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Nine-month-olds start to perform sequential actions. Yet, it remains largely unknown how they acquire and control such actions. We studied infants' sequential-action control by employing a novel gaze-contingent eye tracking paradigm. Infants experienced occulo-motor action sequences comprising two elementary actions. To contrast chaining, concurrent and integrated models of sequential-action control, we then selectively activated secondary actions to assess interactions with the primary actions. Behavioral and pupillometric results suggest 12-month-olds acquire sequential action without elaborate strategy through exploration. Furthermore, the inhibitory mechanisms ensuring ordered performance develop between 9 and 12months of age, and are best captured by concurrent models. Copyright © 2015 Elsevier B.V. All rights reserved.
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RUNNING TITLE: Sequential action control in infancy
The developing cognitive substrate of sequential action control in 9- to 12-month-olds:
Evidence for concurrent activation models
Verschoor1,4, S. A., Paulus4, M., Spapé2, M., Biro1,3, S. & Hommel1, B.
In press
Cognition
1 Leiden University Institute for Psychological Research & Leiden Institute for Brain and Cognition
2 Helsinki Institute for Information Technology
3 Center for Child and Family Studies, Leiden University
4 Developmental psychology unit, LMU München
Keywords: action-effects; eye tracking; pupillometry; goal-directed action; infancy; cognitive
development, sequential action.
Word count: 8211
Development of sequential action control in infancy 2
Abstract
Nine-month-olds start to perform sequential actions. Yet, it remains largely unknown how they
acquire and control such actions. We studied infants’ sequential-action control by employing a
novel gaze-contingent eye tracking paradigm. Infants experienced occulo-motor action
sequences comprising two elementary actions. To contrast chaining, concurrent and integrated
models of sequential-action control, we then selectively activated secondary actions to assess
interactions with the primary actions. Behavioral and pupillometric results suggest 12-month-
olds acquire sequential action without elaborate strategy through exploration. Furthermore, the
inhibitory mechanisms ensuring ordered performance develop between 9 and 12 months of age,
and are best captured by concurrent models.
Development of sequential action control in infancy 3
The developing cognitive substrate of sequential action control in 9- to 12-month-olds:
Evidence for concurrent activation models
Infants are active, goal-directed agents (e.g., McCarty, Clifton, Ashmead, Lee, & Goubet, 2001).
Interestingly, some of the actions they produce can be considered sequential, such as reaching for
a rattle in order to shake it — a rather simple sequence, that comprises two dissociable
components that differ in function and motor demands. Piaget (1936) and others (Claxton, Keen,
& McCarty, 2003; Hauf, 2007; Willatts, 1999; Woodward and Sommerville, 2000; Woodward,
Sommerville, Gerson, Henderson & Buresh, 2009) have stated that true goal-directed action
emerges around 9 months of age when infants begin to be able to organize means-end action
sequences in the service of overarching goals. Yet, the cognitive substrate of early sequential
action control in infants remains completely uncharted territory. The purpose of the current study
is to explore the cognitive mechanism sub-serving sequential action control in infants.
Development of action control in infancy
There are three prerequisites for infants to control sequential action: that they can
represent actions, that they can represent sequential information and that they can combine those
abilities to represent and control sequential action. Let us turn to the first prerequisite. There is
ample evidence that actions are represented in terms of their effects. In his ideomotor theory,
James (1890) states that actions are learned on the fly through sensorimotor exploration; an
automatic mechanism creates bidirectional associations between perceived effects and the
actions producing them (Hommel, 2009; Hommel, Müsseler, Aschersleben, & Prinz, 2001).
These associations bring the actions under voluntary control, enabling the agent to activate the
Development of sequential action control in infancy 4
action by “thinking of” the corresponding effect. The theory can thus account for learning new
actions and new goals.
This idea is typically tested in a two-stage paradigm. Experimenters first let subjects
perform actions that lead to specific effects. After acquisition, they test if exogenously cueing an
effect cues the action that previously caused it (Elsner & Hommel, 2001; Greenwald, 1970). This
approach resulted in demonstrations of bidirectional action-effect acquisition for a wide range of
actions and effects in children (Eenshuistra, Weidema & Hommel, 2004; Kray, Eenshuistra,
Kerstner, Weidema & Hommel, 2006) and adults, suggesting the mechanism responsible to be
fast-acting (Dutzi & Hommel, 2009), automatic (Elsner & Hommel, 2001; Band, Steenbergen,
Ridderinkhof, Falkenstein & Hommel, 2009), implicit (Elsner & Hommel, 2001; Verschoor,
Spapé, Biro & Hommel, 2013), and modulated by the same factors that influence instrumental
learning (Elsner & Hommel, 2004) (for a review on action-effect learning see: Hommel &
Elsner, 2009). Furthermore, action-effects have also been found to be important for action
evaluation (Band, Van Steenbergen, Ridderinkhof, Falkenstein & Hommel, 2009; Verschoor et
al., 2013).
Until recently, research on the importance of action effects for infants mainly focused on
third-person action interpretation (e.g., Biro & Leslie, 2007; Hauf, 2007; Kiraly, Jovanovic,
Prinz, Aschersleben, & Gergely, 2003; Paulus, 2012; Paulus, Hunnius, & Bekkering, 2013;
Woodward, 1998, for a review, see: Hauf, 2007; Kiraly, Jovanovic, Prinz, Aschersleben, &
Gergely, 2003) and imitation (Hauf & Aschersleben, 2008; Klein, Hauf & Aschersleben, 2006;
for a review see: Elsner 2007; Paulus, 2014). Such findings are corroborative in view of the
upsurge of theories stressing similar representations for first- and third-person action (e.g. Baker,
Saxe & Tenenbaum, 2009; Fabbri-Destro & Rizzolatti, 2008; Melzoff, 2006, 2007; Tomasello,
Development of sequential action control in infancy 5
1999). Interestingly, increased model- to self- similarity aids imitation (Shimpi, Akhtar &
Moore, 2013). Yet given their focus on action understanding, such studies tell us little about the
function action effects have for the development of action control in infancy.
Direct evidence regarding action-effect learning was recently obtained from first-person
paradigms similar to that of Elsner and Hommel (2001). Verschoor, Spapé, Biro and Hommel
(2013) showed that 7-month-olds use action effects for first-person action monitoring. By eight
months, infants show motor resonance when listening to previously self-produced action-related
sounds (Paulus, Hinnius, Elk & Beckering, 2011). The youngest infants showing evidence for
reversing bidirectional action effects for action control are 9-month-olds (Verschoor, Weidema,
Biro & Hommel, 2010). Comparable results were found in 12- (Verschoor et al., 2013), and 18-
month-olds (Verschoor et al., 2010). Additionally 6-, 8- (Wang et al., 2012) and 10-month-olds
(Kenward, 2010) anticipate action outcomes. Taken together these studies illustrate that 7-
month-olds represent and monitor first- and third-person action in terms of action effects, while
9-month-olds additionally use action effects for action control.
Representing sequential information in infancy
Another prerequisite for representing sequential action is the ability to encode sequential
information. Infants can register whether items are consistent with familiarized deterministic or
probabilistic sequences (Romberg & Saffran, 2013). For instance, infants are susceptible to
sequential grammar information in speech from birth (Gervain, Berent, & Werker, 2012;
Teinonen, Fellmann, Näätänen, Alku & Huotilainen, 2009), 3-month-olds are susceptible to
spatiotemporal (Wentworth Hait & Hood, 2002) and audio-visual sequences (Lewkowicz, 2008)
and 8-month-olds to analogous information in artificial sound (Marcus, Fernandes & Johnson,
2007). Studies like these suggest an implicit, early-appearing, domain-general statistical
Development of sequential action control in infancy 6
information-acquisition mechanism for sequential information (e.g. Kim, Seitz, Feenstra &
Shams, 2009; Kirkham, Slemmer & Johnson, 2002; Marcovitch & Lewkowicz, 2009) thought to
sub-serve action- and language-segmentation (e.g. Baldwin, Andersson, Saffran & Meyer, 2008;
Saffran, Johnson, Aslin & Newport, 1999). Nonetheless these studies leave open whether infants
encode ordinal information among sequence elements. Indeed, Violation Of Expectation (VOE)
research suggests that while 4-month-old infants encode statistical sequential properties, they
cannot code the invariant order of sequences (Lewkowicz & Berent, 2009). This ability emerges
during the second half of the first year (Brannon, 2002; Picozzi, de Hevia, Girelli & Macchi-
Cassia, 2010; Suanda, Tompson & Brannon, 2008).
Sequential action representation in infancy
The reviewed literature shows that the first two prerequisites for infants’ representation of
sequential action emerge around 9 months. Yet, the question remains whether they can actually
combine these abilities to represent and control action sequences. Indirect evidence comes from
research that suggests infants are able to interpret third-person sequential actions. Evaluating
such actions requires them to be parsed in order to perceive overall syntax and ultimately their
goal (Conway and Christiansen, 2001; Lewkowicz, 2004; Baldwin, Baird, Saylor, & Clark
2001). VOE studies report that around the age of 6 months infants start to evaluate the efficiency
of sequential actions (Biro, Verschoor & Coenen, 2011; Csibra, 2008; Gergely & Csibra, 2003;
Verschoor & Biro, 2012) and causality towards their goals (Baillargeon, Graber, DeVos &
Black, 1990; Woodward & Sommerville, 2000). Olofson and Baldwin (2011) found that 10-
month-olds take into account the kinematics of an observed reaching motion to judge whether it
is part of a familiar action sequence. Yet, Paulus, Hunnius, and Bekkering (2011) showed that
20-, but not 14-month-old infants use such information to predict goals. Additionally,
Development of sequential action control in infancy 7
Gredebäck, Stasiewicz, Falck-Ytter, Rosander and von Hofsten, (2009) showed that 14- but not
10-month-olds’ predictive eye movements are influenced by the models later intention with the
object. Moreover, infants use social context to bind actions of two collaborating actors into
action sequences for goal evaluation (Henderson & Woodward, 2011; Henderson, Wang, Matz
& Woodward, 2013) and goal prediction (Fawcett & Gredebäck, 2013). Although these studies
provide evidence that infants have some understanding of others’ sequential action, they do not
reveal the cognitive mechanisms underlying infants’ control of their own sequential action
Turning to infants’ own action control, studies on (deferred) imitation of enabling action
sequences (sequences in which one action is temporally prior to and necessary for a subsequent
action) report that only a subset of 9-month-olds can (immediately) reproduce such sequences
under ideal circumstances (e.g., Bauer, Wiebe, Waters & Bangston, 2001; Carver & Bauer, 1999,
2001). Adding salient action-effects to separate action steps increases performance (Elsner, Hauf,
& Aschersleben, 2007). However, production of sequential action is in itself not enough to
evince infantssequential action control, since subsequent actions may simply be subsequent. In
enabling sequences, stimulus enhancement could externally trigger such sequences. Indeed, an
advantage for imitating enabling- over arbitrarily-ordered actions is reported (e.g. Barr & Hayne,
1996; Bauer, Hertsgaard, & Wewerka , 1995; Mandler & McDonough, 1995, for a review see:
van den Broek, 1997). Earliest evidence for imitation of arbitrarily-ordered action sequences is
reported for 16-month-olds (Bauer, Hertsgaard, Dropik & Daly, 1998).
