di: DI and Neuroplasticity?

Tue Sep 11 18:50:35 PDT 2018

If we extend the topic to include the role of neuroscience in education,
there are some bits and pieces here:

“Background: Our ability to look at structure and function of a living
brain has increased exponentially since the early 1970s. Many studies of
developmental disorders now routinely include a brain imaging or
electrophysiological component. Amid current enthusiasm for applications of
neuroscience to educational interventions, we need to pause to consider
what neuroimaging data can tell us. Images of brain activity are seductive,
and have been used to give credibility to commercial interventions, yet we
have only a limited idea of what the brain bases of language disorders are,
let alone how to alter them. Scope and findings: A review of six studies of
neuroimaging correlates of language intervention found recurring
methodological problems: lack of an adequate control group, inadequate
power, incomplete reporting of data, no correction for multiple
comparisons, data dredging and failure to analyse treatment effects
appropriately. In addition, there is a tendency to regard neuroimaging data
as more meaningful than behavioural data, even though it is behaviour that
interventions aim to alter. Conclusion: In our current state of knowledge,
it would be better to spend research funds doing well designed trials of
behavioural treatment to establish which methods are effective, rather than
rushing headlong into functional imaging studies of unproven treatments”
(p.247).

“The impression is that the field is trying to run before it can walk. Our
first priority should be to first develop interventions for children with
language impairments and other neurodevelopmental disorders, and to produce
good evidence of their efficacy using randomized controlled trials. Second,
we also need to do far more methodological work to ensure our neuroimaging
tools are as reliable, sensitive and standardized as our behavioural
measures (Dichter et al., 2012). Third, we will need to develop multicentre
collaborations to do studies with adequate statistical power to detect
treatment effects. Only then will we be in a strong position to combine
neuroimaging with intervention to answer questions about underlying
mechanisms of effective intervention” (p.257).

Bishop, D. V. M. (2012). Neuroscientific studies of intervention for
language impairment in children: interpretive and methodological problems.
Research Review: Emanuel Miller Memorial Lecture 2012. *Journal of Child
Psychology and Psychiatry, 54*(3), 247–259.
------------------------------

“Neuroplasticity the one thing we know about plasticity, which is the
capacity to adjust and adapt, is it's greatest when the brain is immature,
and it is less as the brain becomes more mature. It's never completely
gone. There is plasticity in the brains of adults. So we do know that there
are some functions that emerge, in terms of brain development, in critical
periods. And the well described ones are in the sensory area, vision and
hearing, to some extent. But there has never been demonstrated in humans a
critical period for anything related to cognition or emotional development
or social development.

In a sensitive period, there isn't a time when the window closes and it's
too late. But what it means is that when you pass the sensitive period,
it's harder for these things to develop in an adaptive way, or they may
develop in a way that is not as efficient as it might be, and that you have
to try to overcome later. Unlike a critical period where it's too late,
missing a sensitive period means that it just gets harder as you get older,
it's harder to get it right. So the messages that come out of that basic
principle of brain development is that getting things right the first time
is better than trying to fix them later, trying to adapt to something that
was not developed in the best way at the time that it was supposed to be
developed. So the sobering message here is that if children don't have the
right experiences during these sensitive periods for the development of a
variety of skills, including many cognitive and language capacities, that's
a burden that those kids are going to carry; the sensitive period is over,
and it's going to be harder for them. Their architecture is not as well
developed in their brain as it would have been if they had had the right
experiences during the sensitive period. That's the sobering message. But
there's also a hopeful message there, which is unlike a critical period
where it's too late. The sensitive period says: It's not too late to kind
of try to remediate that later. And you can develop good, healthy, normal
competencies in many areas, even if your earlier wiring was somewhat
faulty. But it's harder. It costs more in energy costs to the brain. The
brain has to work at adapting to earlier circuits that were not laid down
the way they should have been. And from a society's point of view, it costs
more in terms of more expensive programming, more specialized help.

