Developmental Cognitive Neuroscience 1 (2011) 101–109

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Developmental Cognitive Neuroscience

journal homepage: http://www.elsevier.com/locate/dcn

Review The developing : From theory to neuroimaging and back

Eveline A. Crone a,b,c,∗, K. Richard Ridderinkhof c,d a Leiden University, Institute for Psychological Research, The Netherlands b Leiden Institute for Brain & Cognition, The Netherlands c Department of Psychology, University of Amsterdam, The Netherlands d Cognitive Science Center Amsterdam, University of Amsterdam, The Netherlands article info abstract

Article history: Surprisingly little headway has been made towards understanding how brain growth maps Received 17 September 2010 onto mental growth during child development. This review aims at bridging and integrat- Received in revised form 2 December 2010 ing recent human neuroscientific brain maturation findings with the conceptual thinking Accepted 4 December 2010 of theorists in the behavioural tradition of studying cognitive development. Developmen- tal research in the field of internal control and self-regulation serves as a reference point Keywords: for understanding the relation between brain maturation and mental growth. Using several Brain maturation recent neuroimaging findings as points in case, we show how a deeper appreciation of struc- Neuroimaging Cognitive development tural and functional neural development can be obtained from considering the traditional Neuroconstructivism conceptual frameworks, and vice versa. We conclude that paradigmatic progress in devel- Working memory opmental neuroscience can rely more on knowledge from developmental experimental psychology, and that developmental models of cognitive development can be constrained and articulated with more precision on the basis of knowledge of differential structural and functional brain maturation. © 2010 Elsevier Ltd. All rights reserved.

Contents

1. Introduction ...... 101 2. Brain maturation...... 102 3. Cognitive development theories vis-à-vis brain development ...... 103 3.1. Developmental theories ...... 103 3.2. Brain development supporting changes in working memory and control ...... 104 4. Merging developmental theory with developmental imaging ...... 106 5. Conclusions ...... 108 Acknowledgements ...... 108 References ...... 108

1. Introduction behaviour. Textbooks on cognitive development are now Developmental neuroimaging studies have had a great incorporating brain development as further explanations impact on thinking about developmental changes in for developmental improvements in a wide area of skills (e.g., Blakemore and Frith, 2005; Goswami, 2008), and neu- roscientists are speculating about how brain development ∗ results in changes in cognitive function (e.g., Shaw et al., Corresponding author at: Department of Developmental Psychology, Wassenaarseweg 52, 2333AK Leiden, The Netherlands. 2006). Despite this mutual interest, the two research areas E-mail address: [email protected] (E.A. Crone). (developmental psychology and neuroscience) are still seg-

