Abstract

The neuropsychological correlates of inter-individual variations in cortical folding are poorly understood. Anterior cingulate (AC) cortex is one region characterized by considerable variability, particularly with respect to the paracingulate sulcus (PCS), which is present in only 30–60% of individuals and more commonly found in the left cerebral hemisphere. To investigate whether inter-individual differences in this PCS asymmetry are related to cognitive performance, we classified 30 healthy right-handed males as displaying either a leftward, rightward or symmetric pattern of folding based on the incidence and extent of the PCS in each hemisphere, and compared their performance on tasks engaging executive cognitive processes associated with frontal lobe function. We found that the more common leftward PCS asymmetry was associated with better performance across verbal and non-verbal executive tasks, but that PCS variability had no effect on tasks less dependent on executive functions. These results suggest that the leftward pattern of folding is associated with a non-specific performance advantage on cognitively demanding executive function tasks, possibly due to differences in functional interactions between AC/paracingulate cortex and connected frontal regions. It therefore appears that normal variations in brain morphology are associated with individual differences in cognitive abilities.

Introduction

The surface morphology of human cerebral cortex is highly variable across individuals, with sulcal landmarks displaying considerable variation in incidence, course and extent (Ono et al., 1990; Thompson et al., 1996). Recent evidence indicates that these topographical variations affect the structure, cytoarchitecture, and pattern of connections of surrounding cortex (Welker, 1990; Rademacher et al., 1993; Vogt et al., 1995; Paus et al., 1996a; Scannell, 1997; Van Essen, 1997), raising the possibility that individual differences in cortical folding may have functional consequences that manifest across aspects of cognition and/or behaviour. Consistent with this, previous studies have demonstrated relationships between variations in sulcal extent and functional specialization in both healthy (Amunts et al., 1997) and clinical populations (Mega et al., 1998). However, these investigations focused on primary sulci, which emerge early in fetal development and are present in all individuals (Chi et al., 1977; Armstrong et al., 1995). In contrast, the functional consequences of variations in the incidence and extent of the more variable tertiary sulci, which emerge during the second and third trimesters of gestation and are not apparent in all individuals (Chi et al., 1977; Armstrong et al., 1995), are poorly understood.

Human anterior cingulate (AC) cortex is well suited for investigating such brain–behaviour relationships, specifically with respect to the incidence and extent of the paracingulate sulcus (PCS). The PCS is a tertiary sulcus present in only 30–60% of cases (Paus et al., 1996b; Yücel et al., 2001), and (when present) runs dorsal and parallel to the cingulate sulcus (CS), forming the superior border of the paracingulate gyrus. Converging evidence from in vivo Magnetic Resonance Imaging (MRI) (Paus et al., 1996a) and post-mortem (Vogt et al., 1995) investigations indicates that this produces a relative expansion of paralimbic AC cortex (corresponding to Brodmann Areas 24c and 32), such that it becomes located on the surface of the paracingulate gyrus, in contrast to occupying the dorsal bank of the CS when the PCS is absent (see Fig. 1). The paralimbic belt of the AC is also termed the paracingulate cortex, and represents a cingulo-frontal transition area, given its reciprocal connections with pre-frontal regions (Vogt et al., 1995; Mega and Cummings, 1997).