Shonkoff, J.P. (2007). *The neuroscience of nurturing neurons.* Children of
the Code. Retrieved from
http://www.childrenofthecode.org/interviews/shonkoff.htm
------------------------------

“Although neurological variables may explain why individuals with dyslexia
struggle more than children without dyslexia in learning to read, the
dyslexic brain may still show plasticity in response to instructional
interventions. Specific language processes may normalize after short-term
treatment, suggesting that if appropriate instruction is sustained, this
treatment may lead to full compensation (full recovery of normal reading).
Evidence for such brain plasticity in individuals with dyslexia, which is
associated with differences in occipital–temporal, temporal–parietal,
and frontal
brain systems (e.g. Shaywitz & Shaywitz, 2003), has been reported following
treatment. fMRI tasks have shown pre- to post-treatment changes in brain
activation levels and patterns in frontal systems (Aylward et al.,
2003; Richards
et al., 2000, 2002; Temple et al., 2000, 2003; Shaywitz et al., 2004),
temporal–parietal regions (Aylward et al., 2003; Eden et al., 2004;
Shaywitz et al., 2004; Simos et al., 2002; Temple et al., 2003), and
occipital–temporal regions (Aylward et al., 2003; Shaywitz et al., 2004).
Plasticity of brain response has been observed across the life span: (a) in
younger students in response to explicit phonological awareness and phonics
instruction (Shaywitz et al., 2004; Simos et al., 2002), (b) in upper
elementary and middle school students in response to instruction designed
to increase the precision of phonological and orthographic word
representations and the efficiency of the working memory architecture (Aylward
et al., 2003; Richards et al., 2000, 2002), and (c) in adults in response
to explicit instruction in sound and articulatory awareness and phonics
training (Eden et al., 2004). Brain plasticity has also been demonstrated
for normal adolescents learning non-word associations (Molfese et al., 2002)
and normal adults learning a miniature visual language (McCandliss, Posner,
& Given, 1997). See Richards et al. (in press) and Berninger (in press) for
additional details of these studies, which varied in imaging modality,
imaging tasks, age of participants, and nature of the treatment”.

Richards, T., Aylward, E., Berninger, V., Field, K., Grimme, A.C., Parsons,
A., Richards, A.L., Nagy, W. (2006). Individual fMRI activation in
orthographic mapping and morpheme mapping after orthographic or
morphological spelling treatment in child dyslexics. *Journal of
Neurolinguistics,* *19**(1),* 56–86.
------------------------------

“Focus, then, must be two-fold. First is the focus on ensuring appropriate
environmental and nutritional conditions that stimulate dendritic growth in
infancy and early childhood. But second must be emphasis on improving the
strength of particular neural circuits, not simply on the overall growth of
dendrites. Most interestingly, instructional activities such as
memorization, mastery learning, and repetition-based activities appear to
best strengthen and solidify the formation and maintenance of these
circuits (Garrett, 2009; Freeberg, 2006). Data strongly support the use of
precision teaching, mastery learning approaches, and programs such as
DISTAR or direct instruction (Kirschner, Sweller, & Clark, 2006; Mills,
Cole, Jenkins, & Dale, 2002; Ryder, Burton, & Silberg, 2006; Swanson &
Sachse-Lee, 2000). In addition, programs that focus on mastery, including
applied behavior analysis and evidence-based approaches such as Treatment
and Education of Autistic and related Communication Handicapped Children
(TEACCH) (Mesibov & Shepler, 2004; Panerai, Ferrante, & Zingale, 2002),
have been shown to elicit better educational growth than instructional
practices, which focus on open-ended or child-guided instructional
practices. Thus, given the data from neuroscience combined with
evidence-based practices used in special education, special educators can
be assured that they are, indeed, using brain-based educational
instruction. Mastery-based programs that focus on fluency and repetition
are most likely to increase both better traditional learning outcomes and
produce neural circuits critical for both educational activities and
transfer to daily living skills” (p. 46).

