Graded Variation In Cortical T1w/T2w Myelination During Adolescence

Myelination influences brain connectivity during sensitive periods of development by enhancing neural signaling speed and regulating synapse formation to reduce plasticity. However, in vivo studies characterizing the maturational timing of cortical myelination during human development remain scant. Here, we take advantage of recent advances in high-resolution cortical T1w/T2w myelin mapping methods, including principled correction of B1+ transmit field effects, using data from the Human Connectome Project in Development (N=628, ages 8-21) to characterize the maturational timing of myelination from childhood through early adulthood throughout the cerebral neocortex. We apply Bayesian spline models and functional latent clustering analysis to demonstrate graded variation in the rate of cortical T1w/T2w myelin growth in neocortical areas that is strongly correlated with the sensorimotor-association (S-A) axis of cortical organization reported by others. In sensorimotor areas T1w/T2w myelin starts at high levels at early ages, increases at a fast pace, and decelerates at later ages (18-21). In intermediate multimodal areas along the S-A axis, T1w/T2w myelin tends to start at intermediate levels and increase linearly at an intermediate pace. In transmodal/paralimbic association areas high along the S-A axis, T1w/T2w myelin tends to start at low levels and increase linearly at the slowest pace. These data provide evidence for graded variation along the S-A axis in the rate of cortical myelination during adolescence, which could reflect ongoing plasticity underlying the development of complex information processing and psychological functioning.Significance StatementMyelin is a lipid membrane that is essential to healthy brain function. Myelin wraps axons to increase neural signaling speed, enabling complex neuronal functioning underlying learning and cognition. Here we characterize the developmental timing of myelination across the cerebral cortex during adolescence using recent advances in non-invasive myelin mapping. Our results provide new evidence demonstrating graded variation across the cortex in the timing of myelination during adolescence, with rapid myelination in lower-order sensory areas and gradual myelination in higher-order association areas. This spatial pattern of microstructural brain development closely parallels the sensorimotor-to-association axis of cortical organization and plasticity during ontogeny.

Biological age vs. chronological age: the impact on the development of the young tennis athlete

The aim of this paper is to understand how various factors such as maturation, peak height velocity, body growth and the effect of relative age can interfere with the athlete's development in sports and in personal terms. Studies indicate that athletes’ development is made up of several stages of maturation, and it is likely that they may occur at different timings depending on the athlete, their birth date, their upbringing, and the type of practice they have undertaken. Thus, we will have to be aware of the prediction we make of an athlete’s progression because this maturational timing influences both the physical and mental progression of the athlete. This is especially true given that evidence shows that those born in the first semester of the season or year may have early advantages over those born in the second semester. This may include finding ways to limit the ability to give more means and selection to teams or players that are stronger or more mature.

Innate talent in sport: from theoretical concept to complex reality – comment on Baker & Wattie

Over the last 20 years, the concept of innate talent has been discussed in the literature, and different factors have been associated with talent in different sports. However, it should be noted that talent identification is sport-, or even position-specific, and no ‘one size fits all’ consensus can be established. Specific talent profiles should be developed, acknowledging the multidimensionality of talent by taking physical, physiological, cognitive, psychological, and motivational factors into account. These profiles should also be age-specific and adjusted for covariates such as maturational timing and training history. To make a step forward in talent identification, we should not only move ahead in identifying innate talent, but also acknowledge the multifaceted and dynamic nature of talent. Therefore, we recommend researchers and practitioners to start approaching talent as a multidimensional, complex system.

BMI percentile-for-age overestimates adiposity in early compared with late maturing pubertal children

ObjectiveEarly pubertal timing is consistently associated with increased BMI percentile-for-age in pubertal girls, while data in boys are more ambiguous. However, higher BMI percentile-for-age may be a result of the earlier pubertyper serather thanvice versa. The aim was to evaluate markers of adiposity in relation to pubertal timing and reproductive hormone levels in healthy pubertal boys and girls.Study designPopulation-based cross-sectional study (The Copenhagen Puberty Study). Eight-hundred and two healthy Caucasian children and adolescents (486 girls) aged 8.5–16.5 years participated. BMI and bioelectric impedance analyses (BIA) were used to estimate adiposity. Clinical pubertal markers (Tanner stages and testicular volume) were evaluated. LH, FSH, estradiol, testosterone, SHBG and IGF1 levels were determined by immunoassays.ResultsIn all age groups, higher BMI (all 1 year age-groups,P≤0.041) was found with early compared with late maturation, despite similar BIA–estimated body fat percentage (BIA–BF%). Neither BMI nor BIA–BF% differed for a given stage of maturation. BMI percentile-for-age and prevalence of overweight/obesity were higher in the early compared with late matured pubertal children (allP≤0.038), despite similar BIA–BF%. Pubertal girls with BIA–BF >29% had significantly lower LH and FSH levels compared with normal-weight girls (P≤0.041).ConclusionsEarly maturational timing was not associated with higher adiposity for a given stage of puberty. Using BMI percentile-for-age overestimated the degree of adiposity in early pubertal compared with late pubertal children.