Although paracingulate cortex is cytoarchitectonically distinct from limbic AC cortex (which consists of areas 24a, 24b and 25), it occupies a large portion of what has been termed the ‘cognitive’ division of the AC (Devinsky et al., 1995; Bush et al., 2000). This corresponds to a dorsal portion of the AC comprising areas 24b′, -c′, and 32′ that extends from the genu of the corpus callosum to the level of the anterior commissure, and is distinct from a rostro-ventral ‘affective’ division and a caudal ‘motor’ division (Devinsky et al., 1995; Bush et al., 2000). Variations in PCS incidence and extent would be expected to affect the functions ascribed to this area, given the consequences such variability entails for the cytoarchitecture, volume, and connections of this region (Welker, 1990; Vogt et al., 1995; Paus et al., 1996a). In particular, Paus et al. (1996a,b) have highlighted the role of paracingulate cortex in language, following evidence that it is part of the AC vocalization region in monkeys (Devinsky et al., 1995), that it is more pronounced in human than non-human primates (Vogt et al., 1995), and that left paracingulate cortex is activated in functional imaging studies of word generation in humans (Herholz et al., 1996; Crosson et al., 1999). It is also interesting to note that that individuals possessing at least one PCS are more likely to demonstrate a leftward asymmetry, such that its incidence and rostro-caudal extent is greater in the left hemisphere (Paus et al., 1996b; Yücel et al., 2001). This has led Paus et al. (1996a,b) to suggest that this leftward population bias in humans, and consequent expansion of left paracingulate cortex, evolved in accordance with left hemisphere specialization for language. A corollary of this view would be that individuals possessing this leftward asymmetry should display a performance advantage on tests of related verbal processes when compared with those with either a rightward or symmetric pattern of AC/paracingulate folding. However, paracingulate activation has also been observed during performance on a variety of non-verbal tests of executive, higher-order processes including spatial working memory (SWM) and planning (Baker et al., 1996; Owen et al., 1996a; Dagher et al., 1999; Duncan and Owen, 2000). Consequently, some have suggested that the dorsal (‘cognitive’) AC serves a less specific role in cognition, interacting with regions of lateral prefrontal cortex (PFC) to mediate performance across a wide variety of cognitively demanding (verbal and non-verbal) tasks, particularly those tapping executive cognitive processes (Carter et al., 1998; Duncan and Owen, 2000). Interestingly, although left paracingulate activation has been reported during verbal tasks (Herholz et al., 1996; Crosson et al., 1999), right paracingulate cortex has been activated during spatial tests of executive function (Baker et al., 1996; Owen et al., 1996a), suggesting that the attribution of PCS asymmetry to language alone may be overly simplistic.

In this study, we sought to investigate the neuropsychological consequences of variations in AC/paracingulate morphology in a healthy sample. Consistent with previous studies (Paus et al., 1996a,b; Yücel et al., 2001), we used a categorical method for classifying PCS variability that is sensitive to variations in both the incidence and extent of the PCS across the two cerebral hemispheres, and examined their performance on a series of verbal and non-verbal neuropsychological tasks. Participants were classified as displaying either a leftward asymmetric, rightward asymmetric, or symmetric pattern of AC/paracingulate cortical folding, and their performance on a verbal and non-verbal test of executive cognition typically associated with frontal lobe function was compared. The former was assessed with a verbal fluency task (Spreen and Strauss, 1998) and the latter with a test of SWM (Owen et al., 1990). Both tasks have been shown to depend on executive cognitive processes that are impaired by lesions to the frontal lobes (Owen et al., 1990, 1996b; Stuss et al., 1998). Furthermore, previous functional imaging studies have demonstrated left paracingulate activation during verb generation (Herholz et al., 1996; Crosson et al., 1999), and right paracingulate activation during the SWM task (Owen et al., 1996a). Consequently, comparing performance across verbal and spatial domains of executive functioning enabled us to determine whether the influence of PCS asymmetry on task performance was related to task parameters common to both tests, or whether it varied as a function of task modality. Consistent with the latter view, we expected that individuals possessing a leftward PCS asymmetry would demonstrate better performance on the Controlled Oral Word Association Task (COWAT), whereas a rightward PCS asymmetry would be associated with better performance on the SWM task. To examine the specificity of our findings, we also report data from performance on tests placing minimal demands on executive cognitive processes. Thus, we expected AC/paracingulate morphology to be associated with performance on tasks requiring executive cognitive processes associated with frontal lobe function, but not those tapping other processes likely to be mediated primarily by non-frontal brain regions.

Materials and Methods

Participants

The data used in this study was obtained from a larger database comprising several ongoing research studies being conducted at the Mental Health Research Institute (MHRI), Victoria. Only participants with the relevant MRI and neuropsychological test data were included in the study. All data were collected following approval from appropriate ethics committees and informed consent was obtained from all participants prior to MRI scanning and neuropsychological testing. The sample comprised 30 right-handed males with no personal or family history of psychiatric illness or neurological complications. Only right-handed males were included since sex differences have been reported with respect to AC morphological asymmetries, and the effects of handedness are as yet unclear (Paus et al., 1996b; Yücel et al., 2001). Handedness was assessed using the Edinburgh Handedness Inventory (Oldfield, 1971). All but two participants had completed high school education. These remaining two had completed a minimum of 10 years of schooling.

