Australian Guidance Counsellors Association Annual Conference
Hobart, April 2009
Neuroscience and
neuromythology
John Geake
School of Education
The University of New England
Armidale, NSW
Daily Telegraph, December 1997
1 neuroimage = 1K words?
+ve media and political
recognition of a role for
neuroscience in social policy:
education, criminology, agecare ...
-ve misinterpretations that
these areas which ‘light up’
are solely responsible for a
particular type of mental
activity
General Limitations of Neuroimaging
1. Structure – function mappings are not one to
one [no unambiguous neural correlates of
learning difficulties, styles]
2. Surrogate measures of brain activation
[activation models may be incomplete ]
3. Individual differences in brain structure –
function [activation maps are statistical]
4. The brain is structurally very complex; brain
function is nonlinear [ it’s a tough problem]
Positron Emission Tomography (PET)
PET images
metabolism in active
areas of the brain using
emissions of a
radioactive tracer
(oxygen in glucose) in
the blood.
Posner & Raichle, 1994
Fischbach, Scientific American, 1992, courtesy M. Raichle
all of which we do simultaneously and in synchrony
EEG measures electrical activity of active areas of the brain
using multiple electrodes placed over the scalp
Quik-Cap, NeuroMedical Supplies
Event-related potentials (ERP)
ERP data consist of changes in the EEG in response to experimental
stimuli.
The waveforms of interest typically occur 100, 300 or 400 milliseconds after
the stimulus onset. In other words, ERP data is temporally sensitive.
However, as the extra-scalp electrical field is a result of widespread neural
activity, the technique is insensitive to spatial correlates.
MEG
Aston University neuroimaging lab
The tiny magnetic fields produced
by brain activity can be measured
using Superconducting Quantum
Interference Devices or SQUIDs
The SQUIDs
operate at
superconducting
temperatures. The
sensors are
therefore placed in a
dewar containing
liquid helium.
CTF 151 channel system
The first half-second of visual word recognition
Morten Kringelbach in collaboration with Kristen Pammer, Peter Hansen, Piers Cornelissen, Gareth
Barnes, Krish Singh & Arjan Hillebrand, Neuroimage, (2004).
Ecological validity: inside a scanner vs. inside a classroom
FMRIB Centre, Oxford
Functional magnetic resonance imaging (fMRI) images blood oxygen level changes in
active areas of the brain using the interaction of pulsed (RF) resonant energy with a very
strong magnetic field (3.0 T)
MRI creates structural brain images
Insert time fmri series
Foetal brain growth
(ADR high)
(ADR lowest)
The red areas are statistical
mountain peaks (histograms)
Z = 2.3
Experimental areas of interest
found by contrasting criterion
with control activations
BOLD signal vs stimulus change in one active
voxel
fMRI data are mostly group averages
MRI - sagittal orientation ~ 2-3mm off the midline left hemisphere
fMRI - individual activation vs group map
interpretation
When a brain ‘lights up’ in response to a task X ...
... a statistical map (coloured histogram, z > 2.3) on an ideal
brain image (computer generated)
of a group average (N = 12 – 15) of right-handed subjects (not
too old, not too young, not too big, not myopic, not pregnant, not
claustrophobic, no metal, no pacemaker ...)
doing multiple X (variations or repeats > 40 times )
differential activation (X vs control task, X – control task)
measured by BOLD (blood oxygen level dependent) signal (%
reduction in deoxygenated haemoglobin concentration) from
(assumed) neurally-induced local increased blood flow due to
enhanced vasculature dilation
in contiguous clusters of most (?) (but not all of) the voxels (1 - 3
mm3) of brain tissue (2.5 – 7 x 106 neurons) where the majority of
neurons are active (excitatory and/or inhibitory)
assumed to be associated with task X.
