1 Review TRENDS in Cognitive Sciences Vol.9 No.3 March 2005 Imaging the developing brain: what have we learned about cognitive development? B.J. Casey 1, Nim Tottenham 1, Conor Liston 1 and Sarah Durston 1,2 1 Sackler Institute for Developmental Psychobiology, Weill Medical College of Cornell University, 1300 York Avenue, Box 140, New York, NY 10021, USA 2 Department of Child and Adolescent Psychiatry, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands The human brain undergoes significant changes in both its structural architecture and functional organization across the life span. Advances in neuroimaging techniques over the past decade have allowed us to track these changes safely in the human in vivo. We review the imaging literature on the neurobiology of cognitive development, focusing specifically on cognitive taskdependent changes observed in brain physiology and anatomy across childhood and adolescence. The findings suggest that cortical function becomes fine-tuned with development. Brain regions associated with more basic functions such as sensory and motor processes mature first, followed by association areas involved in top-down control of behavior. Introduction The year 2005 marks a decade since the first application of fmri to developmental questions . It is well established that brain development and cognitive maturation occur concurrently during childhood and adolescence [2 4], but much less is known about the direct relationship between neural and cognitive development. This review highlights what we have learned about the biological substrates of cognitive development over the past decade, advances and limitations of the methods, and the relevance of these studies to understanding and developing interventions for individuals with atypical development. Emphasis is placed on studies that inform how cognitive development and learning map onto changes in brain anatomy, connectivity and physiology across childhood and adolescence. Contemporary non-invasive neuroimaging methods have provided developmental scientists with the opportunity to track safely cognitive and neural processes underlying human development (see Box 1). These methods have advanced the field of developmental neuroscience by providing evidence of changes in structural architecture and functional organization in the developing brain in vivo. However, these measures provide only an indirect measure of brain structure and Corresponding author: Casey, B.J. function. Changes in the volume of a structure or amount of activity as measured by MR methods lack the resolution to characterize the mechanism of change definitively. Histological evidence suggests that brain development is a dynamic process of regressive and progressive changes (see Box 2). As such, MRI-based cortical changes observed with development may be a combination of myelination, dendritic pruning and changes in the vascular, neuronal and glial density. Nonetheless, the methodologies provide information about regional development that, in conjunction with histological studies, could tease these processes apart. Furthermore, because these tools permit not only scanning of children but also repeated scanning of the same individual over time, they can provide measurement of general neuroanatomical changes with both learning and development. This review highlights MR-based measures of change in neuroanatomy, cortical connectivity and cortical function with learning and development. Neuroanatomical development of the human brain Several structural imaging studies have mapped the neuroanatomical course of human brain development . The findings parallel many of the post-mortem histological findings, providing validity for in vivo imaging measures, and also parallel behavioral and cognitive development. Claims of causality between coincidental changes in brain and behavioral development is a common trap into which one could fall by simply assuming linear changes across systems and direct associations between these changes. Nonetheless, the synchrony in time course of the changes reported in MRI-based anatomical studies and cognitive development have driven more direct tests of these associations in functional imaging studies. For this reason, MRI-morphometric studies of change in structural architecture are highlighted. The most compelling reports of structural changes with development over the period of childhood and adolescence have come from recent longitudinal MRI studies [6,7]. In general, the sequence in which the cortex matures parallels cognitive milestones in human development [6 9]. First, regions subserving primary functions, such as motor and sensory systems, mature earliest, with /$ - see front matter Q 2005 Elsevier Ltd. All rights reserved. doi: /j.tics
2 Review TRENDS in Cognitive Sciences Vol.9 No.3 March Box 1. Magnetic resonance methods Magnetic resonance technologies have introduced a new set of tools for capturing features of brain development in living, developing humans. The three most common MR methods used in the study of human development and learning are illustrated in Figure I. These imaging methods became especially important to cognitive and developmental scientists when the functional capabilities were discovered. The functional methodology measures changes in blood oxygenation in the brain that are assumed to reflect changes in neural activity [55,56], and eliminates the need for exogenous contrast agents, including radioactive isotopes [57,58]. DTI is a relatively new MR technique that can detect changes in white matter microstructure based on properties of diffusion [59,60]. Diffusion of water in white matter tracts is affected by myelin and the orientation and regularity of fibers and provides an index of brain connectivity. Because all three of these MR techniques are non-invasive, development and learning can be tracked more precisely within individuals with repeat scans over short or long intervals of time (days to years). Figure I. (a) Structural MRI produces structural images of the brain that are useful for anatomical and morphometric studies; (b) DTI measures connectivity of fiber tracts between anatomical structures; and (c) functional MRI measures patterns of brain activity within those structures. temporal and parietal association cortices associated with basic language skills and spatial attention maturing next. Higher-order association areas, such as the prefrontal and lateral temporal cortices, which integrate primary sensorimotor processes and modulate basic attention and language processes, seem to mature last [6,7]. Specifically, MRI-based measures showed that cortical gray matter loss occurred earliest in the primary sensorimotor areas Box 2. Structural architecture of the developing brain The human brain undergoes dramatic changes in both its structural architecture and functional organization that reflect a dynamic interplay of simultaneously occurring progressive and regressive events. Although the total brain size is about 90% of adult size by age 6 years, the brain continues to undergo dynamic changes throughout adolescence and well into young adulthood . Figure I illustrates some of these developmental changes, including proliferation and migration of cells mostly during fetal development [62,63], regional changes in synaptic density during postnatal development [11,12,64], and protracted development of myelination well into adulthood . Current non-invasive neuroimaging methods do not have the resolution to delineate which of these processes underlies observed developmental changes beyond gray and white matter subcomponents. Developmental course of human brain development Experience-dependent synapse formation and dendritic arborization Prefrontal cortex Parietal and temporal association cortex Sensorimotor cortex Neurulation Cell proliferation and migration Synaptogenesis and synaptic pruning Myelination Conception Months Months Years Birth TRENDS in Cognitive Sciences Figure I. See text for details. Adapted with permission from Ref. .