MRI Protocol

Participants were scanned using a GE Signa 1.5 T scanner at the Royal Melbourne Hospital, Victoria, Australia. A three-dimensional volumetric SPGR sequence generated 124 contiguous, 1.5 mm coronal slices. Imaging parameters were: time-to-echo, 3.3 ms; time-to-repetition, 14.3 ms; flip angle, 30_; matrix size, 256 × 256; field of view, 24 × 24 cm; voxel dimensions, 0.938 × 0.938 × 1.5 mm. MRI data were transferred from DAT tape to an SGI-02 workstation and coded to ensure participants confidentiality and blinded rating. Classification of AC morphology was performed using MEDx 3.0 (Sensor Systems).

Classification of Anterior Cingulate Morphology

Within each hemisphere, the PCS was classified according to its presence/absence and rostro-caudal extent using a reliable method (see Yücel et al., 2001). Briefly, if there was a clearly observable horizontal sulcus running dorsal and parallel to the CS for >40 mm, with no more than 20 mm of interruptions in total between its anterior origin and an arbitrary vertical line passing through the anterior commissure, the PCS was considered ‘prominent’. If these interruptions were >20 mm, but there was still a clearly identifiable horizontal element running parallel to the CS for >20 mm, a classification of ‘present’ was made. If there were no clearly identifiable horizontal sulci running dorsal and parallel to the CS for >20 mm, the PCS was considered ‘absent’. An asymmetry occurred if the PCS classification made in one hemisphere indicated a larger PCS than in the other. For example, a participant with a ‘prominent’ right PCS and a ‘present’ or ‘absent’ left PCS would be classified as rightward asymmetric. Similarly, someone with a ‘present’ left PCS and an ‘absent’ right PCS would be classified as leftward asymmetric, and so on. A symmetric pattern occurred if the PCS classification was equivalent for both hemispheres. All classifications were made blind to cognitive performance. Examples of each PCS type and asymmetry category are presented in Figure 1.

In addition to facilitating comparisons with previous anatomical investigations of this region (Paus et al., 1996b; Yücel et al., 2001), the advantage of this categorical method is that it allows consideration of all cases, irrespective of whether the PCS is present or absent. Other approaches, such as measuring the volume of intrasulcal grey matter (Paus et al., 1996a), are limited to the extent that they are only applicable to individuals that actually have a PCS. Furthermore, the approach of ‘pairing’ left and right hemisphere classifications to define a measure of asymmetry is more amenable to analysis of variance (ANOVA) models, since these analyses assume independence between categories and analysing the effects of morphology in both hemispheres separately for each individual does not yield independent observations.

Hemispheric Gyrification Index (HGI)

To determine the specificity of results regarding AC folding, we also used a previously validated and semi-automated method (see Yücel et al., 2001) to derive a hemispheric gyrification index (HGI) for each hemisphere of each participant. Briefly, surface-to-volume ratios were calculated separately for each hemisphere, expressed as the total number of surface voxels divided by the total number of volume voxels. As such, higher ratios indicate greater complexity of cortical folding. We derived an asymmetry score by subtracting the HGI for the right hemisphere from that of the left. Thus, negative values represent an overall rightward asymmetry and positive values a leftward asymmetry.

Neuropsychological Measures

Participants completed a number of cognitive tasks as part of ongoing research protocols conducted within our unit. Selection of specific tasks for this study was based on previous evidence indicating that the task tapped processes associated with dorsal AC function, and the practical constraint that performance data on all the tasks was available for all participants in the sample.

Verbal Fluency

Verbal fluency was assessed using the COWAT administered according to standard procedures (Spreen and Strauss, 1998). It comprises three 60 s trials and requires participants to generate as many words as possible beginning with a particular letter within the allotted time. Participants were instructed to avoid using proper nouns or numbers, repeating words, or adding suffixes to previously generated words (e.g. ‘shoot, shooting, shot’). Performance was assessed by summing the number of words produced across the three 60 s trials. As a corollary analysis, we divided the task into 30 s epochs to examine whether the influence of PCS variability varies with the working memory demands of the task. This follows recent evidence that these demands, and associated neural activity, vary as a function of time spent performing the task (Wood et al., 2001). That is, while the first 30 s requires active search and retrieval of words from the lexical store, the latter 30 s places an increased demand on participants’ manipulation and inhibitory processes, as they must remember which words they have previously produced while trying to generate new ones. This, in turn, coincides with changes in regions of frontal cortex activated during task performance (Wood et al., 2001).

