Prefrontal–parietal correlation during performance of the towers of Hanoi task in male children, adolescents and young adults

Developmental Cognitive Neuroscience 2 (2012) 129–138

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Prefrontal–parietal correlation during performance of the towers of Hanoi task in male children, adolescents and young adults Miguel Angel Guevara a , Lucía Ester Rizo Martínez a , Francisco Abelardo Robles Aguirre b , Marisela Hernández González a,∗ a b

Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo 180, Col. Arcos Vallarta, C. P. 44130, Guadalajara, Jalisco, Mexico Departamento de Neuropsicología y Grupos de Apoyo, Instituto Nacional de Neurología y Neurocirugía, México, D.F., Mexico

a r t i c l e

i n f o

Article history: Received 21 December 2010 Received in revised form 12 February 2011 Accepted 11 May 2011 Keywords: Towers of Hanoi Electroencephalogram Correlation Prefrontal cortex Parietal cortex Development

a b s t r a c t Potential age differences in the electroencephalographic (EEG) correlation (r) between the prefrontal and parietal cortices during performance of the Tower of Hanoi task were studied. In three groups of healthy males (G1, 11–13; G2, 18–20, and G3, 26–30, years of age) EEGs were recorded at baseline and during performance of the Tower of Hanoi task. The parameters of the task showed no significant differences among groups, though the majority of younger subjects failed to complete it. The G1 group showed increases only in the interparietal r. The G2 group showed an increased interhemispheric and intrahemispheric r in almost all frequency bands, while the r in G3 increased only in selected frequency bands in the right hemisphere. These findings demonstrate that the functional coupling between these two cortices shows a characteristic pattern during performance of the Hanoi task that, while specific to each age group, was not associated with the successful performance of the task. © 2011 Elsevier Ltd. All rights reserved.

1. Introduction The central nervous system, specifically the human brain undergoes considerable maturational changes throughout its development. The executive functions which have been attributed to the frontal lobe include planning, inhibition and flexibility response, working memory, and complex reasoning among others (Bull et al., 2004; Casey et al., 2000; Fireman, 1996; Gnys and Willis, 1991; Goel and Grafman, 1995; Welsh and Huizinga, 2001) also present a maturing process with age. Interesting results have been obtained by mean fMRI in subjects performing tasks that involve executive functions (e.g., go-no-go, Stroop), in which progressively greater

∗ Corresponding author at: Instituto de Neurociencias, Universidad de Guadalajara. Francisco de Quevedo 180. Col. Arcos Vallarta, Guadalajara, Jalisco, Mexico. Tel.: +52 33 38 18 07 40; fax: +52 33 38 18 07 40. E-mail address: [email protected] (M. Hernández González). 1878-9293/$ – see front matter © 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.dcn.2011.05.002

frontal region activation occurs during development from childhood to adulthood (Casey et al., 2008). This supports the idea that maturation of the frontal lobe (mainly the prefrontal cortex) may influence cognitive control processes during development, particularly in adolescence (Anderson, 2002; Fuster, 1999, 2002; Thatcher, 1992). Studies of brain development, particularly of the frontal lobe, have used the measurement of scalp-recorded brain electrical activity (EEG) (Barry et al., 2004; Fox and Bell, 1990; Thatcher et al., 1986) and it has been demonstrated that certain EEG parameters may be useful in reflecting substantial developmental changes during adolescence and the integrity of anatomical and functional connections among brain structures (Farber and Dubrovinskaya, 1991; Nunez, 1981; Thatcher et al., 1986). Both cognition and behavior depend on the integration of activity in different brain regions (Pribram and Luria, 1973), indeed, PFC may play a role in orchestrating the collective functional organization of other cortical regions during development, hence examination of the functional interrelations between