3 106 Review TRENDS in Cognitive Sciences Vol.9 No.3 March 2005 and latest in the dorsolateral prefrontal cortex [6,10]. These findings are consistent with non-human and human primate postmortem studies showing that the prefrontal cortex matures at a more protracted rate than sensorimotor cortex in synaptic density [11,12]. Cross-sectional studies of normative brain maturation during childhood and adolescence have shown somewhat similar patterns concluding that gray matter loss during this period reflects a sculpting process of the immature brain into the fully functioning mature one [10,13 16]. As such, the pattern of development observed is suggested to reflect the ongoing neuronal regressive events, such as pruning and the elimination of connections. Developmental changes in subcortical regions occur over this period of development as well [10,13,15 19]. One of the more reliable patterns reported is in subcortical regions to which association cortex projects. For example, both cross-sectional  and longitudinal studies  show patterns of development in portions of the basal ganglia to which the prefrontal cortex directly projects. Again, this pattern could reflect the gradual elimination of connections, with strengthening of others. What is the corresponding pattern of change in white matter volume over this period? In contrast to an inverted U-shaped pattern of development in gray matter with age, white matter volume increases in a roughly linear pattern, increasing throughout development until approximately young adulthood [6,13,14,17,20], as evidenced by increases in volume and density . These changes presumably reflect ongoing myelination of axons by oligodendrocytes enhancing neuronal conduction and communication. Therefore, both regressive and progressive processes are occurring in parallel, which could enhance neural and cognitive processes. Connections are being fine-tuned with the elimination of an overabundance of synapses and strengthening of relevant connections with development and experience. How do these structural changes relate to cognitive changes? Developmental changes in cortical development have been found to correlate with behavioral performance measures. Sowell and colleagues  showed an association between prefrontal lobe structural maturation and memory function using neuropsychological measures. Similar associations have been reported between MRI-based prefrontal volume and specific measures of cognitive control (i.e. the ability to override an inappropriate response in favor of another) in cross-sectional studies [21,22]. Together these studies suggest that, perhaps not surprisingly, functional changes in brain development are reflected in structural changes. Development of human brain connectivity The MRI-based morphometry studies reviewed suggest that cortical connections are being fine-tuned with the elimination of an overabundance of synapses and the strengthening of relevant connections with development and experience. Recent advances in MR technology, such as diffusion tensor imaging (DTI), provide a potential tool for examining the role of cortical connectivity in the development of cognitive and brain development in greater detail. This method (see Box 1) provides information on directionality and regularity of myelinated fiber tracts (e.g. ). Until recently, few studies have linked brain connectivity measures with cognitive development, although indirect measures of white matter suggest regional development in prefrontal cortex and presumably in function . Of these studies, one showed that development of working memory capacity was correlated positively with prefrontal parietal connectivity , consistent with imaging studies showing differential recruitment of these regions in children relative to adults [39,42]. Using a similar approach, Liston and colleagues  showed that DTI-based connectivity in both frontostriatal and posterior fiber tracts correlated with age, but only frontostriatal connectivity correlated with efficient (fast and accurate) performance on a Go/No-go task. The prefrontal fiber tracts examined were defined by regions of interest identified in an fmri study using the same task . Similarly, combined DTI and fmri analytical approaches have shown the importance of the maturation of prefrontal parietal connectivity in the performance of a working memory task . As such, DTI and fmri-based measures with these regions correlated across age. In these studies, measures of brain connectivity were correlated with development, but specificity of the involvement of particular fiber tracts in cognitive performance was shown by dissociating the particular tract  or cognitive ability . These dissociations are important when distinguishing between performance and agerelated differences in imaging measures. Functional organization of the developing human brain What do the previously described changes in brain structure, such as prolonged development of the prefrontal volume and connectivity, mean in terms of function? The development of the prefrontal cortex is thought to play an important role in the maturation of higher cognitive abilities [27,28]. Mature cognition is characterized by the ability to filter and suppress irrelevant information and actions (sensorimotor processes), in favor of relevant ones (i.e. cognitive control) . A child s capacity to filter information and suppress inappropriate actions in favor of appropriate ones continues to develop across the first two decades of life, with susceptibility to interference from competing sources lessening with maturity [29 32]. Many paradigms used to study cognitive development require cognitive control such as the Stroop and Go/No-go tasks [33 35]. Collectively, imaging studies using these tasks as probes show that children recruit distinct but often more prefrontal regions, both ventral and dorsal, when performing these tasks than do adults. Based on cross-sectional  and longitudinal studies , regions whose brain activity correlates with task performance (reaction time and/or accuracy) become more focal or fine-tuned, whereas regions not correlated with task performance decrease in activity with age (see Figure 1). It has been suggested that this pattern of activity, observed across a variety of paradigms, reflects development within, and refinement of, projections to and from these regions [28,30,34,36,38], consistent with the DTI findings presented previously.