SWM

SWM was assessed with the SWM subtest of the Cambridge Neuropsychological Test Automated Battery (CANTAB), and a detailed description has been provided elsewhere (Owen et al., 1996b). Briefly, participants had to perform a self-ordered search through an array of boxes in order to find a token hidden inside one of them (see Fig. 2). Once found, the boxes went blank again so that another search could be initiated, with the key instruction being that a token would never appear in a box in which it had already been found. The test comprised five levels of increasing difficulty, corresponding to two-, three-, four-, six-, and eight-box stages. Performance was assessed by recording the number of errors committed at each of the five stages. These occurred when, during the same search sequence, participants erroneously searched a box in which a token had already been found.

Spatial Span

We controlled for differences in SWM capacity using the Spatial Span subtest of the CANTAB (Owen et al., 1996b), which is a computerized version of the Corsi block tapping task (Milner, 1971). Participants were presented with a series of white squares that changed colour and were required to remember the location and sequential order of the colour changes. The test began at a two square level, and increased by one following each successful trial until a maximum of nine squares. The spatial span was defined as the highest level at which participants remembered at least one sequence of colour changes correctly. While there is some evidence to suggest that intact spatial span performance relies on storage processes mediated by the parietal lobes, patients with frontal lobe lesions are unimpaired on this task (Owen et al., 1990, 1996b; D’Esposito and Postle, 1999). Consequently, this task served as a spatial control task deemed to be less dependent on the integrity of executive cognitive functions associated with the frontal lobes.

Verbal Paired Associate Learning (VPAL)

In the Verbal Paired Associate Learning (VPAL) task, participants must remember eight word pairs read to them by the experimenter. Four of these are ‘easy’ pairs, based on their obvious semantic relation (e.g. baby-cries), and four are ‘hard’ pairs that are made more difficult by their apparently arbitrary pairings (e.g. cabbage-pen). Performance on the easy pairs was at ceiling, so we only report that for the hard pairs, which was measured by summing the number of correctly recalled pairs across three learning trials (a maximum of 12 pairs). Performance on this task requires the ability to form arbitrary associations, and appears to be critically dependent on the integrity of medial temporal lobe structures (Saling et al., 1993; Weintrob et al., 2002). Thus, it was employed here as a verbal control task that places less demand on executive cognitive processes traditionally associated with frontal lobe function.

National Adult Reading Test — Estimated Intelligence Quotient (NART-estimated IQ)

Wechsler Adult Intelligence Scale — Revised Full Scale IQ (Wechsler, 1981) was estimated from performance on the NART using re-standardization tables (Nelson and Willison, 1991). Additionally, because the NART tests participants’ ability to read irregular words (e.g. KNIFE), performance depends on both IQ and vocabulary size. As such, this measure served as an appropriate control for both intellectual ability and individual differences in overall vocabulary size (an important consideration with respect to verbal fluency performance).

Data Processing and Analysis

Total verbal fluency performance was assessed using between-groups analysis of covariance (ANCOVA), while performance across the two 30 s COWAT epochs was analysed with repeated measures ANCOVA, using SPSS for Windows version 10.0. SWM performance at the two-, three- and four-box levels was at ceiling and produced insufficient variance for statistical analysis (see Fig. 4), so our analysis was restricted to the six- and eight-box levels. Initial inspection of these variables indicated gross departures from normality, meaning that traditional ANOVA was inappropriate.

Count data such as errors often follow a non-normal Poisson distribution, where the mean is equal to the variance. However, this was not the case for the present data, as the variables had greater variance than expected (i.e. they were overdispersed with respect to the assumptions of the Poisson model). In such situations, it is appropriate to employ negative binomial models (Gardner et al., 1995). Typically, these analyses assume that observations are independent, meaning that they cannot be applied to repeated-measures data. To overcome this, we used the method of generalizing estimated equations (Diggle et al., 1994; Liang and Zeger, 1986; Zeger and Liang, 1986) as implemented in the STATA 7.0 (STATA Corporation) software package. This method initially estimates regression parameters assuming independent observations, and then uses the residuals to estimate correlations among observations from the same participants in order to derive new parameter estimates. This process continues until the change between the two successive estimates is very small. This allowed the effects of group, level and additional covariates to be modelled. The influence of age at testing, NART-estimated IQ, and HGI asymmetry on performance was investigated by employing these measures as covariates in all analyses. All comparisons were made with α = 0.05.

