Food cue reactivity in successful laparoscopic gastric banding: A sham-deflation-controlled pilot study.

Laparoscopic adjustable gastric banding (LAGB) offers a unique opportunity to examine the underlying neuronal mechanisms of surgically assisted weight loss due to its instant, non-invasive, adjustable nature. Six participants with stable excess weight loss (%EWL ≥ 45) completed 2 days of fMRI scanning 1.5-5 years after LAGB surgery. In a within-subject randomized sham-controlled design, participants underwent (sham) removal of ∼ 50% of the band's fluid. Compared to sham-deflation (i.e., normal band constriction) of the band, in the deflation condition (i.e., decreasing restriction) participants showed significantly lower activation in the anterior (para)cingulate, angular gyrus, lateral occipital cortex, and frontal cortex in response to food images (p < 0.05, whole brain TFCE-based FWE corrected). Higher activation in the deflation condition was seen in the fusiform gyrus, inferior temporal gyrus, lingual gyrus, lateral occipital cortex. The findings of this within-subject randomized controlled pilot study suggest that constriction of the stomach through LAGB may indirectly alter brain activation in response to food cues. These neuronal changes may underlie changes in food craving and food preference that support sustained post-surgical weight-loss. Despite the small sample size, this is in agreement with and adds to the growing literature of post-bariatric surgery changes in behavior and control regions.

Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Brain responses to anticipatory cues and milkshake taste in obesity, and their relationship to bariatric surgery outcome.

There is substantial variability in percent total weight loss (%TWL) following bariatric surgery. Functional brain imaging may explain more variance in post-surgical weight loss than psychological or metabolic information. Here we examined the neuronal responses during anticipatory cues and receipt of drops of milkshake in 52 pre-bariatric surgery men and women with severe obesity (OW, BMI = 35-60 kg/m2) (23 sleeve gastrectomy (SG), 24 Roux-en-Y gastric bypass (RYGB), 3 laparoscopic adjustable gastric banding (LAGB), 2 did not undergo surgery) and 21 healthy-weight (HW) controls (BMI = 19-27 kg/m2). One-year post-surgery weight loss ranged from 3.1 to 44.0 TWL%. Compared to HW, OW had a stronger response to milkshake cues (compared to water) in frontal and motor, somatosensory, occipital, and cerebellar regions. Responses to milkshake taste receipt (compared to water) differed from HW in frontal, motor, and supramarginal regions where OW showed more similar response to water. One year post-surgery, responses to high-fat milkshake cues normalized in frontal, motor, and somatosensory regions. This change in brain response was related to scores on a composite health index. We found no correlation between baseline response to milkshake cues or tastes and%TWL at 1-yr post-surgery. In RYGB participants only, a stronger response to low-fat milkshake and water cues (compared to high-fat) in supramarginal and cuneal regions respectively was associated with more weight loss. A stronger cerebellar response to high-fat vs low-fat milkshake receipt was also associated with more weight loss. We confirm differential responses to anticipatory milkshake cues in participants with severe obesity and HW in the largest adult cohort to date. Our brain wide results emphasizes the need to look beyond reward and cognitive control regions. Despite the lack of a correlation with post-surgical weight loss in the entire surgical group, participants who underwent RYGB showed predictive power in several regions and contrasts. Our findings may help in understanding the neuronal mechanisms associated with obesity.

Searching for Imaging Biomarkers of Psychotic Dysconnectivity.

