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J Exp Child Psychol. Author manuscript; bachelor in PMC 2011 Nov 1.

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PMCID: PMC2907473

NIHMSID: NIHMS216635

The Human relationship between the Perception of Axes of Symmetry and Spatial Memory in Early Childhood

Abstract

Early on in development there is a transition in spatial working memory (SWM). When remembering a location in a homogeneous space (such as in a sandbox) immature children are biased toward the midline symmetry axis of the infinite. Over development a transition occurs that leads to older children being biased abroad from midline. The Dynamic Field Theory (DFT) explains this transition in biases as existence caused by a change in the precision of neural interaction in SWM and improvements in the perception of midline. According to the DFT, young children perceive midline, but there is a quantitative improvement in the perception of midline over development. In the experiment reported here, children and adults had to decide on which one-half of a big monitor a target was located. In support of the DFT, even the youngest children performed higher up risk at most locations, but operation also improved gradually with age.

Keywords: spatial cognition, spatial memory, symmetry perception

Spatial retentivity develops early. Even infants are capable of remembering locations (east.g., Newcombe, Huttenlocher, & Learmonth, 1999), but spatial retention continues to develop into childhood (due east.1000., Huttenlocher, Newcombe, & Sandberg, 1994; Spencer & Hund, 2003). One aspect of spatial memory that develops in babyhood is children'south use of symmetry axes equally reference axes (Huttenlocher et al., 1994; Schutte & Spencer, 2002, 2009), but what leads to this development? One possibility is that at that place are changes in children'due south perception of symmetry axes. The current study examines the ability of children to perceive the symmetry axis of a space.

Several studies have found a developmental transition in spatial working memory (SWM) biases in tasks that used a homogenous infinite (Huttenlocher, Hedges, & Duncan, 1991; Huttenlocher et al., 1994; Schutte & Spencer, 2002, 2009). For example, in the spaceship SWM chore (Schutte & Spencer, 2002), children were presented a spaceship-shaped target on a homogeneous table pinnacle and after a filibuster they pointed to where they remembered the target. In this task the vertical symmetry axis, or midline, of the chore space acted as a reference axis. At effectually 3 years of age, children'southward retentiveness responses were biased toward midline for a wide range of hiding locations (Huttenlocher et al, 1994; Schutte et al., 2010; Schutte & Spencer, 2002). After in development children'southward responses were biased away from midline (Hund & Spencer, 2003; Huttenlocher et al, 1994; Schutte et al., 2010; Spencer & Hund, 2003). This transition in geometric biases occurred gradually, and when the transition occurred depended on target location (Schutte & Spencer, 2009).

The Dynamic Field Theory (DFT), a dynamic systems model of SWM made up of a network of dynamic neural fields, has been used to explain this transition (Schutte & Spencer, 2009; Simmering et al., 2008). Simulations of the model using the older 3-year-quondam parameter set up and the 6-year-old parameter fix from Schutte and Spencer (2009) are shown in Figure 1a and 1b, respectively. The model is made up of three interconnected fields: an excitatory perceptual field (PF, first layer) which codes the perceptual structure in the task space; an excitatory SWM field (SWM, third layer) which receives excitatory input from the perceptual field (run across solid arrows) and maintains the memory of the target location; and a field of inhibitory interneurons (Inhib, 2nd layer) which receives input from both the perceptual and SWM fields (meet solid arrows) and sends inhibition back to both fields (run into dashed arrows). For each field location is represented forth the x-axis, activation forth the y-axis, and time along the z-centrality. Neurons in each field send positive activation to nearby neurons, and, through the inhibitory field, inhibition to neurons farther away. The consequence of these interactions is a form of local excitation/lateral inhibition that allows the SWM field to sustain a summit of activation in the absenteeism of input.

Iii-year-old (a) and 6-yr-former (b) simulations of the Dynamic Field Theory. Panels correspond: perceptual field [PF]; inhibitory field [Inhib]; excitatory spatial working memory field [SWM]. Arrows represent interaction between fields. Solid arrows represent excitatory connections and dashed arrows represent inhibitory connections. In each field, location is represented along the ten-axis (with midline at location 0), activation along the y-centrality, and time along the z-axis. The trial begins at the front end of the figure and moves toward the back. Time slices from the end of the delay for the perceptual field are shown on the right. See text for additional details.