Cognitive neuroscience as bootstrapping
There is no
Users’ Manual of the Brain
The mapping problem
Relationships between
brain functional modularity
and
cognitive behavioural
categories
are not one to one
Abandonment of old phrenology
To suppose the roof-brain consists of point to
point centres identified each with a particular item
of intelligent concrete behaviour is a scheme over
simplified and to be abandoned.
Rather, the contributions which the roof-brain …
makes toward integrated behaviour will … resolve
into components for which we at present have no
names.
Sir Charles Sherrington, Man on His Nature,1938
fMRI of subtraction - interconnectivity
Dehaene & Naccache, Cognition, 2001
Dehaene, 1997
Common brain functions for all acts of
intelligence: NB school learning
• Working memory <= lateral
frontal cortex
• Long term memory <=
hippocampus + …
• Decision making <=
orbitofrontal cortex
• Emotional mediation <= limbic
subcortex + ofc
• Sequencing of symbolic
representation <= fusiform
gyrus + temporal lobe
• Conceptual inter-relationships
<= parietal lobe
• Conceptual rehearsal <=
cerebellum
Diffusion Weighted MRI
or Diffusion Tensor Imaging (DTI)
Diffusion Weighted MRI or Diffusion Tensor Imaging (DTI) is an MRI technique in
which the directions of movement of water in white matter tracts are compared.
Significant directional biases (fractional anisotropy) are indicative of a more
robust interconnectivity of those tracts.
Fibre connectivity from Diffusion Weighted MRI
Function is determined by
input and output connectivity
Connectivity maps of grey matter in
pre-motor and motor cortex
Johansen-Berg & Behrens,
FMRIB Oxford
Can neural cartography inform us about
mathematical thinking in schools?
The functional
modularity of brain
organisation predicts
that where necessary
connections are not
robust, there will be
breakdowns in
mathematical
understanding.
Correlation vs Causation
Most neuroimaging data (fMRI) inform correlations between levels of
neural activation and behaviour.
Opportunistic neuropsychological analyses of neural lesions or trauma
inform necessity conjectures of causation.
But, the location and extent of lesions is obviously uncontrolled, and due
to the distribution of major vasculature tracts, spare some areas of brain
more than others.
And, functional interconnectivity and plasticity in recovery can limit
interpretation of lesion data.
Transcranial Magnetic Stimulation (TMS)
TMS temporarily disables a small area of brain to test its
necessity for an aspect of behaviour.
TMS + fMRI => interconnectivity
Mapping causal interregional influences with concurrent TMS–fMRI. Bestmann,
Ruff, Blankenburg, Weiskopf, Driver, Rothwell Exp Brain Res (2008) 191:383–
402
Neuromyths
Neuromytholgies of quantity:
“If we can get more of the brain to ‘light up’ then
learning will improve ...”
– using only 10 percent of our brains
– brain gym
Neuromytholgies of quality:
“If we concentrate teaching on the ‘lit-up’ brain areas
then learning will improve ...”
– left and right brain thinking
– VAK learning styles
AGCA 2009
Neuroscience and neuromythology
“We only use 10% of our brains”
Sources of the 10% myth
• Italian neuro-surgery removing scoops of brains
of psychiatric patients (1890)
• Einstein imploring us to think more (1920)
• American advertisers of home-help manuals
(1930)
• Wishful thinking educationists (1980 - 2000)
The absurdity of the 10% myth
Evolution does not produce excess, much less 90%
excess.
In the millions of neurological studies ever
conducted, no one has ever found an unused
portion of the brain!
Beyerstein, 2004
AGCA 2009
Neuroscience and neuromythology
“There is left- and right-brain thinking, and
left- and right-brained people”
Kolb & Wishaw, 1996
Semantic system is left lateralised
language = left hemisphere
graphic & emotional = right
hemisphere
“A significant quantitative
bias found in the brains of
extremely right-handed
subjects.”
“It is dangerous to suppose
that language processing
only occurs in the left
hemisphere of all people.”