1878-9293/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.dcn.2010.12.001 102 E.A. Crone, K. Richard Ridderinkhof / Developmental Cognitive Neuroscience 1 (2011) 101–109 regated and a gap remains between our knowledge of brain confirmed, however, for instance by longitudinal studies development and cognitive development. Developmental showing consistent relations between individual differ- neuroimaging studies tend to be data-driven rather than ences in brain growth and cognitive development. theory-driven; that is, these studies tend to be inspired Here, we set out to revive and rejuvenate this general more by the prospect of finding differential maturational approach by relating recent neuroimaging findings using trajectories of specific structures and functions than by pre- cognitive paradigms to the theoretical bases which have dictions derived from theoretical perspectives on mental shaped the thinking of developmental scientists. Given that growth (see also Johnson, 2001, 2010). It is not uncom- functional developmental neuroimaging studies to date mon that developmental changes in cognitive function are have focused mainly childhood and adolescence (ages 6–7 interpreted as the simple maturation of a single brain area and older), we will restrict the review to this age period. or circuit, ignoring the long history of cognitive theorizing This focus allows us to make more solid inferences on the about the development of thought and behaviour. Like- relation between brain developmental and cognitive devel- wise, it is not uncommon that developmental changes in opment. We further restrict our review to the functional domains such as working memory are explained in terms of domain of internal control and working memory develop- classic stage-wise development while ignoring the signifi- ment, because this domain is well described in both the cant improvements that have been made in relating these information-processing theories of cognitive development functions to brain maturation, which could constrain the and in recent neuroimaging studies. Many of the recom- currently available developmental theories. mendations we present following this review, however, The goal of this review is to identify initial steps towards are also applicable to other domains of cognitive develop- understanding recent neuroscientific brain development ment where links are made with brain development, such findings in the context of classic developmental theories as inhibition, reasoning, self-regulation, and mentalizing of cognitive development. We identify several problems functions (e.g., theory of mind). which occur when neuroimaging studies are designed without taking into account the prior findings from classic 2. Brain maturation developmental theories. Before the advent of developmental neuroimaging, sev- Biological models of brain development have made eral endeavors have been undertaken towards integrating great progress in understanding the development of brain mental development and brain maturation (e.g., Crnic structure, especially since the use of magnetic resonance and Pennington, 1987; Dawson and Fischer, 1994; Schore, imaging (MRI). In the early days of developmental neuro- 1994; Segalowitz and Rose-Krasnor, 1992; for an extensive science, our knowledge of brain structure and development review see van der Molen and Ridderinkhof, 1998). Initial were mostly based on post-mortem studies, which demon- attempts focused on measures of brain size. In a series of strated that the size of the brain increases until age studies, Epstein (1974a,b) derived his phrenoblysis hypoth- 9–10 and by that time the size and weight of the brain esis (the Greek word “phreno” stands for skull or mind does not change that much anymore until senescence while “blysis” refers to welling-up of matter), suggesting (Huttenlocher, 1979; Huttenlocher et al., 1983). These that the brain grows in spurts with peaks in growth rate studies reported on two main changes which occur in the occurring between 6 and 8, 10 and 12, and 14 and 17 years developing brain. First, expansion of the layer of of age. The correlated patterns of peaks and troughs in brain around the axon of developing continues into ado- growth and mental growth (as indexed by intelligence lescence, especially for the frontal regions of the brain. tests) suggested to Epstein (1978) a link with Piagetian the- Second, synaptic density, or the number of synapses in a ory. The spurts in brain growth would precede and prepare certain volume of brain tissue, increases dramatically in stage transitions in cognitive development. The phrenobl- early in post-natal development, followed by pruning dur- ysis hypothesis has met with considerable methodological ing maturation. criticism, however. The rise of in vivo brain scanning methods in the last Other attempts focused on the spectral analysis of 20–30 years, including MRI, allowed researchers to exam- brain electrical activity, as measured using the electro- ine changes in brain structure on a much broader scale encephalogram (EEG). Matousek and Petersén (1973) and in much more detail. Brain structure changes could reported developmental changes in spectral power that now be studied across time within the same individuals, showed periods of rapid growth alternating with peri- and several reports have confirmed that there are impor- ods of slow growth, taken to support stage theories of tant changes in grey and structure until brain maturation (Hudspeth and Pribram, 1992), echoing late adolescence. The development of white-matter tracks Epstein’s hypothesis formulated almost 20 years earlier. has recently been studied by the use of diffusion tensor Thatcher (1994) suggested that EEG coherence, a spectral imaging (DTI), which provides sensitive measures of the measure that provides an index of the functional coupling changes in microstructure of white matter in the brain that of neural generators, revealed growth spurts in cortical occurs across childhood and adolescence. These studies organization are repeated during three major develop- have reported a steady increase in white-matter den- mental cycles, with transitions at approximately 6 and sity and myelination across childhood, and despite some 10 years. These findings were interpreted to provide sup- reports showing region-specific changes, the majority of port for neo-Piagetian views of cognitive development. The studies propose that these changes are wide-spread across hypothesis of stage-wise cognitive development driven by brain regions (Pfeffenbaum et al., 1994; Paus et al., 1999; iterative and sequential brain-growth cycles remains to be Giorgio et al., 2008). In contrast to white-matter