BACKGROUND: Progress in precision psychiatry is predicated on identifying reliable individual-level diagnostic biomarkers. For psychosis, measures of structural and functional connectivity could be promising biomarkers given consistent reports of dysconnectivity across psychotic disorders using magnetic resonance imaging. METHODS: We leveraged data from four independent cohorts of patients with psychosis and control subjects with observations from approximately 800 individuals. We used group-level analyses and two supervised machine learning algorithms (support vector machines and ridge regression) to test within-, between-, and across-sample classification performance of white matter and resting-state connectivity metrics. RESULTS: Although we replicated group-level differences in brain connectivity, individual-level classification was suboptimal. Classification performance within samples was variable across folds (highest area under the curve [AUC] range = 0.30) and across datasets (average support vector machine AUC range = 0.50; average ridge regression AUC range = 0.18). Classification performance between samples was similarly variable or resulted in AUC values of approximately 0.65, indicating a lack of model generalizability. Furthermore, collapsing across samples (resting-state functional magnetic resonance imaging, N = 888; diffusion tensor imaging, N = 860) did not improve model performance (maximal AUC = 0.67). Ridge regression models generally outperformed support vector machine models, although classification performance was still suboptimal in terms of clinical relevance. Adjusting for demographic covariates did not greatly affect results. CONCLUSIONS: Connectivity measures were not suitable as diagnostic biomarkers for psychosis as assessed in this study. Our results do not negate that other approaches may be more successful, although it is clear that a systematic approach to individual-level classification with large independent validation samples is necessary to properly vet neuroimaging features as diagnostic biomarkers.

Associations of cannabis use disorder with cognition, brain structure, and brain function in African Americans.

Although previous studies have highlighted associations of cannabis use with cognition and brain morphometry, critical questions remain with regard to the association between cannabis use and brain structural and functional connectivity. In a cross-sectional community sample of 205 African Americans (age 18-70) we tested for associations of cannabis use disorder (CUD, n = 57) with multi-domain cognitive measures and structural, diffusion, and resting state brain-imaging phenotypes. Post hoc model evidence was computed with Bayes factors (BF) and posterior probabilities of association (PPA) to account for multiple testing. General cognitive functioning, verbal intelligence, verbal memory, working memory, and motor speed were lower in the CUD group compared with non-users (p < .011; 1.9 < BF < 3,217). CUD was associated with altered functional connectivity in a network comprising the motor-hand region in the superior parietal gyri and the anterior insula (p < .04). These differences were not explained by alcohol, other drug use, or education. No associations with CUD were observed in cortical thickness, cortical surface area, subcortical or cerebellar volumes (0.12 < BF < 1.5), or graph-theoretical metrics of resting state connectivity (PPA < 0.01). In a large sample collected irrespective of cannabis used to minimize recruitment bias, we confirm the literature on poorer cognitive functioning in CUD, and an absence of volumetric brain differences between CUD and non-CUD. We did not find evidence for or against a disruption of structural connectivity, whereas we did find localized resting state functional dysconnectivity in CUD. There was sufficient proof, however, that organization of functional connectivity as determined via graph metrics does not differ between CUD and non-user group.

Genetic Contributions to Multivariate Data-Driven Brain Networks Constructed via Source-Based Morphometry.

Identifying genetic factors underlying neuroanatomical variation has been difficult. Traditional methods have used brain regions from predetermined parcellation schemes as phenotypes for genetic analyses, although these parcellations often do not reflect brain function and/or do not account for covariance between regions. We proposed that network-based phenotypes derived via source-based morphometry (SBM) may provide additional insight into the genetic architecture of neuroanatomy given its data-driven approach and consideration of covariance between voxels. We found that anatomical SBM networks constructed on ~ 20 000 individuals from the UK Biobank were heritable and shared functionally meaningful genetic overlap with each other. We additionally identified 27 unique genetic loci that contributed to one or more SBM networks. Both GWA and genetic correlation results indicated complex patterns of pleiotropy and polygenicity similar to other complex traits. Lastly, we found genetic overlap between a network related to the default mode and schizophrenia, a disorder commonly associated with neuroanatomic alterations.

Cognitive impairment from early to middle adulthood in patients with affective and nonaffective psychotic disorders.

