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Developmental Cognitive Neuroscience 6 (2013) 102–112
Contents lists available at ScienceDirect
Developmental Cognitive Neuroscience
journal homepage: http://www.elsevier.com/locate/dcn
Relational congruence facilitates neural mapping of spatial
and temporal magnitudes in preverbal infants
Daniel C. Hyde a,∗ , Chris L. Porter b , Ross Flom c , Sarah A. Stone b
a
b
c
Department of Psychology, University of Illinois at Urbana-Champaign, United States
School of Family Life, Brigham Young University, United States
Department of Psychology, Brigham Young University, United States
a r t i c l e
i n f o
Article history:
Received 11 March 2013
Received in revised form 24 June 2013
Accepted 12 August 2013
Keywords:
Event-related potentials
Infancy
Perception
Intersensory
Multisensory
Sensory integration
Attention
Memory
Auditory processing
Visual processing
PSW
Nc
a b s t r a c t
Mental representations of space, time, and number are fundamental to our understanding of the world around us. It should come as no surprise that representations of each are
functional early in human development, appear to share a common format, and may be
maintained by overlapping cortical structures. The consequences of these similarities for
early learning and behavior are poorly understood. We investigated this issue by assessing neurophysiological processing of audio-visual temporal and spatial magnitude pairs
using event-related potentials (ERPs) with young infants. We observed differential early
processing and later enhanced attentional processing for pairings of spatial and temporal
magnitudes that were relationally congruent (short visual character paired with a short
auditory tone or long visual character paired with a long auditory tone) compared to the
same stimuli paired in a relationally incongruent manner (short visual character with the
long auditory tone or long visual character with a short tone). Unlike previous studies,
these results were not dependent on a redundancy of information between the senses or
an alignment of congruent magnitude properties within a single sense modality. Rather,
these results demonstrate that mental representations of space and time interact to bias
learning before formal instruction or the acquisition of spatial language.
© 2013 Elsevier Ltd. All rights reserved.
1. Introduction
Immanuel Kant (1781/1998) proposed that a primitive
understanding of space, time, and number is innate and
forms the basis of later learning and experience. Kant’s
philosophical assertion has garnered support in light of
research showing that preverbal human infants, as well as
many non-human animals, have the cognitive capacity and
underlying neural structure to support mental representation of space, time, and number (Dehaene and Brannon,
∗ Corresponding author at: University of Illinois at Urbana-Champaign,
621 Psychology Building, 603 East Daniel Street, Champaign, IL 61821,
United States. Tel.: +1 217 300 0382.
E-mail addresses: [email protected], [email protected]
(D.C. Hyde).
1878-9293/$ – see front matter © 2013 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.dcn.2013.08.003
2010; Feigenson, 2007; Lourenco and Longo, 2011). Furthermore, research with human adults demonstrates that
mental representations of space, time, and number interact with each other (e.g. Casasanto and Boroditsky, 2008;
Cohen Kadosh et al., 2007; Pinel et al., 2004; Walsh, 2003).
For instance, Casasanto and Boroditsky (2008) found that
judgments made regarding the temporal duration of visual
stimuli are influenced by the physical length of the stimuli.
Likewise, past work (e.g. Algom et al., 1996; Cohen Kadosh
et al., 2007; Tzelgov et al., 1992) with the “numerical Stroop
task” has shown that adults’ judgments of numerical size
(e.g. which is numerically larger?) are influenced by the
physical size of the Arabic digits (i.e. 2 vs. 7). These interactions suggest that representations of one dimension (e.g.
size) activate representations in the other (e.g. number).
Unfortunately, the origin of these interactions remains
hotly debated and largely unknown. One possibility is
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D.C. Hyde et al. / Developmental Cognitive Neuroscience 6 (2013) 102–112
that interactions between distinct representations of space,
time, and number arise as a result of repeated associations
between particular pairings of space, time, and/or number in the context of sensory-motor experience, language,
or culture (Boroditsky, 2000, 2011; Gelman and Williams,
1998; Johnson, 2003; Piaget, 1927/1969). Alternatively,
interactions between representations of space, time, and
number might arise because of an innate link, heretofore
referred to as a functional overlap, between these dimensions (e.g. Cantlon et al., 2009; Pinker, 1997; Srinivasan and
Carey, 2010; Walsh, 2003). Some have hypothesized that
innate functional overlap could be realized as an initially
privileged relationship between distinct representations of
space, time, and number (e.g. van Marle and Wynn, 2006),
while others hypothesize that innate functional overlap
could be realized as an generalized magnitude system,
which may later become differentiated over development
(e.g. Lourenco and Longo, 2010; or see Lourenco and Longo,
2011 for a review). In either case, the current study tests for
the presence of functional overlap in 5-month old infants,
before associations between space, time, and number could
likely be culturally, linguistically, or educationally constructed.
