Chapter 11

Reaching the Mountain Top
Your brain, on steroids

A few references related to my description of the general development of motor control ability in childhood (note that many hundreds could be cited):

  1. For a description of fetal movement patterns, see de Vries JL, Fong BF (2006) Normal fetal motility: an overview. Ultrasound Obstet Gynecol 27:601
  2. For an introduction to studies documenting the integration of body senses and vision in controlling body position in space, see Andersen RA (1997) Multimodal integration for the representation of space in the posterior parietal cortex. Philos Trans R Soc Lond B Biol Sci 352:1421; for a more current example considering the specific example outlined in the text (reaching out to grasp an object of interest), see Vesia M, Crawford JD Specialization of reach function in human posterior parietal cortex. Exp Brain Res 221:1; or for an intriguing slant on underlying function-mapping issues, see Silver MA, Kastner S (2009) Topographic maps in human frontal and parietal cortex. Trends Cogn Sci 13:488.
  3. My understanding of the ontogeny of movement control originally stems from the seminal studies of the late Esther Thelen: See Thelen E (1995) Motor development. A new synthesis. Am Psychol 50:79; or Thelen E, Corbetta D (1994) Exploration and selection in the early acquisition of skill. Int Rev Neurobiol 37:75.
  4. There are hundreds of books summarizing the main neurological and behavioral benchmarks of normal child development.
  5. Myelination resulting from higher levels of correlated activities in late-/post-critical period epochs hypothetically arise from both direct (e.g., see Wake H et al. (2011) Control of local protein synthesis and initial events in myelination by action potentials. Science 333:1647; and indirect causes. For example, in the latter case, BDNF expression grows as local correlated activity grows across the critical period; manipulation of BDNF results in changes in the timing of critical period closure (e.g., Maffei L, 2002, Plasticity in the visual system: role of neurotrophins and electrical activity. Arch Ital Biol 140:341) and directly promotes myelination (e..g, Xiao J, et al. (2010) Brain-derived neurotrophic factor promotes central nervous system myelination via a direct effect upon oligodendrocytes. Neurosignals 18:186.
  6. We have shown that critical period closure is determined by changes that occur very locally (minicolumn by minicolumn) within the developing cortex, demonstrated by rearing animals through the critical period with exposure to either a narrow band of noise, or in the presence of continuous broadband noises with a narrow noiseless spectral notch. Background noises frustrate the progression to “adult plasticity” because (we conclude) in that case the cortex receives a very weak schedule of coordinated inputs. In this study, only the noise-exposed part of the brain remained permanently immature. By striking contrast, the cortical zone representing sound frequencies outside the noise band (or within a noise-less notch in a broadband noise) advance on the normal schedule to an adult status. In our study, these two (“immature” vs “mature”) zones were extraordinarily sharply bounded. On one side of the boundary, the brain was “mature” in every examined physical, functional and chemical respect. On the other side, it remained “infantile,” as if it has had no experience, in every physical, functional and chemical respect we examined. These studies are among many that indicate that experience ultimately resulting in strongly correlated and reliable local cortical organization, achieved mini-column by mini-column, underlies the transition from “critical period” to “adult” plasticity. See de Villers-Sidani et al (2008) Manipulating critical period closure across different sectors of the primary auditory cortex. Nat Neurosci 11:957.
  7. The stringent time-coincidence requirements for inducing cortical plasticity and underlying mechanisms have been discussed in the notes provided with “ten rules of plasticity” described in Chapter 10 (
  8. The progression of myelination reaching a “mature” state in young-adult females and males has been documented in studies beginning with Paul Fleschsig in the late 19th and early 20th Centuries. The story was well told back then; not too much about the overall average timing of changes leading to full maturation has been added—except for the VERY important discovery (which we’ll discuss in the notes for Chapter 29) that myelination OR de-myelination can be induced, plastically, at any age, by appropriate forms of brain plasticity-based exercise. The predominant view throughout the 20th Century was that central nervous system myelination could NOT be modified by experience in the adult brain. Wrong, again
  9. A large number of studies have documented changes in processing speed every which way, and have very richly related it to measures of cognition (e.g., Salthouse, TA, 2000, Aging and measures of processing speed. Biol Psychol 54:35; or Salthouse TA, 1996, The processing-speed theory of adult age differences in cognition. Psychol Rev 103:403.) Several research teams have argued that because myelination is obviously correlated with transmission times speed, the growth then loss of myelin with parallel changes in speed must account for our rise to a performance peak (they say in your 30’s), then our fall (slowing) into older age. These arguments are specious, in the sense that there is much more to “speed” then myelination—as I’ve discussed in part in the notes following Chapter 10 and shall discuss in still more detail in the notes following Chapters 22-24.
  10. We have measured the speed of processing in a large population of adults of all ages (20-100) in another way, by measuring the time it takes from the onset of an initial brief stimulus before the onset of a second equally brief stimulus to identify both stimuli, and reconstruct the sequence order of the two. Shortest onset-to-onset times were recorded for most individuals between roughly 20 and 30 years of age. In both auditory and visual domains, dramatic declines were recorded at older ages—but virtually all older individuals could recover processing speed that was as fast as most 30-year-olds through about 10 hours of computer-guided training. See references after Chapter 28 ( a related, early, precedent-setting visual-system example, see Triesman A (1991) Search, similarity and the integration of features between and within dimensions. J Exp Psychol Hum Perc Perf 17:652.