Advance planning would make a stronger point for sequential action control. Claxton,
Keen and McCarty (2003) reported that 10-month-olds plan the kinematics of reaching
depending on subsequent intentions. Furthermore, McCarty, Clifton and Collard (1999) showed
that 19- but not 14-month-olds inhibit reaching for an object with their dominant hand when this
Development of sequential action control in infancy 8
is inefficient towards an overarching goal (see Cox & Smitsman (2006) for a conceptually
similar result in 3-year-olds). Both McCarty et al.’s (1999) and Cox and Smitsman’s (2006) tasks
depend on inhibition of pre-potent responses and suggest inhibition is important for sequential
action planning (for a review see McCormack & Atance, 2011). Likewise, the disadvantage for
reproducing arbitrarily-ordered action sequences seems to come from an increased need to
temporally organize such sequences (Bauer, Hertsgaard, Dropik & Daly, 1998), which many
theorists hypothesize inhibition to be crucial for (e.g. Constantinidis, Williams & Goldman-
Rakic, 2002; Norman & Shallice, 1986).
To sum up, the studies mentioned above suggest the rudimentary abilities to learn from
and interpret third-person sequential action, as well as the abilities to plan and control first-
person sequential action emerge by the end of the first year. The studies further suggest that
temporal organization, action effects and goals are important sources of information, yet they
leave open how such information is used for integrating action steps into coherent sequences. In
the current study we will attempt to clarify the cognitive mechanism responsible for this feat.
Models of sequential action representation
As there is little specific developmental literature on the subject, we turn to general
psychological theories on sequential action control. Through the years many influential
theoretical incarnations of sequential action representation have been conceived (de Kleijn,
Kachergis, & Hommel, 2014). All of these theories hold that sequential actions consist of
elementary actions that are somehow combined into sequences, as suggested the observation that
the speed of sequence-initiation increases with the number of elements therein (e.g., Henry &
Rogers, 1960; Rosenbaum, 1987). The theories can be distinguished into three ontological types
Development of sequential action control in infancy 9
that differ with respect to the representations action control operates on. We refer to them as
chaining, concurrent, and integrative theories of sequential action control (see Figure 1).
Chaining theories stress that elementary actions are selected and combined through association
processes. Concurrent (Hebbian) theories focus on competitive processes that account for the
orderly production of an action sequence. Integrated approaches highlight crosstalk between
elementary actions resulting in chunked actions.
Development of sequential action control in infancy 10
=== FIGURE 1 ===
Goal
A1 A2
Goal
A1 A2
Goal
A1 A2
A B C
Figure 1. Models of sequential action. Schematic representation of activation in A:
Chaining models of sequential action, activation cascades forward through the different
elementary actions, B: Concurrent models of sequential action, all elementary actions are
activated simultaniously whereafter competion through inhibition ensures the correct order of
execution, C: Integrated models of sequential action, the sequence of actions has been integrated
into a new elementary action.
Development of sequential action control in infancy 11
The prototypical theory of sequential action is James’ (1890) chaining theory. It holds
that elementary actions can be chained by sequentially activating the anticipated effect of each
element. With practice, the sensory effect of each elementary action becomes associated with the
next elementary action through stimulus-response learning, thereby eliminating the need for
sequential activation. The model thus effectively reduces sequential action representation to a
combination of ideomotor and stimulus-response learning. Furthermore, James’ theory can
account for the finding that infants better encode enabling- than arbitrarily ordered action
sequences (Barr & Hayne, 1996; Bauer, Hertsgaard, & Wewerka , 1995; Mandler &
McDonough, 1995), since the proposed feedback dependent effect-response learning he proposes
is aided by stimulus enhancement in such sequences. Although James’ theory is temptingly
simple, it has a number of important drawbacks resulting in additions to the model. Hull (1931)
pointed out that to stay goal-directed and flexible during performance, the representation of the
end state should remain active during execution to compare the actual to the expected outcome.
Hull thus introduces hierarchy into the representation by proposing continuous activation of an
overarching goal. Secondly, in the conception of James (1890) the second action of a sequence is
cued by the sensory effect of the first, suggesting sequential action to rely on sensory feedback.
Yet, empirical evidence suggests feedback mechanisms to be too slow to account for the speed of
practiced sequential action (e.g. Sternberg, Monsell, Knoll & Wright, 1978). Greenwald (1970)
suggested that instead of the sensory effects, the anticipated action effects of the preceding action
are associated to those of the next action. This enables the initiation of the sequence by
anticipating its end effect. However the model does not specify how the end effect activates the
sequence instead of just the final elementary action.
Development of sequential action control in infancy 12
An important criticism on chaining models is that they seem to imply that elementary
actions are equally associated with preceding and subsequent actions, making orderly
performance of sequences impossible. In other words, chaining models of sequential action
assume, but fail to describe how activation moves forward through the sequence. This lack of
temporal dynamics in chaining models resulted in the emergence of a second ontological class of
theories, the concurrent activation theories. Estes (1972) suggested an initial concurrent
activation of all elementary actions by a superseding goal. Thereafter, temporal inhibitory
processes ensure that activation moves forward through the sequence. To guarantee such forward
flow he introduced inhibitory links flowing from each element to the next and secondary self-
inhibition for completed elements (e.g., Henson, 1998, but also James, 1890), equivalent to
inhibition of return in visual attention (Posner & Cohen, 1984; Houghton & Tipper, 1996). The
concurrent model can account for the empirical finding of more prospective than retrospective
intrusion errors (Dell, Burger, and Svec, 1997; Lindenberger, Rünger & Frensch, 2000;
Rumelhart & Norman, 1982, for a review see: Houghton & Tipper, 1996). Concurrent models of
sequential action representation thus utilize inhibition processes which are implicated in studies
on action planning in infants (McCarty et al., 1999; Cox & Smitsman’s, 2006).
The third class of theories, integrative theories of sequential action control, does not
presuppose that action elements remain independent when combined into sequence. Such
theories state that through practice elementary actions can be integrated into one common action
plan or “chunk”, implying considerable crosstalk between the elementary actions (Miller, 1956;
Sakai, Hikosaka, & Nakamura, 2004). Their main support comes from studies that find
reductions in the sequence-length effect by extensive practice (e.g. Klapp 1995). Chunking of the
elementary actions is possible by relating the sequences to internal or external context thus
Development of sequential action control in infancy 13
creating a unique identifying criterion for the associations (Hull, 1931). This Integration process
can account for crosstalk between elementary actions and thus explains end-state comfort effects
(Rosenbaum et al., 1990) as found in infant studies (Claxton, Keen and McCarty, 2003; Cox &
Smitsman, 2006; McCarty; Clifton & Collard, 1999).
Experimental approach
Chaining, concurrent and integrated models generate different predictions with regard to
the spreading of activation from one sequence element to another. Consider a sequence of two
actions, with element R1 preceding element R2. All models imply that priming or otherwise
activating R1 might spread activation to R2, but they differ regarding their predictions when R2
is primed/activated. James’ (1890) chaining model would not predict that priming R2 leads to
activation of R1, since the sequence is assumed to be represented by unidirectional effect-
response bindings (R1!R2). Greenwald’s (1970) version would predict the spreading of
activation from R2 to R1, as sequences are represented by associations formed between the
effects of the elementary actions. Conversely, concurrent activation models would predict that
activating R2 leads to the inhibition of R1, as activation is allowed to spread in forward direction
only and backward connections are inhibitory. Finally, integrated models would predict that
activating one element would activate the representation of the entire sequence, including R1.
The aim of the present study was to pit these different predictions against each other.
In the current study we were not only interested in the cognitive substrate of sequential
action control, but also in the development thereof. Given findings that infants develop the
ability for sequential action control around the end of the first year of life (e.g., Claxton et al.,
2003), we hypothesized to find a developmental change in the cognitive substrate of sequential
action control between 9 and 12 months of age. This line of reasoning is also supported by
Development of sequential action control in infancy 14
findings that the prerequisites for the ability seem to emerge in this interval. In 9-month-olds the
ability to represent sequential information and action is rudimentary at best. Nonetheless, and
crucial to the experimental logic, 9-month-olds represent actions in terms of their effects.
To tackle our questions regarding sequential-action control, we modified a recently
developed gaze-contingent eye-tracking paradigm that assessed action-effect learning in infants
and adults (Verschoor et al., 2013). This paradigm, conceptually identical to that of Elsner and
Hommel (2001), overcomes problems arising due to limited motor control in infants (Verschoor
et al., 2013; Wang et al., 2012). Verschoor and colleagues (2013) first let subjects perform
actions that lead to specific effects. After acquisition, they tested whether exogenously cueing
the effects primes the action that previously caused it. The paradigm uses eye movements which
infants can accurately control from 4 months of age (Scerif et al., 2005) and which can be
considered goal-directed (Gredebäck & Melinder, 2010; Falck-Ytter, Gredebäck, & von Hofsten,
2006; Senju & Csibra, 2008). The paradigm records Reaction Times (RTs) and Response
Frequencies (RFs). The study of Verschoor and collegues (2013) and other recent studies that
demonstrated saccade-effect learning in adults (Huestegge & Kreutzfeldt, 2012; Herwig &
Horstmann, 2011), showed shorter RTs for responses congruent with the previously acquired
action-effect association (Verschoor et al., 2013). There is strong evidence that RT and RF differ
in their sensitivity to congruency effects depending on age. In 9- and 12-month-olds RT is a
sensitive measure (Verschoor et al., 2010; Verschoor et al., 2013), while in 18-month-olds RF
additionally diagnoses congruency effects (Verschoor et al., 2010). The paradigm concurrently
records Task-Evoked Pupillary Responses (TEPRs). The use of TERPs is relatively new in
developmental research (Falck-Ytter, 2008; Jackson & Sirois, 2009; Laeng, Sirois & Gredebäck,
2012; Verschoor et al., 2013). TERPs indicate motivational phenomena such as increased arousal
Development of sequential action control in infancy 15
(Bradley, Miccoli, Escrig & Lang, 2008; Laeng & Falkenberg, 2007), attention allocation (e.g.