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neocortical regions should help our understanding of the development of normal brain functions as well as of the executive functions. Although there is a large variety of measures to quantify EEG synchrony (Dauwels et al., 2010; Alba et al., 2007), two of the most common methods in the literature are the coherence and correlation analyses. Both are mathematical indices that make it possible to determine the degree of synchronization between two EEG signals. The coherence of the EEG activity between two sites, conceptualized as the correlation in the time domain between two signals in a given frequency band (Shaw, 1981), can provide such information (Guevara and Corsi-Cabrera, 1996). In contrast, correlation is sensitive to both phase and polarity, regardless of amplitude. Therefore, when interest is focused mainly on waveform and time coupling between two sites, correlation is a better choice than coherence (Guevara and Corsi-Cabrera, 1996). It is widely accepted that normal brain development from birth to the pre-adult years involves periods of both synaptic proliferation and pruning (Anderson et al., 2001; Cummings, 1993; Huttenlocher et al., 1982) however, the impact of these processes on the maturation of executive functions and EEG correlation has not been fully specified. Several studies have investigated the age effect on EEG coherence; for example, Gasser et al. (1988) reported a systematic development of EEG coherence as a function of age from 8 to 12 years in normal children, while Marosi et al. (1992) reported a significant increase in the coherence between the posterior regions and vertex, as well as a significant decrease with age in the coherence between frontal areas in children from 6 to 16.8 years old. Thatcher et al. (1986) advanced a two-process model of corticocortical associations in which short and long neuronal fibers contribute differentially to coherence as a function of inter-electrode distance. At longer distances, coherence is mainly dependent on the longer fibers alone, increases with their density/development, and falls off systematically with increasing inter-electrode distance. In contrast, increased density/development of short fibers in specialized neuronal populations reduces coherence by increasing the complexity and competition of interactions within the cell population. Thus, data from these authors indicate that periods of change in the magnitude of coherence between electrode sites during the first 12 years of life may correspond to the ages of major cognitive change (Thatcher et al., 1987). Several tests have been used to evaluate the executive processes; for example, the Stroop test. Using this test, León-Carrión et al. (2004) found the existence of age-related differences both in response time and in the errors that follow a non-linear relationship. The Towers of Hanoi task is another test that involves many complex steps of cognition and motor action in rapid succession. It has been widely used to evaluate executive functions and processes such as planning (Gnys and Willis, 1991), cognitive inhibition and flexibility (Goel and Grafman, 1995; Welsh and Huizinga, 2001), working memory (Bull et al., 2004; Welsh and Huizinga, 2001), and complex reasoning (Fireman, 1996). In addition, it has been used to evaluate changes in maturation during development (Bull et al., 2004).

Thus, considering the suggestion that the executive abilities present a maturating process with age and that this abilities depend on integrity of the prefrontal cortex and its functional interaction with other posterior association cortical areas, the aim of the present study was to detect and analyze the degree of EEG correlation between prefrontal and parietal areas, during performance of the Towers of Hanoi task in male children, teenagers and young adults. We hypothesized that the functional interactions between these cortices would be different during the performance of Towers of Hanoi in relation to age. If this is indeed the case, then this different correlation patterns should prove to be detectable through the EEG spectral analysis of both cortices in a precise relation to the different ages of the subjects. 2. Methods 2.1. Subjects The fifty-one males that participated in this study as volunteers were divided into three groups: G1, 11–13 (n = 17); G2, 18–20 (n = 17) and G3, 26–30 (n = 17) years of age. These divisions were selected because they correspond to specific stages of executive function development identified in the literature. It has been suggested that from 11 to 13 years of age both executive function and the maturation of the brain present substantial development (De Luca and Leventer, 2008). At the age of 11–13 years, neither the brain nor certain executive function are mature (Braver et al., 1997; Kwon et al., 2002), but in the third decade of life (26–30 years) maturation is almost complete, with only a few indices continuing to mature (Anderson, 2008), thus, in this study the age of 18–20 years was considered an intermediate age between puberty and young adulthood. All participants were healthy, right-handed and had no prior history of neurological or psychiatric disorders, learning disabilities, drug abuse or chronic illness. Subjects in G1 also had to score in the normal range on measures of attention using the Child Neuropsychological Assessment Battery for Spanish-speaking Children (Evaluación Neurop˜ sicológica Infantil, ENI) (Matute-Villasenor et al., 2007); while a short neuropsychological test battery in Spanish nol, NEUROPSI) (Evaluación Neuropsicológica Breve en Espa˜ (Ostrosky-Solís et al., 1997) was applied to subjects in G2 and G3. No participant was familiar with the Tower of Hanoi task before the study. All procedures involved in this experiment were approved by the Ethics Committee of the Institute of Neuroscience in accordance with the ethical standards laid down in the 1964 Helsinki Declaration, and all participants gave their informed consent prior to their inclusion. 2.2. HANOI application The task used in this study was a computerized version of Tower of Hanoi (HANOIPC3) that has only one level of difficulty based on the use of 3 disks, but stipulates an additional rule: only one disk may be moved at a time, and only to an adjacent peg (i.e., no peg can be skipped over). In the original version – without this stipulation – the minimum