4 Review TRENDS in Cognitive Sciences Vol.9 No.3 March Figure 1. The development of human cortical function, as measured by contemporary imaging methods, reflects fine-tuning of a diffuse network of neuroanatomical regions [28,36,37]. Collectively, developmental neuroimaging studies of cognitive control processes suggest a general pattern of increased recruitment of slow maturing prefrontal cortex (references depicted here in red), especially dorsolateral prefrontal cortex [30,35,36,40,43] and ventral prefrontal cortex [28,34,37,39,42], and decreased recruitment of lower level sensory regions (references in blue), including extrastriate [36,40] and fusiform cortex  and also posterior parietal areas [30,37,38]. Importantly, specific activations vary with task demands, so working memory  and Stroop tasks  recruit different regions from response inhibition tasks [28,34,37,39,41,42]. This pattern of activity, which has been observed across a variety of paradigms, suggests that higher cognitive abilities supported by association cortex become more focal or fine-tuned with development, whereas other regions not specifically correlated with that specific cognitive ability become attenuated. AZanterior; PZposterior. Performance differences versus maturational differences The region-specific differences in activation with age that have been reported could reflect maturation, but might also reflect simple performance differences. For this reason, the collection of behavioral responses is crucial across these studies. As children almost always perform worse than adults on higher cognitive tasks, without equating performance between age groups or controlling for performance differences it is difficult to specify whether the activation differences are age related or simply reflect an overall difference in performance. To address this issue, investigators have adopted different approaches for teasing apart age versus performancedriven differences. One key strategy is to use performance matching to equate behavioral performance [28,36,39,40]. Post hoc, subjects are divided into subgroups based on behavioral performance that is either matched across groups or not matched . Three patterns of activation emerge from performance matching-based analyses: (i) performance/age-independent; (ii) performance-related; and (iii) age-related. These patterns help to identify the basis of the observed activation and/or regional differences and how they relate to the task demands. As such, this approach provides a better understanding of how maturation relates to increased cognitive abilities. For instance, in a study of cognitive control that showed performance-related neural recruitment , children were divided into better and worse performers. Children with effective response inhibition did not recruit the same prefrontal regions as those activated by adults, suggesting an age-related recruitment in this region. However, they did recruit a subset of the same posterior association areas (parietal regions) consistently activated in adults. Children with poor response inhibition did not recruit these posterior regions, suggesting that improved ability to withhold an inappropriate response might first require mature activation of posterior parietal regions that is task specific. Tasks of lesser cognitive demand (e.g. selective attention tasks without response competition) do not seem to show age-related differences . As not all tasks yield comparable performance across age groups, a second approach that has been used to equate performance across groups is to manipulate task difficulty parametrically (e.g. [42,43]). In a parametric design, task difficulty is varied with increases in task demands (e.g. increased response competition, memory load or stimulus degradation), allowing comparisons between children and adults on trials equated for accuracy. Durston and colleagues  used a version of a Go/No-go task that parametrically manipulated the number of Go trials (responses) preceding a No-go trial (withhold response). Behaviorally, they showed that both children and adults had more errors as the number of responses preceding a No-go trial increased. Children, however, had as many errors for No-go trials following a single Go trial as adults had when a No-go trial followed as many as five Go trials. The imaging data from adults showed a monotonic increase in association areas of the ventral prefrontal and posterior parietal cortices as the number of Go trials preceding a No-go trial increased, but children activated these regions maximally regardless of whether they had to withhold a response after one, three or five Go trials (responses). These data are consistent with other reports showing  that immature cognition is characterized by an enhanced sensitivity to interference from competing sources (e.g. response competition) that coincides with immature association cortex, specifically in prefrontal and posterior parietal-related circuitry. Cross-sectional studies versus longitudinal studies Most of the developmental observations described above have relied on cross-sectional samples (e.g. ) or even comparisons across studies [1,44].However,cross-sectional analyses might falsely suggest changes over time or fail to detect the specificity or magnitude of these changes, given the large individual variability in brain structure among individuals, especially during development [6,7,15]. In a recent study, Durston and colleagues  used fmri to track cognitive and brain development from late
5 108 Review TRENDS in Cognitive Sciences Vol.9 No.3 March 2005 childhood into early adolescence during performance of a Go/No-go task. There was a developmental shift in patterns of cortical activation from diffuse to focal activity similar to those reported in large cross-sectional studies . Regions uncorrelated with task performance were recruited less with age, whereas a region in the ventral prefrontal cortex that correlated with performance (speed and accuracy) in this study and prior studies [28,42,45,46] showed enhanced recruitment. This change in pattern of activity was associated with enhanced performance of the cognitive control task. Activation in earlier developing regions such as the primary motor cortex remained unchanged. A parallel cross-sectional analysis based on a second group of children, the same ages as the longitudinal group, showed less specific results, supporting the importance of longitudinal studies in evaluating cortical changes with age. These studies, together with the longitudinal MRIbased morphometry studies , suggest differential developmental trajectories for sensorimotor relative to association areas such as the prefrontal cortex. Both the imaging-based neuroanatomical studies and the functional studies highlight the importance of examining changes in ability within individuals over time. As such, this work can begin to delineate processes specific to learning or development. Cortical organization with learning The importance of tracking cortical changes in individuals over time is perhaps most evident in the area of learning. Using repeated scanning of the same individuals, Karni and others (e.g. [47,48]) have shown rapid learning effects in primary motor cortex of adults during motor sequence learning that were apparent within a single imaging session, but that increased over weeks of training. This use of fmri to trace learning-related changes in cortical areas is currently being