Psychophysiology, 50 (2013), 70–73. Wiley Periodicals, Inc. Printed in the USA.
Copyright © 2012 Society for Psychophysiological Research
DOI: 10.1111/j.1469-8986.2012.01479.x
BRIEF REPORT
Separating stimulus-driven and response-related LRP components
with Residue Iteration Decomposition (RIDE)
BIRGIT STÜRMER,a GUANG OUYANG,b,c CHANGSONG ZHOU,b,c ANNIKA BOLDT,a,d and WERNER SOMMERa
a
Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong
c
Centre for Nonlinear Studies and The Beijing–Hong Kong–Singapore Joint Centre for Nonlinear and Complex Systems, Hong Kong Baptist University,
Kowloon Tong, Hong Kong
d
Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
b
Abstract
When the lateralized readiness potential (LRP) is recorded in stimulus–response compatibility (SRC) tasks, two
processes may overlap in the LRP, stimulus-driven response priming and activation based on response selection rules.
These overlapping processes are hard to disentangle with standard analytical tools. Here, we show that Residue Iteration
Decomposition (RIDE), based on latency variability, separates the overlapping LRP components from a Simon task into
stimulus-driven and response-related components. SRC affected LRP amplitudes only in the stimulus-driven component,
whereas LRP onsets were affected only in the response-locked component. Importantly, the compatibility effect in
reaction times was more similar to the effect in the onsets of the RIDE-derived response-locked LRP component than in
the unseparated LRP. Thus, RIDE-separated LRP components are devoid of distortions inherent to standard LRPs.
Descriptors: ERP, Lateralized Readiness Potential (LRP), Residue Iteration Decomposition (RIDE), Stimulus–
Response Compatibility (SRC)
LRP in incompatible trials fits well with dual-route accounts of
SRC (Kornblum, Hasbroucq, & Osman, 1990) and is seen as indicating visuo-motor priming by stimulus location via a direct route
(Stürmer, Siggelkow, Dengler, & Leuthold, 2000), whereas the
later correct LRP deflection is considered to reflect instructionrelated response selection (indirect route).
In compatible trials, both direct visuo-motor priming and indirect instruction-related response selection activate the correct
response and, therefore, result in negative LRP deflections, which
overlap and seamlessly merge in the standard (composite) LRP. For
compatible trials, it is therefore impossible to disentangle effects of
response priming and correct response selection in the LRP.
Moreover, as illustrated in Figure 1, the overlap of priming with
instruction-related correct response activation distorts the onset
of the correct LRPs. In compatible trials, the overlaps of both
negative-going LRP components shortens the onset of the composite LRP. In incompatible trials, however, the initial positive-going
activation partially cancels the overlapping negative-going activation and postpones the onset of the composite LRP. Together, both
distortions exaggerate the compatibility effect in the onsets of the
negative response selection-based LRPs.
As a case in question, Böckler, Alpay, and Stürmer (2011)
conducted a Simon task with choice responses (left vs. right hand)
according to stimulus shape. Stimuli were presented above or
below fixation, although stimulus location was irrelevant for
response selection; response buttons were arranged within the midsaggital line. In compatible trials, stimulus location and response
The lateralized readiness potential (LRP) is a useful tool indicating
hand-specific response activation. The LRP is calculated from the
electroencephalogram (EEG) recorded above the hand areas of the
motor cortices and reflects effector-specific asymmetric brain
activity. When the LRP is derived for hands, it is of negative
polarity if the correct response hand is activated. In stimuluslocked LRPs (S-LRP), the onset of a negative deflection indicates
the time demands of mental processes until the correct response
hand is selected (Masaki, Wild-Wall, Sangals, & Sommer, 2004;
Osman, Moore, & Ulrich, 1995). In stimulus-response compatibility (SRC) research, the S-LRP shows two effects. First, incompatible trials prolong the onset of the negative-going S-LRP because
response selection is more time-demanding than in compatible
trials. Second, in incompatible trials the correct negative-going
LRP deflection is often preceded by a short-lived positive deflection indicating activation of the incorrect hand (De Jong, Liang,
& Lauber, 1994; Gratton, Coles, & Donchin, 1992; Stürmer,
Leuthold, Soetens, Schröter, & Sommer, 2002). The early incorrect
bs_bs_banner
This research was supported by the High Performance Cluster Computing Centre, Hong Kong Baptist University, and by grants of the Hong Kong
Baptist University, the Hong Kong Research Grants Council (HKBU
202710) to G.O. and C.Z., the German Academic Exchange Service
(DAAD) to G.O., and the German Research Foundation (STU248/3-1)
to B.S.