BACKGROUND: Cognitive impairment is a core feature of psychotic disorders, but the profile of impairment across adulthood, particularly in African-American populations, remains unclear. METHODS: Using cross-sectional data from a case-control study of African-American adults with affective (n = 59) and nonaffective (n = 68) psychotic disorders, we examined cognitive functioning between early and middle adulthood (ages 20-60) on measures of general cognitive ability, language, abstract reasoning, processing speed, executive function, verbal memory, and working memory. RESULTS: Both affective and nonaffective psychosis patients showed substantial and widespread cognitive impairments. However, comparison of cognitive functioning between controls and psychosis groups throughout early (ages 20-40) and middle (ages 40-60) adulthood also revealed age-associated group differences. During early adulthood, the nonaffective psychosis group showed increasing impairments with age on measures of general cognitive ability and executive function, while the affective psychosis group showed increasing impairment on a measure of language ability. Impairments on other cognitive measures remained mostly stable, although decreasing impairments on measures of processing speed, memory and working memory were also observed. CONCLUSIONS: These findings suggest similarities, but also differences in the profile of cognitive dysfunction in adults with affective and nonaffective psychotic disorders. Both affective and nonaffective patients showed substantial and relatively stable impairments across adulthood. The nonaffective group also showed increasing impairments with age in general and executive functions, and the affective group showed an increasing impairment in verbal functions, possibly suggesting different underlying etiopathogenic mechanisms.

Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls.

The human brain is active during rest and hierarchically organized into intrinsic functional networks. These functional networks are largely established early in development, with reports of a shift from a local to more distributed organization during childhood and adolescence. It remains unknown to what extent genetic and environmental influences on functional connectivity change throughout adolescent development. We measured functional connectivity within and between eight cortical networks in a longitudinal resting-state fMRI study of adolescent twins and their older siblings on two occasions (mean ages 13 and 18 years). We modelled the reliability for these inherently noisy and head-motion sensitive measurements by analyzing data from split-half sessions. Functional connectivity between resting-state networks decreased with age whereas functional connectivity within resting-state networks generally increased with age, independent of general cognitive functioning. Sex effects were sparse, with stronger functional connectivity in the default mode network for girls compared to boys, and stronger functional connectivity in the salience network for boys compared to girls. Heritability explained up to 53% of the variation in functional connectivity within and between resting-state networks, and common environment explained up to 33%. Genetic influences on functional connectivity remained stable during adolescent development. In conclusion, longitudinal age-related changes in functional connectivity within and between cortical resting-state networks are subtle but wide-spread throughout adolescence. Genes play a considerable role in explaining individual variation in functional connectivity with mostly stable influences throughout adolescence.

The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder.

BACKGROUND: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. METHODS: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. RESULTS: FDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < -0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. CONCLUSIONS: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.

Genetic Influences on the Development of Cerebral Cortical Thickness During Childhood and Adolescence in a Dutch Longitudinal Twin Sample: The Brainscale Study.

Previous studies have demonstrated that cortical thickness (CT) is under strong genetic control across the life span. However, little is known about genetic influences that cause changes in cortical thickness (ΔCT) during brain development. We obtained 482 longitudinal MRI scans at ages 9, 12, and 17 years from 215 twins and applied structural equation modeling to estimate genetic influences on (1) cortical thickness between regions and across time, and (2) changes in cortical thickness between ages. Although cortical thickness is largely mediated by the same genetic factor throughout late childhood and adolescence, we found evidence for influences of distinct genetic factors on regions across space and time. In addition, we found genetic influences for cortical thinning during adolescence that is mostly due to fluctuating influences from the same genetic factor, with evidence of local influences from a second emerging genetic factor. This fluctuating core genetic factor and emerging novel genetic factor might be implicated in the rapid cognitive and behavioral development during childhood and adolescence, and could potentially be targets for investigation into the manifestation of psychiatric disorders that have their origin in childhood and adolescence.

A QTL on chromosome 3q23 influences processing speed in humans.