devel- E.A. Crone, K. Richard Ridderinkhof / Developmental Cognitive Neuroscience 1 (2011) 101–109 103 opment, grey-matter development seems to follow an describes the periods of major change in cognitive pro- inverted U-shaped pattern of region-specific developmen- cesses that support abstract thinking (Piaget, 1952a,b, tal changes. Thus, whereas white matter develops steadily 1965; Piaget and Inhelder, 1974). Before he started to and linearly across brain areas, grey-matter density follows describe his observations of developing children, cognitive progressive and regressive changes, which follow a differ- developmental psychology was hardly if at all established ent time course depending on the specific brain region. The as a discipline in its own right. His thinking about devel- latest changes are observed in the prefrontal cortex, pari- opment was based on questions which have inspired etal cortex and superior temporal cortex, with grey-matter philosophers for centuries, such as ‘Where does knowledge peaks around puberty. In prefrontal and parietal cortex come from?’ and ‘How does intelligence develop?’ In addi- peaks around age 12 for males and around tion, Piaget’s early interest in cognitive development grew age 11 for females, whereas in temporal cortex grey mat- out of his interest in biology. Inspired by the likes of Dar- ter peaks around age 17 (Gogtay et al., 2004; Sowell et al., win, Piaget was interested in questions such as ‘How do 2004). people and knowledge evolve?’ In this sense, the theory Despite the large body of evidence about structural of Piaget had already a strong link with brain develop- brain development, much less is known about how these ment, because it was based on assumptions of interaction changes map onto the development of cognitive functions between preprogrammed biological systems and chang- which are observed across childhood and adolescence. A ing environmental demands, which together produce rapid handful of studies have examined how structural brain changes in development. Piaget’s theory does nowadays no development is predictive of cognitive functioning, as longer accommodate for the full range of findings derived expressed in for instance IQ, and these studies show that from developmental experimental psychology, particularly region-specific changes in synaptogenesis in prefrontal with respect to its description of mental changes in infancy. cortex can predict whether children are low, middle or Much research in recent years with young infants and high in IQ (Shaw et al., 2006). It is also believed that toddlers has shown that Piaget’s approach to studying cog- critical or sensitive periods in learning, which are time nitive development may have underestimated cognitive points in development during which children learn new abilities in younger children by using complicated designs skills that cannot be learned with the same precision and and methods. For example, there is evidence that shows success during other periods of life, are the result of synap- that preoperational toddlers will pass a false-belief task, if tic changes which allow a great speed of assimilation to it is designed appropriately (e.g., Southgate et al., 2010), currently changing environmental demands (Blakemore or that 9-month-old infants exhibit predictive motor acti- and Choudhury, 2006; Blakemore, 2008; Johnson, 2001, vation when perceiving grasping movements (Southgate 2010). The exact relation between structural brain develop- et al., 2009). Despite the controversial nature of his detailed ment and cognitive development, however, is still largely theoretical claims, Piaget’s theory can provides an example unknown. to illustrate the kinds of ideas and concepts that originated A method which maps cognitive functioning to brain from psychology and that developmental neuroscience function more directly is functional MRI (fMRI). Using this needs to tackle. approach, it is possible to examine brain functioning in vivo Perhaps the most influential of Piaget’s ideas are his in developing populations while they perform a certain developmental stages, propelled by dynamic processes of cognitive task (Casey et al., 2005). Despite the limitations assimilation and accommodation. These ideas could be said that co-occur with this technique, such as the correla- to be reminiscent of sensitive periods in brain develop- tive nature of the data or the commonly applied use of ment, as indicated by synaptogenesis and synaptic pruning. reversed inferences (Poldrack, 2005), the cumulating num- For example, Piaget suggested that a child cannot reach a ber of developmental MRI studies is most likely the most new stage before mastering the old one (Brainerd, 1978; promising approach for integrating knowledge of brain Flavell, 1963, 1971), which has similarities with the idea development with classic developmental theories of cog- of a hierarchical development of conscious control levels nitive development. The promising steps in this direction (Zelazo, 2004). Interestingly, synaptic density studies sug- are indicative of interpretable changes in brain function gest that changes in grey matter develop at different rates and behaviour, although it should be noted at the outset for different brain regions (Huttenlocher et al., 1983; see that the developmental imaging studies to date do not yet also Gogtay et al., 2004), and the change in grey matter in allow for a direct test of cognitive developmental theo- a higher-order brain region would not contribute to cog- ries. These shortcomings are mostly related to the use of nitive function if the grey-matter changes in a supporting wide age ranges and broad experimental manipulations, brain region were not yet completed (Casey et al., 2005). and these limitations will also be highlighted during this Whether the changes occur suddenly or through slow accu- review. mulation of knowledge (which is suddenly observable) has remained unclear (Fisher and Bidell, 1991; Siegler, 3. Cognitive development theories vis-à-vis brain 1981), but theories of brain maturation and of stage-wise development mental development agree that changes in cognitive skills occur through an interplay between biological programs 3.1. Developmental theories and accumulating environmental input (see also Karmiloff- Smith, 2006). The work of has probably been most influ- Information-processing theories, which often build ential in our thinking about cognitive development, as it upon the classic Piagetian framework, have empha- 104 E.A. Crone, K. Richard Ridderinkhof / Developmental Cognitive Neuroscience 1 (2011) 101–109 sized how biologically based growth of internal control, 3.2. Brain development