Input into the perceptual field which marks the location of the reference axis influences the target peak in the SWM field. When the target peak overlaps with excitatory input from the midline reference axis the target top drifts toward the input (Figure 1a). If, withal, the target peak overlaps with the inhibition from the reference axis the peak drifts abroad from it (Figure 1b). According to the spatial precision hypothesis (Schutte, Spencer, & Schöner, 2003; Schutte & Spencer, 2009; Simmering et al., 2008) over development the model changes in ii means: neural interaction becomes stronger and, as a result, peaks get narrower and more than stable; and the perception of midline becomes more than precise, i.e., the reference input to the perceptual field becomes narrower and stronger. The transition in geometric biases occurs gradually equally the result of these two quantitative changes (Schutte & Spencer, in press; Schutte & Spencer, 2009).

In improver to explaining functioning in SWM tasks, the DFT has been applied to position discrimination tasks (Simmering & Spencer, 2008; Simmering, Spencer, & Schöner, 2006). Simmering and colleagues take shown that the DFT and the spatial precision hypothesis can account for children and adults' operation in position discrimination tasks. In these tasks, participants are shown two targets in succession, and they determine if the targets are in the same or dissimilar locations. Based on the DFT, Simmering and colleagues (2006) predicted that adults would perform more than accurately when the targets were closer to midline, and when the second target appeared toward midline relative to the get-go target. In contrast, Simmering and Spencer (2008) predicted that immature children would exist more accurate when the 2d target was away from midline. Results supported these predictions, and demonstrated the generalizability of the DFT to discrimination tasks.

The enquiry presented hither tests predictions of the DFT for another type of position discrimination task, the discrimination of a target location relative to midline. According to the DFT, over development the precision with which children perceive midline improves (Schutte & Spencer, 2002, 2009; Simmering et al., 2008). The graphs shown to the right of Figures 1a and 1b evidence a section of the perceptual field. In the 3-year-former model the midline reference axis activation in PF is weak and wide while the midline activation for the 6-yr-old model is stronger and narrower. Thus, according to the DFT, 6-yr-olds should do better than 3-twelvemonth-olds at discriminating locations relative to midline. This comeback should be gradual between 3 and 6 years of age, because in the DFT the perception of midline changes gradually (Schutte & Spencer, 2009, in press).

Previous research has plant that the perception of symmetry develops at a young age (eastward.g., Bornstein, Ferdinandsen, & Gross, 1981). Developmental studies of symmetry have examined the detection of symmetrical versus asymmetrical objects or patterns (eastward.g., Bornstein et al., 1981; Bornstein & Stiles-Davis, 1984) or take focused on the development of a preference for symmetrical objects (Royer, 1981). Studies have found that the perception of symmetry develops in infancy (e.m., Bornstein & Krinsky, 1985) with the perception of vertical symmetry developing kickoff (Bornstein et al., 1981). Previous research, nonetheless, has not examined how accurately children can localize a symmetry centrality. It is possible that for young children the location of the axis may be "fuzzy", peculiarly in cases where there are no symmetry cues most the reference axis as is the example in large task spaces such as a large monitor. The electric current study investigated developmental changes in the perception of midline past having children view a target on a big-screen monitor and determine on which half of the monitor the target was located.

Method

Participants

Fifteen three-twelvemonth-olds (9 males, half dozen females: mean age = 3.6 years, SD = 4.half dozen months), 15 4-year-olds (seven males, 8 females: mean historic period = 4.6 years, SD = four.ane months), 18 five-year-olds (five males, 13 females: mean historic period = 5.6 years, SD = 3.1 months), 15 6-yr-olds (6 males, ix females: mean age = six.6 years, SD = 3.7 months), and xv adults (4 males, xi females: mean age = 22 years, SD = one year 2 months) participated in this study. An additional vi children came into the lab but were not included in the analyses due to unwillingness to end the game (two iii-twelvemonth-olds) or non answering at least three of the four control trials correctly (iii three-year-olds, one 4-year-old; encounter below for details). Parents and developed participants gave informed consent. Children were given $10 and a small toy every bit compensation, and developed participants received course credit.