Three lines of evidence suggest a similarity, or overlap, in the way space, time, and number are mentally
represented. First, these representations appear to share
a common analog format, where quantities are represented as approximate physical magnitudes proportional
to that being represented (see Meck and Church, 1983;
Walsh, 2003). Second, representations of space, time, and
number have common or signature behavioral limits (see
Dehaene and Brannon, 2010 for a review). For example,
the ability of human infants, human adults, and many
non-human animals to compare two magnitudes, whether
they be spatial, temporal, or numerical, is limited by
the ratio of the two magnitudes being compared rather
than the absolute difference between them (e.g. Brannon
et al., 2006, 2008; Lipton and Spelke, 2003; van Marle
and Wynn, 2006). Infants of the same age make comparisons at about the same level of precision, or ratio,
regardless of the magnitude domain (e.g. Brannon et al.,
2006, 2007; Feigenson et al., 2004). While the particular precision of each domain diverges in later childhood,
all domains show continued gains in precision into adulthood (e.g. Droit-Volet et al., 2008; Halberda and Feigenson,
2008). Third, representations of space, time, and number
have also been hypothesized to share a common neural
substrate (Fias et al., 2003; Izard et al., 2009; Meck and
Church, 1983; Walsh, 2003). For example, neuroimaging
and neurophysiological work suggests overlap in regions
of the intraparietal sulcus (IPS) involved in the representation and/or comparisons of number and physical size (i.e.
area or length) (e.g. Pinel et al., 2004; Cohen Kadosh et al.,
2007; Cohen Kadosh and Henik, 2006). In sum, while evidence suggests behavioral and neural similarities in the
way space, time, and number are represented, the functional significance of this similarity for learning remains
unclear. In the current study, we ask if similarity between
representations of space and time biases early learning.
Specifically, can young 5- to 6-month-olds learn magnitude
relationships between dimensions of space and time more
103
readily when they are relationally congruent compared to
when they are relationally incongruent?
Several recent studies suggest that the overlap between
representations of space, time, and number plays a functional role in learning, especially early in development
(deHevia and Spelke, 2010; Lourenco and Longo, 2010; Mix
et al., 1999, 2002; Srinivasan and Carey, 2010). For example, work with pre-school and elementary school children
suggests that early numerical calculation abilities may be
aided by corresponding cues to spatial magnitude, or extent
(Mix et al., 2002). Similarly, understanding of fractions may
be facilitated by overlap in the way in which numerical
and spatial magnitudes are represented (e.g. Mix et al.,
1999). Again, like with human adults, explicit instruction,
linguistic metaphor, or cultural experience may explain the
facilitation of learning of children in these contexts.
Recent work with pre-verbal infants suggests the learning may be facilitated between dimensions before such
experience. For example, Lourenco and Longo (2010)
demonstrated that infants are able to form interchangeable associations between number and space and time in
learning which stimuli go together. Additional work shows
that infants learn associations between relationally congruent line lengths and numerical quantities more readily
(smaller numbers of objects associated with shorter line
lengths/larger numbers of items associated with longer
lines) than they learn relationally incongruent pairings of
the same stimuli (shorter lines with larger numbers of
items/longer lines with smaller number of items) (deHevia
and Spelke, 2010). In both of these experiments (i.e.
deHevia and Spelke, 2010; Lourenco and Longo, 2010),
however, pairings were made only over visual dimensions.
Thus, it is unclear whether infants made the associations
because of functional overlap between abstract representations of space, time, and number, an abstract generalized
magnitude, or whether the results were due to common
visual-specific properties of the stimuli.
In an attempt to discern whether the ability to learn
associations between space and time was a product of
functional overlap between abstract mental representations or whether previous results are due to common
visual properties, Srinivasan and Carey (2010) required
such associations between space and time to be made
across two different sense modalities. Srinivasan and Carey
(2010) found that infants are better at learning associations
between visually presented length (space) and temporal
duration of an auditory tone (time) when they are relationally congruent (e.g. relatively long duration tone with
long line, short duration tone with short line) than when
they are relationally incongruent. Moreover, Srinivasan
and Carey (2010) argue that the functional overlap between
abstract representations of space and time allow the correspondences between them to be spontaneously aligned,
facilitating the learning for relationally congruent pairings
but not for incongruent pairings.
While the results of Srinivasan and Carey (2010) support
their position, it should be noted that temporal magnitude information was conveyed both aurally and visually.
That is, the duration of stimulus was redundant across
the senses, or could be obtained both visually and aurally.
Spatial and temporal information was also presented in
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perfect temporal synchrony from stimulus onset to stimulus offset. This is significant because related work has
shown that, within the domain of number as well as other
domains, redundant and temporally synchronous information conveyed across multiple senses enhances learning
compared to bimodal presentation without redundancy
(e.g. Bahrick and Lickliter, 2000; Jordan et al., 2008; Flom
and Bahrick, 2010). Therefore, it is unclear if the ability to learn congruent pairings in Srinivasan and Carey
(2010) was dependent on the redundancy of temporal
magnitude information across both sense modalities (see
Bahrick and Lickliter, 2000; Bahrick et al., 2004 for reviews).
