Review: Dynamic Cycles of Cognitive and Brain Development

Dynamic Cycles of Cognitive and Brain Development

This is an interesting chapter from the book, The Educated Brain, which was published in 2008. Recent research has shown that human development can be better understood as a dynamic process rather than a fixed set of development phases.


Neurocognitive development should be conceived not as a ladder of successive stages but as a
complex network of interactions and attractors, convergent and divergent paths,
nested cycles, stabilities and instabilities, progressions and regressions, clusters of
discontinuities and stable levels of performance.

The complexity and detail in this quote are a clear sign of the growing recognition that neurological development is a complex dance between genetics and environment, or in more traditional terminology between nature and nurture. A child’s brain does not develop in clear steps forward, but rather jumps backwards and forwards, developing simultaneously in different directions. This reminds me of Steven Pinker’s wonderful book, Words and Rules, in which he discusses the development (and apparent regression) of language by using the example of the past tense. Initially, a child learns all irregular verbs as words (lexis) and says them correctly. However, when the child learns how to form the regular past tense (e.g. adding -ed to the stem of the verb), he/she overgeneralizes this to all verbs including irregular verbs and hence makes mistakes. Eventually the child manages to create the right balance between words and rules. Pinker’s example illustrations several most of the concepts in the quote above including:
– a complex network
-interactions and attractors
– convergent and divergent paths (Rules of grammar can be considered as convergent and Words can be considered as divergent)
– stabilities and instabilities
– progressions and regressions

Interestingly, in the overview to this paper, while Fischer initially suggests that a dynamic model is superior to a level-based model, he then suggests a ten-level developmental scale. While this initially suggested a contradiction to me, I assume that both perspectives (dynamic/cyclical and linear) are necessary to describe cognitive development.

I like the observation that “public expectations about relating brain science to educational practice are running far ahead of the realities of scientific knowledge.” It seems to me that we are still a long way from being able to make clear statements for the classroom, but of course in the meantime this is a fascinating area and just thinking about it can give us great teaching ideas.

The information about the growth of the cortex was completely new to me.

A prime
example is the growth of the cortex, which grows six layers in a cyclical
process of neuron generation and migration, as described by Rakic (1971;
1988). A single growth process thus produces six distinct layers in which
cells for different layers end up with vastly different functions, even
though they are all created by the same process.

To think that something as complex as the cortex can be developed in this way through evolution and to be repeated for every child is a truly wondrous thing. And that we can contemplate the wonder with that same cortex is a higher level of wonder again!

The graphs showing increasing (and sometimes decreasing) pronoun use as age increases is fascinating and is a good illustration of the spurts in performance:

Infants, children,adolescents, and young adults all move through periods when their skills are leaping forward at a fast pace, especially under conditions that support optimal performance (upper line).

and also of the periods in between these spurts:

In more ordinary performance, where they are not pushing the limits of their capacity, they commonly show either linear growth or unsystematic change.

Figure 8.2 is very similar to a figure that Robert introduced in one of his conference presentations. I have added it below:


I am still struggling a little in understanding how these ‘levels’ in the figure are actually realized in practice. Fischer helpfully answers part of my question by noting that a child’s development does not actually follow this linear progress for all skills simultaneously. Rather, people develop in a web-like manner with many strands progressing at the same time, all of which could be travelling at different speeds. In addition, people can regress or perform at lower levels than expected if the context is not supportive.

Fischer gives a detailed explanation of the development from single abstractions to abstract mappings all the way up to principles. I must confess to getting a bit lost in some of these explanations ;)

It is very interesting that spurts in EEG energy seem to correspond to the ages for cognitive spurts.

The description of the development of the cortex is also useful, especially:

The prefrontal cortex leads
the way, since empirical evidence indicates that the large majority of
systematic changes with age in networks involve connections between the
prefrontal cortex and other regions.

Figure 8.10 is also interesting and I have reproduced it below.

It is useful to see that skill level naturally rises and drops cyclically and that it is not anything that we are doing wrong in the classroom ;)

The collapses do not indicate difficulties. Instead they are normal and
required, reflecting the need to build and rebuild a skill with variations so
that the person can eventually sustain it in the face of changes in context
and state.

The section on p145-146 is illuminating in warning about the potential dangers of brain science claims for education. The researchers used their data to claim that no learning could occur during particular development phases and so no new concepts should be introduced at these times. This kind of prescriptive approach can clearly be dangerous, especially in our current state of knowledge, and without a clear understanding of individual education contexts.

Overall, I found this paper useful in understanding the development of the human brain over time.