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number of movements required to complete the task is 7, but under the conditions of the computerized version this number increases to 26 (Guevara et al., 2009). Executing this program requires a PC-compatible computer and a numerical mini-keyboard connected to the computer by a USB port. Subjects only needed to press the key that corresponded to the disk they wished to move. They were not told the rules for the task beforehand; rather, they were informed that the rules are implicit and had to be learned through the voice feedback that was added to the computer program to tell them when a movement was “incorrect,” a message that was shown simultaneously on the computer screen where subjects could read it. During the performance of HANOIPC3, the following parameters were measured: latency to first movement, total number of movements and number of correct movements.

(␣1, 7.5–10.5 Hz) alpha2 (␣2, 10.5–13.5 Hz), beta1 (␤1, 13.5–19.5 Hz) and beta2 (␤2, 19.5–30 Hz) and then the correlation spectrum is calculated from the autospectra and from the cross-spectrum of the signals proportioning values between −1 and +1. Correlation spectra at 0 delay for each subject and condition were obtained for each frequency band using amplitude values by means of Pearson product-moment coefficients such that interhemispheric correlation (INTERr) between homologous left and right derivations (F3–F4; P3–P4) and intrahemispheric correlation (INTRAr) between derivations of the same hemisphere (F3–P3; F4–P4) were obtained. Correlation values were transformed to Fisher’s z scores to approximate them to a normal distribution before any statistical procedure (Guilford and Fruchter, 1978). This z-score calculation was based on individual scores.

2.3. EEG recordings and procedure

2.4. Statistical analyses

All subjects were tested in a single session that lasted approximately 1 h. The EEGs were recorded in a shielded, dimly lit room, and recordings were made with subjects awake and in a sitting position, their heads supported by the back of a comfortable chair in two conditions: with eyes open at rest (5 min) and during performance of the Tower of Hanoi task (7 min maximum, with a 5-min interval between the two conditions). The recording sites were F3–F4, considered prefrontal areas, and P3–P4, considered parietal areas (Herwig et al., 2003; Homan et al., 1987; Okamoto et al., 2004; Rossi et al., 2001), according to the 10–20 International System (Jasper, 1958). All derivations were referred to linked ears, while the ground electrode was placed on the forehead. Linked ears were chosen as reference to avoid as far as possible the reference electrode and volume conduction contributions on scalp correlation, a procedure similar to those that have been proposed by Nunez et al. (1997) although digitally. EEGs were amplified using a Grass model P7 polygraph with EEG filters set at 1 and 30 Hz. Impedance for the EEG electrodes was kept below 10 kV. Specially designed software (Guevara et al., 2000) was used to sample (1024 points at a sample rate of 512 Hz) and store the EEG data for off-line processing. In addition, electrooculograms were recorded to detect eye-movement artifacts using a bipolar montage with electrodes placed at the outer canthi of both eyes. Epoch rejection was based on both visual and computer selection. The first and second authors examined the EEG signals off-line in order to identify saturated epochs or epochs with noise due to muscle activity, eye movement or heart activity. Thus, the EEG epochs that were visually identified as contaminated by noise were automatically removed by means of a computer program (CHECASEN) (Guevara et al., 2010) so that the background noise in the EEG was not different among the groups. The recordings were then reduced to 40 epochs (approx. 2 s each) which were representative of the entire time that EEG recording lasted. The EEGs were analyzed by means of a computerized program called EEGmagic (Guevara and Hernández-González, 2009) that initially calculates the Fast Fourier Transform (FFT) to six frequency bands: delta (ı, 1.5–3.5 Hz), theta (, 3.5–7.5 Hz), alpha1