Alternatively, despite using audio-visual stimuli, differential learning between congruent and incongruent pairs in
Srinivasan and Carey (2010) could also have taken place
purely within the visual domain. Visual length and visual
duration changed as a function of condition. It is plausible
that the duration of visual stimulation was mapped to the
spatial extent of the visual stimulation and this mapping
was easier when the temporal and spatial information was
congruent compared to when it was incongruent. In this
case, auditory information could be completely ignored
and still produce the observed results. If this is so, it is
still unclear whether differential learning occurs as a result
of functional overlap in representations of space and time
abstracted away from basic sensory properties or whether
differential learning can be explained based on basic sensory correspondences, or lack thereof, between temporal
and spatial properties of primary visual stimulation.
The current study was designed to overcome the limitations of previous work by using audio-visual stimuli with
asynchronous offsets, thereby presenting non-redundant
audio and visual magnitude information for length and
time in distinct sense modalities (see Fig. 1). In this way,
the learning of space–time magnitude pairings could not
be explained by temporal synchrony of information or
redundancy of spatial and temporal information across
the senses. In addition, differential learning in the current study could not be explained by temporal and spatial
magnitude correspondences within a single sense modality because visual–temporal information was held constant
across all test conditions. Finally, while behavioral measures used within previous studies (e.g. deHevia and
Spelke, 2010; Lourenco and Longo, 2010; Srinivasan and
Carey, 2010) have revealed interesting patterns of results,
they provide limited, if any, insight into the level of processing at which differential processing or learning may occur.
It is possible, for example, that enhanced learning of congruent spatial–temporal pairings is due to facilitated early
processing, more attention toward, and/or better memory
for congruent pairings compared to incongruent pairings.
The current study allowed for an assessment at each of
these levels by employing event-related potentials (ERPs)
to measure the brain response.
Neurophysiological work with infants employing ERPs
has documented early and mid-latency posterior activity
related to processing of high-level properties of complex
stimuli such as the configuration or structure of faces and
objects (e.g. N290 and P400), mid-latency anterior activity related to attentional orienting (Nc), and late anterior
slow wave activity related to memory (e.g. PSW, NSW,
Fig. 1. Audiovisual stimulus pairings used for training and test phases of
the experiment. All visual stimuli were presented for 1000 ms and auditory stimuli were presented for 250 or 750 ms. The audiovisual onset was
always synchronous and offset was always asynchronous. (A) Short caterpillar paired with a short duration tone. (B) Long caterpillar paired with a
long duration tone. (C) Short caterpillar paired with a long duration tone.
(D) Long caterpillar paired with a short duration tone.
or LPC) (e.g. Halit et al., 2004; Scott and Nelson, 2006;
Scott, 2011; Carver et al., 2003; de Haan and Nelson, 1997;
Nelson, 1994; Richards, 2003; Grossmann et al., 2009;
Quinn et al., 2006). Given the established functional properties of these distinct ERP components, measuring the
infants’ neurophysiological response to relationally congruent and incongruent pairings may not only provide
further evidence of functional overlap between representations of space and time, but may also help determine at
what level differences arise.
In order to investigate the neural basis of crossmodal magnitude learning, we recorded event-related
potentials as 5-month old infants viewed asynchronous,
non-redundant, audiovisual space–time pairings. Separate groups of infants were familiarized to audio-visual
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D.C. Hyde et al. / Developmental Cognitive Neuroscience 6 (2013) 102–112
length-time pairings that were either relationally congruent (a long visual image was paired with a long auditory
tone, or a short image was paired with a short tone) or
relationally incongruent (short tone with long image or
vice versa) (Fig. 1). The same auditory tones and visual
cartoon characters were used in the training of both
groups, but their relative pairings were different. This
training phase was necessary to familiarize children
with the range of magnitudes and particular pairings,
as previous work has shown that young children may
understand magnitudes better when defined in contrast
to other magnitudes (rather than in isolation) (see Duffy
et al., 2005). After a training phase, all participants were
shown equal numbers of familiar and novel test pairings
of the same visual–spatial lengths and auditory durations.
Importantly, both groups of infants viewed the exact
same test pairings of stimuli. Whether a given test pairing
was familiar or novel was dependent on the training
condition they had previously viewed (e.g. if trained with
relationally congruent pairs, then relationally incongruent
pairings were novel and vice versa). Thus, differences in
brain responses to test trials between groups could not be
readily explained by basic sensory differences between the
test stimuli as all infants saw the same set of test stimuli.
Instead, differences in neural processing between training
conditions would likely to be due to the type of training
they previously received (i.e. congruent or incongruent).