used by others in adults (e.g. [49,50]). Across these studies, the pattern of results shows that activity in task-relevant regions becomes increasingly enhanced with training, whereas task-irrelevant regions become less activated over time . This pattern of change during adult learning studies mimics the observed changes in cross-sectional  and longitudinal  developmental studies. The findings highlight the importance of examining and distinguishing between contributions from experience and learning compared to those associated more with maturational development, in driving the cortical patterns of activation observed. Future directions Future research will no doubt take advantage of the ability to image children multiple times with fmri over the course of learning to delineate developmental and experience-based processes in cortical activity (see Box 3). For example, to determine whether the immature brain after extended practice engages in the same neural processes as the mature brain, we could compare brain activity in the mature system with brain activity in the immature system both before and after extended experience. Investigators are already beginning to take advantage of this approach in investigating the impact of Box 3. Questions for future research Do the biological substrates of learning and development differ? On what timescale can we see neuroanatomical and physiological changes with learning and development? What neural changes coincide with enhanced learning during development that could hinder learning with maturity? How can we move beyond claims of causality between coincidental changes in brain and behavioral development with converging methods? Can typical human development provide important clues on the type and timing of interventions with atypical development? behavioral and cognitive interventions on developmental disorders such as dyslexia [51,52] and attention deficit hyperactivity disorder . Another future direction of developmental imaging studies will be in the combined use of complementary imaging methods. For example, a method not mentioned in this review, but one that has been used to address questions about cognitive and brain development, is electrophysiology. This technique records brain electrical activity that can be time-locked to presentation of a stimulus or to the production of a response (i.e. eventrelated potentials or ERPs). These electrophysiological measures have millisecond temporal resolution that can provide important information on the developmental changes in the temporal characteristics of neural and cognitive processes beyond that provided by fmri . Clearly, the combination of these two techniques, together with other methods such as DTI, will strongly enhance our ability to understand neural and cognitive development and constrain current developmental theories. Investigators have begun to move in that direction with parallel fmri and DTI studies in adults and children [25,26]. Conclusions Findings from both cross-sectional and longitudinal imaging studies of late childhood and adolescence show that brain regions associated with more basic functions such as motor and sensory processes mature first, followed by association areas involved in top-down control of thoughts and action. This pattern of development is paralleled by a shift from diffuse to more focal recruitment of cortical regions with learning and cognitive development. Fine-tuning of cortical systems occurs with protracted refinement of association cortex (e.g. prefrontal cortex) relative to sensorimotor cortex. These findings seem to parallel changes observed over shorter time periods in studies of adult learning. The reported shift in cortical architecture and function is presumably an experience-driven maturational process that reflects fine-tuning of neural systems with experience and development, but future work delineating how learning during development affects this pattern is needed. These imaging studies map onto findings from animal and human postmortem studies indicating that pruning and elimination of connections, in combination with strengthening of relevant ones, occur during this time period, and illustrate the subtle interplay between neuroanatomical and physiological changes in neural circuitry and cognitive maturation.
6 Review TRENDS in Cognitive Sciences Vol.9 No.3 March Acknowledgements This work was supported in part by P01 MH62196, R01 MH63255 and R21 DA15882 to B.J.C. References 1 Casey, B.J. et al. (1995) Activation of prefrontal cortex in children during a nonspatial working memory task with functional MRI. Neuroimage 2, Casey, B.J. et al. (2000) Structural and functional brain development and its relation to cognitive development. Biol. Psychol. 54, Spear, L.P. (2000) The adolescent brain and age-related behavioral manifestations. Neurosci. Biobehav. Rev. 24, Sowell, E.R. et al. (2001) Improved memory functioning and frontal lobe maturation between childhood and adolescence: a structural MRI study. J. Int. Neuropsychol. Soc. 7, Durston, S. et al. (2001) Anatomical MRI of the developing human brain: What have we learned? J. Am. Acad. Child Adolesc. Psychiatry 40, Gogtay, N. et al. (2004) Dynamic mapping of human cortical development during childhood through early adulthood. Proc. Natl. Acad. Sci. U. S. A. 101, Sowell, E.R. et al. (2004) Longitudinal mapping of cortical thickness and brain growth in normal children. J. Neurosci. 24, Giedd, J.N. (2004) Structural magnetic resonance imaging of the adolescent brain. Ann. N. Y. Acad. Sci. 1021, Sowell, E.R. et al. (2003) Mapping cortical change across the human life span. Nat. Neurosci. 6, Reiss, A.L. et al. (1996) Brain development, gender and IQ in children. A volumetric imaging study. Brain 119, Huttenlocher, P.R. (1979) Synaptic density in human frontal cortex: Developmental changes and effects of aging. Brain Res. 163, Bourgeois, J.P. et al. (1994) Synaptogenesis in the prefrontal cortex of rhesus monkeys. Cereb. Cortex 4, Jernigan, T.L. et al. (1991) Magnetic resonance imaging abnormalities in lenticular nuclei and cerebral cortex in schizophrenia. Arch. Gen. Psychiatry 48, Pfefferbaum, A. et al. (1994) A quantitative magnetic resonance imaging study of changes in brain morphology from infancy to late adulthood. Arch. Neurol. 51, Caviness, V.S. et al. (1996) The human brain age 7 11 years: a volumetric analysis based on magnetic resonance images. Cereb. Cortex 6, Giedd, J.N. et al. (1996) Quantitative magnetic resonance imaging of human brain development: ages Cereb. Cortex 6, Giedd, J.N. et al. (1999) Brain development during childhood and adolescence: a longitudinal MRI study. Nat. Neurosci. 10, Sowell, E.R. et al. (2003) Mapping cortical change across the human life span. Nat. Neurosci. 6, Sowell, E.R. et al. (1999) In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nat. Neurosci. 2, Paus, T. et al. (1999) Structural maturation of neural pathways in children and adolescents: in vivo study. Science 283, Casey, B.J. et al. (1997) Implication of right frontostriatal circuitry in response inhibition and attention-deficit/hyperactivity disorder. J. Am. Acad. Child Adolesc. Psychiatry 36, Casey, B.J. et al. (1997) The role of the anterior cingulate in automatic and controlled processes: A developmental neuroanatomical study. Dev. Psychobiol. 