Alferink, L.A., & Farmer-Dougan, V. (2010): Brain-(not) based education:
Dangers of misunderstanding and misapplication of neuroscience
research, *Exceptionality,
18*(1), 42-52.
------------------------------

“The first point to note here is that the term ‘brain-training’ is somewhat
of a tautology, since all learning happens in the brain. As one of our
colleagues is known to say: “it certainly doesn’t happen in your big toe”.
Any intervention that is given to any child, will, in some way, “train
their brain”. So the question here is not should we train children’s
brains, but how should we train their brains? … neuroplasticity tells us
that the brain can adapt, but it does not tell us how the brain should be
stimulated (or trained). Thus, neuroplasticity per se also does not inform
us about how to treat learning difficulties.” (p.1)

Castles, A., & McArthur, G. (2013). ‘Brain-training’… or learning as we
like to call it. *Learning Difficulties Australia Bulletin, 45*(1), 1-2.
------------------------------

“For example, the research described above on the formation of memory
through long-term potentiation strongly suggests that neural connections
are strengthened through repetition or practice (Freeberg, 2006; Garrett,
2008; Hardiman, 2003). Note that the importance of practice and rehearsal
has been known for more than a century, long before the process of
long-term potentiation was identified (Ebbinghaus, 1913; Hebb, 1949;
Thorndike, 1913). Likewise, the data suggest that formation of memories
through neural consolidation works best if students have a number of short
learning sessions separated over time, not single long sessions. Again, the
advantages of spaced or distributed practice over massed practice have also
been known for many decades (see Olson & Hergenhahn, 2009; Ebbinghaus,
1913). Neuroscience, in this case, reinforced these best practices by
providing the data at the neural level that supported these methods” (p.50).

Alferink, L.A., & Farmer-Dougan, V. (2010): Brain-(not) based education:
Dangers of misunderstanding and misapplication of neuroscience
research, *Exceptionality,
18*(1), 42-52.
------------------------------

“The idea that neuroscience research might provide guidance for teachers
sounds promising. However, as with any new and aspiring research field,
educational neuroscience has suffered to some extent from over-optimism and
wishful thinking. A huge demand for improving educational practice has been
a fertile ground for misconceptions around the question of how neuroscience
can be applied to education. Speculative educational applications have
emerged in the name of neuroscience (p.136) … In contrast with some of the
ideas behind the whole language approach, reading is therefore not innate;
brain regions that have evolved for tasks such as object (not letter)
recognition, or understanding spoken (not printed) language, need to be
combined to form a new skill. Reading is, after all, an acquired human
ability that emerged only after the cultural invention of the alphabet”
(p.138).

Weigmann, K. (2013). Educating the brain. *EMBO Reports, 14*(2), 136-9.
Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566840/
------------------------------

“Three complementary sources of evidence suggest that words are the units
of reading. First, eye movements during fluent reading are made mostly by
making saccades from one word to the next. Second, the reading time of a
single word is relatively independent of the number of letters. Third, a
single letter may be more easily detected in brief presentations when
embedded in a word. A possible inference of these findings is that
education should be organized to teach children to read entire words
instead of focusing in letter-by-letter identification. This procedure,
usually termed holistic reading, led to concrete implementations that
turned out to be a major pedagogical fiasco. As it turns out, the
neuroscience of visual learning could actually have predicted this failure.
The development of literacy is a case of pop-out learning, a process by
which, after extensive practice, one can identify a specific set of shapes
in cluttered fields very rapidly and with a subjective feeling of
automaticity and lack of effort. For non-readers, reading is a slow,
effortful and serial process that becomes automatic after many hours of
training. What sort of transformation elicits this type of learning in the
brain and what material is optimal for this learning process?