Specifically, we examined differential learning in the training conditions by comparing event-related brain signatures
of early high-level processing, mid-latency attentional
orienting, and later memory updating. If infants are able to
quickly and reliably learn both relationally congruent and
incongruent pairings, then the brain processes reflecting
early high level processing, attention, and/or memory
should discriminate between familiar and novel stimulus
pairings regardless of the training condition. However, if
learning is facilitated by relationally congruent pairings
compared to incongruent pairings, then brain processes
reflecting high-level processing, attention, and/or memory
should discriminate familiar and novel test pairings in
those infants who were exposed to the congruent pairings
during the training phase but not in those infants exposed
to the incongruent pairings during the training phase.
2. Materials and methods
2.1. Participants
Thirty-two five-month old infants (18 females; M
age = 152 days) were randomly assigned to a relationally
congruent (n = 16) or relationally incongruent training condition (n = 16). An additional 62 infants participated but
were excluded from the analyses: 31 for early termination
of experiment due to fussiness, crying, or inattentiveness
and 31 for retaining too few good data segments after ERP
artifact rejection. This attrition rate is within the range of
attrition rates in other ERP studies of similar-aged infants
(e.g. Hyde et al., 2010a,b; Hyde and Spelke, 2011; Izard et al.,
2008; Quinn et al., 2006).
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2.2. Stimuli and procedure
Infants were initially exposed to 20 relationally congruent (10 spatially long image-temporally long tone/10
spatially short image-temporally short tone) or 20 relationally incongruent (10 spatially long image—temporally
short tone/10 spatially short image—temporally long tone)
audio-visual length-time pairings. Stimuli were presented
in a pseudorandom order with the constraint that each (of
the two) space–time pairings had to be presented before
re-randomization occurred. After the training period, all
infants were shown the same 44 test images of familiar (22
trials) or novel (22 trials) pairings of the same stimuli using
the same pseudo-random procedure described above (each
of the four pairings presented in a random order before
re-randomization occurred). Length stimuli consisted of
cartoon images of a yellow caterpillar of differing lengths
(short and long) presented on a white background (Fig. 1).
Stimuli were adapted with permission from Srinivasan and
Carey (2010). Specifically, we adapted two of the more
extreme versions of “long” and “short” visual and auditory stimuli that differed in magnitude by a 1:3 ratio, as
previous infant studies have shown this difference to be
sufficient for behavioral discrimination of spatial and temporal information at 5-months of age (Brannon et al., 2006,
2008). The short caterpillar consisted of three overlapping
concentric body segments 2.5 in. in height and 2.5 in. in
length. The long caterpillar consisted of 11 overlapping
concentric body segments 2.5 in. in height but 7.75 in. in
length. Both caterpillars had two eyes and antennas on
the right-most segment to look like a head. Time stimuli consisted of the auditory tones lasting 250 ms (short
temporal duration) and 750 ms (long temporal duration)
played at approximately 70 decibels (Fig. 1). Congruent
familiarization pairings consisted of equal numbers of trials with the longer caterpillar paired with the temporally
longer tone and the shorter caterpillar paired with the temporally shorter tone. Incongruent familiarization pairings
consisted of equal numbers of trials containing the shorter
tone paired with the longer caterpillar and the longer tone
paired with the shorter caterpillar. Two exemplars were
used for each relationship (congruent or incongruent) to
make it less likely that the average ERP response to familiar
and novel pairings would be due to idiosyncratic sensory
properties of a particular stimulus pairing used and more
likely due to the overarching relational congruence of stimuli in relation to training.
Critically, the temporal and spatial information were not
redundant across the senses. Visual stimuli were always
presented for 1000 ms and, while onset of the visual and
auditory tones were synchronous, offset of the visual and
auditory stimulus was never synchronous (determined
by the length of the auditory stimulus: either 250 ms
or 750 ms). All trials were followed by a blank-screen
inter-stimulus interval that varied randomly in length
from 900 to 1500 ms (1000 ms stimulation + 900–1500 ms
ISI = 1900–2500 ms trial duration).
Stimuli were presented from a 17-in. computer screen
and computer speakers approximately 35–50 cm from the
infant seated in a parent’s lap. The parent was instructed to
look at the back of the infant’s head instead of the display in
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order to blind them from the experimental condition that
was being presented. Parents were also instructed not to
speak to the infant in an attempt to reduce environmental
interference. Looking behavior was monitored online, both
training and test trials were only started when the infant
was looking at the screen, and the experiment was paused
when infants looked away for more than 1 s. If the baby
became fussy, began to cry, or continually looked away,
data collection was terminated. Halfway through the familiarization period and two times during the testing phase a
short break was taken by showing the infant a picture of an
animal with an accompanying animal sound (e.g. picture of
a dog with a barking sound, picture of duck with quacking
sound, etc.). This was done in an effort to reduce boredom
and recapture infants’ attention to the video screen. This
rest/break stimulus was presented at the same point in the
experiment for all infants.