30, Klingberg, T. et al. (1999) Myelination and organization of the frontal white matter in children: a diffusion tensor MRI study. Neuroreport 10, Nagy, Z. et al. (2004) Maturation of white matter is associated with the development of cognitive functions during childhood. J. Cogn. Neurosci. 16, Liston, C. et al. (2003) Developmental differences in diffusion measures of cortical fiber tracts. J. Cogn. Neurosci. 15, S57 S58 26 Olesen, P.J. et al. (2003) Combined analysis of DTI and fmri data reveals a joint maturation of white and grey matter in a frontoparietal network. Brain Res. Cogn. Brain Res. 18, Casey, B.J. et al. (2002) Clinical, imaging, lesion, and genetic approaches toward a model of cognitive control. Dev. Psychobiol. 40, Casey, B.J. et al. (1997) A developmental functional MRI study of prefrontal activation during performance of a Go/No-go task. J. Cogn. Neurosci. 9, Diamond, A. (1996) Evidence for the importance of dopamine for prefrontal cortex functions early in life. Philos. Trans. R. Soc. London B Biol. Sci. 351, Casey, B.J. et al. (2002) Dissociating striatal and hippocampal function developmentally with a stimulus response compatibility task. J. Neurosci. 22, Goldman-Rakic, P.S. (1987) Development of cortical circuitry and cognitive function. Child Dev. 58, Munakata, Y. and Yerys, B.E. (2001) All together now: when dissociations between knowledge and action disappear. Psychol. Sci. 12, Casey, B.J. et al. (2000) Structural and functional brain development and its relation to cognitive development. Biol. Psychol. 54, Tamm, L. et al. (2002) Maturation of brain function associated with response inhibition. J. Am. Acad. Child Adolesc. Psychiatry 41, Adelman, N.E. et al. (2002) A Developmental fmri study of the Stroop color word task. Neuroimage 16, Brown, T.T. et al. Developmental changes in human cerebral functional organization for word generation. Cereb. Cortex (in press) 37 Durston, S. et al. (2004) Longitudinal functional MRI of the development of cognitive control. Soc. Neurosci. Abstr Thomas, K.M. et al. (2004) Evidence of developmental differences in implicit sequence learning: an fmri study of children and adults. J. Cogn. Neurosci. 16, Bunge, S.A. et al. (2002) Immature frontal lobe contributions to cognitive control in children: evidence from fmri. Neuron 33, Schlaggar, B.L. et al. (2002) Functional neuroanatomical differences between adults and school-age children in the processing of single words. Science 296, Booth, J.R. et al. (2003) Neural development of selective attention and response inhibition. Neuroimage 20, Durston, S. et al. (2002) A neural basis for the development of inhibitory control. Dev. Sci. 5, F9 F16 43 Klingberg, T. et al. (2002) Increased brain activity in frontal and parietal cortex underlies the development of visuospatial working memory capacity during childhood. J. Cogn. Neurosci. 14, Cohen, J.D. et al. (1994) Activation of prefrontal cortex in a non spatial working memory task with functional MRI. Hum. Brain Mapp. 1, Konishi, S. et al. (1999) Common inhibitory mechanism in human inferior prefrontal cortex revealed by event-related functional MRI. Brain 122, Konishi, S. et al. (1998) No-go dominant brain activity in human inferior prefrontal cortex revealed by functional magnetic resonance imaging. Eur. J. Neurosci. 10, Karni, A. et al. (1998) The acquisition of skilled motor performance: fast and slow experience-driven changes in primary motor cortex. Proc. Natl. Acad. Sci. U. S. A. 95, Karni, A. et al. (1995) Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature 377, Green, C.S. and Bavelier, D. (2003) Action video game modifies visual selective attention. Nature 423, Olesen, P.J. et al. (2004) Increased prefrontal and parietal activity after training of working memory. Nat. Neurosci. 7, McCandliss, B.D. and Noble, K.G. (2003) The development of reading impairment: a cognitive neuroscience model. Ment. Retard. Dev. Disabil. Res. Rev. 9, Temple, E. (2002) Brain mechanisms in normal and dyslexic readers. Curr. Opin. Neurobiol. 12, Klingberg, T. et al. (2002) Training of working memory in children with ADHD. J. Clin. Exp. Neuropsychol. 24, Casey, B.J. and de Haan, M. (2002) Introduction: new methods in developmental science. Dev. Sci. 5, Logothetis, N.K. et al. (2001) Neurophysiological investigation of the basis of the fmri signal. Nature 412, Bandettini, P.A. and Ungerleider, L.G. (2001) From neuron to BOLD: new connections. Nat. Neurosci. 4,
7 110 Review TRENDS in Cognitive Sciences Vol.9 No.3 March Kwong, K.K. et al. (1992) Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc. Natl. Acad. Sci. U. S. A. 89, Ogawa, S. et al. (1990) Oxygenation-sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields. Magn. Reson. Med. 14, Le Bihan, D. (2003) Looking into the functional architecture of the brain with diffusion MRI. Nat. Rev. Neurosci. 4, Pierpaoli, C. et al. (1996) Diffusion tensor MR imaging of the human brain. Radiology 201, Conel, J.L. ( ) The Postnatal Development of the Human Cerebral Cortex (Vols 1 6), Harvard University Press 62 Rabinowicz, T. (1986) The differentiated maturation of the cerebral cortex. In Human Growth (Falkner, F. and Tanner, J.M., eds), pp , Plenum Press 63 Jacobson, M. (1991) Developmental Neurobiology, Plenum Press 64 Huttenlocher, P.R. (1990) Morphometric study of human cerebral cortex development. Neuropsychologia 28, Yakovlev, P.I. and Lecours, A. (1967) The myelogenetic cycles of regional maturation in the brain. In Regional Development of the Brain in Early Life (Minkowski, A., ed.), pp. 3 65, Blackwell 66 Thompson, R.A. and Nelson, C.A. (2001) Developmental science and the media. Early brain development. Am. Psychol. 56, 5 15 Five things you might not know about Elsevier 1. Elsevier is a founder member of the WHO s HINARI and AGORA initiatives, which enable the world s poorest countries to gain free access to scientific literature. More than 1000 journals, including the Trends and Current Opinion collections, will be available for free or at significantly reduced prices. 2. The online archive of Elsevier s premier Cell Press journal collection will become freely available from January Free access to the recent archive, including Cell, Neuron, Immunity and Current Biology, will be available on both ScienceDirect and the Cell Press journal sites 12 months after articles are first published. 3. Have you contributed to an Elsevier journal, book or series? Did you know that all our authors are entitled to a 30% discount on books and stand-alone CDs when ordered directly from us? For more information, call our sales offices: (US) or (Canada, South & Central America) or (rest of the world) 4. Elsevier has a long tradition of liberal copyright policies and for many years has permitted both the posting of preprints on public servers and the posting of final papers on internal servers. Now, Elsevier has extended its author posting policy to allow authors to freely post the final text version of their papers on both their personal websites and institutional repositories or websites. 5. The Elsevier Foundation is a knowledge-centered foundation making grants and contributions throughout the world. A reflection of our culturally rich global organization, the Foundation has funded, for example, the setting up of a video library to educate for children in Philadelphia, provided storybooks to children in Cape Town, sponsored the creation of the Stanley L. Robbins Visiting Professorship at Brigham and Women s Hospital and given funding to the 3rd International Conference on Children s Health and the Environment.