Processing speed is a psychological construct that refers to the speed with which an individual can perform any cognitive operation. Processing speed correlates strongly with general cognitive ability, declines sharply with age and is impaired across a number of neurological and psychiatric disorders. Thus, identifying genes that influence processing speed will likely improve understanding of the genetics of intelligence, biological aging and the etiologies of numerous disorders. Previous genetics studies of processing speed have relied on simple phenotypes (eg, mean reaction time) derived from single tasks. This strategy assumes, erroneously, that processing speed is a unitary construct. In the present study, we aimed to characterize the genetic architecture of processing speed by using a multidimensional model applied to a battery of cognitive tasks. Linkage and QTL-specific association analyses were performed on the factors from this model. The randomly ascertained sample comprised 1291 Mexican-American individuals from extended pedigrees. We found that performance on all three distinct processing-speed factors (Psychomotor Speed; Sequencing and Shifting and Verbal Fluency) were moderately and significantly heritable. We identified a genome-wide significant quantitative trait locus (QTL) on chromosome 3q23 for Psychomotor Speed (LOD = 4.83). Within this locus, we identified a plausible and interesting candidate gene for Psychomotor Speed (Z = 2.90, P = 1.86 × 10-03 ).

Association between structural brain network efficiency and intelligence increases during adolescence.

Adolescence represents an important period during which considerable changes in the brain take place, including increases in integrity of white matter bundles, and increasing efficiency of the structural brain network. A more efficient structural brain network has been associated with higher intelligence. Whether development of structural network efficiency is related to intelligence, and if so to which extent genetic and environmental influences are implicated in their association, is not known. In a longitudinal study, we mapped FA-weighted efficiency of the structural brain network in 310 twins and their older siblings at an average age of 10, 13, and 18 years. Age-trajectories of global and local FA-weighted efficiency were related to intelligence. Contributions of genes and environment were estimated using structural equation modeling. Efficiency of brain networks changed in a non-linear fashion from childhood to early adulthood, increasing between 10 and 13 years, and leveling off between 13 and 18 years. Adolescents with higher intelligence had higher global and local network efficiency. The dependency of FA-weighted global efficiency on IQ increased during adolescence (rph =0.007 at age 10; 0.23 at age 18). Global efficiency was significantly heritable during adolescence (47% at age 18). The genetic correlation between intelligence and global and local efficiency increased with age; genes explained up to 87% of the observed correlation at age 18. In conclusion, the brain's structural network differentiates depending on IQ during adolescence, and is under increasing influence of genes that are also associated with intelligence as it develops from late childhood to adulthood.

Genetic influences on individual differences in longitudinal changes in global and subcortical brain volumes: Results of the ENIGMA plasticity working group.

Structural brain changes that occur during development and ageing are related to mental health and general cognitive functioning. Individuals differ in the extent to which their brain volumes change over time, but whether these differences can be attributed to differences in their genotypes has not been widely studied. Here we estimate heritability (h2 ) of changes in global and subcortical brain volumes in five longitudinal twin cohorts from across the world and in different stages of the lifespan (N = 861). Heritability estimates of brain changes were significant and ranged from 16% (caudate) to 42% (cerebellar gray matter) for all global and most subcortical volumes (with the exception of thalamus and pallidum). Heritability estimates of change rates were generally higher in adults than in children suggesting an increasing influence of genetic factors explaining individual differences in brain structural changes with age. In children, environmental influences in part explained individual differences in developmental changes in brain structure. Multivariate genetic modeling showed that genetic influences of change rates and baseline volume significantly overlapped for many structures. The genetic influences explaining individual differences in the change rate for cerebellum, cerebellar gray matter and lateral ventricles were independent of the genetic influences explaining differences in their baseline volumes. These results imply the existence of genetic variants that are specific for brain plasticity, rather than brain volume itself. Identifying these genes may increase our understanding of brain development and ageing and possibly have implications for diseases that are characterized by deviant developmental trajectories of brain structure. Hum Brain Mapp 38:4444-4458, 2017. © 2017 Wiley Periodicals, Inc.

Genetic transmission of reading ability.