2.3. Data acquisition and reduction
Infants’ heads were first measured and then, while the
vertex was being located and marked on the baby’s scalp,
the appropriate size sensor net was soaked in a potassium chloride solution. While the infant sat in a parent’s
lap, the sensor net was systematically placed on the head
with reference to the identified vertex and left and right
mastoid bones. Before data collection, impedances were
checked and maintained below 50 k. The ongoing EEG
was then recorded from scalp locations using a 64 channel
EGI HydroCel Sensor Net (Electrical Geodesics Inc., Eugene,
OR) as infants were presented with stimuli in a dimly lit
room. Data were recorded at 250 samples per second and
digitally filtered online at 0.1–100 Hz, referenced to the
vertex.
Data from infants that completed the experiment were
further processed in three steps. First, raw data were lowpass filtered at 30 Hz, segmented into epochs from 200 ms
before to 1450 ms after stimulus onset, and baseline corrected to the 200 ms before the stimulus was presented.
Second, two experienced staff members independently
visually examined each epoch for artifacts. Any epoch containing an eye blink, eye movement, excessive noise, or
more than 12 bad channels was rejected from further analysis. Questionable epochs were discussed between staff
members until consensus could be reached. Any infant
retaining less than 10 good epochs in either test type
(familiar or novel test pairings) after artifact rejection
was eliminated from the final analysis (see Section 2.1
for exact numbers). Remaining acceptable epochs were
further processed by running an automated bad channel
replacement algorithm based on spherical spline interpolation from surrounding good channels for trials containing
less than 13 bad channels, then creating averages for each
test type (familiar and novel test pairings) for each subject, re-referencing the data to the average reference, and
again baseline correcting to 200 ms before stimulus onset
to correct for any absolute amplitude differences created
by processing. In addition to averages for each test type, a
grand average for both test types (collapsed across familiar
and novel pairings) was created for each training condition separately for visual inspection and peak latency
analysis purposes. Individual participants included in the
final analysis contributed no less than 10 trials per condition, and, on average, 12.328 trials per condition. There
were no significant differences or interactions in the number of trials retained between Training Conditions or Test
Types (all p’s > .18) (congruent training: M familiar test trials = 12.50, M novel test trials = 11.50; incongruent training:
M familiar test trials = 12.75, novel test trials = 12.56).
2.4. Data analysis
Early posterior processing was characterized as the
average response over left, central and right posterior parietal electrode groups (EGI Hydrocel GSN electrodes: 31,
33-left; 36, 37-central; and 38, 40-right). Mid-to-late anterior processing was characterized as the average response
over a fronto-central electrode group (sites 3, 6, 9). Electrode groups were chosen to characterize early posterior
and mid-to-late anterior activity based on previous literature (see de Haan, 2007 or Reynolds and Richards, 2005 for
reviews). We temporally focused our analysis from 250 ms
post stimulus onset, given that none of the conditions could
be distinguished before then (“short” auditory stimulus
was 250 ms), to the end of the segment (1450 ms). Our
analysis of the early posterior activity was restricted to
rising second half of the first major posterior negativity
(250–450 ms). Time windows of interest for the mid-to
late latency anterior components (Nc, PSW) were chosen
by using broad time windows to first acquire the peak
latency of the grand mean (collapsed across familiar and
unfamiliar test trial pairings) for each training condition
(Nc = 450–950 ms; PSW = 950–1450 ms). Statistical analyses (see Section 3) revealed significant differences in peak
Nc latency but not PSW latencies between training conditions (see Section 3). As a result, distinct, symmetrical
time windows (−100/+100 ms) around the corresponding peak latencies for each training condition (congruent
training: 599 ms; incongruent training: 711 ms) were used
to characterize the Nc (congruent training: 499–699 ms;
incongruent training: 611–811 ms) and a single, fixed, symmetrical time window (−100/+100) around the average
peak latency (1131 ms) was used to characterize both training conditions for the PSW (average amplitude between
1031 and 1231 ms).
Independent samples t-tests were used to test for
latency differences between training conditions (collapsed
across test type). ANOVAs with the between-subjects factor
of Training Condition (relationally congruent vs. relationally incongruent) and the repeated within-subject factor of
Test Type (familiar vs. novel pairing) statistically assessed
mean component amplitude. Scalp Region was also a factor in the analysis of posterior processing (left, central,
right electrode groups). Significant interactions were further examined post hoc using paired sample t-tests.