Hess & Polt, 1960), cognitive load (Kahneman & Beatty, 1966) and mental effort (Kahneman,
1973; Hess & Polt, 1964). Whatever the exact interpretation of the measure, it enables us to
contrast acquisition contingent vs. non-contingent responses since all interpretations suggested
that dilations should be larger for actions requiring more processing. Furthermore, pupil TERPs
are sensitive to congruency in all ages, showing lesser dilation during congruent action
(Verschoor et al., 2013). Thus, given that we tested 9- and 12-month-olds, we mainly expected
congruency effects on RTs and TERPs.
In previous studies (that all used single-component actions), the definition of congruency
was straightforward: participants were exposed to two action-effect contingencies during
acquisition, in which responses Ra and Rb were followed by action effects Ea and Eb (Ra ! Ea; Rb
! Eb). Performing action Ra in response to (or as a result of being primed by) effect Ea in the test
phase (Ea ! Ra) would be considered congruent, while performing the same action in response
to Eb (Eb ! Ra) would be considered incongruent.
Introducing sequences that consist of two action components (components 1 and 2)
renders the definition somewhat more complicated (see Table 1). Our participants were exposed
to two sequences of actions (A and B) and their effects during acquisition: R1A ! E1A ! R2A !
E2a and R1B ! E1B ! R2B ! E2B. In the test phase, we presented the action effect of one of the
second action components (E2A or E2B) and we tested whether this would affect processes
related to the first action components (R1A and R1B). If infants represent the experienced action
sequences as a unity, cueing the effect of the second element (E2A or E2B) could affect the
activation of the first action elements (R1A or R1B). The pairings of effect E2A and action R1A
Development of sequential action control in infancy 16
(E2A ! R1A) or of effect E2B and action R1B (E2B ! R1B) were considered congruent, and the
pairings of E2A and action R1B (E2A ! R1B) or of E2b and action R1A (E2B ! R1A) incongruent.
Development of sequential action control in infancy 17
=== TABLE 1 ===
Table 1. The action sequences learned during acquisition and the congruent and
incongruent responses during test.
ACQUISITION
TEST
SEQUENTIAL ACTION
CONGRUENT
INCONGRUENT
R1A ! E1A ! R2A ! E2a
And
R1B ! E1B ! R2B ! E2B
E2A ! R1A
And
E2B ! R1B
E2A ! R1B
And
E2B ! R1A
Development of sequential action control in infancy 18
Finding any difference depending on congruency would provide evidence for a coherent
cognitive representation of sequential action in infants. Crucially, the direction of the effect
would speak to the internal structure of that representation: While chaining and integrative
models would lead one to expect facilitation (shorter latencies and smaller pupil dilations) in
congruent responses, concurrent activation models would predict the opposite.
Development of sequential action control in infancy 19
METHODS
Subjects
Two age groups were tested: 14 9-month-olds (mean: 8.94 months, SD= .37, SE=.9, 5
female) and 16 12-month-olds (mean: 11.99 months, SD= .42, SE=.10, 9 female), another 4 9-
and 7 12-month-olds were excluded for not meeting the criterion for the minimal amount of test
trials. They were recruited through the municipality and received small gifts as compensation.
An informed consent and a questionnaire regarding general health and development were
obtained. The infants were all healthy full-term and without pre- or perinatal complications.
Test environment and apparatus
During the experiment the infants sat in a specially designed, stimulus-poor booth on the
lap of their caretaker, who was seated in front of the eye-tracker apparatus. The distance between
eyes and apparatus was approximately 70 centimeters (the screen’s viewing angle was 34.1° by
21.8°). The behavior of the infants was monitored online by the experimenter from a separate
control room by means of a camera located above the apparatus. A 17 inch TFT-screen (1280 x
1024 pixels), equipped with an integrated Tobii T120 eye-tracker operating at 60 Hz, was used
for visual and auditory data presentation, and data collection. The Tobii T120 has an optimal
accuracy of .5° and allows for a certain amount of head movement by the subjects
(30x22x30cm). It recorded gaze direction and pupil-size. Stimulus presentation was controlled
by a PC running E-prime® software (Schneider, Eschman & Zuccolotto, 2002).
Stimuli
The visual stimuli used were as follows (see Figure 2). The background color of the
screen was grey. The fixation point was a brightly colored dot with a superimposed line drawing
Development of sequential action control in infancy 20
(4.3° by 4.3°). To keep infants interested, the color of the dot changed randomly from trial to
trial (selected from eight colors) and the line drawing was randomly selected (without
replacement) from a selection of 50 drawings (Snodgrass & Vanderwart, 1980). As Response
Areas (RA’s), we used 100 grayscale pictures from the “Nottingham scans” faces database,
(http://pics.psych.stir.ac.uk), displaying emotionally neutral frontal faces of 50 men and 50
women. Faces were chosen to elicit spontaneous saccades as they are known to attract infants’
attention (Goren, Sarty & Wu, 1975; Johnson, Dziurawiec, Ellis & Morton, 1991). To maximize
the chance of finding an effect, the faces looked at the participant, since Sato and Itakura (2013)
showed that eye contact enhances action-effect binding. We used two pairs of 200ms effect
sounds which were equalized on loudness, “tring” and “piew” (Verschoor et al.,2013, 2012) and
complex high- and low- note sound waves of 1574- and 776-Hz.
Procedure
Infants were tested at a time when they were likely to be alert. Prior to the experiment the
caretakers were instructed not to move after calibration and gently hold the infant in order to
maintain eye-tracker alignment, and to entertain the infant during the 1-min interruption between
calibration and the experiment. The eye-tracker was calibrated using a 9-point calibration
consisting of a small animation. The calibration was accepted with a minimum of eight points
acquired. The experimenter could play an attention-grabbing sound during the experiment. If this
no longer worked caretakers were encouraged to direct the infant’s attention to the middle of the
screen by pointing. Lighting conditions were kept constant.!Furthermore, luminance levels were
controlled for by presenting the stimuli in a random fashion. After completion an explanation of
the experiment was provided.
Development of sequential action control in infancy 21
Acquisition phase
The experiment began with an acquisition-phase of 36 trials (see Figure 2). If during the
acquisition phase the subject showed declining attention, the acquisition phase could be
shortened (minimum number of acquisition trials was set at 24). In each trial participants could
freely choose to perform one of two saccade sequences (R1A ! E1A ! R2A ! E2a or R1B ! E1B !
R2B ! E2B). Each saccade sequence consisted of two distinct actions, first one to the left or right
(R1A or R1B) whereafter an up- or downward action followed (R2A or R2B, depending on the
mapping assigned). Each saccade was followed by an effect-sound which was consistently
designated to left-, right-, up- and downward Response Areas (RA’s).
A trial started with the fixation dot. The dot disappeared after fixation on it for an interval
that varied (to remove any bias or habituation caused by fixed intervals), between 150- and 350-
ms. After disappearance, photographs of two different faces (randomly selected without
replacement from 100 pictures) appeared to the left and right. The faces served as Response
Area’s (RA’s). The 5.3° by 5.3° pictures appeared at 9.7° to center. To avoid perseverance to
either side across trials the images pulsated. One of them started shrinking to 4.1° while the other
started growing to 6.5° (side shrinking was randomized); one cycle from intermediate size to
small, to intermediate, to large and back to intermediate, took 2 s.
When a saccade towards one of the faces was detected it stopped pulsating and the other
face disappeared. Depending on the targeted side, one of two distinct 200ms effect-sounds
(“tring” or “piew”) was presented (E1A or E1B, the mapping was balanced across participants).
RA’s were defined as the maximum size of the pulsating images: 6.5° by 6.5°. A saccadic
response was defined as eye movement (minimally 4.3°) into the left or right response area.
Development of sequential action control in infancy 22
Immediately after the effect the current face disappeared and reappeared 7.8° above or below
that location (depending on the mapping) in the same dimension and continued to pulsate serving
as RA again (again defined as the maximum size of the image). Upon detection of a saccade to
that location (minimal 1.3°), one of two distinct 200ms effect-sounds (E2A or E2B, “high note” or
“low note”) was presented (the mapping was balanced across participants). RTs were defined as
the time interval between disappearance of the fixation dot and detection of a saccade in the
secondary RA. The maximum allowable RT was 2000ms; if by then no response was detected,
the trial was repeated. After each trial, an inter-trial-interval of 500ms was used.
Test phase
The test phase of 32 trials followed directly afterwards (see Figure 2). The minimum
number of test trials to enter analysis was 22. A trial started with the fixation dot as during
acquisition. However, after fixation (fixation time identical to acquisition), the dot remained on
display for 200ms during which an effect-sound was presented that was previously triggered by
one of the two secondary eye-movements (E2A or E2B). Thereafter the dot disappeared. Then, two
identical 5.3° by 5.3° images of the same face (randomly selected without replacement) appeared
9.7° to the left and right of the screen center serving as RAs. The two images were identical to
minimize gaze preference. To further reduce bias the faces pulsated in synchrony, meaning that
they either both grew or shrank (randomized and with the same motion parameters as during
acquisition). Again, the images were expected to evoke saccades (R1A or R2B). The question of
interest was whether the direction of these saccades (R1A or R2B) would be biased by the tones
(E2A or E2B). Except for absence of auditory effects after the saccades, the remaining procedure
was as during acquisition.
Development of sequential action control in infancy 23
=== FIGURE 2 ===
T1
T2
T3
T4
TIME
1 or 2
3 or 4
TIME
T1
T2
T3
3 or 4
T1
T2
T3
T4
TIME
1 or 2
3 or 4
TIME
T1
T2
T3
3 or 4
Figure 2.
Acquisition trial.: Each trial starts with an intertrial interval of 500 ms. T1: A fixation
dot is displayed at screen center. T2: After successful fixation, faces appear at either side of the
screen where they started to pulsate. T3: Depending on the saccade target, the face at the other
side disappears and an effect sound is played for 200 ms. T4: Depending on which side was
chosen the face moves up or down whereafter a second saccade is made and a second sound
effect is played for 200 ms.
Test trial. Each trial starts with an intertrial interval of 500 ms. T1: A fixation dot is
displayed at screen center. After succesful fixation one of the secondary effects from the
acquisition is played. T2: The dot diasppears whereafter the same face appears on both sides. T3:
The participant freely chooses where to saccade.
