Griffin etal. 2002). The
Posnerian cuing paradigm typically uses spatial-attentional
manipulations, which may explain why early amplitude
enhancements have been observed in many of previous
studies. The latency shift in the studies investigating atten-
tion to time (Correa et al. 2006; Griffin et al. 2002; see
also Miniussi etal. 1999) was observed for the P3 possibly
reflecting the cognitive nature of their temporal manipula-
tion. Correa and colleagues also found a speeding-up (by
9ms) in the N2 potential by temporal attention. They attrib-
uted the earlier N2 shift to a higher demand on perceptual
processing, which is also the case for TOJ studies. This is
comparable to the results here, showing perceptual latency
shifts, probably due to the perceptual nature of the discrim-
ination. The nature of the task may, therefore, interact with
the attentional dimension in the modulation of ERPs.
The results of the research reported here suggest that
attention directed to spatial locations operates slightly later
in time than does attention to sensory modalities (see also
Spence et al. 2001). Though, it should be borne in mind
that enhanced contralateral positivities reported in previ-
ous studies of spatial attention consistently emerged in the
interval of the P1 (e.g., Nobre and Silvert 2008). In sum-
mary, despite using the same task and parameters as Vibell
etal. (2007), and only switching the dimension of attention
and the dimension of response, latency modulations were
observed at slightly later stages. This suggests that atten-
tion to spatial locations modulates peak latencies slightly
later than attention to sensory modalities. Therefore, the
present data suggest that the type of attention induced the
exceptionally early latency shifts in Vibell et al.’s (2007)
study. The findings show the ability of ERPs to discrimi-
nate different neural mechanisms underlying what looks
like the same behavioural effect. Future work should refine
our understanding of how attention to spatial locations and
to sensory modalities influences early sensory processing
differently. It would be particularly interesting, for instance,
to include a different attentional dimension for space (e.g.,
up/down) to be able to compare attention to spatial loca-
tions and to sensory modalities using the same response
dimension (respond left/right) for both conditions.
Acknowledgements The Cartool software (http://brainmapping. has been programmed by Denis Brunet, from the
Functional Brain Mapping Laboratory, Geneva, Switzerland, and is
supported by the Center for Biomedical Imaging (CIBM) of Geneva
and Lausanne.
Open Access This article is distributed under the terms of the
Creative Commons Attribution 4.0 International License (http://, which permits unrestricted
use, distribution, and reproduction in any medium, provided you give
appropriate credit to the original author(s) and the source, provide a
link to the Creative Commons license, and indicate if changes were
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... Interestingly, however, in crossmodal tasks (i.e., audio-visual presentations) the visual stimuli had to lead auditory stimuli by approximately 40-80 ms for participants to perceive them as being presented simultaneously (PSS; Hirsh & Sherrick, 1961;. Other research also suggests that the baseline resolution of temporal acuity is better in the auditory modality than in the visual or tactile modalities (Chen & Yeh, 2009;Gebhard & Mowbray, 1959;O'Connor & Hermelin, 1972;Vibell et al., 2007Vibell et al., , 2017Welch, DuttonHurt, & Warren, 1986). ...
... This would indicate that determining the spatial resolution of temporal order may be more difficult than simply determining the order of modality of presentation. Additionally, Zampini et al. noted that across different modalities, an average increase in the temporal resolution of 10-30 ms could be observed when stimuli were presented from different spatial locations (i.e., first on the left and second on the right), as opposed to when they were repeatedly presented from the same location (i.e., first on the left and second also on the left), suggesting that spatial information can provide additional help in discriminating temporal order (see Vibell et al., 2017, for similar findings between vision and touch). ...
... This is ideal as the additional spatial cues not only provide an opportunity for a better understanding of how information processing is modulated but are perhaps more analogous to real-world situations requiring attention to be directed to a task while at the same time being presented with irrelevant within and across modality stimuli. The presentation of exogenous cues prior to stimuli onset in a TOJ task creates a ''prior entry'' effect, whereby attention is directed towards the cued side and subsequently affects performance on the task, regardless of whether or not the cue is predictive of location (i.e., in our task the cue is only correct half of the time; see also Spence et al., 2001;Vibell et al., 2017;Zampini, Shore, & Spence, 2005). ...