Constitutive elements of shapes are represented by pools of neurons
encoding basic traits (strokes) that recombine to form new elements of
intermediate complexity, which are subsequently recombined to encode more
complex objects69. This notion was incorporated into a model of neural
codes for written words, based on a hierarchy of increasingly complex
neuronal detectors, from individual letters to bigrams and morphemes. Only
specific patterns that conform certain letters from strokes (as opposed to
other patterns with similar regularities, but which do not occur in the
alphabet) are trained by visual experience64. The hypothesis was that this
process relies on the same learning mechanisms that carve a cortical
circuitry for grouping contours and segmenting textures, namely the
assembling of object statistical regularities in the visual world62. This
hypothesis was tested by measuring brain responses to visual strings that
progressively disrupt the ‘natural statistics’ of the alphabet at different
scales: JZWYZK (infrequent letters), QOADTM (frequent letters), QUMBST
(frequent bigrams) and AVONIL (frequent quadrigrams). Results showed a
gradient of selectivity spanning the left occipito-temporal cortex, with
increasing selectivity for higher level stimuli toward the anterior
fusiform region70.

The importance of this finding for education is that even after extensive
practice with reading, words are still represented by their constitutive
components. This process goes all the way to what appears to be the
constitutive elements of all alphabets, that is, oriented elements or
strokes. For this reason, one aspect that may impair fluent reading is the
inability to parse words into letters. In agreement with this prediction,
the remarkably simple intervention of increasing letter spacing
substantially improves text reading in some kinds of dyslexic children71.
An additional piece of evidence required to bring these data together is
that visual crowding, the inability to identify objects in clutter, is more
severe in dyslexic children, making it hard to parse letters from
continuous words” (p.500).

Sigman, M., Peña, M., Goldin, A.P., & Ribeiro, S. (2014). Neuroscience and
education: Prime time to build the bridge. *Nature Neuroscience, 17*(4),
497-502.
------------------------------

“A clinical and educational goal of reading research is to improve the
accuracy with which children at risk for dyslexia are identified so that
they can receive early, preventive intervention rather than intervention
that follows years of reading failure (Strickland, 2002
<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B56>). Although
behavioral measures of phonological awareness, RAN, and letter knowledge in
kindergartners predict reading ability years later (Catts et al., 2001
<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B7>; Schatschneider
et al., 2004 <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B48>),
the sensitivity and specificity of these behavioral measures is modest
(Pennington
and Lefly, 2001 <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B39>).
There is some evidence that brain measures substantially enhance the
accuracy of predicting reading ability across a school year (Hoeft et al.,
2007 <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B24>; Rezaie et
al., 2011 <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B44>) or
across multiple years (Maurer et al., 2009
<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B31>; Hoeft et al.,
2011 <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/#B25>). The
present study indicates that DWI measures of white matter organization
reveal a specific structural risk factor for reading difficulty that, in
combination with behavioral and other brain measures, may improve the
identification of prereaders at risk for dyslexia” (p.13256).

Saygin, Z.M., Norton, E.S., Osher, D.E., Beach, S.D., Cyr, A.B.,
Ozernov-Palchik, O., Yendiki, A., Fischl, B., Gaab, N., & Gabrieli,
J.D.E. (2013).
Tracking the roots of reading ability: White matter volume and integrity
correlate with phonological awareness in prereading and early-reading
kindergarten children. *The Journal of Neuroscience 33*(33), 13251-13258.
Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3742917/
------------------------------

“These results indicate that the GMV differences in dyslexia reported here
and in prior studies are in large part the outcome of experience (e.g.,
disordered reading experience) compared with controls, with only a fraction
of the differences being driven by dyslexia per se.”