Structural brain imaging is a window on postnatal brain development in children Terry Jernigan Old (but still widely held) View of Human Brain Structure All neurons are present at birth. Myelination of
NEUROSCIENCE PERSPECTIVES Development of Human Brain Functions Mark H. Johnson Aspects of postnatal human brain development are reviewed. The development of brain function has commonly been characterized
Lecture 7 Methods of Scientific Observation and Analysis in Behavioral Psychology and Neuropsychology 1.Obtaining Knowledge 1. Correlation 2. Causation 2.Hypothesis Generation & Measures 3.Looking into
Charles A. Nelson III Children s Hospital Boston/Harvard Medical School Harvard Center on the Developing Child Presented at NICHD Cognition Workshop, 14-15 March 2011, Bethesda, MD Outline I. Declaration
Cognitive Neuroscience Approaches to Thinking about the Mind Cognitive Neuroscience Evolutionary Approach Sept 20-22, 2004 Interdisciplinary approach Rapidly changing How does the brain enable cognition?
REVIEW Neuroimaging Studies of Normal Brain Development and Their Relevance for Understanding Childhood Neuropsychiatric Disorders RACHEL MARSH, PH.D., ANDREW J. GERBER, M.D., PH.D., AND BRADLEY S. PETERSON,
Neurobiology of Depression in Relation to ECT PJ Cowen Department of Psychiatry, University of Oxford Causes of Depression Genetic Childhood experience Life Events (particularly losses) Life Difficulties
Cognitive Neuroscience Exploring Brain/Behavior relations Neuroscience Psychology Cognitive Neuroscience Computational Sciences / Artificial intelligence Franz Joseph Gall & J. C. Spurzheim localization
Nervous System Development PSY 415 Dr. Schuetze Question What are the basic patterns of synaptic and brain development in infancy? How they are influenced by experience? What can go wrong in this pattern?
This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution
Journal of Child Psychology and Psychiatry 47:3 (2006), pp 296 312 doi:10.1111/j.1469-7610.2006.01611.x Development of the adolescent brain: implications for executive function and social cognition Sarah-Jayne
How are Parts of the Brain Related to Brain Function? Scientists have found That the basic anatomical components of brain function are related to brain size and shape. The brain is composed of two hemispheres.
General Summary: - Marijuana use appears to have a significant effect on adolescents brain structure and development. In particular, heavy marijuana use is associated with attention, memory, and planning
Myelinization THOMAS P. NAIDICH, MD FACR Mt. Sinai Medical Center New York, NY USA ALTERS BRAIN WATER LOCALLY MYELIN CONTAINS: GLYCOLIPIDS PHOSPHOLIPIDS & CHOLESTEROL Maturation of the White Matter Maturation
runl I IUI%I/\L Magnetic Resonance Imaging SECOND EDITION Scott A. HuetteS Brain Imaging and Analysis Center, Duke University Allen W. Song Brain Imaging and Analysis Center, Duke University Gregory McCarthy
Functional neuroimaging Imaging brain function in real time (not just the structure of the brain). The brain is bloody & electric Blood increase in neuronal activity increase in metabolic demand for glucose
Learning with Your Brain Should what (and how) we teach be associated with what we know about the brain and the nervous system? Jonathan Karp, Ph.D. Dept of Biology 5/20/2004 Teaching With the Brain in
Methods in Cognitive Neuroscience Dr. Sukhvinder Obhi Department of Psychology & Centre for Cognitive Neuroscience 1 Methods for studying the brain Single Cell Recording Lesion Method Human Psychophysiology
An Introduction to ERP Studies of Attention Logan Trujillo, Ph.D. Post-Doctoral Fellow University of Texas at Austin Cognitive Science Course, Fall 2008 What is Attention? Everyone knows what attention
Homework #1: Multiple choice: 1. Which of the following statements about the expression of genes in the nervous system is true? a. Every gene in the human genome is expressed in the CNS. b. There are tens
Neurobiology and the Law: A Role in Juvenile Justice? Staci A. Gruber & Deborah A. Yurgelun-Todd * Human behavior is determined by a complex interaction between biology and experience. In childhood, it
Why does an understanding of brain development matter? In the last ten years there has been an explosion of interest and research in brain development. New technologies such as MRI scanners have allowed
FUNCTIONAL EEG ANALYZE IN AUTISM Dr. Plamen Dimitrov Preamble Autism or Autistic Spectrum Disorders (ASD) is a mental developmental disorder, manifested in the early childhood and is characterized by qualitative
THE NEUROSCIENCES AND MUSIC III: DISORDERS AND PLASTICITY The Effects of Musical Training on Structural Brain Development A Longitudinal Study Krista L. Hyde, a Jason Lerch, b Andrea Norton, c Marie Forgeard,
THEORY, SIMULATION, AND COMPENSATION OF PHYSIOLOGICAL MOTION ARTIFACTS IN FUNCTIONAL MRI Douglas C. Noll* and Walter Schneider Departments of *Radiology, *Electrical Engineering, and Psychology University
Proc. Natl. Acad. Sci. USA Vol. 95, pp. 876 882, February 1998 Colloquium Paper This paper was presented at a colloquium entitled Neuroimaging of Human Brain Function, organized by Michael Posner and Marcus
THE TEENAGE BRAIN IN SEARCH OF ITSELF A WEBQUEST FOR THE ADOLESCENT BRAIN RoseMary McClain Londondonderry High School Londonderry, NH Introduction: Why do you feel like an alien in your body? Why don t
The! ERP Localization! All slides S. J. Luck, except as indicated in the notes sections of individual slides! Slides may be used for nonprofit educational purposes if this copyright notice is included,
It s All in the Brain! Presented by: Mari Hubig, M.Ed. 0-3 Outreach Coordinator Educational Resource Center on Deafness What is the Brain? The brain is a muscle In order to grow and flourish, the brain