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Considerable evidence converges on the plasticity of attention and the possibility that it can be modulated through regular training. Music training, for instance, has been correlated with modulations of early perceptual and attentional processes. However, the extent to which music training can modulate mechanisms involved in processing information (i.e., perception and attention) is still widely unknown, particularly between sensory modalities. If training in one sensory modality can lead to concomitant enhancements in different sensory modalities, then this could be taken as evidence of a supramodal attentional system. Additionally, if trained musicians exhibit improved perceptual skills outside of the domain of music, this could be taken as evidence for the notion of far-transfer, where training in one domain can lead to improvements in another. To investigate this further, we evaluated the effects of music training using tasks designed to measure simultaneity perception and temporal acuity, and how these are influenced by music training in auditory, visual, and audio-visual conditions. Trained musicians showed significant enhancements for simultaneity perception in the visual modality, as well as generally improved temporal acuity, although not in all conditions. Visual cues directing attention influenced simultaneity perception for musicians for visual discrimination and temporal accuracy in auditory discrimination, suggesting that musicians have selective enhancements in temporal discrimination, arguably due to increased attentional efficiency when compared to nonmusicians. Implications for theory and future training studies are discussed.
... The morphology of SEP waveforms from stimulation at different regions of the body are similar but can show slight differences ( Figure 2). After about 100 ms, S2, posterior parietal and frontal regions activate, with the P100 generated in bilateral S2 [e.g., 8, [10][11][12][13] and the N1, P2, N2 and P3 bilaterally in increasingly frontal areas [4,14,15]. ...
Electroencephalography (EEG) is one of the major tools to non-invasively investigate cortical activations from somatosensation in humans. EEG is useful for delineating influences on the processing pathways of tactile stimulation and for mapping the dynamics between the cortical areas involved in and linked to tactile perception. This chapter focuses on the process of recording somatosensory EEG from mechanical tactile stimulation, including affective touch, and their related cortical activations. Practical and participant-specific challenges are detailed, and best practices are shared. In addition, the main areas of research in tactile perception using EEG are discussed. These include perception, attention, and multisensory perception, as well as emotional and self-other processing. We discuss the major considerations when conducting these types of research.Key wordsTactileSomatosensoryElectroencephalography EEG ERPs SEPs MultisensoryAttentionAffect
... While early lesion work placed the PPC to serve spatial localization (Ungerleider, 1982), it has since been implicated in stimulus-driven attention, extending to aspects of spatial cognition including the analysis of external multisensory information (Colby et al., 1996;Corbetta and Shulman, 2002;Sack, 2009;Sack et al., 2008). In non-human primates, activity in the parietal lobule, particularly area 7 in the monkey (thought to be homologous to the SPL in the human; (Anderson, 1988), has been shown to change as a function of spatial attention, in the visual, auditory and haptic domains (Burton et al., 1999;Pugh et al., 1996;Vibell et al., 2017Vibell et al., , 2007. This region seems to be particularly well-equipped to integrate multi-sensory data due to its position as part of a broader frontoparietal network that handles representations along viewer-centric and allocentric references frames (Szczepanski et al., 2013). ...
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A widely used example of the intricate (yet poorly understood) intertwining of multisensory signals in the brain is the audiovisual bounce inducing effect (ABE). This effect presents two identical objects moving along the azimuth with uniform motion and towards opposite directions. The perceptual interpretation of the motion is ambiguous and is modulated if a transient (sound) is presented in coincidence with the point of overlap of the two objects’ motion trajectories. This phenomenon has long been written-off to simple attentional or decision-making mechanisms, although the neurological underpinnings for the effect are not well understood. Using behavioural metrics concurrently with event-related fMRI, we show that sound-induced modulations of motion perception can be further modulated by changing motion dynamics of the visual targets. The phenomenon engages the posterior parietal cortex and the parieto-insular-vestibular cortical complex, with a close correspondence of activity in these regions with behaviour. These findings suggest that the insular cortex is engaged in deriving a probabilistic perceptual solution through the integration of multisensory data.