supporting changes in working self-regulation, working memory and automatization memory and control allows children to progressively increase processing lim- its (Demetriou et al., 1993; Fisher, 1980; Halford, 1993, Functional neuroimaging studies have built upon the 1995). For example, the development of working memory idea that working memory development increases across capacity has been explained as an age-related increase in this specific age period, by comparing brain activation in processing space, in which the absolute capacity of work- 8–17-year-old children relative to adults. Neuroimaging ing memory does not change, but the capacity functions studies in adults have shown that regions within prefrontal more efficiently with advancing age. Early in development, cortex (PFC, in particular lateral PFC) and parietal cor- children are thought to rely more on working memory stor- tex are important for the maintenance and manipulations age space, but the processes are less efficient. In contrast, of information in working memory (Smith and Jonides, across development, children increase in processing abil- 1999; Passingham et al., 2000; Bunge et al., 2003; Olesen ity, and consequently, there is a decrease in the necessary et al., 2004, see also Fig. 1). The first developmental neu- storage space (Case, 1992). These changes in capacity may roimaging studies have focused on the pure maintenance be influenced by a general increase in processing speed of information in memory, by instructing participants to which could underlie performance enhancements in a wide maintain verbal or spatial information online over the variety of domains, including working memory (Kail, 1991, course of several seconds, followed by a probe demanding a 2007). button press. These studies have shown that the increased More recently, and influenced by findings from patients ability to maintain information online between ages 8 and with prefrontal damage, it is assumed that internal 12 and young adulthood coincides with increased activa- control and working memory capacity are associated tion in lateral PFC and parietal cortex (Klingberg et al., with the emergence of executive functions (Dempster, 2002; Luna et al., 2001; Kwon et al., 2002; O’Hare et al., 1993; Diamond, 2002). Executive functions refer to the 2008; Thomason et al., 2009). A comparison of fMRI data ability to control our thoughts and actions with the and DTI data revealed that increased fractional anisotropy purpose of achieving future goals. Changes in executive in fronto-parietal white matter – suggestive of increased functions could account for developmental improve- strength of anatomical connectivity between these regions ments in a variety of higher-order processing domains, – is positively correlated with BOLD activation in the lat- although it is still debated whether these are co-occurring eral PFC and parietal cortex and with visuospatial working but separate developments (Huizinga et al., 2006)or memory capacity (Olesen et al., 2003). Thus, these find- whether a general reflective level of processing under- ings seem to be in favour of the hypothesis that processing lies these improvements (Zelazo, 2004). For example, an capacity increases over the course of child development. information-processing theory referred to as the levels- Prior behavioural research, however, postulated that of-consciousness theory, postulates that the development working memory depends on the interplay between stor- of the levels of consciousness goes via hierarchical func- age capacity and processing efficiency (Case, 1992). In this tional system changes, where young children may master sense, the developmental studies which have focused on one level of processing (e.g., keeping rules active in mind) pure maintenance may only have tapped improvements in but not another level of processing (e.g., flexibly switch- storage capacity with stable processing demands. Subse- ing between competing rules). Once the highest level of quent studies have examined these processing demands consciousness is reached, children can solve the most com- in more detail by asking children to manipulate informa- plex problems, which can explain the observed age-related tion in working memory (Crone et al., 2006a,b; Jolles et al., improvements in executive functions (Zelazo, 2004). in press; Fig. 1). These studies differentiated between pure Based on these behavioural models, it is generally maintenance and manipulation and found evidence for dif- predicted that two or more brain systems work closely ferent neural systems which support these functions. That together when performing complex tasks, but the way in is, ventrolateral PFC was active only for maintenance tri- which they work together is predicted to be different. For als, whereas dorsolateral PFC was additionally recruited example, according to Case’s conceptualization of working for manipulation trials. The finding of slower development memory development, there should be one system which is of dorsolateral PFC could be taken as evidence for delayed important for storage of information, and a second system processing development. According to Case’s terminology, which is important for processing information (or execu- especially working memory manipulation should result in tive control of stored information, Baddeley, 1992, 2003), increased demands on processing capacity, whereas work- and the relative contribution of these systems changes ing memory maintenance should rely more on storage during development. In contrast, the levels of conscious capacity. Therefore, the brain imaging results could be processing account suggests that executive function and taken to suggest that storage capacity can remain stable (as reflective consciousness is dependent on the maturation of indicated by stable levels of ventrolateral PFC activation), additional brain regions in prefrontal cortex (see also Bunge and processing capacity may independently increase with and Zelazo, 2006). The challenge is now to use neuroimag- advancing age (as indicated by increased levels of dorso- ing methods to directly test the developmental theories of lateral PFC activation when processing demands increase). working memory and executive function. For this purpose, Whereas the neuroimaging studies described above we will summarize neuroimaging research which focused have mainly reported change in terms of increases and on different types of working memory and control func- decreases of task-relevant areas, qualitative developmen- tions. tal differences have been reported as well. For example, E.A. Crone, K. Richard Ridderinkhof / Developmental Cognitive Neuroscience 1 (2011) 101–109 105