Krafnik, A. J., Flowers, D. L., Luetje, M. M., Napoliello, E. M., & Eden,
G. F. (2014). An investigation into the origin of anatomical differences in
dyslexia. *The Journal of Neuroscience, 34*(3), 901-908.
------------------------------

“Scholarly treatments have been positive about the prospects, but more
sober, and most have taken a position that is broadly consistent with ours.
They argue that neuroscience has been and will continue to be helpful to
education — indeed, recent reviews show beyond doubt that this is true
(e.g., Katzir & Paré-Blagoev, 2006 ) — but they argue that data from
neuroscience must be funneled through a behavioral level of analysis (e.g.,
Bruer, 1997, 1998; Hirsh-Pasek & Bruer, 2007) or that neuroscience should
be part of a broader approach to research in education, not the sole savior
(e.g., Ansari & Coch, 2006; Byrnes & Fox, 1998; Fischer et al., 2007; Geake
& Cooper, 2003 ) (p. 147).

Willingham, D.T., & Lloyd, J.W. (2007). How educational theories can use
neuroscientific data. *Mind, Brain, and Education*, *1*(3), 140-149.
Retrieved from
http://www.danielwillingham.com/uploads/5/0/0/7/5007325/willingham__lloyd_2007.pdf
------------------------------

“Likewise, the data suggest that formation of memories through neural
consolidation works best if students have a number of short learning
sessions separated over time, not single long sessions. Again, the
advantages of spaced or distributed practice over massed practice have also
been known for many decades (see Olson & Hergenhahn, 2009; Ebbinghaus,
1913). Neuroscience, in this case, reinforced these best practices by
providing the data at the neural level that supported these methods” (p.50).

Alferink, L.A., & Farmer-Dougan, V. (2010): Brain-(not) based education:
Dangers of misunderstanding and misapplication of neuroscience
research, *Exceptionality,
18*(1), 42-52.
------------------------------

“Students with higher and lower math scores use different parts of the
brain when doing simple calculations, according to a new study
<http://r20.rs6.net/tn.jsp?e=001eZ1skbl-Ve3mXl31WhwvNXVgnNVsi-A0R3ur_wQvrcJpa0vqcopIizATKTf7eXlwL5oMGBrALFEQbzBFGrdjvq4tAHuhwTRqU83VN_LI89lGjVBe0FCIly0OPOqOpEtHRSGwullVvA7pJbb0ijiyNgWjEH0kQxSR>
in *The Journal of Neuroscience*. High achievers use an area of the brain
associated with arithmetic fact retrieval, whereas students with lower
scores use an area associated with quantity-processing mechanisms. The
suggestion is that the ability to recall math facts (rather than do the sum
from scratch) helps the students to go onto more complex mathematics.

The researchers used an fMRI scanner to examine the brains of 33 students
(aged 17-18) as they performed simple, single-digit arithmetic. There was a
clear association between particular areas of the brain and the students'
scores in the PSAT math test (taken at age 15-16). The results suggest a
correlation between arithmetic fact retrieval and higher scores, but more
research is needed to see whether there is also a causational link - for
example, whether interventions where lower-scoring students learn math
facts lead to changes in brain activity and/or higher math scores.”

Price, G.R., Mazzocco, M.M.M., & Ansari, D. (2013). Why mental arithmetic
counts: Brain activation during single digit arithmetic predicts high
school math scores. *The Journal of Neuroscience, 33*(1), 156-163.
------------------------------

"So I remain skeptical about the implications of neuroscience for education
currently and into the near future. Maybe I should say the *direct*
implications of neuroscience for education. I do believe that eventually we
will be able to bridge neuroscience at its various levels of analysis with
education, but I am convinced that all of these bridges will have a least
one pier on the island of psychology.

Bruer, J.T. (2006). Points of view: On the implications of neuroscience
research for science teaching and learning: Are there any? *CBE Life
Science Education, 5*(2), 111-7. Retrieved from
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1618519/
------------------------------

“As yet it is not possible to predict or assess an individual’s specific
learning disability from a brain scan (73). This is because even within a
diagnostic category, such as developmental dyslexia, there is substantial
anatomical variation from one individual to another.” … while there is
strong evidence that genetic factors are implicated in specific learning
disabilities,(74) one can seldom identify a single gene as responsible,
because multiple genes are involved and their impact depends on the
environment.(75) Furthermore, even when a genetic risk or neurological
basis for a learning disability can be identified, this does not mean the
individual is unteachable; rather, it means that it is necessary to
identify the specific barriers to learning for that person, and find
alternative ways.” (p. 12)