... Here, it is important to note that while directing attention to one sensory modality or another does not always enhance behavioural performance, presenting stimuli in a modality that has been actively inhibited (i.e., unattended) does appear to impair performance, be it in a spatial attention or discrimination task, or even an unspeeded perceptual task (see also Johnson, Strafella, & Zatorre, 2007;Johnson & Zatorre, 2006;Kawashima, O'Sullivan, & Roland, 1995;Shomstein & Yantis, 2004;Spence, Nicholls, & Driver, 2001;, for a review). 19 Finally here, it should be borne in mind that differences between the perceptual consequences/neural signatures associated with attending to a sensory modality versus spatial location have been reported Vibell, Klinge, Zampini, Nobre, & Spence, 2017;Vibell, Klinge, Zampini, Spence, & Nobre, 2007). 20 But what, one might ask, do such fundamental findings from the lab have to do with driving? ...
Cognitive neuroscientists have started to uncover the neural substrates, systems, and mechanisms enabling us to prioritize the processing of certain sensory information over other, currently less-relevant, inputs. However, there is still a large gap between the knowledge generated in the laboratory and its application to real-life problems of attention as when, for example, interface operators are multi-tasking. In this Element, laboratory studies on crossmodal attention (both behavioural/psychophysical and cognitive neuroscience) are situated within the applied context of driving. We contrast the often idiosyncratic conditions favoured by much of the laboratory research, typically using a few popular paradigms involving simplified experimental conditions, with the noisy, multisensory, real-world environments filled with complex, intrinsically-meaningful stimuli. By drawing attention to the differences between basic and applied studies in the context of driving, we highlight a number of important issues and neglected areas of research as far as the study of crossmodal attention is concerned.
... 2018 • volume 14(2) • 39-50 41 periments typically yield s-shaped distributions of judgment frequency across temporal intervals (see Figure 2). Wada et al. fitted a psychometric function to the TOJ data and estimated its parameters, a common procedure both historically (Finney, 1971;Guilford, 1954;Woodworth & Schlosberg, 1961) and today (e.g., Vibell, Klinge, Zampini, Nobre, & Spence, 2017). ...
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The theory of visual attention (TVA) provides a formal framework for the assessment of visual attention and related processes. Its center is a mathematical model of visual encoding processes and discretely defined components of attention. Building on this model, TVA offers quantitative and process-related explanations for a variety of phenomena in the domain of visual attention. Because the theory relies on very general assumptions which might hold true for other domains of sensory processing, we tested its possible explanatory value for tactile processing in mice. Reanalyzing published data of temporal-order judgments by mice, we show how a TVA-based analysis identifies the processes which drive observable behavior and that it comes to conclusions quite different from those of conventional analyses of temporal-order judgments. According to this anal- ysis, despite the same overall capacity dedicated to the task, some mice assume attentional biases toward one side, possibly to optimize their overall performance. We suggest that TVA's concepts provide a powerful point of vantage to find explanations for observable behavior where conventional analysis easily leads to dead ends.
... Here, it is important to note that while directing attention to one sensory modality or another does not always enhance behavioural performance, presenting stimuli in a modality that has been actively inhibited (i.e., unattended) does appear to impair performance, be it in a spatial attention or discrimination task, or even an unspeeded perceptual task (see also Johnson, Strafella, & Zatorre, 2007;Johnson & Zatorre, 2006;Kawashima, O'Sullivan, & Roland, 1995;Shomstein & Yantis, 2004;Spence, Nicholls, & Driver, 2001;, for a review). 19 Finally here, it should be borne in mind that differences between the perceptual consequences/neural signatures associated with attending to a sensory modality versus spatial location have been reported Vibell, Klinge, Zampini, Nobre, & Spence, 2017;Vibell, Klinge, Zampini, Spence, & Nobre, 2007). 20 But what, one might ask, do such fundamental findings from the lab have to do with driving? ...