Results

Of the 30 participants in the sample, eight were classified as rightward asymmetric, nine as symmetric, and 13 as leftward asymmetric. Demographic and other group details are presented in Table 1. No significant group differences were identified for any of these variables.

Verbal Fluency

Age and HGI asymmetry were not significant predictors of verbal fluency performance. As such, the results reported here are derived from models that do not covary for these measures. Covarying for NART-estimated IQ, there was a significant effect of PCS asymmetry on total verbal fluency performance [F(2,26) = 3.84, P = 0.035]. Simple planned contrasts revealed that individuals with either a symmetric or rightward pattern generated significantly fewer words than those with a leftward asymmetry [t(20) = –2.16, P = 0.021 and t(19) = –2.46, P = 0.041, respectively]. There was no difference between the rightward and symmetric groups [t(15) = –1.29, p = 0.723]. The effect of PCS asymmetry on total COWAT performance was no longer significant when NART-estimated IQ was omitted as a covariate [F(2,27) = 1.031, p = 0.370]. One possibility may have been that entry of NART-estimated IQ as a covariate lead to a significant difference because it suppressed the influence of outliers. To examine this further, we computed Cook’s distance for all points in the data set. None of these values were >1 (range: 0.00–0.27), suggesting our results are not due to covariate suppression of outlier effects.

All groups produced significantly fewer words in the latter 30 s when controlling for NART-estimated IQ [F(1,26) = 4.30, P = 0.048]. However, there was no interaction between PCS asymmetry and epoch [F(2,26) = 0.46, P = 0.635], suggesting that the effect of PCS asymmetry was constant across COWAT epochs. This effect is illustrated in Figure 3.

SWM

Given the non-normal distribution of the SWM variables, means and standard deviations are not the appropriate descriptive statistics. Rather, we present box and whisker plots of the number of errors committed by each group at each stage of the SWM task in Figure 4 to illustrate relative group differences as a function of working memory load. NART-estimated IQ, age, and HGI asymmetry were not significant predictors of SWM performance. Consequently, the results reported here are derived from models that do not covary for these measures. There were significant main effects of working memory load (z = 6.22, P < 0.001) and PCS asymmetry (z = –2.35, P = 0.019), but no interaction (z = –0.34, P = 0.732). Despite this, pairwise comparisons indicated that although there were no group differences at the six-box level, the leftward asymmetric group committed significantly fewer errors than either the symmetric or rightward asymmetric groups at the eight-box level (z = –2.08, P = 0.037 and z = –2.36, P = 0.018, respectively).

Spatial Span

Group means for spatial span performance are presented in Table 1. There were no significant group differences [F(2,26) = 0.301, P = 0.742]. NART-estimated IQ, age, and HGI asymmetry did not contribute to the model.

VPAL

The mean total VPAL (hard pairs) performance of each group is presented in Table 1. There were no significant group differences in VPAL performance [F(2,27) = 0.25, P = 0.78]. NART-estimated IQ, age, and HGI asymmetry did not contribute to the model.

Discussion

Our results support the notion that individual differences in cortical folding carry implications for cognitive function, to the extent that participants with a leftward PCS asymmetry demonstrated better performance than those displaying either a rightward or symmetric pattern on both a verbal and spatial task engaging executive cognitive processes. Further, these morphological variations were not found to affect performance on tasks that place minimal demand on these processes. These findings were not due to differences in age at time of testing, overall HGI asymmetry, or NART-estimated IQ, and suggest that inter-individual variations in brain morphology affect the efficiency with which related functions are engaged by adjacent cortex.

Why Is a Leftward Asymmetry Associated with Better Task Performance?