Address correspondence to: Prof. Dr. Birgit Stürmer, HumboldtUniversität zu Berlin, Institute for Psychology, Rudower Chaussee 18,
12489 Berlin. E-mail: [email protected]
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LRP component separation by RIDE
71
Figure 1. Top panel: A schematic demonstration that the overlap of the early and late components of the LRP may advance the onset of the standard LRP
for compatible trials and delay the onset for incompatible trials. LRP components related to visuo-motor priming (gray) and response selection (black)
sum up to the LRP (dashed). In compatible trials (left) visuomotor priming shortens the onset of the correct negative-going LRP, whereas in incompatible
trials (right), the onset is delayed. Bottom panel: (A) Standard LRP for compatible and incompatible trials (thick and thin lines, respectively) for the different
arousal conditions. (B–D): LRPs computed from RIDE-derived component clusters S, C, and R, respectively, separated according to the same conditions as
the standard LRP.
location corresponded, whereas in incompatible trials, they did not.
As expected, the onset of the correct LRP deflection was delayed in
incompatible trials. In half of the trials, accessory tones preceded
the Simon stimuli and shortened overall reactions times (RTs) as
well as LRP onsets. Moreover, the compatibility effect was
enhanced by accessory stimuli in both measures. However, the
compatibility effect in LRP onsets exceeded the effect in RTs by
40 ms. It seems plausible that this excess compatibility effect is an
artifact, produced by the advancement of correct LRP by the early
correct activation and its delay by early incorrect activation in
compatible and incompatible trials, respectively (Figure 1).
Because the overlap of LRP activations via separate routes is a
general problem in compatibility experiments, a separation method
is highly desirable. Here, we applied Residue Iteration Decomposition (RIDE)—a method developed by Ouyang, Herzmann, Zhou,
and Sommer (2011)—to the LRP. RIDE is able to separate eventrelated potential (ERP) component clusters by virtue of their
latency variability. RIDE utilizes the latency variability and time
markers to separate ERP components into a stimulus-locked component cluster (named S), a response-locked component cluster
(named R), and an intermediate component cluster (named C). The
term component cluster refers to all components with similar timelocking properties across single trials, but each may involve several
ERP components. RIDE is based on the assumption that component clusters are linearly superimposed whereas their latencies vary
independently, with the internal components of the same component cluster being locked to one another.
By applying RIDE to LRPs in an SRC task, we aimed to
disentangle the two response activations described above: (a)
response activations due to visuo-motor priming via direct route
processing, which should be coupled to stimulus processing and,
hence, be observed in the S component separated by RIDE and (b)
instruction-related response selection via the indirect route, which
is closely linked to response execution and should, therefore, be
observed in the R component. The present work is based on the
EEG recordings reported by Böckler et al. (2011).
Methods
Sixteen students (mean age 22.7 years; 12 women; 15 righthanded) participated in the experiment.
72
B. Stürmer et al.
Details of the stimuli and procedure can be found in Böckler
et al. (2011). Compatible and incompatible Simon task conditions
were orthogonally combined with three arousal conditions. A tone
of 65 dB was presented either 500 or 200 ms before the visual
stimulus or there could be no tone.
The EEG was recorded from 64 Ag/AgCl electrodes, referenced to the left mastoid. Bandpass was 0.01 Hz to 70 Hz; sampling rate was 250 Hz. The LRP was taken from electrode sites C3
and C4 and calculated according to Coles (1989).