In order to obtain homogeneous values for the behavioral parameters (total number of movements and number of correct movements) only the first three minutes of the Hanoi task were considered. In G1, latency was calculated with the values of all subjects; in G2 and G3, only the latency values of the subjects that completed the Hanoi task after 3 min were considered. These behavioral parameters were compared by means of a one-factor (three groups) analysis of variance (ANOVA) and a post hoc Tukey’s test was carried out to identify significant differences among comparisons. The level of significance was set at p ≤ 0.05. Also, a non-parametric analysis (X2 ) was performed for the complete or incomplete task parameter in the allotted time (7 min). In the EEG analyses, the total time that subjects used to solve the Hanoi task was considered. A two-factor analysis of variance (3 groups × 2 conditions) was performed for EEG correlations of each frequency band and for each pair of derivations. In other words, an analysis of variance was conducted for the values of EEG INTERr (F3–F4 and P3–P4) and INTRAr (F3–P3 and F4–P4) for each band, followed by Tukey’s tests for post hoc comparisons. Differences were considered significant when p < 0.05 was reached. 3. Results 3.1. Behavioral performance There were no effects related to age in any of the behavioral variables (latency to the first movement, total number of movements and number of correct movements). The X2 test revealed that the only significant difference among groups (p ≤ 0.01) was that a larger number of subjects in G2 (11/17) and G3 (12/17) completed the task in the allotted time (7 min), as compared to participants in G1 (4/17). 3.2. EEG correlation data 3.2.1. Comparisons among groups This comparison indicated that the INTERr (F3–F4, P3–P4) and INTRAr (F3–P3 and F4–P4) correlation of G2 and G3 showed a significant increase (p ≤ 0.01) in almost all

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Fig. 1. Mean ± 2 SE of the INTERr (A: F3–F4, B: P3–P4) and INTRAr (C: F3–P3, D: F4–P4) correlation in all bands of the three groups in both the basal and Hanoi conditions. The significant interactions are indicated by arrows (G1 vs. G2 and G3) and black lines above the bars (G2 vs. G3). Two-way ANOVA followed by Tukey tests. (p < 0.01 as compared to G1.

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bands in both the basal and Hanoi conditions as compared to G1 (Fig. 1). Two-way ANOVAs (3 Groups × 2 Conditions) showed significant differences in the interaction, but only in certain frequency bands, indicating that G2 and G3 showed a greater prefrontal INTERr than G1 as well as that G2 was different from G3 but only in the delta band (F2,48 = 2.93, p < 0.05) during the Hanoi performance (Fig. 1A). In the parietal INTERr significant interactions were also demonstrated, such that in the delta (F2,48 = 7.0, p < 0.01), theta (F2,48 = 4.59, p < 0.01), alpha1 (F2,48 = 2.79, p < 0.05) and beta2 bands (F2,48 = 3.89, p < 0.05) the G2 and G3 groups presented a greater correlation but only during the Hanoi performance as compared to G1; a significant interaction showed that G3 was different from G2 only in the delta (F2,48 = 7.0, p < 0.01) and theta (F2,48 = 4.59, p < 0.01) bands (Fig. 1B). In the left (F3–P3) and right prefrontal–parietal INTRAr (F4–P4), G2 and G3 showed similar r increases but only in the Hanoi condition as compared to G1 in delta (F2,48 = 7.93, p < 0.01; F2,48 = 3.51, p < 0.05), beta1 (F2,48 = 3.57, p < 0.05; F2,48 = 3.93, p < 0.05) and beta 2 (F2,48 = 3.82, p < 0.05; F2,48 = 3.76, p < 0.05) bands respectively (Fig. 1 C and 1D); only in the right prefrontal–parietal INTRAr a significant interaction showed that G2 was different from G3 in the delta (F2,48 = 3.51, p < 0.05) and beta2 bands (F2,48 = 3.76, p < 0.05) (Fig. 1D). 3.2.2. Comparison between conditions In the prefrontal INTERr (F3–F4) the G2 group presented a significant increase (p < 0.05) of the delta and theta bands during the Hanoi condition with respect to the basal condition, although a significant interaction was reached only in the delta band (F2,48 = 2.93, p < 0.05) (Fig. 2A). A characteristic parietal INTERr (P3–P4) was found for each age group during performance of the Hanoi task: statistical interaction between group × condition was significant (F2,48 = 7.0, p < 0.01) and indicated that G1 showed an increase only in the theta band, although in the comparison by conditions the alpha2 band was also significant (P < 0.01); G2 showed a significant increase in all frequency bands (Fig. 2B) in the comparison between conditions, but a significant interaction was observed only in the delta (F2,48 = 7.0, p < 0.01), theta (F2,48 = 4.59, p < 0.01), alpha1 (F2,48 = 2.79, p < 0.05) and beta2 bands (F2,48 = 3.89, p < 0.05), similarly, although in the comparison between conditions G3 showed an increase in delta, theta and beta1 bands, a significant interaction was reached only in the delta (F2,48 = 7.0, p < 0.01) and theta (F2,48 = 4.59, p < 0.01) bands (Fig. 2B). The left prefrontal–parietal INTRAr (F3–P3) showed no differences in G1, however, the G2 group presented a significant increase in all bands during Hanoi performance as compared to the basal condition, reaching a significant interaction in the delta (F2,48 = 7.93, p < 0.01), beta1 (F2,48 = 3.57, p < 0.05) and beta2 (F2,48 = 3.82, p < 0.05) bands. The G3 group was characterized by an increase in the alpha2 band (P < 0.05) that did not reach a significant interaction (Fig. 2C). The right prefrontal–parietal INTRAr (F4–P4), as in the case of the left hemisphere, showed no differences between the basal and Hanoi conditions in G1; in G2, significant