Thierry, Giraud & Price, Neuron, 2003
AGCA 2009
Neuroscience and neuromythology
“There are individual sensory learning
styles: visual, auditory, kinaesthetic”
Brain interconnectivity includes the senses
• All primates are
VAK
– including humans
• All primates construct spatial maps
– including blind humans!
Visual-auditory cross-modal binding
reinforcing = additive
interfering = subtractive
5 year olds can reliably distinguish different sized groups (V x V)
vs
?
5 year olds can reliably distinguish different sized groups (V x V)
vs
?
What happens when one group is replaced by as many sounds (V x A)?
vs
?
5 year olds can reliably distinguish different sized groups (V x V)
vs
?
What happens when one group is replaced by as many sounds (V x A)?
vs
No change in accuracy!
?
VAK not learning styles but pre-learning
perceptual acuities
• Input modalities in the brain are inter-linked
visual
auditory
visual
motor
motor
auditory
visual
taste
• Input information is abstracted to be processed
and learnt, mostly unconsciously, through the
brain’s interconnectivity
VAK classroom paradoxes
• The V and K ‘learners’ at a concert
• The A and K ‘learners’ at an art gallery
• The V and A ‘learners’ in a craft practical lesson
VAK research
• 121 different learning style inventories
• Commercially available
• Independent research: no learning benefit from any
• No improvement of learning outcomes with V, A, K
above teacher enthusiasm
“attempts to focus on learning styles were wasted effort” Kratzig & Arbuthnott (2006)
Why do VAK and other ‘learning-styles’
seem so attractive?
• folk psychology: we seem to learn differently from
each other, and we have 5 senses …
… has created
• folk neuroscience: the working of our brains directly
reflects our folk psychology …
… BUT …
• … if our brains were that simple we wouldn’t be here
today!
Visual ‘learners’ convert words to pictures in the
brain, and vice versa
Picture problem
Self-rated visual
‘learners’
Self-rated verbal
‘learners’
Word problem
Fusiform gyrus
Supra-marginal
gyrus
Kraemer et al, 2009, University Pennsylvania
AGCA 2009
Neuroscience and neuromythology
“There are multiple intelligences”
Nothing new here ...
•
•
•
•
•
•
•
Plato (500 BC)
logic
rhetoric
arithmetic
geometry-astronomy
music
dance-physical
meditation
•
•
•
•
•
•
•
Gardner (1980 AD)
logic-mathematics
verbal
interpersonal
spatial
music
movement
intrapersonal
Nothing new here ...
•
•
•
•
•
•
•
Plato (500 BC)
logic
rhetoric
arithmetic
geometry-astronomy
music
dance-physical
meditation
•
•
•
•
•
•
•
Gardner (1980 AD)
logic-mathematics
verbal
interpersonal
spatial
music
movement
intrapersonal
Common brain functions for all acts of
intelligence: NB school learning
• Working memory <= lateral
frontal cortex
• Long term memory <=
hippocampus + …
• Decision making <=
orbitofrontal cortex
• Emotional mediation <= limbic
subcortex + ofc
• Sequencing of symbolic
representation <= fusiform
gyrus + temporal lobe
• Conceptual inter-relationships
<= parietal lobe
• Conceptual rehearsal <=
cerebellum
AGCA 2009
Neuroscience and neuromythology
“There are structural and functional
differences between male and female
brains”
Sex differences in neurogenesis
Differing relative concentrations of
testosterone and oestrogen as neurotaxic
agents produce sex differences in
neuroanatomy
e.g. females - larger corpus callosum
males - denser parietal areas
Males – larger parietal areas
Females - larger corpus callosum
Sex-linked preferences
for processing different
types of information
Posner & Raichle, 1994
Each brain has a unique configuration of
gyri and sulci
• Secondary and tertiary
sulci are not found in all
individuals.
• In addition, the sulci can
have very different
configurations.
• Cortical structures are
individual, like fingerprints.