Leftward PCS asymmetry is the most common pattern of AC/paracingulate folding seen in healthy populations (Paus et al., 1996b; Yücel et al., 2001). That this asymmetry was associated with a performance advantage on both a verbal and non-verbal task goes against the view that the functional significance of such a population bias is restricted to the domain of language, as suggested by Paus et al. (1996a,b). Moreover, the results contradict our expectations that the relationship between PCS asymmetry and task performance would vary as a function of task modality (i.e. that a leftward asymmetry would be associated with better verbal fluency performance, and a rightward asymmetry with better SWM performance). Rather, our findings indicate that a leftward PCS asymmetry is associated with an advantage for broader cognitive processes common to performance on both tasks (discussed below).

As a consequence, the precise reason for the existence of a leftward population bias, and why this may confer a processing advantage over a symmetric or rightward asymmetric pattern, remains unclear. Regarding why healthy individuals are more likely to manifest a leftward PCS asymmetry, the fact that sulcal/gyral patterns are principally formed perinatally (Armstrong et al., 1995; Chi et al., 1977) suggests that certain aspects of the intrauterine environment bias the mechanisms responsible for gyral development (Welker, 1990; Van Essen, 1997) in such a manner that the incidence of the PCS will be greater in the left hemisphere for most people (Paus et al., 1996b; Yücel et al., 2001). Interestingly, Paus et al. (1996a) have found that PCS grey matter volume negatively correlates with that of the anterior portion of the CS, leading them to suggest that the tendency towards a leftward PCS asymmetry is secondary to increased grey matter volume in the right anterior CS, since the latter is a primary sulcus whose emergence precedes that of the PCS. Given that the absence of a PCS is associated with enlarged limbic AC cortex and reduced paracingulate cortex (Vogt et al., 1995; Paus et al., 1996a), it is unclear whether the performance advantage of individuals with a leftward PCS asymmetry in our study was due to such an asymmetry leading to increased paracingulate volume in the left hemisphere, or increased limbic AC cortex in the right hemisphere. Considering the reported connections between paracingulate cortex and lateral PFC (Vogt et al., 1995; Mega and Cummings, 1997), and the fact that the dorsal, ‘cognitive’ portion of the AC (of which the paracingulate forms a large part) is the specific region most often co-activated with lateral PFC during functional imaging studies of cognitive performance (Passingham, 1998; Carter et al., 2000; Duncan and Owen, 2000; Koski and Paus, 2000), we expect that the former is more likely.

Investigation of the nature of functional lateralization within AC and paracingulate cortex and how this is related to morphological variations of this region is needed to clarify such issues, and to begin to parse structure–function relationships within the more broadly defined ‘cognitive’ AC region (Bush et al., 2000). Indeed, our results suggest that a leftward PCS asymmetry represents a particularly efficient configuration, either within dorsal AC or between this region and other parts of the cerebrum, that facilitates its role within a neural network subserving performance on tests engaging executive cognitive processes.

How Might Variations in AC/Paracingulate Morphology Affect Task Performance?

The finding that AC/paracingulate morphology affected performance only on tasks engaging executive cognitive processes suggests that anatomical variations of this region have implications for frontal lobe function. Further, the performance advantage of leftward asymmetric individuals on both the verbal fluency and SWM task suggests that this influence does not vary as a function of task modality, but that it is related to cognitive processes common to both tasks. Recently, researchers have begun to emphasize the working memory component associated with COWAT performance, with patterns of neural activity varying in a predictable manner in accordance with the test’s working memory demands (Wood et al., 2001). This would implicate the engagement of working memory processes as the common thread associated with a performance advantage for leftward asymmetric individuals across the verbal fluency and SWM tasks.