3. Results
3.1. Early posterior activity
Test stimuli evoked a large negativity followed by a
rising positivity over widespread posterior parietal scalp
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107
Fig. 2. Topographical scalp maps for components of interest as viewed from the top of the head (oriented with back of the head facing the bottom of the
figure). Black dots represent electrode sites used to compute mean response.
locations between about 175–700 ms after stimulus onset
(Fig. 2). Timing and topography were consistent with the
previously identified infant N290/P400 complex (e.g. de
Haan, 2007). Waveform morphology, however, was slightly
different (see Fig. 3) from that observed in previous studies using only visual stimulation (see de Haan, 2007 for
review of infant visual-evoked posterior activity). Given
that congruent and incongruent stimuli could only be differentiated after 250 ms and mid-latency anterior activity
started around 450 ms, we were restricted to analyzing the
rising (second) half of this early posterior negative component using the mean amplitude of a fixed time window
(250–450 ms) averaged over left, midline, and right posterior sites.
The amplitude analysis revealed a main effect of Scalp
Region (F (2, 60) = 4.384, p < .05, 2p = .127), a main effect of
Training Condition (F (1, 30) = 6.160, p < .05, 2p = .170), and
an interaction between Training Condition and Test Type
(F (1, 30) = 4.253, p < .05, 2p = .124) (all other p’s > .14). The
left posterior parietal scalp group showed the most negative mean amplitudes during this time frame. Further post
hoc analysis revealed that the interaction between Training
Condition and Test Type on the second half of the early posterior negativity could be explained by a main effect of Test
Type (F (1, 15) = 5.462, p < .05, 2p = .267) for those infants
that were familiarized to the congruent pairing, with more
negative amplitudes observed for familiar pairings compared to unfamiliar pairings, and no significant differences
in Test Type for those infants who were familiarized to the
incongruent pairings (all p’s > .35) (Fig. 3).
3.2. Mid-latency anterior negativity
Test stimuli also evoked a mid-latency anterior negativity between 450 and 950 ms after stimulus onset (Fig. 2).
Scalp topography and timing were consistent with the
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Fig. 3. Mean posterior event-related potentials. (A) Average waveform over posterior channels between −200 and 1450 ms to familiar and novel test
pairings for each training condition. The shaded region represents approximate time window of analysis. (B) Mean amplitude for the early posterior
negativity to familiar and novel test pairings for each training condition. The “*” indicates a significant difference between conditions.
previously identified Nc component (e.g. de Haan and
Nelson, 1997; Nelson, 1994; Reynolds and Richards, 2005).
Again, however, morphology was somewhat different
(Fig. 4) than that observed in purely visual studies and
more consistent with Nc morphology seen in studies with
multisensory stimuli (Hyde et al., 2010b, 2011).
An analysis of the peak latency of the Nc between 450
and 950 ms revealed a main effect of Training Condition
(t (30) = −2.445, p < .05), with the Nc peaking significantly
earlier (601 ms) for those infants presented with the congruent pairing during the training period compared to
those infants presented with the incongruent pairing during the training phase (708 ms). Given the significant
differences in Nc timing between groups, distinct time
windows were used to characterize the mean amplitude
of the Nc for each training group. Specifically, Nc was
defined as a symmetrical 200-ms time window (−100 to
+100 ms) surrounding the peak for each Training Condition
over the fronto-central scalp group1 (congruent training
599–799 ms; incongruent training: 611–811 ms).
An analysis of the mean Nc amplitude revealed a significant interaction between Training Condition and Test
Type over anterior scalp (F (1, 30) = 4.183, p < .05, 2p =
.122) (other p values > .43) (Fig. 4). Post hoc comparisons
revealed that infants presented the congruent pairing during the training phase showed more negative frontal Nc
responses to the familiar (congruent) pairings than to
the novel (incongruent) pairings during the test phase
(t (15) = −2.701, p < .05) (see Fig. 4). In contrast, infants
1
Given the sampling rate of 250 Hz per second or 1 sample every 4 ms,
time windows of interest were centered (−100 to +100 ms) on the closest
sampled time to the actual mean peak latency.
presented incongruent pairings during the training phase
showed no difference in mean Nc amplitudes to congruent and incongruent pairings at test (t (15) = .739, p > .47)
(Fig. 4).
3.3. Late anterior positive component
Some test stimuli evoked an anterior, late-going slow
wave, which emerged once stimuli were no longer present
(around 1000 ms) and returned to baseline around 1400 ms
(see Fig. 2). Scalp timing, anterior topography, and wave
morphology (see Figs. 2 and 4) were consistent with characterizations of the PSW or LPC in previous ERP studies
with infants of this age (see de Haan, 2007 or Reynolds
and Richards, 2005 for reviews). An analysis of peak latency
over a broad time window (950–1450 ms), collapsed across
test trial types, revealed no differences in timing between
training conditions. As a result, a single symmetrical time
frame (−100/+100 ms) around the average peak latency
(1130 ms) was used to analyze the anterior positive slow
wave for all conditions (1030–1230 ms).