Development of sequential action control in infancy 24
Data acquisition
E-prime® 1.2 (Psychology Software Tools, Sharpsburg, PA) was used to collect RTs, the
number of left and right responses and congruent and incongruent responses during test. The
gaze- data files Tobii produced were imported into BrainVision Analyzer 1.05 (BrainProducts
GmbH, Gilching, Germany) to analyse gaze position and pupillary data. Depending on analysis,
segments were created from 2000ms before the presentation of the sound onset or RT, to 8000ms
after, while allowing overlapping segments. Responses were sorted on congruency of the
response and stimulus- and response-locked functions were averaged (Verschoor et al., 2013).
Following Bradley et al. (2008), pupil-diameter measurement began after the initial pupil reflex
caused by the fixation stimulus. Visual inspection showed it to end around 500ms after effect
presentation (see Figure 4) (see also Verschoor et al., 2013). Dilations were calculated as the
percentage of dilation relative to the baseline to make the data comparable across age groups.
The percentage of trials rejected due to erroneous data points (leaving 29 valid trials on average)
did not differ across age groups, p > .8. Dilations of both eyes were averaged to reduce noise.
Artifacts and blinks detected by the eye-tracker were corrected using a linear interpolation
algorithm, after which a 10 Hz low-pass filter was applied (c.f., Hupe, Lamirel & Lorenceau,
2009). Further artifact rejection was done using a threshold based approach, including those
segments with pupil sizes between 1 and 5 mm, and a maximum change in pupil size of .03mm
in 17ms. Gaze data were recorded in pixel coordinates, averaged between eyes and filtered using
a 10Hz low-pass filter.
Given that the acquisition of action-effect associations is sensitive to the same factors as
stimulus-response learning (Elsner & Hommel, 2004), the Number Of Completed Acquisition
Development of sequential action control in infancy 25
Trials (NOCAT) was taken as an individual measure of action-effect learning. The Mean
Acquisition Reaction Time (MART) was taken as an individual measure for general speed and
activity. Both NOCAT and MART variables were used as covariates in the analyses when
appropriate.
RESULTS AND DISCUSSION
Acquisition phase
First we tested for age group differences in dependent variables collected during
acquisition to ensure that the learning experiences of the age groups were comparable (see Table
2). All ANOVA’s were performed with age group as a between-subjects factor. There were no
effects for the percentage of completed acquisition trials (p >.5), mean RT (p >.5), or the
percentage of right vs. left responses (p >.2) or upward vs. downward responses (p >.2). Two
reliable effects were obtained for RTs. Firstly, horizontal response location interacted with age
group, F(1,25)=6.25, p= .019, η2p=.20. Separate analyses showed no main effect in 9-month-
olds (RT-left=999ms, RT-right=104 6ms) and a tendency toward faster right-ward responses in
12-month-olds, F(1,12)=3.84, p=.074, η2p=.24 (RT-right=982ms, RT-left=1089ms). Secondly,
vertical response location interacted with age group, F(1,25)=4.63, p=.04, η2p=.16. Separate
analyses showed no main effect in 9-month-olds (RT-up=1008ms, RT-down=1037ms) and a
tendency toward faster downward responses in 12-month-olds, F(1,12)=3.82, p=.07, η2p=.24
(RT-up=1089, RT-left=982ms). We also performed a repeated measures ANOVA on RT’s with
Time (dividing the responses in three equal bins) and found no effect (p >.13). Lastly, we
performed a repeated measures ANOVA on the partial RTs of the primary action to test if
contraction vs. expansion had an effect on these partial RTs. We found a significant effect,
Development of sequential action control in infancy 26
F(1,28)=175, p <.001, η2p=.86, indicating responses toward contracting pictures were slower
(partial RT-contracting=603ms, partial RT-expanding=428ms).
Development of sequential action control in infancy 27
=== TABLE 2 ===
Table 2. Mean scores of acquisition phase (standard deviation in brackets).
AGE GROUP
SCORES
Percentage of
completed
acquisition
trials
Percentage of
left responses
RT in ms
RT
left
RT
right
RT up
RT
down
9-month-olds
92.9
(11)
42.8
(38)
1007
(81)
999
(107)
1046
(90)
1008
(116)
1037
(83)
12-month-olds
92.0
(14)
38.5
(40)
1023
(83)
1089
(167)
982
(73)
982
(78)
1089
(164)
Development of sequential action control in infancy 28
We concluded that the learning experiences were comparable across age groups. The
interaction of horizontal response location and age on RTs might reflect the fluctuating
emergence of general right-side preference during the first year (Corbetta & Thelen 1999;
Michel, 1998), which also affects infants’ eye movements (Cohen, 1972). An orthogonal effect
may be reflected in our analysis of upward vs. downward RTs. However, little is known about
such preferences. Additionally, we found that infants responded faster toward expanding
pictures. This effect probably reflects automatic attentional processes to avoid collisions (e.g.,
Kayed & Van der Meer, 2000; Van Hof, Van der Kamp & Savelsbergh, 2006). Importantly,
these observations are not detrimental to our research question since both age groups received
approximately the same amount of training for all combinations of response locations.
Test phase
All ANOVA’s were performed with age group as a between-subjects factor. There was
no effect on the percentage of completed test trials (p >.4).
Response frequency
Overall, participants looked more often (64%) to the right than left side, F(1,28)=9.00,
p=.02, η2p=.19, but the effect did not interact with age. More important for our purposes,
ANOVAs with congruency as within-subjects factor were not significant, adding MART,
NOCAT or both as covariates didn’t change this ( p’s >.2). We concluded that, if infants control
sequential actions, this does not seem to affect the probability to choose a particular sequence.
Development of sequential action control in infancy 29
Reaction times
There were no reliable effects with regard to overall RT (p > .6), left vs. right response
location (p >.3) (see Table 3) or inter-trial interval, (p > .5) (which we analyzed because the test-
phase was self-paced). More important for our purpose, an ANOVA with congruency (see Table
1 for mapping details) as within-subjects factor, revealed a significant effect indicating 29ms-
slower responses for congruent trials, F(1,28)=4.15, p=.05, η2p=.13; the interaction with age
was not significant (p >.3). Although the statistics did not necessitate further exploration, given
our directed hypothesis about age effects, we looked at both age groups separately. In the 9-
month-olds the effect was not significant (p >.4) while in the 12-month-olds it was F(1,15)=5.47,
p =.03, η2p=.27. A non-parametric Wilcoxon signed rank test confirmed these results (9-month-
olds: Z=-1.57, p=0.88, 6 of 14 infants showed the pattern, 12-month-olds: Z=-2.02, p=0.04, 12 of
16 infants showed the pattern). However, adding NOCAT as a covariate into the separate
ANOVA for the 9-month-olds resulted in a significant effect (F(1,12)=4.96, p=.05, η2p=.29).
Development of sequential action control in infancy 30
=== TABLE 3 ===
Table 3. Mean frequency and RT scores of test phase (standard deviation in brackets).
AGEGROUP
SCORES
Percentage
completed
test trials
Percentage
left
responses
Percentage
congruent
responses
ITI
ms
RT
ms
RT
Congruent
ms
RT
Incongruent
ms
9-month-olds
93.5
(11)
43.2
(38)
47.5
(8)
1637
(323)
431
(90)
440
(104)
424
(91)
12-month-
olds
96.5
(10)
29.0
(21)
49.3
(7)
1563
(393)
447
(74)
468
(83)
425
(83)
Development of sequential action control in infancy 31
Our main finding is: cueing of the secondary action of the action sequence interfered with
executing its first, as evidenced by the longer RT’s for congruent responses in the 12-month-olds
(see Table 1 for mapping details). Results were less clear in the 9-month-olds. The signed rank
test did not show significant results while using Number of Completed Acquisition Trials
(NOCAT) as a covariate in the RT analysis resulted in a significant effect in 9-month-olds. This
suggests that the NOCAT was an important factor for the strength of the effect in this age group
whereas the 12-month-olds showed a ceiling effect for the NOCAT necessary for the uptake of
the sequential action. The fact that we found an effect can be considered as evidence that 12-
month-olds control sequential action. Performing two consecutive actions is sufficient to
integrate them into a coherent representation. Twelve-month-olds apparently represent action
sequences in a format that allows for interactions between the codes of their individual elements
(which excludes fully symbolic formats). Moreover, our findings provide specific support for
concurrent activation theories, as only these would predict interference. Furthermore our findings
suggest sequential action control is developing in 9-month-olds.
Development of sequential action control in infancy 32
=== FIGURE 3 ===
Figure 3. Mean reaction times (+SE) for 9-month-olds (N=14) and 12-month-olds (N =
16) in congruent and incongruent test trials.
Development of sequential action control in infancy 33
Pupil dilation
To accommodate for the variable RTs across age groups and conditions, we considered
both stimulus-locked and response-locked Task-Evoked Pupillary Responses (TEPR’s). The
stimulus-locked analysis for congruent and incongruent (see Table 1 for mapping details)
responses TERPs used a 500ms pre-effect baseline (Beatty & Lucero-Wagoner, 2000). A
repeated measures ANOVA on TERPs with congruency as within subjects factor revealed no a
priori effects of congruency on baselines (-500 to 0ms), p’s > .7. Adults’ TEPRs start from 200
to 300ms after stimulus onset and peak in the range of 500ms to 2000ms (Beatty, 1982; Beatty &
Lucero-Wagoner, 2000). We therefore calculated the mean TERPs for congruent and
incongruent responses as the mean percentage of change from baseline to 500-2000ms post
effect onset. An ANOVA with MART as covariate revealed that, overall, participants exhibited
larger relative pupil dilations during congruent responses, F(1,27)=4.12, p=.05, η2p=.13,
independent of age group (p >.7). Since the time window was based on adult findings, which
likely underestimate the pupillary reactions of the slower infants (Verschoor et al., 2013), we
reran the analysis with a 1000-2500ms post effect onset time window. Again, pupil dilations
were significantly larger in congruent trials, F(1,25)=5.03, p=.03, η2p=.16, independently of
age, p >.09 (see Figure 4).
Development of sequential action control in infancy 34
=== FIGURE 4 ===
Figure 4. Relative pupil sizes for congruent and incongruent responses to baseline,
stimulus-locked.
Development of sequential action control in infancy 35
For the response-locked analysis, we calculated the percentage of dilation from a 700-ms
time window starting at saccade onset, to the same 500ms pre-stimulus baseline. An ANOVA
with MART as covariate yielded a tendency for larger relative dilation in congruent trials,
F(1,27)=3.51, p=.07, η2p=.12, while the interaction with age group was not significant, p >.8
(see Figure 5). Adding NOCAT as additional covariate resulted in a significant effect
(F(1,26)=5.48, p=.03, η2p=.17), again without an interaction with age group (p >.9).