Fig. 1. Working memory related activation in children and adults. In the working memory task, participants were required to remember a sequence of objects in forward order (maintenance condition) or backward order (manipulation condition) during a delay of 6 s. After the delay period, one object was presented and participants had to indicate the position of the object in the forward or backward sequence. This figure shows delay-period activation when three objects had to be remembered. The images are overlaid on axial and sagittal slices (z = 60 and x = −42) of a standard anatomical image. The left side of the image is the right side of the brain. Results are thresholded at p < .05, cluster corrected, using clusters determined by z > 2.3 (orange) and at p < .001, uncorrected (red). Maint. = maintenance; Manip = manipulation (based on Jolles et al., 2010; Developmental Science). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of the article.)

Scherf et al. (2006) demonstrated that 8–12-year-old chil- What theoretical framework can we use to interpret dren and 13–17 years old show a qualitatively different the neuroimaging findings? There is probably not one the- activation pattern when performing a working memory ory available which serves this goal, but there are theories maintenance task. This study showed that 8–12-year-old available which allow for a direct mapping between cog- children failed to recruit the working memory network nitive theories and brain development trajectories. The that is core to working memory performance in adults functional development of the human brain could, for (lateral PFC and parietal cortex), but instead rely on a dif- example, be related to developmental theories in a testable ferent region within PFC to perform the task (ventromedial way using the neural maturation accounts put forward by PFC). In contrast, adolescents aged 13–17 years recruited Johnson (2001, 2010) and Johnson et al. (2009). This the- lateral PFC, just like adults did, but failed to activate this ory was developed to provide a biological framework for region to a similar extent. The results by Scherf et al. (2006) the development of early attention systems. According to could be interpreted as a shift in storage or processing Johnson (2001, 2010), cognitive abilities emerge through capacity between ages 8–12 and 13–17 (see also Ciesielski three possible routes of neuroanatomical development: et al., 2006 for a similar shift between children and adults, (1) maturational progress (the maturation of additional although in a different network). The results also indicate brain areas), (2) interactive specialization (changes in inter- that adult levels of working memory are not yet reached actions between brain areas that were already partially in adolescence, and that there is a refinement of control active) and (3) skill learning (the patterns of activation abilities that cannot always be observed on the basis of of cortical regions change during the acquisition of new behaviour only (see also Kwon et al., 2002; Klingberg et al., skills). Even though this model was developed to account 2002). In this sense, the neuroimaging findings extend for postnatal and experience-dependent changes in the the results from information-processing theories by show- first two years of life, these trajectories of neuroanatom- ing that the underlying network which is important for ical development could also be used as a starting point abstract thought is still improving across adolescent devel- for studying more advanced levels of cognitive develop- opment. ment, such as working memory. Fig. 2 provides an example Taken together, prior studies which have used working of how these maturation accounts can be translated in memory paradigms have reported that the brain regions activation patterns observed in ventrolateral PFC, dor- that are important for these functions in adults are differ- solateral PFC and superior parietal cortex. For example, entially engaged in childhood and adolescence. However, the additional recruitment of dorsolateral PFC in work- the paradigms are often relatively simple and do not ing memory manipulation studies could be interpreted in allow for a direct test of changes in storage capacity, the terms of the maturational account (as predicted by theo- processing of information in working memory, and the ries of executive function development), but also in terms relation with competing information in working memory. of the interactive specialization account (as predicted by Therefore, a challenge for future research is to develop classic working memory information-processing theories). experimental paradigms based on developmental theory In contrast, the qualitative differences in brain activation which allows for the test of different neural development between children and adults support the skill learning accounts. account. Judicious task manipulations should allow for 106 E.A. Crone, K. Richard Ridderinkhof / Developmental Cognitive Neuroscience 1 (2011) 101–109