Broadly, working memory may be defined as the ability to retrieve and maintain information ‘on-line’, and to manipulate and use this information to guide behaviour (Baddeley, 1996). Although working memory processes are typically associated with lateral PFC (D’Esposito et al., 1998; Goldman-Rakic, 1998; Owen et al., 1999), a role for AC cortex during performance on these tasks is suggested by converging evidence that it serves to detect non-routine situations and signal lateral PFC to engage working memory and other top-down cognitive processes that optimize task performance (Carter et al., 2000; MacDonald et al., 2000; Bunge et al., 2001; Miller and Cohen, 2001). Thus, one possibility is that the influence of PCS variability on task performance observed in our results reflects an alteration in the efficiency of functional interactions between dorsal AC and prefrontal regions. This view is supported by the fact that the effect of PCS variability on verbal fluency was significant only when controlling for differences in vocabulary size (using NART-estimated IQ), suggesting it was related to the ‘on-line’ aspects of working memory performance, rather than differences in information (e.g. vocabulary) likely to be stored in posterior association areas (Jonides et al., 1998). A similar pattern of performance was evident in the spatial domain to the extent that we found no group differences for the spatial span task. Performance on this task depends on integrity of posterior, but not frontal, cortical regions (Owen et al., 1990; D’Esposito and Postle, 1999), suggesting the additional working memory processes engaged by the SWM task appear to be those that were affected by PCS variability. Moreover, while a recent functional MRI study conducted by Wood et al. (2001) has reported activation of both AC cortex and lateral PFC on the COWAT, only activation of the latter predicted task performance. Thus, the effect of PCS variability observed in our study may not be on the efficiency with which relevant functions are mediated by dorsal AC cortex per se, but may instead reflect differences in the efficiency of functional interactions between dorsal AC and prefrontal regions.

A final, unresolved issue is whether the influence of AC/paracingulate morphology on performance varies as a function of working memory load. Although co-activation of AC/paracingulate cortex and PFC in response to increasing load has been a common finding (Barch et al., 1997; Seidman et al., 1998; Koski and Paus, 2000) our results remain inconclusive on this issue. That is, although there was no interaction between PCS asymmetry and working memory load on the SWM task, simple comparisons revealed that significant differences only emerged at the most difficult eight-box level (see Fig. 4). Thus, the absence of an interaction in our results is likely to reflect the fact that we could only reliably analyse one increment in working memory load, which provided a relatively insensitive measure of performance as a function of increasing cognitive demands. A similar limitation applies to the verbal fluency task, limiting the conclusions that can be drawn on this issue. Alternatively, the lack of relationship in our results may reflect the fact that dorsal AC activity is associated with processes other than working memory during performance under conditions of increasing difficulty (Barch et al., 1997).

Limitations and Conclusions

We attempted to minimize confounds by limiting our sample to right-handed males, following evidence that PCS asymmetries are not as pronounced in females, and that the influence of handedness is unclear (Paus et al., 1996b; Yücel et al., 2001). As such, our findings are not generalizable outside this population until these effects are elucidated.

One of the problems in conducting an investigation of the type reported here in a prospective manner is that it requires large numbers, since it cannot be known a priori which PCS category an individual will fall into and previous evidence suggests an asymmetric distribution of group membership (Paus et al., 1996b; Yücel et al., 2001). However, our retrospective analysis suggests that structure–function relationships in AC/paracingulate cortex warrant further study. To this end, further testing of larger samples with a variety of neuropsychological tasks aimed at identifying the specific cognitive processes influenced by variations in AC/paracingulate morphology would assist in clarifying the nature of such relationships.

Despite these limitations, our results provide preliminary support for the notion that inter-individual variations in the convolutional patterns of the AC/paracingulate region, which reflect differences in its underlying structural and functional properties (Welker, 1990; Rademacher et al., 1993; Vogt et al., 1995; Paus et al., 1996a; Scannell, 1997; Van Essen, 1997), are related to differential performance on tests of related cognitive functions. That is, our results suggest that the population bias for a leftward PCS asymmetry may represent a more efficient configuration of dorsal AC cortex that facilitates functional interactions between this region and lateral PFC. These findings carry implications not only for understanding the relationship between variations in brain morphology and individual differences in cognitive abilities, but also for functional imaging research that employs group averaging procedures. Indeed, our results suggest that the use of such methods reduces potentially important information regarding the influence of brain structure and function on cognitive performance.

This research was supported by the Melbourne Neuropsychiatry Centre (Sunshine Hospital), Department of Psychiatry, the University of Melbourne, the National Health and Medical Research Council (ID 236 175), the Jack Brockhoff Foundation, the Ian Potter Foundation, the L.E.W. Carty Trust, and the Percy Baxter Charitable Trust, Melbourne, Australia.

Address correspondence to Alexander Fornito, Cognitive Neuropsychiatry Research and Academic Unit, Sunshine Hospital, PO Box 294, St Albans, Victoria, 3021 Australia. Email: alexander.fornito@wh.org.au.