Development of sequential action control in infancy 36
=== FIGURE 5 ===
Figure 5. Relative pupil sizes for congruent and incongruent responses to baseline,
response locked.
Development of sequential action control in infancy 37
Finding larger relative pupil dilations for congruent responses in both stimulus-locked
and response-locked analyses corresponds nicely to the outcome of the RT analysis. Cueing the
second component of an action sequence makes the execution of the first slower and more
effortful.
Gaze position
In the test phase we primed the second action of the two-element sequences carried out in
the acquisition phase by presenting the corresponding action effect (see Table 1 for mapping
details). Activating the second element of the sequence might affect action planning directly.
One of the second elements was an upward movement while the other was a downward
movement. Priming these elements by their effects might induce a vertical bias in the direction of
the cued element. Alternatively: the selection of the primary action results in forward inhibition
of the second. This might induce the opposite bias. To investigate these effects, we analyzed the
mean vertical deviation from the horizontal midline toward the primed action element as a
function of congruency. To do this we collapsed all vertical deviations from horizontal midline
toward the direction cued to one side and divided the data segments according to congruency
from stimulus onset to 650ms thereafter (corresponding to the mean RT plus mean random ITI)
and compared these segments to a 150ms pre-effect baseline (the minimum fixation time before
effect onset).
There were no a priori effects of congruency on baselines, p> .5. An ANOVA with
MART as covariate showed that during congruent responses gaze position deviated vertically
significantly less toward the direction cued by the effect sound, F(1,27)=4.83, p=.04, η2p=.15
Development of sequential action control in infancy 38
(effect size = 22 pixels; see Figure 6) than in incongruent responses, and this effect did not vary
with age, p >.5. We additionally performed separate ANOVAs with MART as covariate testing
congruent- and incongruent- responses against no deviation. The effect was significant for
incongruent responses (F(1,27)=4.70, p=.04, η2p=.15) and did not vary with age ( p=.2), but not
significant for congruent responses (p >.26).
Development of sequential action control in infancy 39
=== FIGURE 6 ===
Figure 6. Vertical distance from midline toward cued direction of gaze position in pixels
for congruent and incongruent responses. Time=0, is the moment the effect starts.
Development of sequential action control in infancy 40
Our gaze position findings show that priming the second action component results in
activation of the vertical component only in incongruent trials. This might be due to competition
between activated components in congruent trials, as concurrent models would hold: the
selection of the primary action results in forward inhibition of the second. This finding provides
further evidence for the concurrent model of sequential action control in infants and highlights its
temporal dynamics. Moreover, the finding is not in accordance with integrative models since no
vertical bias was found for the primary actions in congruent trials.
GENERAL DISCUSSION
The aim of the current study was to examine (the development of) the cognitive substrate
for sequential action control in 9- to 12-month-olds using a novel gaze-contingent paradigm.
Relying on the idea that if two elementary actions are bound together in a sequence, priming the
secondary action component would influence the availability of the primary component, we
presented the infant participants with a two-step action sequence. While chaining and integrative
models would lead one to expect facilitation in congruent responses, concurrent activation
models would predict the opposite. Our major finding is that priming the second action inhibits
the primary action, as indicated by latencies and pupil dilation. Secondly, we found an effect on
gaze position indicating that action control inhibits the second component of an action sequence
whilst preparing the first part of the sequence. Our findings on three different measures suggest
an emerging ability for sequential action control in 9-month-olds that fully develops by the first
birthday, and is best captured by concurrent activation models (Estes, 1972).
From a developmental perspective our findings extend behavioral studies suggesting
infants can control sequential action (e.g., Claxton, Keen & McCarty, 2003; McCarty, Clifton
Development of sequential action control in infancy 41
&Collard, 1999), and studies showing that this ability to be present only under ideal
circumstances in 9-month-olds, or only a subset of subjects of this age group (Bauer, Wiebe,
Waters & Bangston, 2001; Carver & Bauer, 1999, 2001; Elsner, Hauf, & Aschersleben, 2007;
Lukowski et al., 2005 Waters & Bangston, 2001). In addition, they are in accordance to studies
suggesting that during the second half of the first year the ability to encode ordinal information
comes online (Brannon, 2002; Picozzi, de Hevia, Girelli & Macchi-Cassia, 2010; Suanda,
Tompson & Brannon, 2008). The fact that evaluation of third-person sequential action is
apparent significantly earlier in development, in 6- to 7-month-olds (Baillargeon, Graber, DeVos
& Black, 1990; Biro, Verschoor & Coenen, 2011; Csibra, 2008; Gergely & Csibra, 2003;
Verschoor & Biro, 2012), tentatively suggests either a different cognitive substrate or a
dissociation between evaluation and production (e.g., Verschoor et al., 2013).
Furthermore, our findings relate to infant studies (Claxton, Keen & McCarty, 2003;
McCarty, Clifton & Collard, 1999; Cox & Smitsman, 2006) and cognitive theories (e.g.
Botvinick & Plaut, 2004; Constantinidis, Williams & Goldman-Rakic, 2002; Cooper & Shallice,
2006; Estes, 1972; Norman & Shallice, 1986 Rumelhart & Norman, 1982) that implicate
inhibition as an imperative faculty for controlling sequential action. Interestingly, inhibitory
control begins to emerge toward the end of the first year and undergoes rapid development
across the toddler period and into the preschool years, a pattern coinciding with age-related
changes in frontal lobe maturation and connectivity (Diamond, 2002, Diamond et al., 2007,
Luria, 1973; Wolfe & Bell, 2007). This onset around 1 year of age relates to the developmental
timeline revealed by our results and supports our interpretation that inhibitory processes play an
important role in the ontogenesis of sequential action control.
Development of sequential action control in infancy 42
Note that the development of inhibitory capacities has been linked to the development of
time perception itself (Zélanti & Droit-Volet, 2011; Mäntylä, Carelli & Forman, 2007).
Furthermore, in clinical (Barkley, 1997; Gerbing, Ahadi & Patton, 1987; Montare, 1977) and
healthy populations (Foster et al., 2013) tests of inhibition show robust relationships to indices of
timing (-deficiency). Thus the question arises whether the inhibitory mechanisms found are
specific for action control or are general for representing temporal events (Fuster, 1993, 2002;
Norman & Shallice, 1986). The literature reviewed here seems to point to the latter, suggesting
temporal representations in the form of concurrent activation may be a precondition for
sequential-action control. One might thus speculate that very early sequential-action evaluation
(e.g., Verschoor & Biro, 2012) depends on non-ordinal, or non-temporal representations.
Interestingly, our paradigm offers a possibility to address these and related questions in future
research.
Concerning current theories on action control, our results seem to point to limitations in
explanatory power of the current ideomotor theory (Hommel et al., 2001; Shin, Proctor &
Capaldi, 2010) with regard to sequential action control, as this theory would predict activation of
actions by their effects whereas we find inhibition of the primary action. Sidestepping the idea
that inhibition of the primary action is not the same as inhibition of the sequence as a whole, Hull
(1931) pointed out that binding of sequential action is possible by relating the sequences to
internal or external context such as an overarching goal. An interesting question that such
reasoning poses, is what kind of context and how such context may be incorporated in an
overarching goal representation. Indeed action-effect learning can be context-specific (Kiesel &
Hoffmann, 2004) which could accommodate such overarching ideomotor representations of
action sequences. Thus we may not have succeeded in cueing the overarching goal because of
Development of sequential action control in infancy 43
insufficient context in the cue, and might have gotten stuck in the underlying concurrent level of
representation. Indeed, Kiesel and Hoffmann (2004) have shown that the same actions can be
accessed by different effect anticipations. They also claim that that response initiation has to wait
for the anticipation of the effects that trigger the response (see also Kunde, 2003), suggesting it
takes longer to initiate a response if it produces a long effect. Although this theory would also
predict slower initiation for sequential actions, if one thinks of a sequence of (actions and) effects
as a long effect, the theory cannot account for competitive processes our findings suggest. Thus
we suggest ideomotor theory should be enhanced by incorporating overarching- and sequential-
levels of goal representation. Such hierarchical structure might be conceived as either structural
(Cooper & Shallice, 2006) or epiphenomenal (Botvinick & Plaut, 2004) to concurrent activation
models.
Nonetheless, our findings do suggest ideomotor processes play a role in sequential action
since we inhibited the primary and secondary action components by cueing the secondary action
via its effect. Ideomotor processes have indeed been implicated in sequential action (Koch,
Keller & Prinz, 2004). Ziessler (1994, 1998) and Elsner et al. (2007) found that action-effects
play an important role in sequence learning and Stöcker & Hoffmann (2004) found that action
effects facilitate chunking. Furthermore, the activation of the secondary vertical component in
the incongruent trails is direct evidence for ideomotor theory. Thus although the current findings
extend cognitive theories of action control by suggesting that ideomotor theory needs
elaborations to incorporate sequential action (see for a similar point: Herbort & Butz, 2012;
Kachergis, Wyatte, O'Reilly R, De Kleijn, & Hommel 2014), they do not counter the ideomotor
principle itself.
Development of sequential action control in infancy 44
Another theoretical implication of our results is that the repeated successiveness of
actions in the acquisition phase sufficed to bind the actions into a sequence. This raises the
question of what the exact criteria might be for such binding to occur. One could think of several
dimensions for such criteria; our study suggests repetition, temporal closeness and spatial
closeness might play a role. This is a particularly interesting question since its answer might
provide clues as to how the cognitive system generates new action sequences, never performed
before. However, more research is needed to answer such questions in more detail. For now, our
results suggest that concerning infants’ own action control, sequential action can be picked up by
exploration and does not necessarily depend on elaborate abstract or explicit strategies
(Cleeremans & McClellend, 1991) that operate in terms of efficiency (e.g. Gergely & Csibra,
2003) or causality (e.g., Woodward & Sommerville, 2000).