Fig. 2. Neural basis of development accounts, based on Johnson (2001), applied to development of working memory. Brain regions implicated in working memory function are ventrolateral prefrontal cortex (VLPFC), dorsolateral prefrontal cortex (DLPFC) and superior parietal cortex (SUPPAR). The maturational account poses that children become better at performing manipulation trials because of the maturation of additional brain areas, such as DLPFC and SUPPAR. The interactive specialization account suggests that the performance increases are associated with a refinement of connectivity between brain regions (VLPFC, DLPFC and SUPPAR). The skill learning account suggests that children may first perform a working memory task based on reliance on a lower-level system (such as VLPFC) but, when older, they rely on different system (such as DLPFC and SUPPAR). the test of these different accounts. Even though all three about ways of improving our experimental designs based theoretical possibilities can account for observed changes on theoretical knowledge of cognitive development. Here, in brain activation, Johnson (2010) argues in favour of we summarize several problems and possible solutions for the interactive specialization. Future studies should test achieving the integration of these fields (see also Table 1). whether this developmental trajectory accounts for devel- One of the main problems with current neuroimag- opmental data better than the maturational and skill ing evidence which could support or falsify developmental learning account. theories lies in the selection of age groups. Whereas information-processing theories argue that the most 4. Merging developmental theory with prominent changes in problem solving and working developmental imaging memory are seen between ages 7 and 12, almost all devel- opmental neuroimaging studies have collapsed across In the prior sections we showed that the interpretation 7–12 years old. Even though the studies report differences of brain imaging results is limited by the relative absence in behaviour between children and adults, it remains to of developmental theories. Despite the advances which be determined whether these changes are predominantly have been accomplished in the field of developmental neu- driven by the youngest children within the selected age roimaging, it is now time to also consider the limitations of group or occur across the whole child group. In future the approaches that have been used so far, and to think studies, it will be important to carefully select age groups E.A. Crone, K. Richard Ridderinkhof / Developmental Cognitive Neuroscience 1 (2011) 101–109 107