Reading is the processing of written language. Family resemblance for reading (dis)ability might be due to transmission of a genetic liability or due to family environment, including cultural transmission from parents to offspring. Familial-risk studies exploring neurobehavioral precursors for dyslexia and twin studies can only speak to some of these issues, but a combined twin-family study can resolve the nature of the transmitted risk. Word-reading fluency scores of 1100 participants from 431 families (with twins, siblings and their parents) were analyzed to estimate genetic and environmental sources of variance, and to test the presence of assortative mating and cultural transmission. Results show that variation in reading ability is mainly caused by additive and non-additive genetic factors (64%). The substantial assortative mating (rfather-mother=0.38) has scientific and clinical implications. We conclude that parents and offspring tend to resemble each other for genetic reasons, and not due to cultural transmission.

No Evidence of Causal Effects of Blood Pressure on Cognition in the Population at Large.

The large body of literature on the association between blood pressure (BP) and cognitive functioning has yielded mixed results, possibly due to the presence of non-linear effects across age, or because BP affects specific brain areas differently, impacting more on some cognitive skills than on others. If a robust association was detected among BP and specific cognitive tasks, the causal nature of reported associations between BP and cognition could be investigated in twin data, which allow a test of alternative explanations, including genetic pleiotropy. The present study first examines the association between BP and cognition in a sample of 1,140 participants with an age range between 10 and 86 years. Linear and quadratic effects of systolic BP (SBP) and diastolic BP (DBP) on cognitive functioning were examined for 17 tests across five functions. Associations were corrected for effects of sex and linear and quadratic effects of age. Second, to test a causal model, data from 123 monozygotic (MZ) twin pairs were analyzed to test whether cognitive functioning of the twins with the higher BP was different from that of the co-twins with lower BP. Associations between BP and cognitive functioning were absent for the majority of the cognitive tests, with the exception of a lower speed of emotion identification and verbal reasoning in subjects with high diastolic BP. In the MZ twin pair analyses, no effects of BP on cognition were found. We conclude that in the population at large, BP level is not associated with cognitive functioning in a clinically meaningful way.

The Computerized Neurocognitive Battery: Validation, aging effects, and heritability across cognitive domains.

OBJECTIVE: The Computerized Neurocognitive Battery (CNB) enables efficient neurocognitive assessment. The authors aimed to (a) estimate validity and reliability of the battery's Dutch translation, (b) investigate effects of age across cognitive domains, and (c) estimate heritability of the CNB tests. METHOD: A population-representative sample of 1,140 participants (aged 10-86), mainly twin-families, was tested on the CNB, providing measures of speed and accuracy in 14 cognitive domains. In a subsample (246 subjects aged 14-22), IQ data (Wechsler Intelligence Scale for Adults; WAIS) were available. Validity and reliability were assessed by Cronbach's alpha, comparisons of scores between Dutch and U.S. samples, and investigation of how a CNB-based common factor compared to a WAIS-based general factor of intelligence (g). Linear and nonlinear age dependencies covering the life span were modeled through regression. Heritability was estimated from twin data and from entire pedigree data. RESULTS: Internal consistency of all tests was moderate to high (median = 0.86). Effects of gender, age, and education on cognitive performance closely resembled U.S. SAMPLES: The CNB-based common factor was completely captured by the WAIS-based g. Some domains, like nonverbal reasoning accuracy, peaked in young adulthood and showed steady decline. Other domains, like language reasoning accuracy, peaked in middle adulthood and were spared decline. CNB-test heritabilities were moderate (median h2 = 31%). Heritability of the CNB common factor was 70%, similar to the WAIS-based g-factor. CONCLUSION: The CNB can be used to assess specific neurocognitive performance, as well as to obtain a reliable proxy of general intelligence. Effects of aging and heritability differed across cognitive domains.

Development of the brain's structural network efficiency in early adolescence: A longitudinal DTI twin study.