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increases were detected during Hanoi in all bands although the interaction was only significant in delta (F2,48 = 3.51, p < 0.05), beta1 (F2,48 = 3.93, p < 0.05) and beta2 (F2,48 = 3.76, p < 0.05). In the comparison between conditions, G3 had increases of the theta (p < 0.05), alpha2 (p < 0.01), and beta2 bands (p < 0.05), but a significant interaction was only reached in beta2 (F2,48 = 3.76, p < 0.05) (Fig. 2D). 4. Discussion The present correlation analyses revealed differences in the patterns of functional synchronization during the performance of the Tower of Hanoi task in relation to age between the prefrontal and parietal cortices, regions that have been associated with the adequate performance of executive functions (Anderson et al., 2005). With respect to performance results, no differences were found in the latency to the first movement among subjects that showed good performance (G2 and G3) and those with poor performance in the Hanoi task (G1); moreover, no differences were found in the total number of movements or the number of correct movements; hence these parameters were not associated with success in adequately completing the task in the allotted time. The fact that only the subjects in G2 and G3 successfully completed the task in the allotted time (7 min) could suggest that the development of the executive processes required to solve the Hanoi task continues through adolescence and into adulthood. These results are in accordance with those reported by León-Carrión et al. (2004) in children and adolescents between the ages of 6 and 17 years, where they demonstrate, using the Stroop test, that the development of the inhibitory control (an executive function implicated in this task), continues during childhood and adolescence. There are several studies that, through different tests and experimental designs, have shown this improvement of the executive functions with age (Anderson et al., 2001; Anderson, 2002; Crone et al., 2006; De Luca et al., 2003; Luna et al., 2004). Thus, this performance results could indicate that by the age of 18–30 years the executive capacities have completed their maturation and thus allow a faster and more efficient solution of the Hanoi task (Anderson, 2002; Crone et al., 2006; Cummings, 1993; Fuster, 2000; Reiss et al., 1996; Thatcher et al., 1987). This absence of differences in the behavioral results agrees with the proposals of other studies (Fireman, 1996) that have shown that the measurement of quantitative parameters alone does not suffice to explain the development of problem-solving abilities. Fireman (1996) suggests that problem-solving in children is more a matter of strategy development than of strategy selection. Taking into account this proposal, it is possible that all subjects in the three groups in this study developed strategies to solve the Hanoi task during application, but that the older subjects devised an adequate strategy more quickly and, therefore, finished the task earlier, whereas the younger subjects were slower to develop a strategy and, hence, most were unable to complete the task. Other studies support this suggestion that older subjects develop strategies to solve tasks faster than younger ones (Magar et al., 2010). Ahonniska

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Fig. 2. Mean ± 2 SE and mean of differences (MD) between the INTERr (A: F3–F4, B: P3–P4) and INTRAr (C: F3–P3, D: F4–P4) correlation during the basal and Hanoi conditions in each one of the three groups (G1, G2 and G3). The arrows indicate the differences that reach significant interactions. Two-way ANOVA followed by Tukey tests. *p ≤ 0.01, • p < 0.05 as compared to basal

et al. (2000), for example, have reported that older participants had a higher level and improved rate of the achieved score, as well as a decrease in total performance time while solving the Hanoi task. In this study, a computerized Hanoi task version was used in which the rules were not made explicit at the outset, but were provided through an auditory feedback procedure that compels the subjects to learn the rules progressively while developing and adjusting a cognitive strategy. Hence, it is probable that with this type of task application several executive processes (such as learning, planning, performing, working memory and ability to inhibit a prepotent response) could occur simultaneously, such that it is difficult to associate the EEG correlation changes to specific

executive process. However, it is possible to make some suggestions. In the EEG correlation analysis, comparisons among groups revealed that subjects of the G2 and G3 presented an increased INTERr and INTRAr in all derivations and almost all bands in both conditions, basal and Hanoi, as compared to subjects in G1. Fig. 1C and D indicate substantial effects at large inter-electrode distances with intrahemispheric correlations increasing with age in all bands except alpha2 in F4–P4. This is compatible with the expectations that arise from Thatcher’s two-compartment model (Thatcher et al., 1986), which suggests that increases in the development of long fibers during maturation will also augment the coupling between structures. These data are also similar to