Table 1 Guidelines for neuroimaging research based on developmental theory.

Suggested guidelines for neuroimaging research

1 Selection of age groups should be theory-driven 2 Compute brain-behaviour correlations and be aware of differences in effect sizes 3 Maturation and change can only be examined using longitudinal designs 4 Training and intervention studies can demonstrate the malleability of cognitive functions and underlying neural mechanisms 5 Compensatory brain activation should be interpreted with caution 6 Differential brain activation can be caused by strategy differences based on theoretical predictions about when the changes publication). These results indicate that the developmental are expected to occur. differences in brain activation are not fixed and can be mod- A second problem concerns the differences in brain and ified by instruction or training. These preliminary findings behaviour effect sizes. The correlations between perfor- do not fit with a purely maturational account and concomi- mance and brain activation are usually modest across all tant structural brain development. Instead they fit in with a participants, but poor when the analysis only includes one skill learning model. More work is necessary to understand age group. This difficulty with interpreting brain-behaviour how brain function is sensitive to training or interventions. correlations across age groups is associated with the dif- One pervasive problem in studies of brain develop- ficulty in distinguishing between effects of maturation ment is that the different control functions have often versus individual differences in performance. It is possible been studied in isolation. Even though consistent findings that these processes cannot be dissociated at all, that is, per- are reported across studies, these are often limited to the formance is usually correlated with maturational changes. observation that a certain brain area which is important for In addition, the poor correlations with performance within behaviour in adults is not yet activated to the same level age groups are usually associated with smaller effect sizes in children. Most of these studies, however, report that for either the brain or the behavioural measures. Again, a children activate several other brain areas in the critical straightforward way to address these problems involves contrast that are not seen in adults. What do these acti- using a theoretically based selection of participants for vation patterns indicate? Currently, we can only interpret age-related comparisons, and by using tasks which vary these post hoc, based on reverse inference about the func- the construct under study at different levels. A combi- tion of these unexpectedly activated brain areas in adults. nation between functional development and structural For example, prior studies have suggested that when chil- development indices (such as developmental DTI studies) dren activate the left rather then right hemisphere more is necessary to further expose the extent to which men- in a certain cognitive task, this can possibly be interpreted tal growth corresponds to growth in (white-matter) brain to reflect that they used a more verbally guided approach, connectivity. such as rehearsal, because in adults language functions A third problem is that little is known about test–retest tend to be left-lateralized (Bunge et al., 2002). Along a simi- effects or longitudinal changes. There is much varia- lar line of reasoning, it has been suggested that 15-year-old tion within individuals and the time at which spurts in adolescents may have larger compensatory skills because development occur may change between individuals and besides PFC, they additionally recruit the hippocampus depend on external factors. In order to track developmen- when they perform a memory task (Finn et al., 2010). tal changes over time, it is important to use multi-level Finally, the differential activation patterns hint towards models of change in longitudinal designs (see also Ferrer another important explanation, that is, children may use et al., 2009). A recently completed 3-year longitudinal different strategies when performing a task. Here, we may study tested 26 participants between ages 8 and 28 on a again learn from classic developmental theories, which performance monitoring task using fMRI (Koolschijn et al., have differentiated between different types of memory submitted for publication). This study showed that, even function, including storage of verbal information, storage of though the network of brain regions which was activated spatial information, and an executive system which works was highly similar at both measurements, age was a poor with information in working memory. Consider, for exam- predictor of test–retest effects. Instead, performance was ple, the differentiation of verbal versus spatial working a very good predictor for change; those individuals who memory and the inhibition of irrelevant information. In improved most from measurement 1 to measurement 2, adults, presenting distracting spatial information impairs also showed the largest change in brain activation. These their spatial working memory capacity, but not their verbal findings indicate that using only age as a predictor for working memory capacity. In contrast, presenting dis- change and ignoring performance changes can result in tracting verbal information impairs their verbal working false or incomplete conclusions. memory capacity, but not their spatial working memory Based on this stable brain-behaviour relation, we rea- capacity. These results suggest a strong interplay between soned that performance can increase with training, and working memory and inhibition, which is modality spe- that brain activation should change accordingly. To test this cific. In 8-year-old children, distracting spatial information hypothesis, we performed a developmental training study also impairs their verbal working memory performance and demonstrated that reduced activation in lateral PFC and distracting verbal information also impairs their spa- in children aged 11–12 years can be improved by exten- tial working memory performance (Hale et al., 1997). How sive working memory training (Jolles et al., submitted for to interpret these changes? Apparently, in early childhood 108 E.A. Crone, K. Richard Ridderinkhof / Developmental Cognitive Neuroscience 1 (2011) 101–109 the differentiation between functions and modalities is References much less segregated than in adults, and this theoretical knowledge should be taken into account when designing Baddeley, A., 1992. Working memory. Science 255, 556–559. Baddeley, A., 2003. 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