Even though we consider the present findings as a first step towards the understanding of
sequential-action control in infants, further research is needed to explore this model in greater
detail. Although our paradigm produced continuous data which are temporally rich, they
nevertheless should be considered as a snapshot of processes at work in sequential-action
control. Earlier we hypothesized that cueing the secondary effect of the two-step sequence might
have been too poor in contextual information to cue the overall sequence, thus resulting in local
competition effects in an underlying concurrent level of representation. Alternatively, more
dynamic explanations could be considered. For instance, it could be that the inhibition of the first
sequence components was due to temporal differences in the process of activating the individual
action components on the one hand and of the overarching goal representation on the other. It is
well documented that initiating more complex sequential actions takes longer than initiating
simpler actions (Henry & Rogers, 1960; Rosenbaum, 1987). One could thus speculate that
Development of sequential action control in infancy 45
cueing the second action component activated the underlying representation quickly, but it took
more time to activate the overarching goal representation. The eventual activation of this goal
representation could have facilitated both components of the sequence (as proponents of
integration theories might suggest), but that may have taken too long to be picked up by our
measures. As a consequence, the inhibition that our findings point to may reflect an initial state
of a dynamic action-planning process. Another possibility would be that cueing an action
component that is not yet appropriate (as none of the secondary components was a valid action in
the test phase) resulted in the inhibition of not only the first component but of the entire
sequence, perhaps including the goal representation. We cannot exclude that the second
component of each sequence was also inhibited—although the lack of gazing “away” from the
direction cued by the second component suggests that it was not. The current experiment was not
set up to distinguish between these more detailed scenarios.
Other studies have shown end state comfort effects in infants (Claxton, Keen & McCarty,
2003; McCarty, Clifton & Collard, 1999; Cox & Smitsman, 2006) indicative of integrated
representations of sequential action. In the current study we did not find evidence for this model.
Nonetheless, we do not wish to claim that integrated sequential action control cannot occur in
infancy. We would like to stress that the chaining, concurrent and integrated theories of
sequential-action control are by no means mutually exclusive or complete. They posit useful
approximations for understanding sequential actions, yet depending on exact circumstances
relating to practice, content, time pressure and strategy, some models may be more adept than
others at explaining specific empirical phenomenon. In our opinion a future all-encompassing
theory of sequential action control will probably encompass elements of all three classes of
theories. Indeed our results on gaze directions indirectly suggest an influence of the secondary
Development of sequential action control in infancy 46
action on the primary action that was cancelled out by counteracting inhibitory and excitatory
processes. However, this does not diminish the importance of showing that concurrent processes
are at work in infant sequential-action control.
One could question whether our findings are generalizable to other action systems
(manual, postural etc.). Ideomotor theory makes no distinction between effectors and effect
modalities, and ideomotor motivated research does not suggest such a distinction. Furthermore,
saccade-effect learning is now established in adults (Huestegge & Kreutzfeldt, 2012; Herwig &
Horstmann, 2011) and infants (Verschoor et al., 2013) suggesting that the oculomotor system is
controlled in the same way as for instance the system for manual action control. We
acknowledge that saccadic eye movements operate on very short timescales where priming and
inhibition may play a larger role than in other types of actions that involve gross movements of
the body (e.g. reaching and locomotion) that operate on relatively slower timescales. Future
research will have to clarify this issue.
Altogether it remains essential to develop a comprehensive theory of (the development
of) sequential action representation, which specifically addresses the question of how novel
components are integrated into a sequential plan, how the sequence is generated, whether this
requires hierarchical representations and what types of information are incorporated in
overarching goals. We are confident that further modifications of our paradigm will help to
increase insight into the general cognitive mechanisms underlying action planning (e.g., by
cueing the first action component and examining how this affects the availability of the second)
since our synergy of methodology provides various measures (frequency-, RT-, pupillary- and
gaze position measures) that can pick up different dynamic aspects of the planning process.
Development of sequential action control in infancy 47
In conclusion, the current study shows that sequential action can be picked up by
exploration and does not depend on elaborate abstract strategies. Furthermore, the present
findings demonstrate that 12-month-olds are able to construct action plans comprising more than
one element, and use inhibition mechanisms as suggested by concurrent activation models to put
elements into the right temporal order. And lastly, we provide further evidence for the claim that
the ability for sequential-action control develops between 9 and 12 months of age.
DISCLOSURE
The authors declare no competing interests.
ACKNOWLEDGEMENT
This research was supported by the Netherlands Organization for Scientific Research. We
thank the reviewers for their useful suggestions and especially thank Thijs Schrama for technical
support and Henk van Steenbergen for analytical support.
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FIGURES
Goal
A1 A2
Goal
A1 A2
Goal
A1 A2
A B C
Figure 1. Models of sequential action. :Schematic representation of activation in A:
Chaining models of sequential action, activation cascades forward through the different
elementary actions, B: Concurrent models of sequential action, all elementary actions are
activated simultaniously where after competion through inhibition ensures the correct order of
execution, C: Integrated models of sequential action, the sequence of actions has been integrated
into a new elementary action.
Development of sequential action control in infancy 65
T1
T2
T3
T4
TIME
1 or 2
3 or 4
TIME
T1
T2
T3
3 or 4
T1
T2
T3
T4
TIME
1 or 2
3 or 4
TIME
T1
T2
T3
3 or 4
Figure 2.
Acquisition trial.: Each trial starts with an intertrial interval of 500 ms. T1: A fixation
dot is displayed at screen center. T2: After successful fixation, faces appear at either side of the
screen where they started to pulsate. T3: Depending on the saccade target, the face at the other
side disappears and an effect sound is played for 200 ms. T4: Depending on which side was
chosen the face moves up or down whereafter a second saccade is made and a second sound
effect is played for 200 ms.
Test trial. Each trial starts with an intertrial interval of 500 ms. T1: A fixation dot is
displayed at screen center. After succesful fixation one of the previous action effects is played.
T2: The dot diasppears whereafter the same face appears on both sides. T3: The participant
freely chooses where to saccade.
Development of sequential action control in infancy 66
Figure 3. Mean reaction times (+SE) for 9-month-olds (N=14) and 12-month-olds (N =
16) in congruent and incongruent test trials.
Development of sequential action control in infancy 67
Figure 4. Relative pupil sizes for congruent and incongruent responses to baseline,
stimulus-locked.
Figure 5. Relative pupil sizes for congruent and incongruent responses to baseline,
response locked.
Development of sequential action control in infancy 68
Figure 6. Vertical distance from midline toward cued direction of gaze position in pixels
for congruent and incongruent responses. Time is 0, is the moment the effect starts.
Development of sequential action control in infancy 69
Table 1. The action sequences learned during acquisition and the congruent and
incongruent responses during test.
ACQUISITION
TEST
SEQUENTIAL ACTION
CONGRUENT
INCONGRUENT
R1A ! E1A ! R2A ! E2a
And
R1B ! E1B ! R2B ! E2B
E2A ! R1A
And
E2B ! R1B
E2A ! R1B
And
E2B ! R1A
Table 2. Mean scores of acquisition phase (standard deviation in brackets).
AGE GROUP
SCORES
Percentage of
completed
acquisition
trials
Percentage of
left responses
RT in ms
RT
left
RT
right
RT up
RT
down
9-month-olds
92.9
(11)
42.8
(38)
1007
(81)
999
(107)
1046
(90)
1008
(116)
1037
(83)
12-month-olds
92.0
(14)
38.5
(40)
1023
(83)
1089
(167)
982
(73)
982
(78)
1089
(164)
Development of sequential action control in infancy 70
Table 3. Mean frequency and RT scores of test phase (standard deviation in brackets).
AGEGROUP
SCORES
Percentage
completed
test trials
Percentage
left
responses
Percentage
congruent
responses
ITI
ms
RT
ms
RT
Congruent
ms
RT
Incongruent
ms
9-month-olds
93.5
(11)
43.2
(38)
47.5
(8)
1637
(323)
431
(90)
440
(104)
424
(91)
12-month-
olds
96.5
(10)
29.0
(21)
49.3
(7)
1563
(393)
447
(74)
468
(83)
425
(83)
... In adults, the PLR sets in with a latency of about 200 ms, which decreases with the brightness of the stimulus (Mathôt, 2018). In infancy research, where bright stimuli could be startling and therefore a low variance in stimulus luminosity is preferred, a latency of the PLR of about 500 ms can be expected and has to be taken into account (Verschoor, Paulus, Spapé, Bíró, & Hommel, 2015). The latency can easily be determined in the data when the time of luminosity change is known, because the pupil restricts fast at first before fully adjusting to the new ambiance light. ...
... Gaze data were processed in relation to a priori defined areas of interest (AOI) that After careful visual inspection, pupil data were shifted to the right by 500ms. Infants' pupils react slower than adults (Verschoor, Spapé, Bíró, & Hommel, 2013;Verschoor et al., 2015) and therefore need more time to adapt to a change in stimulus. Also, by not including the phases of pupillary constriction (PC) following a stimulus onset in the average, a more accurate representation of the tonic pupil dilation is achieved (see Hepach & Westermann, 2016). ...
... After careful visual inspection, pupil data were shifted to the right by 500ms. Infants' pupils react slower than adults (Verschoor et al., 2013(Verschoor et al., , 2015 and therefore need more time to adapt to a change in stimulus. Also, by not including the phases of pupillary constriction (PC) following a stimulus onset in the average, a more accurate representation of the tonic pupil dilation is achieved (see Hepach & Westermann, 2016). ...
Thesis
At the end of their first year, infants start to engage in meaningful, if nonverbal communication with their caregivers. At the same time, they appear to show sophisticated understanding of physical objects and their continued existence during occlusion. Many studies have brought forward evidence of this early conceptual understanding of referentiality and object permanence, but have remained vulnerable to the critique of supporters of leaner, non-mentalistic explanations of infant behavior. The goal of this thesis was to investigate how infants at the end of their first year process the referential content of socialcommunicative cues, and represent objects during occlusion, using (neuro-)physiological measures that are more resistant to low-level perceptual accounts than traditional behavioral measures. Therefore, two different methodological approaches were taken: On the one hand, pupillometry was used to measure cognitive load during the presentation of socially meaningful scenes and surprising occlusion-related events. On the other hand, EEG was used to find neuro-correlates of object representation in response to social and nonsocial cues. In particular, increase in gamma band activity was interpreted as a marker for object maintenance. Three studies explored infants’ comprehension of social-communicative cues and object representation. In the first two studies, pupil dilation was measured to investigate expectation elicited by pointing (Study 1) and expectation elicited by an occlusion event (Study 2) in violation-of-expectation paradigms. In Study 1 (Chapter 2), I found that infants expected an object to appear after they had seen an agent point towards the occluder at 12 months, but not at 8 months, and not after a non-social control cue. In Study 2 (Chapter 3), I found that 18-month-olds, but not 10-month-olds, expected an object in a nonsocial occlusion experiment. In Study 3 (Chapter 4), I measured activity in the EEG gamma band to investigate pointing comprehension and spontaneous object expectation in two experiments. Infants saw an occlusion event followed by a cue which was either social-communicative or nonsocial (Experiment 1) or social-communicative or social-noncommunicative (Experiment 2). In the first experiment, I was able to establish the previously reported object maintenance effect and a new response pertaining to the communicative cue in 12-month-olds. In the second experiment, I found the object maintenance effect only in the social-communicative, but not in the social-noncommunicative control condition, in 10-month-olds. The findings of Study 1 support the hypothesis that infants understand the referential content of communicative cues, like declarative pointing, around their first birthday. The divergence of the results between Study 1 and Study 2 led me to suspect that object representation may not be independent from social cues. The findings of Study 3 further emphasize the idea that cognitive processing of object occlusion events may be influenced by the communicative context in which they occur.