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those reported by Marosi et al. (1992), who found that normal subjects between 6 and 16 years of age at rest showed an increased EEG coherence in relation to age between the vertex and posterior regions mainly in the delta and alpha bands. In this work, however, the correlation at shortto-medium interhemispheric distances showed no overall decrease with increasing age as Thatcher’s model would lead us to expect. On the contrary, an increase in the interhemispheric correlation was observed. The absence of any decrease in the interhemispheric correlation with age has been found in other reports (e.g., Barry et al., 2004). It has been suggested that higher levels of maturation in this cortico-cortical association system during adolescence may facilitate a faster and more accurate performance of mental tasks, including intelligence tests (Anokhin et al., 1999; Thatcher et al., 1986); thus, it is probable that this high coupling between the prefrontal and parietal cortices in older subjects could represent a characteristic functional organization that is reached with age which, as observed in this study, allowed those subjects to attain a faster and more efficient performance on the Hanoi task. Turning to comparisons between conditions, a different and characteristic correlation pattern was observed among the groups during performance in the Tower of Hanoi task. The younger subjects who failed to complete the task showed only increased parietal INTERr in the theta and alpha2 bands. The G2 group presented a higher prefrontal INTERr in the delta and theta bands during the Hanoi condition as well as an increased parietal INTERr and left and right INTRAr in almost all bands as compared to the basal condition; while G3 presented only well-defined and selective increases in the parietal INTERr and right INTRAr as compared to the basal condition. Considering that the subjects in G2 and G3 showed the highest efficacy and fastest execution of the Hanoi task, we hypothesized that these two groups would manifest a similar pattern of correlation. However, this did not prove to be the case. One possible explanation of the increase in the parietal INTERr and INTRAr of almost all bands during execution of Hanoi is that the subjects in G2 probably required a high level of processing and had to make a major effort to solve and complete the task in the assigned time. Some reports have demonstrated that the delta band appears during “concentration processes” in the execution of mental tasks which require attention to internal processing (Harmony et al., 1996). EEG synchrony in theta appears to facilitate functional connections in tasks with high demand for working memory and focused attention (Anokhin et al., 1999) and an increase in this band has been observed in relation to executive functions (Mizuhara and Yamaguchi, 2007) and the difficulty of the task (Basar et al., 2001; Fernandez et al., 2000; Harmony et al., 1999; Mizuki et al., 1980; Rugg and Dickens, 1982). Similar changes have been observed in the alpha band depending on the task difficulty (Rugg and Dickens, 1982) and increases in the beta rhythm have also been observed in association with attention during cognitive processes (Gundel and Wilson, 1992; Gutiérrez and Corsi-Cabrera, 1988; Ramos et al., 1993). Because the adequate performance of the Hanoi task requires the simultaneous occurrence of all the aforementioned processes, it is probable that this increased