Visual Attention and Emotional Perception Luiz Pessoa 1 and Leslie G. Ungerleider 2 (1) Department of Psychology, Brown University, Providence, RI (2) Laboratory of Brain & Cognition, National Institute
Adolescent Brain Development and Effects of Alcohol Use Monica Luciana, Ph.D. Professor and Chair Department of Psychology and Center for Neurobehavioral Development University of Minnesota (email@example.com)
Neurotrophic factors and Their receptors Huang Shu-Hong Institute of neurobiology 1 For decades, scientists believed that brain cells of the central nervous system could not regrow following damage due
Healthy Development Builds a Strong Foundation For Kids and For Society 1 Child development is a critical foundation for community development and economic development, as capable children become the foundation
The Teen Brain: Still Under ConStrUCtion NATIONAL INSTITUTE OF MENTAL HEALTH One of the ways that scientists have searched for the causes of mental illness is by studying the development of the brain from
The Teen Brain What s Going on in There? Sion Kim Harris, PhD Boston Children s Hospital Harvard Medical School Center for Adolescent Substance Abuse Research www.ceasar-boston.org Leading Causes of Mortality,
PSYCHOLOGY OF CHILDHOOD REVIEW QUESTIONS These review questions are designed to help you assess your grasp of the facts and definitions covered in your textbook. Knowing facts and definitions is necessary
Review 119 Overlapping mechanisms of attention and spatial working memory Edward Awh and John Jonides Spatial selective attention and spatial working memory have largely been studied in isolation. Studies
FUNCTIONAL BRAIN DEVELOPMENT IN HUMANS Mark H. Johnson There is a continuing debate in developmental neuroscience about the importance of activitydependent processes. The relatively delayed rate of development
Intellectual functions of the brain: Learning, Memory and higher order functions Sinan Canan,PhD firstname.lastname@example.org www.sinancanan.net Learning&Memory Learning: Neural mechanisms that modifes behavior
Basic Architecture of the Visual Cortex A.L. Yuille (UCLA) The Retina and the Cortex. Basic Biology. With about 10 million retinal receptors, the human retina makes on the order of 10 to 100 million measurements
Oxford Medicine Online You are looking at 21-30 of 1902 items for: functional AND neuroimaging Can neuroimaging help distinguish bipolar depression from major depressive disorder? Matthew T. Keener and
Neurocomputing 52 54 (2003) 419 424 www.elsevier.com/locate/neucom A model ofvisual working memory in PFC Frank van der Velde, Marc de Kamps Cognitive Psychology Unit, Leiden University, Wassenaarseweg
Atypical Visual Lecture Development 5: in! Brain Infants Development at Risk and for Evolution! Autism Spectrum Osher Series Disorders (ASD)! Karen Dobkins! Karen Dobkins Psychology Department University
PSYCHOLOGICAL SCIENCE Research Report When Actions Speak Louder Than Words Improving Children s Flexibility in a Card-Sorting Task Jennifer J. Brace, 1 J. Bruce Morton, 2 and Yuko Munakata 1 1 University
CHAPTER 6 PRINCIPLES OF NEURAL CIRCUITS. 6.1. CONNECTIONS AMONG NEURONS Neurons are interconnected with one another to form circuits, much as electronic components are wired together to form a functional
Review The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour John Duncan MRC Cognition and Brain Sciences Unit, 15 Chaucer Road, Cambridge CB2 7EF, UK A common
PSYC PSYCHOLOGY PSYC1003 is a prerequisite for PSYC1004 and PSYC1004 is a prerequisite for all remaining Psychology courses. Note: See beginning of Section F for abbreviations, course numbers and coding.
Processing Strategies for Real-Time Neurofeedback Using fmri Jeremy Magland 1 Anna Rose Childress 2 1 Department of Radiology 2 Department of Psychiatry University of Pennsylvania School of Medicine MITACS-Fields
M A R I N A B E D N Y Johns Hopkins University Department of Psychological and Brain Sciences 3400 N. Charles Street, Ames Hall Baltimore, MD 21218 email@example.com ACADEMIC POSITIONS Fall 2013 to present
CONTE Summer Lab Experience Application When preparing your application for funding from the CONTE Summer Lab Experience through the Undergraduate Program in Neuroscience, please read these instructions
T he Visual Cortex 0 Chapter contents Contents Chapter 2... 0 T he Visual Cortex... 0 Chapter Contents... 1 Introduction... 2 Optic Chiasm... 2 Where do the eye's ganglion cells project to?... 3 To where
1 Neuroimaging module I: Modern neuroimaging methods of investigation of the human brain in health and disease The following contains a summary of the content of the neuroimaging module I on the postgraduate
Phases of Prenatal Development Three periods of fertilized ovum period of the zygote, embryo & fetus Period of the zygote: ~2 weeks Fertilization to implantation in uterine lining blastocyst - protective
Temporal BOLD Characteristics and Non-Linearity Douglas C. Noll, Alberto Vazquez Dept. of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA Introduction While many early neuroimaging studies
A Primer on Brain Development or/and Why First 5 is Very Important to the Children of Northern California Heidi M Feldman MD PhD Professor. Stanford University Proud Grantee of First 5 San Mateo Learning
Medicinal Marijuana and the Developing Adolescent Brain John R. Knight, MD Associate Professor of Pediatrics Harvard Medical School Associate in Medicine & Psychiatry Children s Hospital Chair in Developmental
Advanced MRI methods in diagnostics of spinal cord pathology Stanisław Kwieciński Department of Magnetic Resonance MR IMAGING LAB MRI /MRS IN BIOMEDICAL RESEARCH ON HUMANS AND ANIMAL MODELS IN VIVO Equipment:
From conception to Age 3: The building of the brain The Urban Child Institute (TUCI) focuses on children from conception to age 3 because it is the period during which 80 percent of the human brain develops.