ERP Component Decomposition with RIDE
RIDE assumes that in each single EEG trial three clusters of
components S, C, and R with different latencies are linearly
superimposed:
EEG (t ) = S (t − LS ) + C (t − LC ) + R (t − LR ) + ξ,
(1)
where LS, LC, and LR denote the latencies of the component clusters
S, C, and R, respectively. S is assumed to be stimulus locked, so
LS = 0. R is assumed to be response locked, so LR = RT. C is the
component cluster in between, and its latencies have to be estimated (Ouyang et al., 2011). The time courses of S, C, and R are
therefore expected to mostly represent the activations by early
stimulus-related (S), intermediate (C), and response related (R)
processes.
RIDE obtains the waveforms of component clusters S, C, and R
separately for each electrode by combining an estimate of the
components from the residue of single trial EEG (EEG-ERP) and
the estimate of the unknown latency Lc in an iterative manner
(Ouyang et al., 2011). Each separated component had the same
dimension as the ERP (1000 ms ¥ 64 channels). The core procedure of RIDE follows the work of Ouyang et al.; for a short rationale please see the introduction. Some specific modifications in
detail were made for improving the performance of RIDE in the
present case:
1. Data preparation. RIDE was independently and separately
applied to all EEG epochs of each participant and condition,
including all 64 recording sites. All single trial epochs were of
1 s duration and centered at mean amplitude.
2. Initial estimation of C latency. An initial estimation of the
latency of component cluster C in single trials was made by
Woody’s (1967) method separately for each recording site
between 200 and 1000 ms, using the standard ERP as template.
The mean latency of all channels was then taken as the overall
latency of C across the scalp, denoted as LC; correspondingly,
denote latency of S (stimulus onsets) as LS and latency of R (RT)
as LR.
3. Residue Iteration Decomposition. With the time markers LS, LC,
and LR, we used RIDE to obtain the component clusters S, C,
and R, which allowed us to improve the estimate of latency LC.
This procedure was iterated until LC converged and the component clusters S, C, and R and the latency LC were obtained. The
baselines of stimulus-locked convolution of C and R in the
interval (0–200 ms) were adjusted to zero. This operation is
based on the assumption that the activity of ERP during
0–200 ms is basically stable in latency across single trials, so
that the latency-variable components C and R should not contribute to 0–200 ms activity. Accordingly, the baseline of component cluster S in (0–200 ms) is readjusted to the level of
standard ERP.
4. Deriving the Lateralized Readiness Potential. The LRP activations were then derived for each component cluster with the
same procedure as for ERPs (Coles, 1989), subtracting the
ERP derived from the ipsi- and contralateral central electrodes
(C3, C4) relative to the required response hand, and averaging
the difference waves.
LRP Analyses
After deriving the LRP for each component cluster, the singlesubject regression method with one degree of freedom by Mordkoff
and Gianaros (2000) was applied to detect the onset of the standard
LRP and for the LRP derived from the stimulus-synchronized component cluster R extracted by RIDE (LRP CC-R). Seven of the 164
onsets were adjusted by hand: We always assumed the S-LRP onset
to occur before response execution. Two participants were completely excluded from further analyses because of their very small
LRPs. Repeated measures analyses of variance (ANOVAs) were
performed on RTs and LRP parameters including the factors accessory tone and compatibility. Huynh–Feldt corrections were applied
if necessary, and p values were adjusted by the given e value.
Results
The Simon effect—calculated as the difference in mean RTs
between incompatible and compatible events—was enlarged by
accessory tones (no tone: 31 ms, tone at stimulus onset asynchrony
[SOA] 200: 53 ms, SOA 500: 46 ms) in the Böckler et al. (2011)
study. Likewise, the Simon effect in standard LRP onsets was
numerically increased by tones (no tone: 67 ms, tone at SOA 200:
106 ms, tone at SOA 500: 111 ms). However, only the main effect
of compatibility was significant in S-LRP onsets, F(1,13) = 59.63,
p < .001, partial h2 = .821. No interaction of compatibility and
accessory tones showed up in S-LRP onsets, F(2,26) = 1.96,
p = .16, partial h2 = .123.
Figure 1d, bottom, shows the LRP for the RIDE-derived stimulus synchronized component cluster R (LRP CC-R). The onsets
of these waveforms showed main effects of compatibility
(Mc = 208 ms, Mic = 257 ms); F(1,13) = 14.09, p < .01, partial
h2 = .520, but not of accessory tone (M for no tone, tone at
SOA 200 and 500 ms = 243, 223, and 233 ms, respectively);
F(2,26) = 1.35, p = .277, partial h2 = .094. The interaction of compatibility and accessory tone was far from significant; F < 1, partial
h2 = .002.