Appliance

Participants viewed the stimuli on a 29 × 42 inch (74 × 107 cm) LCD monitor with a screen resolution of 1024 × 768 pixels. The monitor was tilted 15 degrees from horizontal. The software program E-Prime was used to run the task. The stimuli were small smiley faces (ane.ii cm broad × .8 cm tall).

Procedure

The children started the session with training trials. The children were told that 2 identical twins each lived in their own yard, and they did not cross into each other's 1000. A piece of paper represented the "yards" with each twin "living" on half of the paper. A transparency with a line drawn downward the center was laid over the paper to show the child how each twin had their own 1000. Afterwards explaining the rules of the task, the experimenter placed a smiley face on the sheet of paper and asked the participant to identify which twin it was by moving a joystick to the left or right to indicate the "yard" in which the smiley face was located. The transparency was and so laid down to provide feedback about the location. Children completed a minimum of three training trials. The club was random, but each side of the newspaper was used at to the lowest degree in one case. If the child was not right on at least ii of the three training trials, trials were added until the child answered two in a row correctly. Generally children did not crave more than three training trials.

Afterward training, the experimenter completed a demonstration trial on the large monitor, followed by two do trials. The smiley face was presented and the participant was asked to answer. The smiley face stayed on the monitor until the participant responded. This was done to avert introducing a spatial retentiveness component. After each trial, a xanthous line on midline appeared along with the target, and the participant was told whether or not he/she was correct. If the participant was incorrect, he/she was told "nice attempt" and encouraged to try again.

Adults started the process at the monitor. They were told that they needed to move the joystick to either the right or left depending on where they saw the smiley face up. The same sit-in trial and 2 practice trials were conducted.

There were two trials to each target location. The targets were ±.654 cm, ±1.307 cm, ±2.605 cm, ±3.882 cm, ±v.130 cm, and ±eleven.491 cm from midline with positive locations to the right and negative locations to the left. There were a total of 24 randomly ordered trials. The ±11.491 cm location was a control location. Data from participants who did not respond correctly on 3 out of four of the command trials were non included in the analyses.

Results

The mean number of correct responses to each altitude from midline, for each historic period grouping, can be seen in Figure two. Distance from midline is on the x-axis and the number of correct responses is on the y-axis. Four is the maximum number correct, and two is chance. Performance of all ages was higher up take a chance for the locations furthest from midline, and performance decreased as the targets approached midline.

Results for each distance from midline. Notation that 2.0 is chance performance and 4.0 is perfect performance.

Nosotros conducted an ANOVA with Side of the monitor (left, right) and Location (0.654 cm, 1.307 cm, 2.605 cm, iii.882 cm, and 5.130 cm) as within-participants factors and Age (iii, 4, v, half dozen, adult) as a between-participants factor. There was a significant Side principal issue, F(1, 73) = 6.173, p<.025. Overall functioning was meliorate on the right than on the left (Right: M=1.57; Left: M=1.70). There was also a significant Location main effect, F(iv, 292) = 40.225, p<.001. Correct performance decreased as location approached midline (see Figure ii). There was likewise a significant Location past Age interaction, F(16, 292) = ane.967, p < .025, and a significant Age master effect, F(four, 73) = 9.253, p < .001. Correct functioning increased as historic period increased (see Figure three). Follow-ups of the Age × Location interaction examined the Age consequence at each target location. At the location closest to midline, in that location was only a marginal Age issue, F(4, 77) = 2.304, p = .07. There was a significant Age event at the other locations (5.130 cm: F(4, 77) = 4.985, p = .001; 3.882 cm: F(4, 77) = 3.938, p < .01; 2.605 cm: F(4, 77) = iii.142, p < .025; one.307 cm: F(4, 77) = 7.126, p < .001). Thus, performance beyond ages differed significantly at all just the location closest to midline.

Average number of correct responses for each historic period. Note that two.0 is hazard. Error bars represent standard error of the mean.