An analysis of the mean positive slow wave amplitude over anterior scalp revealed a significant interaction
between Training Condition and Test Type (F (1, 30) = 5.631,
p < .05, 2p = .158) (all other p’s > .82). Post hoc analysis
revealed only a marginal difference between test types
for those infants trained on the congruent test pairs (F (1,
15) = 3.393, p = .085, 2p = .184), with unfamiliar test trials eliciting a more positive amplitude than familiar test
pairs, and no difference between test types for those infants
trained on incongruent test pairs (F (1, 15) = 2.42, p > .14,
2p = .139).
Given that the late slow wave activity is associated with
memory updating for partially encoded stimuli and that
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D.C. Hyde et al. / Developmental Cognitive Neuroscience 6 (2013) 102–112
109
Fig. 4. Mean anterior event-related potentials. (A) Average waveform over anterior channels between −200 and 1450 ms to familiar and novel test pairings
for those subjects in the congruent training condition. The shaded region represents approximate time window of analyses. (B) Mean amplitude for the
mid-latency Nc over anterior sites to familiar and novel test pairings for each training condition. The “*” indicates a significant difference between conditions.
(C) Mean amplitude for the later positive slow wave (PSW) over anterior sites to familiar and novel test pairings for each training condition. The “*” indicates
a significant response above baseline. (D) Average waveform over anterior channels between −200 and 1450 ms to familiar and novel test parings for those
subjects in the incongruent training condition. The shaded region represents approximate time window of analyses.
Author's personal copy
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D.C. Hyde et al. / Developmental Cognitive Neuroscience 6 (2013) 102–112
a return to baseline is observed for full-encoded items
and also for items that are not encoded at all (Nelson,
1994; Nelson and Collins, 1992; Nelson and de Regnier,
1992; Reynolds and Richards, 2005; Richards, 2003), we
further analyzed, in a post hoc manner, the PSW relative to baseline using one-sample t-tests (against zero).
This analysis revealed only the familiar test stimuli for
those trained on incongruent pairings produced a PSW
significantly greater than baseline (t (15) = 2.780, p < .05)
(congruent training/familiar test, p = .79; congruent training/novel test: p = .063; incongruent training/novel test:
p = .973).
4. Discussion
We observed that the infant brain discriminates
relationally congruent from relationally incongruent crossmodal space–time pairings when briefly familiarized with
the relationally congruent pairings but not when familiarized with the relationally incongruent space–time pairings.
These results are not due to low-level sensory differences
between conditions, as infants in both training groups were
presented with the same test stimuli. Furthermore, the
design of our stimuli allowed us to rule out that differential processing was due to common spatio-temporal cues
across a single sense modality, was dependent on redundant cues across multiple sense modalities, or was based on
lower-level similarities between dimensions in the visual
domain alone; instead, it appears that associations were
made over amodal representations of space and time,
abstracted away from non-redundant and asynchronous
auditory and visual information. Therefore, we interpret
the asymmetry in processing (i.e. congruent compared to
incongruent pairings) between training groups to a functional overlap between mental representations of space
and time, or a relational congruence bias, where structural similarities in the neural representation facilitate the
automatic aligning and mapping between dimensions for
relationally congruent pairings over relationally incongruent pairings, as suggested by Srinivasan and Carey (2010).
By measuring the neurophysiological response, we
observed that the asymmetry in processing begins, over
posterior scalp sites, almost immediately after stimulus differences emerge. Neural processing was further
differentiated both in timing and magnitude between
training groups during mid-to-late latency time periods over anterior sites. Our functional interpretation is
that, after a brief familiarization period to define relatively long and short magnitude pairings of auditory
durations (tones) visual lengths (cartoon characters), relationally congruent pairings showed enhanced processing
and attention orienting relative to incongruent pairings in
those infants first familiarized to congruent pairings (long
duration-long character/short duration-short character).
In contrast, infants familiarized to incongruent pairings
(short-long/long-short) showed no differences in early processing or attentional orienting between congruent and
incongruent pairings in the test phase.
Early posterior activity was temporally and topologically consistent with the infant N290/P400 complex
typically observed for visual processing of faces and objects
(e.g. Halit et al., 2004; Scott and Nelson, 2006; Scott,
2011). However, we are not committed to the idea that the
observed early posterior differences have the same hypothesized ventral origin as those observed typically for visual
processing of faces and objects (e.g. Halit et al., 2004; Scott
and Nelson, 2006; Scott, 2011). Studies of numerical, spatial, and temporal processing, in contrast to face processing,
typically activate dorsal cortical areas in the parietal cortex
(Izard et al., 2008; Hyde et al., 2010a; Brannon et al., 2008).
The spatial nature of the variables of interest, the audiovisual nature of the stimuli, and the gross scalp topography
of the effects are at least equally consistent with a parietal
rather than a temporal–ventral brain origin. This speculation, however, should be followed up using imaging
techniques with better spatial resolution if our claim is to
be empirically substantiated.