Figure 1. Magnetic resonance images of the right and left cerebral hemispheres of three individuals demonstrating examples of a leftward asymmetry (R < L; top two images), rightward asymmetry (R > L; bottom two images) and symmetry (R = L; middle two images) of the PCS. The images on the right (from top to bottom) also illustrate the three classifications of paracingulate morphology (prominent, present and absent) with the paracingulate gyrus (paralimbic region) highlighted in red and the anterior cingulate gyrus (limbic region) highlighted in green. The images on the left also illustrate the three classifications of paracingulate morphology (in reverse order) without the highlights. Arrows indicate the location and course of the PCS. Note that although there appears to be a sulcus running dorsal and parallel to the cingulate sulcus in the top left image, the morphological classification is absent because this sulcus does not persist for >20 mm on three adjacent slices. The vertical red line passing through the anterior commissure was used to demarcate the boundary between anterior and posterior cingulate cortices.

Figure 1. Magnetic resonance images of the right and left cerebral hemispheres of three individuals demonstrating examples of a leftward asymmetry (R < L; top two images), rightward asymmetry (R > L; bottom two images) and symmetry (R = L; middle two images) of the PCS. The images on the right (from top to bottom) also illustrate the three classifications of paracingulate morphology (prominent, present and absent) with the paracingulate gyrus (paralimbic region) highlighted in red and the anterior cingulate gyrus (limbic region) highlighted in green. The images on the left also illustrate the three classifications of paracingulate morphology (in reverse order) without the highlights. Arrows indicate the location and course of the PCS. Note that although there appears to be a sulcus running dorsal and parallel to the cingulate sulcus in the top left image, the morphological classification is absent because this sulcus does not persist for >20 mm on three adjacent slices. The vertical red line passing through the anterior commissure was used to demarcate the boundary between anterior and posterior cingulate cortices.

Figure 2. Example of the visual display presented during the SWM task.

Figure 2. Example of the visual display presented during the SWM task.

Figure 3. Mean words generated by each group during each COWAT epoch, adjusted for estimated IQ. Error bars represent 95% confidence intervals around adjusted means.

Figure 3. Mean words generated by each group during each COWAT epoch, adjusted for estimated IQ. Error bars represent 95% confidence intervals around adjusted means.

Figure 4. Box-and-whisker plots of errors committed by each group at each level of the SWM task. Heavy bars represent median values and the limits of the box correspond to the interquartile range. Whiskers mark the 5th and 95th percentiles. Circles represent values between the fifth and first percentiles, and asterisks values beyond the first percentile.

Figure 4. Box-and-whisker plots of errors committed by each group at each level of the SWM task. Heavy bars represent median values and the limits of the box correspond to the interquartile range. Whiskers mark the 5th and 95th percentiles. Circles represent values between the fifth and first percentiles, and asterisks values beyond the first percentile.

Table 1


 Demographic and control measures for each group

 PCS morphological asymmetry 
 Leftward Symmetric Rightward 
Age at testing  26.41 (10.30)  25.73 (6.89)  23.35 (8.85) 
HGI asymmetry  –0.31 (0.27)  –0.28 (0.33)  –0.30 (0.20) 
NART-estimated IQ 101.38 (11.67) 103.44 (11.72) 104.50 (11.75)  
Spatial span    7.38 (1.19)   6.89 (1.76)   7.00 (1.91) 
VPAL (hard pairs)   7.23 (2.68)   7.89 (2.37)   8.00 (3.21) 
 PCS morphological asymmetry 
 Leftward Symmetric Rightward 
Age at testing  26.41 (10.30)  25.73 (6.89)  23.35 (8.85) 
HGI asymmetry  –0.31 (0.27)  –0.28 (0.33)  –0.30 (0.20) 
NART-estimated IQ 101.38 (11.67) 103.44 (11.72) 104.50 (11.75)  
Spatial span    7.38 (1.19)   6.89 (1.76)   7.00 (1.91) 
VPAL (hard pairs)   7.23 (2.68)   7.89 (2.37)   8.00 (3.21) 

Data are presented as means (and standard deviations). HGI = Hemispheric gyrification index. Negative values indicate a rightward asymmetry for increased hemispheric cortical folding; NART-estimated IQ = National Adult Reading Test estimated Intelligence Quotient. VPAL = Verbal Paired Associated Learning.

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