In society to make up one's mind which ages differed from each other we performed follow-up t-tests (two-tailed) comparison ages at the locations with a significant age event. At 5.130 cm, the 3-year-olds differed significantly from the 4- and 5-year-olds (3 and 4 years: t(28) = −2.117, p < .05; 3 and 5 years: t(31) = −three.520, p = .001) and differed marginally from the 6-twelvemonth-olds (t(28) = −ii.005, p = .055). The performance of the 4-, 5-, and vi-year-olds did not differ at this location (all ps > .09). The iii- and iv-year-olds' operation differed significantly from the adults (three years and adults: t(28) = −iii.595, p = .001; 4 years and adults: (28) = −2.256, p < .05). The five- and 6-yr-olds did not differ significantly from the adults (all ps > .x).

At 3.882 cm the three-year-olds differed significantly from the half-dozen-year-olds, t(28) = −three.035, p = .005. All other comparisons betwixt the 3-, 4-, 5-, and vi-year-olds were not significant (all pdue south > .09). The 3-, four-, and 5-year-olds differed significantly from the adults (three years and adults: t(28) = −4.583, p < .001; iv years and adults: t(28) = −2.477, p < .025; v years and adults: t(31) = −two.153, p < .05). In contrast, the six-yr-olds did not differ from the adults, t(28) = −1.000, northward.s.

The operation of the iii-, iv-, 5-, and 6-yr-olds did non differ significantly at 2.605 cm (all ps > .10). The 3-, four-, and 5-year-olds all differed significantly from the adults (3 years and adults: t(28) = −3.154, p < .005; 4 years and adults: t(28) = −four.026, p < .001; 5 years and adults: t(31) = −iii.754, p = .001), while the 6-year-olds did not differ from the adults, t(28) = −1.974, n.south.

At 1.307 cm, the performance of the 3-, 4-, 5-, and 6-yr-olds did non differ significantly from each other (all ps > .10), while all ages differed significantly from the adults (3 years and adults: t(28) = −6.205, p < .001; 4 years and adults: t(28) = −4.795, p < .001; 5 years and adults: t(31) = −three.891, p < .001; six years and adults: t(28) = −5.292, p < .001).

To decide if operation was better than chance, nosotros conducted planned t-tests. Results of the t-tests are presented in Tabular array 1. Note that the adults' performance at the four locations farthest from midline was perfect so t-values could not be computed. Functioning at all locations was above chance for the three-year-olds and the adults. For iv-, v-, and half dozen-year-olds, all locations except the closest location were above chance.

Table one

T-tests for Each Age Comparing Performance at Each Location to Chance

Age and location	df	t
3-year-olds
0.654 cm	14	2.26*
1.307 cm	14	2.26*
two.605 cm	14	vii.36**
three.882 cm	14	vi.87**
5.130 cm	14	5.39**
4-year-olds
0.654 cm	xiv	1.57
1.307 cm	xiv	iii.67*
2.605 cm	14	five.26**
3.882 cm	14	half-dozen.81**
5.130 cm	fourteen	14.67**
five-yr-olds
0.654 cm	17	0.81
1.307 cm	17	4.78**
2.605 cm	17	8.25**
3.882 cm	17	ix.lxxx**
five.130 cm	17	35.00**
6-year-olds
0.654 cm	14	1.00
1.307 cm	xiv	2.65*
two.605 cm	14	6.49**
three.882 cm	14	14.00**
5.130 cm	xiv	nine.00**
adults
0.654 cm	14	iv.43**
1.307 cm		--
2.605 cm		--
3.882 cm		--
5.130 cm		--

In summary, operation of the children declined as locations approached midline. Adults, on the other mitt, were perfect at all but the closest location. Performance of the 3-year-olds differed significantly from the other age groups, but in that location were no differences betwixt the 4- to 6-year-olds. All ages differed significantly from the adults at 1 or more locations.

Word

Between three and 6 years of age there were small developmental changes in the power to categorize locations around midline. Between 3 and 6 years of age there was a small, but significant increase in the number of correctly categorized targets. According to the DFT, the transition in the management of geometric biases occurs due to 2 developmental changes: stronger neural interactions and changes in the perception of the symmetry axis. The results of this study support the DFT's proposal that even young children are able to perceive the symmetry axis and over development at that place is a gradual, quantitative change in the precision of their perception (Schutte & Spencer, 2009). Interestingly, the largest change was not between iii and 4 years of age which is when the transition in geometric biases occurs. Instead, the largest change in performance occurred between childhood and adulthood which was also the largest age deviation in the report. This result fits with DFT's proposal that the changes in the perception of midline occur gradually (Schutte & Spencer, in press, 2009).