The Royal Society. (2011). Brain waves module 2: Neuroscience: Implications
for education and lifelong learning. Retrieved from
https://royalsociety.org/~/media/Royal_Society_Content/policy/publications/2011/4294975733.pdf

(73) Giedd, J.N., & Rapoport, J.L. (2010). Structural MRI of pediatric
brain development: What have we learned and where are we going? *Neuron 67*(5),
728–734.

(74) Willcutt, E.G., Pennington, B.F., Duncan, .L, Smith, S.D., Keenan,
J.M., & Wadsworth, S., et al. (2010). Understanding the complex etiologies
of developmental disorders: Behavioral and molecular genetic
approaches. *Journal
of Developmental and Behavioral Pediatrics, **31*(7), 533–544.

(75) For a discussion see
www.deevybee.blogspot.com/2010/09/genes-for-optimism-dyslexia-andobesity.html
------------------------------

“Working-memory training as currently implemented does not work. One
hundred years of research on basic memory phenomena has discovered many
procedures that do!” (p.190)

McCabe1, J.A., Thomas S. Redick, T.S., & Engle, R.W. (2016). Brain-training
pessimism, but applied-memory optimism. *Psychological Science in the
Public Interest, 17*(3) 187–191. Retrieved from

http://psi.sagepub.com/content/17/3/187.full.pdf+html
------------------------------

“Practicing a cognitive task consistently improves performance on that task
and closely related tasks, but the available evidence that such training
generalizes to other tasks or to real-world performance is not compelling.”
(p.173).

Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C.
F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016). Do “brain training”
programs work? *Psychological Science in the Public Interest, 18*, xxx–xxx.
Retrieved from http://psi.sagepub.com/content/17/3/187
------------------------------

“It is important to keep in mind that reading is a uniquely human skill
that is explicitly taught over several years of formal schooling. During
this time, significant functional changes occur as a direct consequence of
learning to read, as has been shown with fMRI (Gaillard et al., 2003;
Schlaggar et al., 2002; Turkeltaub et al., 2003). However, reading does not
have a sufficiently long evolutionary history that would reserve dedicated
neural populations specifically to this skill. Therefore, reading makes use
of brain areas that were most likely dedicated to other functions, an idea
that has been captured in the ‘‘neuronal recycling hypothesis’’ (Dehaene et
al., 2010). As such, the process of learning to read most likely results in
diminishing of some skills, while at the same time promoting others. The
consequential outcomes of reading acquisition have been elegantly revealed
in studies contrasting literates with illiterates, demonstrating that the
profound anatomical and physiological effects that learning to read has on
the brain exist within and well beyond brain regions directly associated
with reading (Carreiras et al., 2009)”. (p.185)

Olulade, O. A., Napoliello, E. M., & Eden, G. F. (2013). Abnormal visual
motion processing is not a cause of dyslexia. *Neuron, 79*(1), 180-190.
------------------------------

“One could conclude from this that … above average reading skills draw more
heavily and more consistently on left hemisphere mechanisms.… Average and
below-average readers, in contrast, draw more heavily on right-hemisphere
skills…. Above-average readers exhibit more hemisphere differences than
average readers, who, in turn, generate more hemisphere differences than
below-average readers”.