The brain is a network and our intelligence depends in part on the efficiency of this network. The network of adolescents differs from that of adults suggesting developmental changes. However, whether the network changes over time at the individual level and, if so, how this relates to intelligence, is unresolved in adolescence. In addition, the influence of genetic factors in the developing network is not known. Therefore, in a longitudinal study of 162 healthy adolescent twins and their siblings (mean age at baseline 9.9 [range 9.0-15.0] years), we mapped local and global structural network efficiency of cerebral fiber pathways (weighted with mean FA and streamline count) and assessed intelligence over a three-year interval. We find that the efficiency of the brain's structural network is highly heritable (locally up to 74%). FA-based local and global efficiency increases during early adolescence. Streamline count based local efficiency both increases and decreases, and global efficiency reorganizes to a net decrease. Local FA-based efficiency was correlated to IQ. Moreover, increases in FA-based network efficiency (global and local) and decreases in streamline count based local efficiency are related to increases in intellectual functioning. Individual changes in intelligence and local FA-based efficiency appear to go hand in hand in frontal and temporal areas. More widespread local decreases in streamline count based efficiency (frontal cingulate and occipital) are correlated with increases in intelligence. We conclude that the teenage brain is a network in progress in which individual differences in maturation relate to level of intellectual functioning.

Domain dependent associations between cognitive functioning and regular voluntary exercise behavior.

Regular exercise has often been suggested to have beneficial effects on cognition, but empirical findings are mixed because of heterogeneity in sample composition (age and sex); the cognitive domain being investigated; the definition and reliability of exercise behavior measures; and study design (e.g., observational versus experimental). Our aim was to scrutinize the domain specificity of exercise effects on cognition, while controlling for the other sources of heterogeneity. In a population based sample consisting of 472 males and 668 females (aged 10-86 years old) we administered the Computerized Neurocognitive Battery (CNB), which provided accuracy and speed measures of abstraction and mental flexibility, attention, working memory, memory (verbal, face, and spatial), language and nonverbal reasoning, spatial ability, emotion identification, emotion- and age differentiation, sensorimotor speed, and motor speed. Using univariate and multivariate regression models, CNB scores were associated with participants' average energy expenditure per week (weekly METhours), which were derived from a questionnaire on voluntary regular leisure time exercise behavior. Univariate models yielded generally positive associations between weekly METhours and cognitive accuracy and speed, but multivariate modeling demonstrated that direct relations were small and centered around zero. The largest and only significant effect size (ß = 0.11, p < 0.001) was on the continuous performance test, which measures attention. Our results suggest that in the base population, any chronic effects of voluntary regular leisure time exercise on cognition are limited. Only a relation between exercise and attention inspires confidence.

Brain SCALE: brain structure and cognition: an adolescent longitudinal twin study into the genetic etiology of individual differences.

From childhood into adolescence, the child's brain undergoes considerable changes in both structure and function. Twin studies are of great value to explore to what extent genetic and environmental factors explain individual differences in brain development and cognition. In The Netherlands, we initiated a longitudinal study in which twins, their siblings and their parents are assessed at three year intervals. The participants were recruited from The Netherlands Twin Register (NTR) and at baseline consisted of 112 families, with 9-year-old twins and an older sibling. Three years later, 89 families returned for follow-up assessment. Data collection included psychometric IQ tests, a comprehensive neuropsychological testing protocol, and parental and self-ratings of behavioral and emotional problems. Physical maturation was measured through assessment of Tanner stages. Hormonal levels (cortisol, luteinizing hormone, follicle-stimulating hormone, testosterone, and estrogens) were assessed in urine and saliva. Brain scans were acquired using 1.5 Tesla Magnetic Resonance Imaging (MRI), which provided volumetric measures and measures of cortical thickness. Buccal swabs were collected for DNA isolation for future candidate gene and genome-wide analysis studies. This article gives an overview of the study and the main findings. Participants will return for a third assessment when the twins are around 16 years old. Longitudinal twin-sibling studies that map brain development and cognitive function at well-defined ages aid in the understanding of genetic influences on normative brain development.