Although the waveform morphology of the mid-latency
anterior processing was different, timing and topography
were consistent with the infant Nc component identified by other as a marker of attentional orienting (see
de Haan et al., 2003 or Reynolds and Richards, 2005 for
reviews). Morphological differences were likely due to the
multimodal nature of our stimuli compared to previous
visual work. Previous work has shown that the infant Nc
response is related to behavioral attention (e.g. Richards,
2003; also see Reynolds et al., 2010). Unfortunately, behavioral looking times could not be obtained in our study
to compare directly with previous behavioral work, given
the necessity for presenting many trials of short duration for the ERP paradigm. We were also unable to obtain
enough artifact-free trials per stimulus type to look at differences in learning between specific pairings of “long” and
“short” auditory and visual stimuli. Nevertheless, “long”
and “short” visual and auditory stimuli differed by a 1:3
ratio and previous work suggests a 1:3 difference is well
within the 5-month old infants’ ability to discriminate
(limit of about a 1:2 ratio; Brannon et al., 2007; Lipton and
Spelke, 2003; Wood and Spelke, 2005). Furthermore, the
patterns of Nc modulation observed in our study accord
with previous behavioral work showing discrimination for
space–time pairs when first familiarized to congruent pairings but not when first familiarized to incongruent pairings
(Srinivasan and Carey, 2010).
We also observed an interaction between Training
Condition and Test Type in the late positive slow wave
component. Post hoc analysis revealed that only familiar test stimuli for those infants training on incongruent
spatial–temporal pairings elicited a late PSW significantly
different from baseline. In contrast, neither the familiar
or novel test conditions for infants who trained on congruent pairings nor the novel condition for infants trained
on incongruent pairings were significantly different from
baseline. Previous studies suggest that late positive slow
wave (PSW) activity is related to memory updating for
partially encoded stimuli, and that stimuli that are fully
encoded in memory and stimuli that are not encoded at all
do not evoke late slow wave activity above baseline (e.g.
de Haan, 2007 or Reynolds and Richards, 2005 for reviews).
Although speculative, the return to baseline for the familiar
stimuli of those trained with congruent pairings may be a
result of the cross-modal spatio-temporal relations being
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D.C. Hyde et al. / Developmental Cognitive Neuroscience 6 (2013) 102–112
fully encoded into memory while the lack of a significant
PSW for the other conditions may be an indicative of a lack
of higher-level encoding at all. In contrast, an increase in
amplitude for the familiar test stimuli of those in the incongruent training group may indicate updating of a partially
encoded stimulus in memory.
More generally, in multisensory contexts, redundancy
of information across the senses has been shown to facilitate learning and early development, particularly in young
infants around the same age as we test here (see Bahrick
and Lickliter, 2000). While onset synchrony may have
equally queued training groups into the events, intersensory redundancy cannot explain the differential learning
patterns between the training groups of our study because
the test stimuli were the same for both groups and because
the relational information was not redundant across the
senses. While redundancy of temporal information would
likely facilitate learning in this context, as it has shown
to do in others (e.g. Jordan et al., 2008) and may have in
Srinivasan and Carey (2010), our study shows that it is not
necessary for learning pairings of audio-visual magnitude
information. A relational congruence bias, in addition to
intersensory redundancy, should now be considered a cue
that facilitates processing of complex audio-visual information.
5. Conclusions
In sum, our results suggest that young infants encode,
attend to, and potentially remember spatial and temporal relations that are congruent more readily than they do
relations that are incongruent. The age of our participants,
5-months, makes it unlikely that explicit instruction or language experience can account for the results. Rather, these
results suggest the structure of the mind biases us to learn
certain magnitude pairings over others. A remaining issue
is if this interaction can be explained by a privileged connection between domain-specific representations of space
and time or by generalized representations of magnitude
(see Lourenco and Longo, 2011 or Walsh, 2003 for reviews).
Another remaining issue is why this bias is present. Is this
a feature or a bug of the brain? Like intersensory redundancy (Bahrick and Lickliter, 2000), this bias may further
highlight and facilitate learning of important magnitude
correspondences that transcend the primary properties
of sound and sight early in development. Alternatively,
relational congruence bias may result from a recycling
of ancient mechanisms originally evolved for other purposes (Gould and Vrba, 1982; Dehaene, 2005). Whatever
the answer, it seems as if this organization has important
implications for human nature and culture as pervasive as
guiding the way we learn about, understand, and choose to
describe the world around us (Clark, 1973; Gruber, 1965;
Jackendoff, 1983; Lakoff and Johnson, 1980; Langacker,
1987; Srinivasan and Carey, 2010; Talmy, 1988).
Conflicts of interest
We declare no conflicts of interest in conducting or publishing this work.
111
Acknowledgements
This study was funded in part through the support of the
Family Studies Center at Brigham Young University and by
the Camilla Eyring Kimball Endowment in the College of
Family, Home, and Social Sciences at Brigham Young University.
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