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Incorrectly perceiving the chronology of events can fundamentally alter people’s understanding of the causal structure of the world. For example, when astronomers used the “eye and ear” method to locate stars, they showed systematic interindividual errors. In the current study, we showed that temporal-order perception may be considered a psychological bias that attention can modulate but not fully eradicate. According to Titchener’s law of prior entry, attention prioritizes the perception of an event and thus can help compensate for possible interindividual differences in the perceived timing of an event by normalizing perception in time. In a longitudinal study, we tested the stability of participants’ temporal-order perception across and within sensory modalities, together with the magnitude of the participants’ prior-entry effect. All measurements showed the persistence of stable interindividual variability. Crucially, the magnitude of the prior-entry effect was insufficient to compensate for interindividual variability: Conscious time order was systematically subjective, and therefore traceable on an individual basis.
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Stimulus contrast and duration effects on visual temporal integration and order judgment were examined in a unified paradigm. Stimulus onset asynchrony was governed by the duration of the first stimulus in Experiment 1, and by the interstimulus interval in Experiment 2. In Experiment 1, integration and order uncertainty increased when a low contrast stimulus followed a high contrast stimulus, but only when the second stimulus was 20 or 30ms. At 10ms duration of the second stimulus, integration and uncertainty decreased. Temporal order judgments at all durations of the second stimulus were better for a low contrast stimulus following a high contrast one. By contrast, in Experiment 2, a low contrast stimulus following a high contrast stimulus consistently produced higher integration rates, order uncertainty, and lower order accuracy. Contrast and duration thus interacted, breaking correspondence between integration and order perception. The results are interpreted in a tentative conceptual framework.
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Peripheral visual cues lead to large shifts in psychometric distributions of temporal-order judgments. In one view, such shifts are attributed to attention speeding up processing of the cued stimulus, so-called prior entry. However, sometimes these shifts are so large that it is unlikely that they are caused by attention alone. Here we tested the prevalent alternative explanation that the cue is sometimes confused with the target on a perceptual level, bolstering the shift of the psychometric function. We applied a novel model of cued temporal-order judgments, derived from Bundesen's Theory of Visual Attention. We found that cue--target confusions indeed contribute to shifting psychometric functions. However, cue-induced changes in the processing rates of the target stimuli play an important role, too. At smaller cueing intervals, the cue increased the processing speed of the target. At larger intervals, inhibition of return was perdominant. Earlier studies of cued TOJs were insensitive to these effects because in psychometric distributions they are concealed by the conjoint effects of cue--target confusions and processing rate changes.
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Perceiving temporal relationships between sensory events is a key process for recognising dynamic environments. Temporal order judgement (TOJ) and simultaneity judgement (SJ) are used for probing this perceptual process. TOJ and SJ exhibit identical psychometric parameters. However, there is accumulating psychophysical evidence that distinguishes TOJ from SJ. Some studies have proposed that the perceptual processes for SJ (e.g., detecting successive/simultaneity) are also included in TOJ, whereas TOJ requires more processes (e.g., determination of the temporal order). Other studies have proposed two independent processes for TOJ and SJ. To identify differences in the neural activity associated with TOJ versus SJ, we performed functional magnetic resonance imaging of participants during TOJ and SJ with identical tactile stimuli. TOJ-specific activity was observed in multiple regions (e.g., left ventral and bilateral dorsal premotor cortices and left posterior parietal cortex) that overlap the general temporal prediction network for perception and motor systems. SJ-specific activation was observed only in the posterior insular cortex. Our results suggest that TOJ requires more processes than SJ and that both TOJ and SJ implement specific process components. The neural differences between TOJ and SJ thus combine features described in previous psychophysical hypotheses that proposed different mechanisms.