Rorden & Brett, MRC Brain and Cognition Unit
Cambridge, UK, 2005
AGCA 2009
Neuroscience and neuromythology
“There are specific physical activities which
cause enhanced activation of specific
brain functions”
Close
Brain vasculature is bilateral and fractal
Exercise that increases
blood flow anywhere,
increases blood flow
everywhere.
If anyone approaches your school with an
offer of a ‘brain-based’ learning programme,
ask them which neuroscience laboratory
they are associated with.
(You don’t necessarily want a brain scientist, but
you do need someone who understands brain
science, and the best way to understand brain
science is to work with brain scientists.)
Australian Guidance Counsellors Association Annual Conference
Hobart, April 2009
Educational neuroscience:
curriculum sequencing
Does abstract mathematical thinking develop from
concrete mathematical thinking?
Provocative answer: NO!
The watershed of fractions
The important analogies for understanding fractions are initially between
abstract quantity ratios, not blocks of chocolate.
Hence the dissociation between concrete and abstract performance, e.g.,
street sellers.
The converse dissociation of kids who get the abstract but not the
concrete is probably very rare since making post hoc analogies with
concrete examples would be easy once you have the abstract.
Neural representations of abstract symbols
The function of a specific subregion of the left fusiform gyrus
(LFG) is the detection of generic
symbolic sequences.
Contrast with the function of
specific sub-regions of the right
fusiform gyrus (RFG) to detect
faces, and familiar objects.
Australian Guidance Counsellors Association Annual Conference
Hobart, April 2009
Educational neuroscience:
executive attention
Complex reasoning in Euclidean geometric proof
Kao & Anderson, IES, 2006
15 adults, fMRI, 2 x 3 factorial design
Complex reasoning in Euclidean geometric proof
Kao & Anderson, IES, 2006
The critical process to understand appears to be how proficient problem-solvers
integrate problem givens and diagram information to support their logical inferences,
and how this process differs in experts, proficient problem solvers, and novices
Australian Guidance Counsellors Association Annual Conference
Hobart, April 2009
Educational neuroscience:
pedagogy
Intraparietal cortex as a potential substrate for a
number sense
Eger et al, Neuron, 2003
In an event-related fMRI study, we presented numbers,
letters, and colours in the visual and auditory modality,
asking subjects to respond to target items within each
category.
In the absence of explicit magnitude processing, numbers
compared with letters and colours across modalities
activated a bilateral region in the horizontal intraparietal
sulcus.
This stimulus-driven number-specific intraparietal response
supports the idea of a supramodal number representation
that is automatically accessed by presentation of numbers
and may code magnitude information.
Why the parietal cortex for magnitude AND
visualisation?
Path integration in mammals and its interaction with visual landmarks
Etienne, Maurer and Seguinot, Journal of Experimental Biology, 1996
During locomotion, mammals update their position with respect to a fixed point of reference, such as their
point of departure, by processing inertial cues, proprioceptive feedback and stored motor commands generated
during locomotion. This so-called path integration system (dead reckoning) allows the animal to return to its
home, or to a familiar feeding place, even when external cues are absent or novel.
However, without the use of external cues, the path integration process leads to rapid accumulation of errors
involving both the direction and distance of the goal. Therefore, even nocturnal species such as hamsters and
mice rely more on previously learned visual references than on the path integration system when the two types
of information are in conflict. Recent studies investigate the extent to which path integration and familiar
visual cues cooperate to optimize the navigational performance.
Why the parietal cortex for magnitude AND
visualisation?
Parietal cortex evolved to help us find our way home
Whole-body propriocentrism
Geometry and trigonometry in the real world
Classroom application: LOGO Turtle!
Australian Guidance Counsellors Association Annual Conference
Hobart, April 2009
Educational neuroscience:
assessment
Nuclear Magnetic Resonance MObile Universal Surface Explorer
NMR-MOUSE
Wearable (near) optical topography headsets
Chinese dyslexia: differences in brain structure
and function
Wai Ting Siok , Zhendong Niu , Zhen Jin , Charles A. Perfetti, and Li Hai Tan, 2008
Conclusion: structural and
functional basis for
dyslexia varies between
alphabetic and
nonalphabetic languages.