Another theory of spatial retention prevalent in the literature is the Category Adjustment Model (CAM; Huttenlocher et al., 1991; Huttenlocher et al., 1994). Although the CAM was not proposed to explain categorization in perceptual tasks, it has been used to explain the transition in geometric biases so it is useful to examine whether these information have implications for the model. The CAM is a Bayesian model that proposes that geometric biases arise out of processes that increase the average accuracy of the estimates of locations (Huttenlocher et al., 2004). According to the CAM (Huttenlocher et al., 1991; Huttenlocher, et al., 1994), as it has been applied to spatial memory, children and adults encode two types of information: categorical and fine-grained. Categorical information relates to the spatial category in which the object is located. The fine-grained information is an inexact, unbiased memory of the location. When a location is presented, people encode both types of information. At recall people combine the fine-grained and categorical information, i.e., the epitome at the center of the category, and are biased toward the prototype. In the CAM the transition in geometric biases is the event of a change in categorization (Huttenlocher et al., 1994). Immature children categorize the space every bit 1 category while older children and adults separate the infinite into ii categories.

According to Huttenlocher and colleagues (2007) boundaries influence bias through truncation. Equally boundaries become uncertain the consequence of truncation reduces due to more than variable boundary locations and, as a result, bias abroad from boundaries decreases (Huttenlocher et al., 1991). Additionally, equally boundaries go uncertain, variability of responses and accented error increase. How does this utilise to changes over development? It is not completely clear in the model how children transition from one to ii categories (see Schutte & Spencer, 2009, for a discussion), but it is possible that initially perception of the midline is so uncertain that treating the space as 1 category leads to lower error than treating it as 2 categories. The findings of a study by Huttenlocher et al. (2004) using a circle-dot task support the proposal that people practise non use uncertain boundaries. In the experiment adults were taught to categorize locations based on diagonal boundaries. Despite the training, when they reproduced the locations from retentiveness their biases reflected vertical and horizontal boundaries.

Wedell and colleagues (Fitting, Wedell, & Allen, 2005, 2007; Wedell, Fitting, & Allen, 2007) proposed a revision to the CAM called the fuzzy-boundary model. According to this model, bias near boundaries reduces due to the prototype from the incorrect category being recruited on some trials (see also Huttenlocher et al., 2004). The results of the electric current study suggest that this could happen at some locations. Even adults were non perfect at determining the category of the closest location which suggests that it could be miscategorized on some trials. The adults, withal, were better than children at categorizing many locations. Therefore, according to the fuzzy boundary model, children'southward responses should be less biased than adults due to children'south miscategorization. Schutte and Spencer (2009) constitute that children at the transition point in geometric biases were not significantly biased which could exist caused by miscategorization. Children, however, were biased away from midline when the targets were 20° from midline before they were biased away when the targets were 30° or fifty° from midline. This outcome is not what would be predicted if the lack of bias was caused by miscategorization. The fuzzy-purlieus model has non been practical to development, however, so it is unclear how information technology would account for the pattern of bias seen during the transition.

One limitation of the current study is that the structure of the task involved asking children to categorize the location of the target rather than determining how they would spontaneously categorize the location. It is possible that when confronted with a SWM chore, 3-year-olds do non spontaneously subdivide the space into two categories fifty-fifty when they are capable of subdivision. There are several differences between SWM tasks and the bigotry task used here that could potentially pb to differences in subdivision. Future work will examine whether children's subdivision ability is predictive of their geometric biases in SWM tasks.

In decision, this study is a significant first step in examining children'due south power to subdivide space. The gradual comeback in the perception of midline supports the DFT's explanation that the transition in geometric biases is partially due to quantitative improvements in the ability to perceive symmetry axes (Schutte & Spencer, 2009). Now that a method for examining immature children's ability to localize symmetry axes has been developed, time to come research tin can examine in more detail the connection between the perception of midline and SWM.

Acknowledgments

Nosotros would like to give thanks the children and parents who participated in this inquiry. We would also similar to give thanks John P. Spencer, Ph.D. for his comments on an earlier version of this manuscript.

Footnotes

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