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correlation in several frequency bands may reflect a richer repertoire of associative connections between the prefrontal and parietal cortices, such that the larger coupling between them could represent the appropriate functional organization that may well be required for the efficient performance of the Hanoi task among 18–20-year-olds. This suggestion may be supported by the fact that only the subjects in G2 showed the increased prefrontal (F3–F4) correlation in the delta and theta bands, which has been associated with a major effort and concentration to solve tasks (Ballard, 1996; Corsi-Cabrera et al., 1994; Inanaga, 1998; Kubota et al., 2001; Paus et al., 1997; Smith et al., 2004). Taking into account this consideration, it is possible to suggest that the poor performance showed by the younger subjects in G1 could be associated with a poor coupling between prefrontal and parietal cortices that proved insufficient to allow a faster and more adequate performance of the Tower task. The subjects in G3 presented a higher parietal INTERr in the delta and theta bands and an increased INTRAr in the theta, alpha2 and beta2 bands mainly in the right hemisphere during the Hanoi task. This specific synchronization of certain frequency bands, mainly at large inter-electrode distances between prefrontal and parietal cortices, could be an index of cerebral efficiency associated with the facility with which those subjects completed the task without manifesting a generalized coupling of all frequency bands. This suggestion could support the “brain efficiency hypothesis,” which holds that the brains of high-IQ individuals show less overall activity during tasks because they are used more efficiently (Anokhin et al., 1999; Haier, 1993). These results also agree with other studies that have found a major frontal–occipital correlation in relation to the performance of cognitive tasks only in specific frequencies (theta and alpha bands) (Anokhin et al., 1999). Although in this study IQ was not measured, we ensured that all subjects included in the experiment had no learning problems, for example in the case of the G1 group, all subjects had a mean schooling above 8.5, whereas the subjects in the G2 and G3 groups were regular students at the university or professional people. Thus, the possibility that the correlation changes could be result from IQ differences between subjects is low. The frequency bands that showed the highest coupling between the prefrontal and parietal cortices in the G3 subjects during the Hanoi task are the same ones that have been associated with the performance of other cognitive tasks. It has been suggested that spatial EEG synchrony, particularly in the theta band, appears to be one of the most important conditions for the successful performance of mental tasks that require the allocation of focused attention and working memory resources (Doppelmayr et al., 1998; Gevins et al., 1995; Grunwald et al., 1999; Mizuhara and Yamaguchi, 2007; Rugg and Dickens, 1982). Sarnthein et al. (1998) have indicated a significant enhancement in theta coherence during cognitive tasks that impose high demands on working memory and concluded that the working memory function involves synchronization between the prefrontal and posterior association cortex through phase-locked theta activity. Similar increases

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in the frequencies (Basar et al., 2001) and coherence of the alpha band have been demonstrated during the performance of cognitive tasks (Anokhin et al., 1999), as well as of the delta (Harmony et al., 1996; Basar et al., 2001; Fernandez et al., 2000) and beta rhythms (Ramos et al., 1993). Although almost one hundred methods have been developed to detect fluctuations in EEG synchrony (for example Granger causality, phase synchrony indices, stochastic event synchrony, Bayesian approach, reduced coherency, among many others) (Dauwels et al., 2010; Alba et al., 2007; Nunez et al., 1997), coefficient correlation was used in this work considering its widespread use in a great quantity of studies as well as its sensitivity to detect changes in phase and polarity, independently of amplitudes (Guevara and Corsi-Cabrera, 1996).This procedure, like other methods, has limitations because several factors, such as reference electrode and volume conduction, can generate erroneous synchrony measures. In the present communication our intention is not to discuss the advantages and disadvantages of the different methods that have been developed to calculate EEG synchronization, nor to determine if the EEG sources are the cortical areas located just under the electrode sites, but simply to compare the degree of prefrontal–parietal correlation in three populations during the performance of the Tower of Hanoi Task, so that explaining and solving this problems clearly goes beyond the scope of this paper. As was mentioned above, the scalp EEG signals depend on the reference, and the synchrony of two signals may thus equally depend on the choice of reference (Nunez et al., 1997). Since we used the same reference (linked ears) for all subjects, it is less probable that differences in EEG synchrony are related to the choice of the reference electrode. On the other hand, coherence may be strongly inflated by volume conduction at short distances and at low frequencies (Leopold and Logothetis, 2003), while volume conductivity can be negligible between long distances (Nunez et al., 2001); thus, considering that the distance between the left and right prefrontal and the left and right parietal electrodes used for the comparisons in the present study is larger than 12 cm, it is probable that the reported changes may be attributed to other brain events and not only to volume conduction. An accurate assessment of synchrony may be obtained by transforming the data with a Surface Laplacian, as suggested by Nunez (2000). Unfortunately, the application of this method requires many derivations (perhaps 48–128 electrodes) and in this study only four were recorded, which are not enough to use this method. Taken together, these results demonstrate that the functional coupling between the prefrontal and parietal cortices shows a characteristic pattern during the performance of the Hanoi task that is specific to each age group, but was not associated with the successful performance of the task. Additional research is required. Although it has been shown that it is very difficult to relate the results of simple Hanoi tasks with cognitive and maturation processes (Bishop et al., 2001), there are other studies in which, using fMRI had reported with moderate accuracy when participants are planning a future sequence of moves in the Hanoi

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