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Particular differences between an object and its surrounding cause salience, guide attention, and improve performance in various tasks. While much research has been dedicated to identifying which feature dimensions contribute to salience, much less regard has been paid to the quantitative strength of the salience caused by feature differences. Only a few studies systematically related salience effects to a common salience measure, and they are partly outdated in the light of new findings on the time course of salience effects. We propose Bundesen’s Theory of Visual Attention (TVA) as a theoretical basis for measuring salience and introduce an empirical and modeling approach to link this theory to data retrieved from temporal-order judgments. With this procedure, TVA becomes applicable to a broad range of salience-related stimulus material. Three experiments with orientation pop-out displays demonstrate the feasibility of the method. A 4th experiment substantiates its applicability to the luminance dimension.
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A considerable body of sensory research has addressed the rules governing simultaneity judgments (SJs) and temporal order judgments (TOJs). In principle, neural events that register stimulus-arrival-time differences at an early sensory stage could set the limit on SJs and TOJs alike. Alternatively, distinct limits on SJs and TOJs could arise from task-specific neural events occurring after the stimulus-driven stage. To distinguish between these possibilities, we developed a novel reaction-time (RT) measure and tested it in a perceptual-learning procedure. The stimuli comprised dual-stream Rapid Serial Visual Presentation (RSVP) displays. Participants judged either the simultaneity or temporal order of red-letter and black-number targets presented in opposite lateral hemifield streams of black-letter distractors. Despite identical visual stimulation across-tasks, the SJ and TOJ tasks generated distinct RT patterns. SJs exhibited significantly faster RTs to synchronized targets than to subtly asynchronized targets; TOJs exhibited the opposite RT pattern. These task-specific RT patterns cannot be attributed to the early, stimulus-driven stage and instead match what one would predict if the limits on SJs and TOJs arose from task-specific decision spaces. That is, synchronized targets generate strong evidence for simultaneity, which hastens SJ RTs. By contrast, synchronized targets provide no information about temporal order, which slows TOJ RTs. Subtly asynchronizing the targets reverses this information pattern, and the corresponding RT patterns. In addition to investigating RT patterns, we also investigated training-transfer between the tasks. Training to improve SJ precision failed to improve TOJ precision, and vice versa, despite identical visual stimulation across tasks. This, too, argues against early, stimulus-driven limits on SJs and TOJs. Taken together, the present study offers novel evidence that distinct rules set the limits on SJs and TOJs.
Several recent studies have shown that the perceptual influences of a peripheral cue can extend beyond the cue's modality. This chapter reviews recent studies of cross-modal attention capture, with an emphasis on studies that demonstrate auditory cueing effects on the perceptual and neural processing of visual stimuli. Psychophysical findings indicate that the appearance of a sudden sound enhances the detectability, perceived timing, and subjective appearance of a subsequent visual stimulus. Concomitant event-related potential recordings indicate that the perceptual consequences of cross-modal attention capture are associated with changes in the magnitude of early neural responses in modality-specific regions of the visual cortex. New findings show that such cortical changes also accompany cross-modally induced illusory line motion. Recent evidence shows that salient sounds activate the visual cortex automatically, and this activation may underlie the influences of auditory stimulation on visual perception.
Temporal-order judgment (TOJ) and simultaneity judgment (SJ) tasks are used to study differences in speed of processing across sensory modalities, stimulus types, or experimental conditions. Matthews and Welch (2015) reported that observed performance in SJ and TOJ tasks is superior when visual stimuli are presented in the left visual field (LVF) compared to the right visual field (RVF), revealing an LVF advantage presumably reflecting attentional influences. Because observed performance reflects the interplay of perceptual and decisional processes involved in carrying out the tasks, analyses that separate out these influences are needed to determine the origin of the LVF advantage. We re-analyzed the data of Matthews and Welch (2015) using a model of performance in SJ and TOJ tasks that separates out these influences. Parameter estimates capturing the operation of perceptual processes did not differ between hemifields by these analyses, whereas parameter estimates capturing the operation of decisional processes differed. In line with other evidence, perceptual processing also did not differ between SJ and TOJ tasks. Thus, the LVF advantage occurs with identical speeds of processing in both visual hemifields. If attention is responsible for the LVF advantage, it does not exert its influence via prior entry. Copyright © 2015 Elsevier Inc. All rights reserved.