Molfese, D. L., Key, A.F., Kelly, S., Cunningham, N., Terrell, S.,
Ferguson, M., Molfese, V.J., & Bonebright, T. (2006). Below-average,
average, and above-average readers engage different and similar brain
regions while reading. *Journal of Learning Disabilities, 39*(4), 352-363.
------------------------------

“The large majority of neuroimaging studies investigating the
neurobiological correlates of poor reading have concentrated on lower-level
reading tasks involving letters and words. One of the most consistent
results in these studies is a finding of reduced or absent activation among
poor readers in the left parieto-temporal and/or occipito-temporal cortices
(e.g. Aylward et al., 2003
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<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib21#bib21>,
[Hoeft et al., 2006]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib23#bib23>,
[Hoeft et al., 2007]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib24#bib24>,
[Paulesu et al., 1996]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib36#bib36>,
[Rumsey et al., 1992]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib39#bib39>,
[Rumsey et al., 1997]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib40#bib40>,
[Shaywitz et al., 1998]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib52#bib52>,
[Shaywitz et al., 2002]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib47#bib47>,
[Shaywitz et al., 2003]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib51#bib51>
and [Shaywitz et al., 2004]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib46#bib46>;
Simos, Breier, Fletcher, Bergman, & Papanicolaou, 2000
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib55#bib55>;
[Simos et al., 2002]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib56#bib56>
and [Temple et al., 2003]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib58#bib58>).
While only a few studies have examined cortical function among poor readers
in higher-level reading tasks, evidence is beginning to emerge indicating
that underactivation in the parieto-temporal and occipito-temporal regions
may likewise characterize poor readers when they are reading sentences for
comprehension (e.g. [Kronbichler et al., 2006]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib29#bib29>,
[Meyler et al., 2007]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib32#bib32>
and [Seki et al., 2001]
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib44#bib44>).
Together, the findings from word-level and sentence-level studies support
the view that underfunctioning of these regions represents a neural
signature of poor reading ability (e.g. Shaywitz & Shaywitz, 2005
<http://www.sciencedirect.com.ezproxy.lib.rmit.edu.au/science?_ob=ArticleURL&_udi=B6T0D-4S4JYYC-1&_user=426478&_coverDate=08%2F31%2F2008&_alid=754125903&_rdoc=1&_fmt=high&_orig=search&_cdi=4860&_sort=d&_docanchor=&view=c&_ct=29&_acct=C000020278&_version=1&_urlVersion=0&_userid=426478&md5=cbc5da623a76662cd21cd4ebc84f5a70#bib49#bib49>
).

Meyler, A., Keller, T.A., Cherkassky, V.L., Gabrieli, J.D., & Just, M.A.
(2008) Modifying the brain activation of poor readers during sentence
comprehension with extended remedial instruction: A longitudinal study of
neuroplasticity. *Neuropsychologia, 46*(10), 2580-92.

On 11 September 2018 at 13:19, Jim Cowardin <jimco66 at gmail.com> wrote:

> Bob, I think I responded to you directly instead of to “the List” as well.
> I forgot to check to see if the DI List was an addressee. I have added it
> this time.
>
> I am certainly not an expert on brain science. I am not an expert on much
> of anything. But I think it boils down to the brain scientists’ (BSs for
> Short, no pun intended) endeavor to show a causal relationship between
> learning activities and brain change-the brain gets larger in “the area
> that is receiving instruction.” I realize that this is your “in a nutshell”
> description of the phenomenon. But I can’t help but wonder how the BSs know
> what part of the brain is “learning.”  It gets larger, so does the new
> knowledge act like food to build new brain cells? Maybe I need to read the
> original research to find out what I am missing.
>
> One of the things you can try with explanations by cognitivists and BSs,
> who are both basing their science on hypothetical constructs is to leave
> their explanations out of their descriptions and see if what is left makes
> sense or even better sense. So let me rewrite your second paragraph:
> ...Mezernich has demonstrated in animal research that clear, consistent
> repetition without distraction leads to more specialization, speed and
> accuracy.  Da, da.
>
> What does it add to the situation that the brain enlarges somewhere?  We
> certainly cannot reverse the process and enlarge the brain (What material
> would we use?) and experience “more specialization, speed and accuracy” in
> some academic response. If you let us enlarge your brain, you will be much
> smarter. We could sell that and make Apple and Microsoft afterthoughts in
> the race for net worth.
>
> If your going to enlarge brains through teaching, you need to teach well,
> and it all comes down to the principles of DI.
>
> Jim
>
> On Mon, Sep 10, 2018 at 22:37 ROBERT <bhullinghorst at comcast.net> wrote:
>
>> Dear Jim:
>>
>> Basically, as I understand it as a layman, neuroplasticity is new
>> research demonstrating that the brain continuously manufactures new
>> neurons, and these plus existing neurons can modify their synapses in
>> response to training and other factors (like physical activity and
>> nutrition).  This contrasts with the general medical position that the
>> brain has fixed segments that cannot be changed.
>>
>> Most of the research focuses on treatment of brain disease.  However, a
>> California researcher, Merzenich, has demonstrated in animal research that
>> clear, consistent repetition without distraction enlarges that portion of
>> the brain receiving instruction.   This eventually is translated into more
>> specialization, more speed, and more accuracy.  Such brain changes have
>> also been identified in humans.
>>
>> While I have read little, yet, to connect Neuroplasticity to education
>> directly, there is a recent report in England that supports "rote
>> memorization" and memory development as superior to the model that has
>> plagued our education system for decades, overwhelming the research that
>> supports Zig's Direct Instruction mode.
>>
>> While I have read other authors, Norman Doige's books on neuroplasticity
>>  have been the core of my reading..
>>
>> I am responding to you directly.  I do not yet know how to participate in
>> the forum.
>>
>> Bob Hullinghorst
>> Boulder, CO
>> 9/10/18
>>
>> Sent from XFINITY Connect App
>>
>>
>>
>> ------ Original Message ------
>>
>> From: Jim Cowardin
>> To: ROBERT
>> Sent: September 10, 2018 at 2:06 PM
>> Subject: Re: di: DI and Neuroplasticity?
>>
>> Bob, Please, define Neuroplasticity for me. I could take a guess
>> (Roughly, generalization), but I would like hear then ‘scientific’
>> description of the concept.
>>
>> Jim Cowardin
>>
>> On Mon, Sep 10, 2018 at 12:13 ROBERT <bhullinghorst at comcast.net> wrote:
>>
>>> For several months, I have been reading serious books and articles about
>>> Neuroplasticity.  While some of the information is too technical for me,
>>> and some is hokum, there seems to be much promise in the direction of this
>>> research.
>>>
>>> As a former public official, I have been similarly interested in Direct
>>> Instruction for more than a decade, because DI is the most promising route
>>> for making public education more successful for all students.  While I am
>>> not a teacher, I have attended DI classes and observed outstanding
>>> successes.
>>>
>>> I would like to begin my participation in the DI forum by positing a
>>> simple question--has there been research about how DI may relate to
>>> Neuroplasticity?
>>>
>>> The simple answer is probably NO.  Even though the unique, structured
>>> educational approach of DI may significantly support, or benefit from, the
>>> phenomena being uncovered by research on Neuroplastinity.
>>>
>>> If the answer is, in fact, NO, I would like to elaborate on my
>>> suspicions about the relationships between DI and neuroplasticity, and
>>> possible areas of research.  Unless too many members of the forum tell me I
>>> am crazy.
>>>
>>> Sincerely,
>>>
>>> Bob Hullinghorst
>>> Boulder, CO
>>>
>>> Sent from XFINITY Connect App
>>> _______________________________________________
>>> di mailing list
>>> di at lists.uoregon.edu
>>> https://lists-prod.uoregon.edu/mailman/listinfo/di
>>> <https://lists-prod.uoregon.edu/mailman/listinfo/di>
>>>
>>
> _______________________________________________
> di mailing list
> di at lists.uoregon.edu
> https://lists-prod.uoregon.edu/mailman/listinfo/di
> domain=lists-prod.uoregon.edu
>
>

-- 
Regards,

Kerry

Dr Kerry Hempenstall
Senior Industry Fellow,
School of Education,
RMIT University,
Melbourne Australia
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