Figure 1b, bottom, shows the LRPs for the RIDE-derived component cluster S (LRP CC-S), and Figure 1c, bottom, shows the
LRP for the component cluster C (LRP CC-C). Overall, the LRP
CC-C does not contribute to present LRP effects. Please note that
this only refers to the hand-related asymmetry that is extracted by
the LRP calculation and only means that there is no such asymmetry in the component cluster C. However, the LRP CC-S beautifully
captures the early visuo-motor priming-related LRP activation with
positive- and negative-going deflections of similar magnitude,
clearly influenced by the accessory tones.
One may have noticed that these positive- and negative-going
deflections are not symmetric relative to the x-axis—as implied by
the model in Figure 1—but they are symmetric relative to a
negative-going slope of the S-LRP. Such slopes due to a nonreturn
to baseline are to be seen in most LRP studies (e.g., Gratton et al.,
1992; Stürmer et al., 2002) but, to the best of our knowledge, have
not found scientific attention. RIDE allocates the slope, which has
no significant latency jitter within our 1-s epoch, to component
cluster S. The earlier peak in the CC-S LRP from the incompatible
as compared to the compatible condition is a consequence of the
negative-going slope: A negative slope superimposed on a positive
LRP component separation by RIDE
73
wave will shift the maximum of the composite signal toward earlier
latencies, whereas superposition on a negative wave will delay the
latency of the minimum. A conceivable way of dealing with the
slope problem would be a detrending of the single trials prior to
RIDE. However, for the moment, we preferred to retain this trend
because it is a property of most LRPs in the literature.
An ANOVA on the average LRP CC-S amplitude within the
time interval 200–280 ms after Simon stimulus onset resulted in
a main effect of compatibility, F(1,13) = 41.49, p < .001. Single
comparisons showed that the compatible no-tone condition
significantly differed from both compatible tone conditions,
Fs(1,13) > 5.03, ps < .043. Incompatible conditions differed significantly between the no-tone and tone 200 conditions, F(1,13) =
7.60, p < .016. Therefore, the S component replicated all amplitude
effects of compatibility and arousal in the standard ERP.
Discussion
We assessed the feasibility of separating the early priming-based
LRP component from the later response-selection based component by means of RIDE, a method for ERP component separation
based on latency variability. As expected, RIDE yielded two LRP
components, one extracted from component cluster S (LRP CC-S)
and one extracted from the component cluster R (LRP CC-R). No
significant LRP was seen on component cluster C.
Compared to the traditional ERP method, RIDE provides
several novel insights. The LRP CC-S captures the direct route of
early visuo-motor processing and fit with standard Simon effect
results in the LRP amplitude. In incompatible trials, the LRP CC-S
showed a clear positive deflection after 200 ms, which later on
shifted toward more negative values. In compatible trials, no such
positive deflection was present in the early part of the LRP CC-S.
The LRP CC-R is devoid of early activation and displays a significant Simon effect in the onset (M = 49 ms). Importantly, this LRP
CC-R Simon effect was very close to that found in mean RT
(M = 43 ms), whereas in the standard LRP the mean effect had
been 95 ms. This result nicely supports the hypothesis that
the overlap of visuo-motor priming-related LRP and response
selection-related LRP advances and delays the onsets of correct
LRP activations in compatible and incompatible trials, respectively.
In addition, the negative deflection in the LRP CC-S of compatible
trials and the positivity in the incompatible conditions (see
Figure 1a,b) confirm the postulated overlap of the mechanisms of
visuo-motor priming and response selection. Therefore, RIDE
serves as a method to separate the two entangled LRP components.
The correct and incorrect response priming effects are closely
linked to stimulus processing and time-locked to stimulus. In contrast, instruction-related response selection is time-locked to the
response.
Applying RIDE to LRPs provides the opportunity to measure
response priming even when these activations overlap with activation due to response selection. Therefore, RIDE appears to be a
useful tool for separating early visuo-motor priming-related activation from later response selection-related activations in the LRP.
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