Australian Guidance Counsellors Association Annual Conference
Hobart, April 2009
Educational neuroscience:
interdisciplinary engagement
Importance of involving educators in
helping set the educational neuroscience
research agenda
• Is there a critical period for learning a second
language? Music? Physics?
• Should boys and girls be taught separately in some
subjects?
• Are the brains of children today different from those
of previous eras due to high levels of IT usage?
• Are there any predictive correlations between
differences in brain structure and school outcomes?
Establishment of a methodology for educational
neuroscience
–
–
–
–
education problem …
science research question …
science finding
…
education implication / application
Professional Development in Educational Neuroscience
Gloucestershire Advanced Skills Teachers
Institute for the Future of the Mind,
21st Century School, University of Oxford
McGraw-Hill / Open University Press, 2009
References: academic articles
Byrnes, JP & Fox, NA (1998) The educational relevance of research in cognitive neuroscience, Educational Psychology
Review, 10(3), 297-342 (and following commentaries to p412).
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004).. Learning styles and pedagogy in post-16 learning: A
systematic and critical review (Report No. 041543). London: Learning and Skills Research Centre.
Geake, JG (2004) Cognitive neuroscience and education: two-way traffic or one-way street? Westminster Studies in
Education, 27(1), 87-98.
Geake, JG (2005) Educational neuroscience and neuroscientific education: In search of a mutual middle way. Research
Intelligence, 92, 10-13.
Geake, JG & Cooper, PW (2003) Implications of cognitive neuroscience for education. Westminster Studies in
Education, 26(10), 7-20.
Goswami, U (2004) Neuroscience and education. British Journal of Educational Psychology, 74, 1-14.
Goswami, U (2006) Neuroscience and education: from research to practice? Nature Reviews Neuroscience, 7, 406-413
Gura, T (2005) Big plans for little brains. Nature, 435, 1156-1158.
Kratzig, G.P. & Arbuthnott, K.D. (2006) Perceptual learning style and learning proficiency: A test of the hypothesis,
Journal of Educational Psychology, 98(1), p238-246.
OECD (2002) Understanding The Brain: Towards a New Learning Science.
OECD (2007) Understanding The Brain: Birth of a Learning Science.
Sharp, JG, Byrne, J & Bowker, R. (2007) VAK or VAK-uous? Lessons in the trivialisation of learning and the death of
scholarship. Research Papers in Education (in press)
Kayser, C. (2007) Listening with Your Eyes. Scientific American Mind, April.
References: for teachers
Beyerstein, BL (2004) Ask the Experts: Do we really use only 10% of our brains? Scientific American,
290(6), 86.
Blakemore, S-J & Frith, U (2005) The Learning Brain: Lessons for Education, Blackwell Publishing.
British Neuroscience Association & European Dana Alliance For The Brain (2003) Neuroscience:
Science of the Brain: An Introduction for Young Students. Liverpool, BNA.
Byrnes, JP (2001) Minds, Brains, and Learning: Understanding the Psychological and Educational
Relevance of Neuroscientific Research, Guilford Press.
Geake, JG (2000) Knock down the fences: Implications of brain science for education. Principal
Matters, April, 41-43.
Geake, JG (2003) Adapting Middle Level educational practices to current research on brain
functioning. Journal of the New England League of Middle Schools, 15(2), 6-12.
Geake, JG (2004) How Children’s Brains Think: Not left or right but both together. Education 3-13,
32(3), 65-72.
Geake, JG (2006) The neurological basis of intelligence: A contrast with 'brain-based' education.
Education-Line, www.leeds.ac.uk/educol/documents/156074.htm.
Geake, JG (2007) A Brainy School Of The Future? Learning Matters (in press)
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