br Knowing things and becoming an individual

Knowing things and becoming an individual take time: the time scale of the research matters As an example, the left-hand graph in Fig. 2 shows the long time course of developing calculation skills in children between ages 5 and 16. Such a protracted increase in calculation skills is consistent with the expected influence of instruction and practice in formal and informal learning environments. Perhaps more surprising is that even the basic capacity to inhibit a primed motor response (shown in the figure\'s right panel) exhibits a similarly protracted course of development. But why do behavioral phenotypes diverge during development? Why, for example, do some children from this study at age 14 exhibit calculation skills more typical of the average 9 year old, and some children at 9 exhibit motor inhibitory functions more typical of 15 year olds? Again, there is evidence for some degree of genetic mediation of variability on both of these kinds of skills, but developing calculation skills are clearly modified by the instruction and learning experiences of children, and by other cultural factors, and even performance on a simple motor inhibitory task like this improves with practice. For simplicity\'s sake, we might begin with this basic conceptual model (Fig. 3) for an emerging behavioral phenotype in a developing child: that it represents some function of the effects exerted by (1) the hypothetical domain-relevant neural genotype; and sometimes by (2) environmental effects on the neural apparatus relevant to the skill or domain (e.g., in cases in which damage or toxic exposure to the naloxone hydrochloride Supplier occurs); but, more generally, also by (3) cumulative experiences throughout development encountering and manipulating material in the domain; and finally by (4) interactions between these factors. Much ongoing research in human developmental neuroscience is aimed at improving models like this one. However if we are ever to achieve our translational aims – that is, to prevent adverse outcomes and lift the trajectories of well-being in at-risk individuals in our society – then we must strive to answer some big questions that strike at the heart of the matter. We might ask: To what degree, and via which biological mechanisms, does common genetic variation constrain – or bias – functions of maturing circuits in the human brain? And to what degree, and under which circumstances, are there consequences (of these gene effects) for experience-dependent developmental processes, or for responses of the developing brain to neuroactive environmental factors (such as trauma, toxicity, drug exposure, etc.)?
Can observing the biological development of the human brain help answer these questions? On this occasion, when we honor Peter Huttenlocher, we revisit one of the first papers published in this area 23 years ago (Jernigan et al., 1991); not, certainly, because it is a particularly interesting paper by today\'s standards, on the contrary, it will serve to illustrate how far we have come in those 2 decades; but it is one of the earliest imaging papers to cite Peter Huttenlocher\'s remarkable observations. In those days, Jernigan was applying early “semi-automated” morphometry methods developed in her lab to analyze MR imaging data. The regions of interest (ROIs) for examining the cortex were essentially stereotactically-defined quadrants of the cerebrum, and are a long way back from the sophisticated surface-based methods we apply in our work today. By performing tissue segmentation based on dual echo MR images, Jernigan et al. measured cortical gray matter volumes in these large ROIs; and in a modest sample of 39 young people ranging in age from 7 to 35, observed highly significant, and linear, decreases in the cortical gray matter volumes (adjusted for volumes of the supratentorial cranial vault) in the two dorsal regions, with no real evidence of change in the ventral areas. Obviously, we know a lot more about the age functions and anatomical pattern of these apparent changes in gray matter volume now, but at the time they were quite surprising to many people; and the biological explanation for them was far from clear. Since the one largely postnatal phenomenon of which we were all aware was the protracted course of myelination and oligodendrocyte maturation (Yakovlev and Lecours, 1967), we, and others, speculated that signal changes associated with the newly generated myelin sheaths of axons coursing beneath the cortex, or even intracortically, might contribute to these apparent volume reductions in cortical gray. In other words, the apparent cortical gray matter reductions might represent the shifting signal characteristics of immature tissue comprised of more lightly myelinated axons (i.e., resembling gray matter) to the signal characteristics of tissue comprised of more fully myelinated axons. But we also had just become aware of Huttenlocher\'s observations suggesting synaptic pruning in what seemed to be an anatomically heterochronous pattern across the cortex (Huttenlocher and de Courten, 1987; Huttenlocher, 1990; Huttenlocher and Dabholkar, 1997). We therefore speculated that our observations and those reported by Huttenlocher might in both cases reflect some later process of maturation in the dorsal cortical regions during adolescence. Before we move into the modern era of neuroimaging, we would emphasize one other result from this early paper, rarely mentioned in the subsequent literature, that seemed to suggest that the mechanisms underlying these apparent cortical volume changes probably involved both loss of tissue volume as well as changing signal contrast on MRI. That was the observation that CSF volume increased in the adjacent subarachnoid space in a very similar anatomical pattern to the cortical volume reductions, as though nearby tissue loss resulted in expansion of this space, ex vacuo.