... In adults, task-evoked pupil dilation has been well established as an index of increased arousal or cognitive load for some time (see Beatty & Lucero-Wagoner, 2000;Goldwater, 1972;Laeng , Sirois & Gredebäck, 2012;Sirois & Brisson, 2014, for reviews), yet it is a recent development 1 in infant research (Gredebäck & Melinder, 2010;Jackson & Sirois, 2009). Over the last decade however, pupillometry has increasingly been recognized as a uniquely useful method to investigate a broad range of infant cognitive processes (Upshaw et al., 2015;Addyman, Rocha, & Mareschal, 2014;Chen & Westermann, 2018;Csink, Mareschal, & Gliga, 2021;Fawcett, Arslan, Falck-Ytter, Roeyers & Gredebäck, 2017;Geangu, Hauf, Bhardwaj & Bentz, 2011;Hellmer et al., 2018;Hepach & Westermann, 2013;Hochmann & Papeo, 2014;Jessen et al., 2016;Kaldy & Blaser, 2020;López Pérez, Ramotowska, Malinowska-Korczak, Haman & Tomalski, 2020;Morita, Slaughter, Katayama, Kitazaki, Kakigi & Itakura, 2012;Verschoor, Paulus, Spapé, Biro, & Hommel, 2015;Zhang, Jaffe-Dax, Wilson, & Emberson, 2018;Zhang & Emberson, 2020). In fact, there is growing recognition that pupil diameter can be a complementary or better index of cognitive processes than looking time data (Gustafsson, Brisson, Beaulieu, Mainville, Mailloux & Sirois, 2015;Hepach & Westermann, 2016;Krüger et al., 2020;Pätzold & Liszkowski, 2019;Sirois & Jackson, 2012), including in areas such as early identification of autistic spectrum disorders (Rudling, Nyström, Bölte & Falck-Ytter, 2021; see also de Vries, Fouquaet, Boets, Naulaers & Steyaert, 2021;Reisinger et al., 2020). ...
Article
Full-text available
Infants’ expectations of the world around them have been extensively assessed through the violation of expectation paradigm and related habituation tasks. Typically, in these tasks, longer looking to impossible events following familiarisation with possible equivalents is taken to reflect surprise at their occurrence, thus revealing infants’ knowledge. In this study, the role of learning during the task itself is explored by switching the archetypal approach on its head and familiarising infants to impossible events. In a partial replication of Jackson and Sirois (2009), nine-month-old infants were presented with short video clips of toy trains moving around a circular track. A tunnel over a short section of the track meant trains were briefly occluded as they completed a circuit. In impossible versions of events, the train switched colours while occluded by the tunnel. Both looking times and pupil dilation were used as dependent measures. Using a factorial design in which perceptual (novelty-familiarity) and conceptual (possible-impossible) variables were independently and jointly analysed, we show that infants showed greater responding to possible events than to impossible events following familiarisation. Pupil dilation data successfully allowed for more precise interpretation of infants’ perception of events than could have been achieved through looking times alone. These findings suggest a central role for learning in violation of expectation tasks, and also further support the use of pupil dilation as a dependent measure in infancy work.
... In this context, the development of action control in infants using gaze-contingent paradigms was investigated. These studies addressed, for example, oculomotor reinforcement learning (Vernetti, Smith, & Senju, 2017) and mechanisms of controlling the environment via gaze (Verschoor, Paulus, Spape, Biro, & Hommel, 2015;Wang et al., 2012;Wass, Porayska-Pomsta, & Johnson, 2011). These studies generally show that infants are already able to anticipate oculomotor action outcomes and to control their environment using their eyes. ...
Thesis
Full-text available
Humans use their eyes not only as visual input devices to perceive the environment, but also as an action tool in order to generate intended effects in their environment. For instance, glances are used to direct someone else's attention to a place of interest, indicating that gaze control is an important part of social communication. Previous research on gaze control in a social context mainly focused on the gaze recipient by asking how humans respond to perceived gaze (gaze cueing). So far, this perspective has hardly considered the actor’s point of view by neglecting to investigate what mental processes are involved when actors decide to perform an eye movement to trigger a gaze response in another person. Furthermore, eye movements are also used to affect the non-social environment, for instance when unlocking the smartphone with the help of the eyes. This and other observations demonstrate the necessity to consider gaze control in contexts other than social communication whilst at the same time focusing on commonalities and differences inherent to the nature of a social (vs. non-social) action context. Thus, the present work explores the cognitive mechanisms that control such goal-oriented eye movements in both social and non-social contexts. The experiments presented throughout this work are built on pre-established paradigms from both the oculomotor research domain and from basic cognitive psychology. These paradigms are based on the principle of ideomotor action control, which provides an explanatory framework for understanding how goal-oriented, intentional actions come into being. The ideomotor idea suggests that humans acquire associations between their actions and the resulting effects, which can be accessed in a bi-directional manner: Actions can trigger anticipations of their effects, but the anticipated resulting effects can also trigger the associated actions. According to ideomotor theory, action generation involves the mental anticipation of the intended effect (i.e., the action goal) to activate the associated motor pattern. The present experiments involve situations where participants control the gaze of a virtual face via their eye movements. The triggered gaze responses of the virtual face are consistent to the participant’s eye movements, representing visual action effects. Experimental situations are varied with respect to determinants of action-effect learning (e.g., contingency, contiguity, action mode during acquisition) in order to unravel the underlying dynamics of oculomotor control in these situations. In addition to faces, conditions involving changes in non-social objects were included to address the question of whether mechanisms underlying gaze control differ for social versus non-social context situations. The results of the present work can be summarized into three major findings. 1. My data suggest that humans indeed acquire bi-directional associations between their eye movements and the subsequently perceived gaze response of another person, which in turn affect oculomotor action control via the anticipation of the intended effects. The observed results show for the first time that eye movements in a gaze-interaction scenario are represented in terms of their gaze response in others. This observation is in line with the ideomotor theory of action control. 2. The present series of experiments confirms and extends pioneering results of Huestegge and Kreutzfeldt (2012) with respect to the significant influence of action effects in gaze control. I have shown that the results of Huestegge and Kreutzfeldt (2012) can be replicated across different contexts with different stimulus material given that the perceived action effects were sufficiently salient. 3. Furthermore, I could show that mechanisms of gaze control in a social gaze-interaction context do not appear to be qualitatively different from those in a non-social context. All in all, the results support recent theoretical claims emphasizing the role of anticipation-based action control in social interaction. Moreover, my results suggest that anticipation-based gaze control in a social context is based on the same general psychological mechanisms as ideomotor gaze control, and thus should be considered as an integral part rather than as a special form of ideomotor gaze control.
... After careful visual inspection, time windows for analyses of pupil size were set to 500ms after the event boundaries of the stimuli. Infants' pupils react slower than adults' [37] and therefore need more time to adapt to a change in stimulus. Also, by not including the phases of pupillary constriction (PC) following a stimulus onset in the average, a more accurate representation of the tonic pupil dilation is achieved [32]. ...
Article
Full-text available
Object permanence has been investigated with a variety of paradigms and measures, yielding heterogeneous findings. The current study employed a novel Violation-of-Expectation paradigm measuring pupil dilation as indicator of cognitive effort and surprise. Across repeated trials, infants watched videos of animated toys either stopping in an open door frame or moving across the open door frame off screen. The door then closed and opened up again to reveal either the toy, or an empty space. In Experiment 1, 18-month-olds’s pupils dilated in response to the unexpected empty outcome more than to the expected empty outcome, establishing the paradigm as a suitable measure of violation of object expectation. Using the same paradigm, Experiment 2 revealed an absence of this object expectation effect for 10-month-olds. Results are discussed with regard to paradigmatic aspects and developmental differences. It is suggested that young infants do not automatically represent occluded objects upon perceiving occlusion events, and that occlusion events may initially require relevance in terms of individual activity or social interaction.
... In sum, they concluded that children's helping behaviors are driven by a genuine care for others. However, even if pupil dilation seems to be an extremely useful measure in studies with preverbal infants (Hepach & Westermann, 2016), an increase in pupil dilation is an unspecific measure that can indicate a range of different psychological processes such as increased attention, emotional arousal, cognitive effort, or surprise (Bradley, Miccoli, Escrig, & Lang, 2008;Laeng, Sirois, & Gredebäck, 2012;Preuschoff, Hart, & Einhauser 2011;Privitera, Renninger, Carney, Klein, & Aguilar, 2010;Sirois & Brisson, 2014;Verschoor, Paulus, Spapé, Biro, & Hommel, 2015; see also Pletti et al., 2017). Concerning Hepach's findings, Pletti and colleagues concluded that "we cannot state that pupil dilation in these studies is due to a genuinely altruistic motivation, rather than a desire to interact with the experimenter, or to comply with her requests" (Pletti et al., 2017, p. 3). ...