NeuroImage 16, 1120 1126 (2002) doi:10.1006/nimg.2002.1170 Frontal Lobe Activation during Object Permanence: Data from Near-Infrared Spectroscopy Abigail A. Baird,* Jerome Kagan,* Thomas Gaudette, Kathryn
Masters research projects 1. Adapting Granger causality for use on EEG data. Background. Granger causality is a concept introduced in the field of economy to determine which variables influence, or cause,
Attentional mechanisms of borderline personality disorder Michael I. Posner*, Mary K. Rothbart*, Nathalie Vizueta*, Kenneth N. Levy, David E. Evans, Kathleen M. Thomas*, and John F. Clarkin *Sackler Institute
Ann. N.Y. Acad. Sci. ISSN 0077-8923 ANNALS OF THE NEW YORK ACADEMY OF SCIENCES Issue: The Year in Cognitive Neuroscience Geraint Rees UCL Institute of Cognitive Neuroscience and Wellcome Trust Centre for
Early Identification and Intervention in Children at Risk for Reading Difficulties A.G.F.M. Regtvoort Summary In most children, learning to read is a process that follows a regular course across several
Effects of hypoglycemia on brain Ji Hyun Kim Department of Neurology Korea University College of Medicine Glucose and brain The brain is dependent on glucose as its principal fuel Interruption of glucose
Program Approval Form For approval of new programs and deletions or modifications to an existing program. Action Requested: Type (Check one): Create New (SCHEV approval required except for minors) B.A.
University Press Scholarship Online You are looking at 1-10 of 11 items for: keywords : traumatic brain injury Memory Development and Frontal Lobe Insult Gerri Hanten and Harvey S. Levin in Origins and
Bachelor of Science in Psychology Abbreviated Module Descriptions Modul A: Physiologische Grundlagen des Verhaltens Module A: Physiological Bases of Behavior (8 Credit Department of Experimental Psychology
ADHD and Executive Functions: Emerging Concepts Thomas E. Brown, PhD Associate Director, Yale Clinic for Attention and Related Disorders Department of Psychiatry Yale Medical School Shifts in Conceptualizing
From Neurons to Neighborhoods: The Science of Early Childhood Development By Jack P. Shonkoff, MD This chapter explains the work of the Committee on Integrating the Science of Early Childhood Development
Bachelor of Science in Psychology Module Descriptions Modul A: Physiologische Grundlagen des Verhaltens Module A: Physiological Bases of Behavior Structure and functions of neurons, synapses, and neurotransmitter
NRSN Summer School in Neuroscience 2016: Neural Circuits and Behavior Kavli Institute of Systems Neuroscience, NTNU, Trondheim 21-28 August 2016 Summary: Understanding the brain or the theory of mind has
Clinical Neuropsychology. Recovery & Rehabilitation Alan Sunderland School of Psychology 1 The Changing Role of Clinical Neuropsychology HISTORY The Origins of Clinical Neuropsychology Emergence as a profession
Sarah Levin Allen, Ph.D., CBIS Executive Director, Brain Behavior Bridge Assistant Professor, Philadelphia College of Osteopathic Medicine Pediatric & NJ School Neuropsychologist www.brainbehaviorbridge.com
Review TRENDS in Cognitive Sciences Vol.7 No.7 July 2003 313 Human recognition memory: a cognitive neuroscience perspective Michael D. Rugg 1 and Andrew P. Yonelinas 2 1 Institute of Cognitive Neuroscience
Neuroimaging Studies of Memory John Jonides Tor D. Wager David T. Badre University of Michigan Address correspondence to: Dr. John Jonides Department of Psychology University of Michigan 525 E. University
Review Training and plasticity of working memory Torkel Klingberg Department of Neuroscience, Karolinska Institute, Retzius väg 8, 171 77 Stockholm, Sweden Working memory (WM) capacity predicts performance
Physiological Basis of the BOLD Signal Kerstin Preuschoff Social and Neural systems Lab University of Zurich Source: Arthurs & Boniface, 2002 From Stimulus to Bold Overview Physics of BOLD signal - Magnetic
CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE Risk Taking in Adolescence New Perspectives From Brain and Behavioral Science Laurence Steinberg Temple University ABSTRACT Trying to understand why adolescents
Cognitive influences on attention In 1880, William James famously defined attention as taking possession by the mind of one out of several simultaneously possible objects or train of thoughts. The modern
ADHD A Focus on the Brain Laurie Hayes Center for Advanced Research and Technology Clovis, California Carrie Newdigger Macksville High School Macksville, Kansas In collaboration with Susanna Visser 1 and
Integrative Body-Mind Training (IBMT) For more information http://www.yi-yuan.net Or Email: firstname.lastname@example.org IBMT was developed in the 1990s by Prof. Yi-Yuan Tang in China based on his scientific
Intro: Brain is made up of numerous, complex parts Frontal lobes by forehead are the brain s executive center Parietal lobes wave sensory information together (maps feeling on body) Temporal lobes interpret
Your consent to our cookies if you continue to use this website.