Thesis
Full-text available
Recent empirical work has shown that toddlers will already help a stranger without being requested at the age of 14 months. This stunning phenomenon has attracted the attention of many researchers all around the world, leading to a wave of studies that have strongly broadened our knowledge on the development of children’s prosocial behavior. However, many crucial questions are still unanswered or remain a matter of much debate. How should the term “prosocial behavior” be defined, and how should the different subtypes of prosocial behavior be categorized? Why do children help? What is the role of socialization in the emergence and development of children’s prosocial behavior? The present dissertation thesis attempts to answer these three questions. I first elaborate on the definition of prosocial behavior, stressing the importance of distinguishing different domains of prosocial behavior such as helping, informing, cooperating, comforting, and sharing. In the first study, I attempted to fill a methodological gap in the field—namely, the lack of a questionnaire accounting for the domain-specific conceptualization of prosocial behavior. Therefore, I developed a parental questionnaire to assess the main prosocial domains in toddlerhood—namely, helping, comforting, and sharing—and gathered empirical evidence on its longitudinal measurement invariance, thereby legitimizing its use for future research. Second, I addressed the question whether children’s prosocial behaviors are driven by a genuine concern for others (prosocial motivation hypothesis), or by affiliative goals (social motivation hypothesis), which is a topic of much debate in the current developmental literature. Therefore, in the second study, children were tested in a helping and in a comforting task as well as in an imitation task that is a well-established indicator of the motivation to affiliate with others. Results showed positive relations between the two prosocial domains and imitation. These findings suggest that affiliative motives play an important role in explaining children’s interindividual differences in prosocial behaviors and should be considered in order to better understand the relations between different domains of prosocial behavior. Overall, the second study provides empirical evidence for the social motivation hypothesis. Finally, the influence of socialization on the emergence and development of children’s prosocial behavior has been a topic of much debate. The third study focuses on this issue and analyzes toddlers’ helping behavior in two different cultural contexts (Delhi and Münster). Results yielded significant differences in toddlers’ helping behaviors as well as cross-cultural differences in parental socialization practices. On an intracultural level, culture-specific relations between parental socialization practices and children’s helping behavior were found. These findings demonstrate that culture affects toddlers’ helping behavior and their motivations from very early in ontogeny.
... Careful visual inspection of the time line of the pupil data showed that changes in luminance in the video stimuli (e.g., bubbles cutting to the start of the scene) caused pupillary restriction (PC) with a delay of 500 ms across all conditions. This delay in response corresponds to previous reports showing that infants' pupils take about 500 ms to adapt to luminance changes in stimuli (Verschoor, Paulus, Spapé, Bíró, & Hommel, 2015). We therefore placed all time windows of analyses concerning pupil data 500 ms later than the corresponding events in the video. ...
... Based on these findings, Hepach (2017) concluded that children's pupil dilation represents a 'prosocial arousal' which reflects the extent to which children are concerned about the person in need, assuming that children's prosocial behaviors are primarily based on other-oriented concerns. However, this assumption cannot be made outright, because, as pointed out by Pletti and colleagues (2017), several studies have shown that pupil dilation can indicate a range of other things, such as cognitive effort, surprise, and attentional and/ or emotional processes (Bradley, Miccoli, Escrig, & Lang, 2008;Laeng, Sirois, & Gredebäck, 2012;Preuschoff, 2011;Privitera, Renninger, Carney, Klein, & Aguilar, 2010;Sirois & Brisson, 2014;Verschoor, Paulus, Spapé, Biro, & Hommel, 2015). Thus, there might be other plausible causes explaining children's increase in pupil dilation. ...
Article
The current study focuses on the motivation that drives children's prosocial behavior by analyzing the association between prosocial behavior and children's imitative tendencies, which is a well‐established indicator of the motivation to affiliate with others. Therefore, we tested 30‐month‐old children (N = 59) in an imitation task and two domains of prosocial behavior, namely helping and comforting. Using a confirmatory factor analysis, we demonstrated that the two prosocial domains were explained by a common factor, which was in turn significantly related to children's imitation. Overall, our findings suggest that affiliative motives should be considered in order to better understand children's motivations to engage in prosocial behaviors. This article is protected by copyright. All rights reserved.
... Participants in the study were 14 months of age, with the motor abilities required to control action sequences (cf. Verschoor, Paulus, Spapé, Biro, & Hommel, 2015) and an interest to participate in the current experimental task requiring reach-to-place actions. ...
Preprint
Prospective motor control, a key element of action planning, is the ability to adjust one’s actions with respect to task demands and action goals in an anticipatory manner. The current study investigates whether 14-month-olds are able to prospectively control their reaching actions based on the difficulty of the subsequent action. We used a reach-to-place task, with difficulty of the placing action varied by goal size and goal distance. To target prospective motor control, we determined the kinematics of the prior reaching movements using a motion-tracking system. Peak velocity of the first movement unit of the reach served as indicator for prospective motor control. Both difficulty aspects (goal size and goal distance) affected prior reaching, suggesting that both these aspects of the subsequent action have an impact on the prior action. The smaller the goal size and the longer the distance to the goal, the slower infants were in the beginning of their reach towards the object. Additionally we modeled movement times of both reaching and placing actions using a formulation of Fitts’ law. The model was significant for placement and reaching movement times. These findings suggest that 14-month-olds are able to plan their future actions and prospectively control their related movements with respect to future task difficulties.
... Yet, given the unspecific nature of physiological arousal, which is granted by the author just a few sentences later-"(c)hanges in pupil size do not appear to indicate the stimulus' valence" (p. 52)-, using pupil dilation as a direct measure of prosocial motivation is not warranted: Current literature suggests that increase in pupil dilation might indicate increased attention, emotional arousal, cognitive effort such as memory processes, target detection and/or surprise (Bradley et al., 2008;Privitera et al., 2010;Preuschoff, 2011;Laeng et al., 2012;Sirois and Brisson, 2014;Verschoor et al., 2015). These processes are not systematically ruled out in the studies that the review mentions, so assuming that an increase in pupil dilation signals an increase in motivation is a big and hasty step. ...
Article
The ability to act efficiently plays an important role in everyday human life. The current study investigated efficient motor planning in 2- to 14-year-old children and adults (N = 246) in two different object manipulation tasks that involved everyday objects (a cup and a spoon). Importantly, we manipulated whether or not the efficient controlled grasp was incongruent with the habitual use of the object. We assessed to what extent participants planned their grasping action in an anticipatory controlled manner or relied on the habitual use of an object. We found the ability of efficient movement planning to be correlated between the two conceptually different tasks. Furthermore, the interplay of controlled and habitual processes of action control showed different developmental patterns for the two tasks and does not indicate a simple linear developmental trend. Thus, this study expands our knowledge on the ontogeny of efficient motor planning and highlights the developmental dynamics of the interplay of controlled and habitual processes in goal-directed action control.
Article
Full-text available
Four experiments provide converging evidence that serial learning in a serial reaction task is based on response-effect learning, mediated by the learning of the relations between a response and the stimulus that follows it. In Experiment 1, the authors varied the stimulus sequence and the response-stimulus relations while holding the response sequence constant. Learning effects depended on the complexity of the response-stimulus relations but not on the stimulus-stimulus relations. In Experiment 2, transfer of serial learning from 1 stimulus sequence to another was only found when both sequences had identical response-stimulus relations. In Experiment 3, a variation of the stimulus sequence alone had no effect on serial learning, whereas in Experiment 4 learning effects increased when the response-stimulus relations but not the stimulus-stimulus relations were simplified. These findings suggest that serial learning is based on mechanisms of voluntary action control.
Chapter
Full-text available
Much effort has been made to understand the role of attention in perception; much less effort has been placed on the role attention plays in the control of action. Our goal in this chapter is to account for the role of attention in action, both when performance is automatic and when it is under deliberate conscious control. We propose a theoretical framework structured around the notion of a set of active schemas, organized according to the particular action sequences of which they are a part, awaiting the appropriate set of conditions so that they can become selected to control action. The analysis is therefore centered around actions, primarily external actions, but the same principles apply to internal actions—actions that involve only the cognitive processing mechanisms. One major emphasis in the study of attentional processes is the distinction between controlled and automatic processing of perceptual inputs (e.g., Shiffrin & Schneider, 1977). Our work here can be seen as complementary to the distinction between controlled and automatic processes: we examine action rather than perception; we emphasize the situations in which deliberate, conscious control of activity is desired rather than those that are automatic.
Book
This book provides a review of historical and current research on the function of the frontal lobes and frontal systems of the brain. The content spans frontal lobe functions from birth to old age, from biochemistry and anatomy to rehabilitation, and from normal to disrupted function. The book covers a variety of disciplines including neurology, neuroscience, psychiatry, psychology, and health care.
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A physiological measure of processing load or "mental effort" required to perform a cognitive task should accurately reflect within-task, between-task, and betweenindividual variations in processing demands. This article reviews all available experimental data and concludes that the task-evoked pupillary response fulfills these criteria. Alternative explanations are considered and rejected. Some implications for neurophysiological and cognitive theories of processing resources are discussed.
Chapter
This chapter describes a series of experiments on the cognitive activity that immediately precedes and allows the execution of voluntary actions. Cognitive activity is referred to as “motor programming” and its resultant representations are referred to as “motor programs.” The control of finger sequences is important in keyboard entry and musical performances. Finger sequences can be performed extremely rapidly and can be executed without direct conscious control. The chapter describes the processes of motor programming and the structure of motor programs. The data of interest are the times and identities of produced responses. If the timing of responses within a sequence changes as a function of an alternative sequence, the changes can be attributed to the operations underlying the programming of the sequence to be performed. A corollary of the motor-program editor model is that successive response sequences can be programmed by changing features that distinguish one sequence from the next. This method of programming is more efficient than the one in which each sequence must be programmed from scratch regardless of its relation to the sequence that has just been performed.
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The frontal lobes play a most important role in human mental activity. Frontal lobe lesions lead to disturbances of conscious behavior. The formal intellect of those patients may remain relatively intact, but they are unable to properly interact with their cultural environment. The delicate components of their mental activity are lost, their critical faculties are violated, and they become spontaneous. Their ability to work out programs of proper behavior, as it were, becomes lost. Specific features of activity of the human frontal lobes may best be investigated under conditions where the patient must fulfill some special task. It is important to study the changes that develop in the frontal lobes of the brain during mental exercise. Electrophysiological methods have been used, along with other methods, to determine the exact nature of that difficulty in mental activity. This chapter discusses the comparison of records of normal subjects and of patients with a delusional form of schizophrenia subjected to special tasks. Mental strain is of particular importance there. When the frontal lobes become nonfunctional, mental activity markedly slows down. The functional state of the cortical frontal lobes and their participation in mental activity are to a considerable degree determined by the corticosubcortical correlations and, above all, by influences exerted by the reticular formation of the midbrain.
Presents a standardized set of 260 pictures for use in experiments investigating differences and similarities in the processing of pictures and words. The pictures are black-and-white line drawings executed according to a set of rules that provide consistency of pictorial representation. They have been standardized on 4 variables of central relevance to memory and cognitive processing: name agreement, image agreement, familiarity, and visual complexity. The intercorrelations among the 4 measures were low, suggesting that they are indices of different attributes of the pictures. The concepts were selected to provide exemplars from several widely studied semantic categories. Sources of naming variance, and mean familiarity and complexity of the exemplars, differed significantly across the set of categories investigated. The potential significance of each of the normative variables to a number of semantic and episodic memory tasks is discussed. (34 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved).