LEAP®: The Learning Enhancement Acupressure Program: Correcting
Learning and Memory Problems with Acupressure and Kinesiology.
By Dr. Charles T. Krebs
Melbourne Applied Physiology, Pty Ltd
P.O. Box 173, Learmonth, Victoria
Australia 3352

ABSTRACT:The Learning Enhancement Acupressure Program, or LEAP®, has been developed since 1985 inconjunction with clinical psychologists, speech pathologists, neurologists and other healthprofessionals, as a very effective program for the correction of most learning difficulties. LEAP® isbased on a new model of learning integrating recent concepts in neurophysiology of the brain anduses highly specific acupressure formatting to address stress within specific brain structures. The
application of specific non-invasive acupressure and other energetic techniques can then resolvethese stresses resulting in a return to normal function.
In the LEAP® model of learning Gestalt and Logic functions are not simply localised in the rightor left cerebral hemisphere as in the popular Right Brain/Left Brain model of learning. But rather,each type of conscious brain function or process appears to have a cerebral "lead" function that iseither predominantly Gestalt (Visuo-spatial, Global) or Logic (Linear, Sequential) in nature. These
cortical “lead” functions provide a “point of entry” into a widely distributed system comprising
many subconscious cortical sub-modules in both hemispheres and many subconscious subcorticalmodules throughout the limbic system and brainstem.
While the Gestalt and Logic “lead” functions are conscious, these functions are dependent upon
many levels of subconscious sensory processing at many levels within the nervous system. While
this processing through multiplexing and parallel processing at many different levels is highly
efficient, it means that brain processing is “time bound”. Since many components of any mental
function are performed in many different parts of the brain, and often at different speeds, coherent
output in the form of “thinking” requires integration and synchronisation of all of these separate
processes.
Loss of integrated brain function, termed loss of Brain Integration in LEAP®, thus results in theloss of a specific mental capacity, the ability to perform a specific type of mental task. When these
specific mental capacities are required for academic performance, their loss can result in SpecificLearning Disabilities.
Specific Learning Disabilities (SLDs) arise in this model by either lack of access to specificsubconscious processing modules, either cortical or subcortical, or the de-synchronisation of neuralflows in the integrative pathways linking processing modules. Thus to resolve SLDs, you need only
“open up” access to the “blocked” processing modules or re-synchronise the timing of information
flow between them to re-instate integrated brain function.
The LEAP® program provides an integrated acupressure protocol using direct muscle biofeedback(kinesiology) as a tool to identify “stress” within specific brain nuclei and areas that have “blocked”
integrated function. The application of the LEAP® acupressure protocol using acupressure and otherenergetic based techniques to re-synchronise brain function resolves learning and memory problems
in a high percent of cases.
HISTORY OF SPECIFIC LEARNING DIFFICULTIES.
Difficulties with learning academic tasks such as reading, spelling and mathematics have beenrecognised for over a century, with Kussmaul in 1877 ascribed as the first person to specificallydescribe an inability to read, that persisted in the presence of intact sight and speech, as word
blindness.1 The word dyslexia was coined by Berlin in 1887.2 Within a decade a Glasgow eye
surgeon James Hinschelwood (1895) and a Seaford General Practitioner Pringle Morgan (1896)
observed students who were incapable of learning to read and hypothesised that this was based on a

failure of development of the relevant brain areas which were believed to be absent or abnormal.
This model was based on the assumption that developmental dyslexia (congenital dyslexia) was
similar in form to acquired dyslexia, which is dyslexia due to brain damage after a person has
already learned to read. Deficits in other types of learning, such as mathematics, would also result
from some other underlying brain damage or abnormality.3
Work in the early part of the twentieth century, particularly by Samuel T. Orton in the 1920s and1930s suggested that learning difficulties such as dyslexia were not based on anatomical absence orabnormality, but rather it was delay in the development of various areas that caused thesedysfunctions. This belief was largely ignored until the 1960s when it was revived by a growinginterest in neuropsychology. However, more recent developments in neuropsychology andneurophysiology support the hypothesis that dysfunctions within the brain, both anatomical anddevelopmental, may be causal in many learning problems.4
It was not until 1963, in an address given by Samuel Kirk, who argued for better descriptions ofchildren’s school problems that the term “learning disabilities” originated. Since that time there’s
been a proliferation of labels that attempt to dissociate the learning disabled from the retarded andbrain damaged.
Definitions
In the context of this synopsis, Specific Learning Disorders or Disabilities (SLDs) relates toproblems with physical co-ordination and acquiring the academic skills of reading, writing, spellingand mathematics including both Dyslexia and Attention Deficit Disorder (ADD) with or without
hyperactivity. ADD with hyperactivity is now commonly called Attention Deficit Hyperactivity
Disorder (ADHD) or hyperkinetic disorder in Europe. Historically, Dyslexia has been widely
defined in terms of deficits in the areas of reading, spelling and language. However, more recent
conceptualisations have included a definition that also encompasses a wide range of problems,
including clumsiness and difficulty with rote learning.5 Fawcett and Nicolson have also challenged
the prevailing hypothesis that Dyslexia is merely a language based problem, suggesting that it
might be a more generalised deficit in the acquisition of skills.6
The term Dyslexia is not defined in the DSM IV (1994) although it is still commonly used inliterature discussing various learning difficulties. The term Learning Disorders (DSM IV) currently
encompasses various types of learning difficulties including dyslexia and Attention Deficit
Disorder (ADD). Learning Disorders are defined in the DSM IV as being essentially a persistentpattern of inattention and/or hyperactivity-impulsivity that is more frequent and severe than is
typically observed in individuals at a comparable level of development. The performance of these
individuals on standardised tests for reading, mathematics, or written expression is substantiallybelow, more than 2 standard deviations (SDs), same age peers even though their IQ scores areaverage or above average.7
Incidence
Frequently, children diagnosed as learning disabled are also inattentive and deficient in linguistic
skills, most often in reading.8 Rutter and Yule examined a large population of children from anumber of different studies and found 3.5% of Isle of Wight 10-year-olds, 4.5% of 14-year-olds andover 6% of London 10-year-olds showed reading difficulties.9 Gaddes looked at the proportion ofchildren with learning disorders in various studies in both North America and Europe and foundthat the need for special training for learning disorders ranged between 10-15% of the school age
population.10 However, estimates of the prevalence of learning disorders for broad age ranges isproblematic because a learning disability is an emergent problem that is often not evident until later
years in schooling. Using the criteria of defining learning disorders as being two years behind on
standardised tests, less than 1% of 6-year-olds are disabled, 2% of 7-year-olds and so on until at age
19, 25% would be classified as learning disabled. So these children fall progressively behind as theymature and the complexity of work increases.11

In an address given by the Australian Federal Schools Minister, Dr David Kemp, in October
1996, Kemp stated that a study of 28,000 students in four surveys in Australia found 30% of year 9
students lacked basic literacy skills. This high incidence of learning disorders in school children
indicates a need for effective treatment. Studies in other countries, both English, French andGerman support these figures, so specific learning difficulties, which cover all types of learning
disabilities from dyslexia, reading problems, ADD to ADHD, probably represent greater than 15%
of school-aged children, and may be as high as one third of all school-aged children.
CausesCurrently hypotheses concerning learning disorders suggest that they are primarily the result of
one or more of five major factors; 1) structural damage, 2) brain dysfunction, 3) abnormal cerebral
lateralisation, 4) maturational lag and 5) environment deprivation. While none of these theories isunequivocally supported by current data, all of these factors may contribute in varying degrees tolearning disabilities.12
Brain damage and overt brain dysfunction would appear to account for a relatively small
percentage of children with learning disorders. The great majority of other children with learning
disorders do not typically show many of the neurological symptoms associated with brain damage
in adults. For instance, EEG and CT studies have not shown structural damage and abnormal EEGs
correlated with known brain damage are not consistently observed in children with learning
disorders.13 Rather than direct brain damage, there is evidence that abnormal physiological orbiochemical processes may be responsible for malfunction in some part of the cerebral cortex.
Electrophysiological recording studies have associated specific high frequency EEG and AEP(averaged evoked potentials) abnormalities with various types of learning disorders.14 Recent
studies with SSVEP (Steady state visual evoked potential) have shown that children diagnosed with
Attention Deficit Disorder demonstrate similar abnormal SSVEP patterns when compared to normal
subjects while performing the same cognitive task.15 The brain dysfunction hypothesis suggests thatthe dysfunction may be a consequence of defective arousal mechanisms resulting in some form of
inadequate cerebral activation.16
This is supported by studies of children with learning disorders that show they have difficulty on
continuous performance tests requiring attention and low distractibility; had slower reaction times
to stimuli, and increased errors due to impulsivity on tests of visual searching.17 Douglas proposedthat the deficits on these tasks resulted from inadequate cerebral activation. Learning disorders ofsome types at least, do improve with drugs like amphetamines that cause cerebral activation via
increasing subcortical arousal. In fact this is the basis of treating hyperactive children with
Ritalin.18
An alternative model of learning disorders is based on recent neurophysiological findings thatsuggest it is the timing and synchronisation of neural activity in separate brain areas that createshigh order cognitive functions. Any loss or malfunction of the timing mechanism may cause
disintegration of neural activity and hence dysfunction in cognitive tasks.19 Clearly, brain
dysfunction due to inadequate cerebral activation may indeed lead to disruption of the timing andsynchronisation of neural flows, and thus these two hypotheses may just be different aspects of thesame process.
This model supports the approach in the Learning Enhancement Advanced Program (LEAP®)
that Dr. Krebs developed in the late 1980s early 1990s.20 In the LEAP® Model, Specific Learning
Disorders are based on the disruption or loss of timing and synchronisation between the neuralactivity in the diverse brain regions, both cortical and subcortical, that must be synchronised inorder for successful integration to produce normal cognitive activity. Learning disorders would
arise in this model from a lack of integration of functions that occur simultaneously in separate
brain regions.
If the brain does integrate separate processes into meaningful combinations we call ‘thought’ or
cognitive ability, then the main risk is mis-timing or loss of synchronisation between theseprocesses. To quote Damasio “any malfunction of the timing mechanism would be likely to create
spurious integration or disintegration”.21 For synchronous firing of neurons in many separate brain
areas to create cognitive functions would require maintenance of focused activity at these different
sites long enough for meaningful integration of disparate information and decisions to be made.
®

THE LEAP MODEL OF LEARNING:
From a review of the major brain structures and the workings of learning and memory in theneurological literature, it is clear that both memory and learning do not involve a single, global
hierarchical system in the brain. But rather, learning involves interplay between many inter-linked
sub-systems or modules.22 Also, the timing and synchronisation of information flow between thesesub-systems and modules appears to be critical to the success of learning and coherent cognitive
function.
However, the sub-systems or modules underlying both learning and memory are both consciousand subconscious with most of the early leveling processing being totally subconscious, and only
the highest levels of neural processing reaching consciousness. Yet, it is indeed these conscious
modules that initiate and direct the processing to be done by the subconscious modules, as bothlearning and memory require “conscious” effort to occur. This means that the memory and learning
processes can be disrupted at both the conscious and subconscious levels, depending upon which
neural substrates or integrative pathways are disrupted.
Sensory processing of all types is initially a relatively linear chain of neural impulses originatingfrom a generator potential of the sensory receptor, and following a chain of neurons into the Central
Nervous System (CNS) and brain. However, this initially linear stream of nerve impulses, the dataof the CNS, rapidly becomes divergent and multiplexed at higher levels of cortical processing.
Conscious perception only arises at the highest levels of these multiplexed data flows as they are reintegrated back into unified conscious perception by the cortical columns directing all conscious
brain activity.
Thinking and other cognitive abilities rely upon all of the proceeding levels of subconscious
sensory processing, which are predominately bilateral initially, but which become progressively
asymmetrical and lateralised with increasing levels of conscious awareness. Sensory information isprocessed initially as neural flows of increasing complexity that generate preverbal images andsymbols, but becomes increasingly defined by language in higher level cognitive processes. And
language by its very nature is based upon abstract representations of external reality (called words),
that follow linear rules (grammar), and word order linked to meaning (syntax). Hence it ispredominately sequential and linear in form, which permits analytical evaluation of the thoughts
generated following rational rules of Logic. From the perspective of Logic, the world is interpreted
as parts that can be constructed into a whole via deductive reasoning.
Sensory and other mental data not suitable for language-based rational processing is processed
via visuo-spatial image and symbols that permit global, holistic comprehension of the whole and isinherently non-rational.23 This global, simultaneous, non-rational visuo-spatial processing has beentermed Gestalt (German for pattern or form), with the meaning of the whole extracted via inductive
reasoning. From the Gestalt perspective, the world is seen as a “whole” with intuitive understandingof the properties of the whole. There is no rational analysis of “Why?”, it just “Is”.
In the LEAP® Model of Learning, it is recognized that most of the lower level linear sensory
processing occurs below conscious perception, that is either subcortical, being processed in thebrainstem or other brain nuclei like the hypothalamus, thalamus, basal ganglia, etc., or ispalaeocortical and limbic. Even the basal levels of cortical processing are largely bilateral andsubconscious, and thus occur outside of conscious perception. All higher level cortical processing,which may become conscious, is thus reliant upon maintenance of integrated function and neuralflows at these subconscious levels.

However, the more overtly cognitive components of learning rapidly become lateralised withprocessing dominated by activation of cortical columns, the functional units of the neocortex, in one
hemisphere of the brain or the other. In right-handed people, Logic processing typically activates
cortical columns in the left hemisphere, that then process the data in a linear analytical way, while
activation of cortical columns in the right hemisphere process data in a Gestalt, visuo-spatial way.
Thus, at the highest levels of conscious neural processing underlying cognition and thought,
whether that “thought” be verbally based language of Logic, or global intuitively based “knowing”
of Gestalt, the neural processing is highly lateralised and is predominately processed in the right orleft hemisphere.
The neural substrates for all “conscious” functions therefore are cortical columns of the
neocortex (Fig. 1). Conscious activation of a cortical column acts to initiate a cascade of neuralflows that rapidly spread to other cortical areas both conscious and subconscious in bothhemispheres, and also into many subcortical structures as well. These consciously activated corticalcolumns initiate either Gestalt or Logic functions depending in which hemisphere they are located.
In LEAP® we term cortical columns activating Logic functions, Logic “lead” functions, and those
activating Gestalt functions, Gestalt “lead” functions. These “lead” functions provide points of entry
into an inter-linked set of cortical and subcortical modules that then perform our mental functions.

CorticalColumnSix Layers of
the Cerebral
CortexInterneuron
Pyramidal Neuron

Axons entering
white matter

Figure 1. Cortical Columns. Vertical slabs of cortex consisting of all six distinct cell layers,
called cortical columns, are the functional units of the cerebral cortex. Some of the cells like thelarge pyramidal cells have dendrites that extend through almost all layers and axons that exit thegray matter to become part of the white matter tracts carrying information to other parts of thebrain and body. There are also innumerable interneurons connecting the cells within each cell
layer and between the layers.
Indeed, it was a misunderstanding about the nature of these “lead” functions from which the
popular “Right Brain – Left Brain” model of learning and brain function arose. Because damage to
specific cortical columns caused loss of specific conscious functions, e.g. the ability to form an
image, or figure out certain types of problems or solve certain types of puzzles, it was assumed thatthe damaged area actually did that specific function. In reality, all that cortical column did wasprovide a point of entry into these inter-linked sets of cortical and subcortical modules that actually
performed the function lost because of the damage to the cortical “lead” function.
An analogy would be damage to the “K” key on your keyboard. Your consciousness is still intact
and able to initiate “K” questions, and your computer system is still able to process and answer “K”
questions, but the interface to initiate “K” processing in the computer has been damaged. Like
wise, if a Gestalt “lead” function is damaged, the process initiated by this “lead” function no longer
activates the inter-linked cortical and subcortical functions that are required for this process tooccur. Thus, while damage to the area initiating a function, “blocks” the rest of the processing
needed to perform the function, the area initiating function never actually ever “did” the function in
the first place. To continue this analogy, in most cases it is not overt “damage” to the cortical “lead”
function or subcortical brain areas that prevents effective thinking, but rather “blocked” access tothese brain areas due to some stressor that is the problem. Thus, much in the same way a “sticky”
key blocks fluent typing, “blocked access” to specific brain areas blocks effective thinking andproblem-solving.
Synopsis of the LEAP® Model of Learning:
In summary, the LEAP® Model of Learning is based on the following suppositions about thenature and location of neural processing underlying learning and memory:•

Sensory processing initiated by sensory receptors generates initially linear neural flowsthat rapidly diverge at each successive processing centre (spinal and cranial nerve
ganglia, brainstem nuclei, subcortical nuclei, limbic cortices, and finally neocorticalcolumns) into a number of different complex data streams. All processing below the
neocortex is subconscious.

•

Each processing centre, at each successive level within the spinal cord, brainstem,
diencephalon, basal forebrain and cortex elaborates the sensory data, defining some
aspect more than another, or adds additional types of information needed to define thesensory data further at the next level of processing. All processing below the neocortex is
subconscious.

•

At the higher cortical levels, input from many lower levels both cortical and subcortical isintegrated to form a conscious perception of the initial sensory experience.

•

These higher cortical levels not only integrate processing of the “raw” sensory data, butalso include integration of input from memory areas about past experiences with similarsensory stimuli.

•

At the highest cortical levels the conscious perceptions formed at lower cortical levels arefurther processed asymmetrically in either Gestalt or Logic cortical columns, and hence
perceived as a visuos-patial pattern or a Gestalt, or abstractly as a verbal word based
language or an abstract symbol based mathematical language.

•

The very highest levels of conscious processing that underlie our thinking about
conscious perceptions, while dependent upon input from all areas of the brain, aregenerally frontal lobe and particularly involve working memory areas in the Dorsolateral
Frontal Cortex.

•

A whole set of basal brainstem mechanisms maintain the organism in a state ofhomeostasis, such that higher level conscious sensory processing can proceed effectively:
These include the Reticular Activating System, the Periventricular Survival System, theVestibular System and the Sensory-Motor System. Imbalances within or between thesesystems may disrupt on-going sensory processing and integration at this and higher
levels. Processing at this level is totally subconscious.

•

The initial “raw” data stream is “sampled” by the Amygdala and other survival centres inthe brainstem, and coloured by the survival emotions paired or associated with thesensory stimuli being analyzed, including the physiological responses to these emotions,and is the basis of Conditioned Learning. These primary survival emotions may disrupt
on-going sensory processing and integration at this and higher levels. Processing at thislevel is subconscious.
•

When survival emotions of the Fight or Flight response are activated above some“threshold” value, the amygdala and other brainstem structures such as thePeriaqueductal Grey Matter of the midbrain inhibit frontal cortical processing, interferingwith reasoning and problem-solving. The cause of this loss of higher level conscious
cortical processing is a direct consequence of activation of the subconscious primarysurvival emotions of the Limbic System and Brainstem.

•

Secondary processing of the sensory stimuli in the Brainstem, Limbic System and lower
cortical levels generates a series of control functions defining the nature of the sensory
data stream (e.g. control of pupils in vision) and second-order integration of this sensory
data (e.g. movement, shape and location of object in space). Processing at this level issubconscious.

•

Further processing in the palaecortical components of the Limbic System (e.g.
hippocampus, cingulate, subcallosal and orbitofrontal cortices) generates secondary
emotions relative to the sensory data stream and primary emotions already supplied by
the amygdala and other brainstem areas via sampling memory of related events. These
secondary limbic emotions may disrupt on-going sensory processing and integration at
this and higher levels. Processing at this level is largely subconscious.

•

Initial cortical processing is predominately bilateral and subconscious, and is dependent
upon earlier processing at brainstem and subcortical levels. Emotions, either primary or
secondary, may disrupt on-going sensory processing and integration at this and higher
levels.

•At some level of cortical processing the sensory data stream emerges into a conscious
perception, and is dependent upon earlier processing at brainstem, subcortical, and earlier
cortical levels. Emotions, either primary or secondary, may disrupt on-going integration
at this and higher levels•

At the highest levels of cortical processing, the processing is largely done in one
hemisphere or the other and perceived consciously as a logical, rational thought or avisuospatial Gestalt, and is dependent upon earlier processing at brainstem, subcorticaland cortical levels. Emotions, either primary or secondary, may disrupt on-going
integration at this level, and any “thinking” dependent upon this level of processing.

•Thinking about the fully processed and integrated sensory experience in the frontal lobes,
based upon remembered sensory experiences relevant to the current experience may leadto decisions, which will be represented neurologically by activation of either Logic orGestalt “lead” functions or both.

•

These “lead” functions will then initiate a cascade of neurological flow, which is initiallyfrontal cortical, but rapidly flows into other cortical areas and subcortical structures likethe basal ganglia, thalamus, and cerebellum, which in turn feedback to the cortex andeach other. Emotions, either primary or secondary, may disrupt on-going processing andintegration at any level of this process, and thus overtly affect the final outcome of thecognitive functions taking place.

•

Coherent neurological processing at any stage of the above process is dependent upon
both uninterrupted flows along integrative pathways and within integrative processing
centres. Disruption or de-synchronisation of the timing of these integrative neural flows
or disruption or de-synchronisation of processing in any of the integrative centres may
result in loss of cognitive function.

•

Maintaining integration along all integrative pathways and within all integrative centres
produces optimum function, a state called Brain Integration in LEAP.

•

Loss of integrated brain function is the principal cause of dysfunction in both mental andphysical performance, called Loss of Brain Integration in LEAP.

•

The primary mechanism causing Loss of Brain Integration is de-synchronisation and lossof timing of neural flows along integrative pathways and within integrative centres by
inhibition or excitation of these pathways and centres by neural flows originating frombrainstem and limbic survival related emotions.

•

On-going Loss of Brain Integration is often generated by early childhood trauma thatcreates long-term disruption of Brain Integration as a mechanism of coping.

•

Other factors affecting Brain Integration are genetic, structural, organic brain damage,and environmental stressors:o Structural defects or abnormalities can be of developmental origin, e.g. neuronalmigration problems, or result from toxin exposure at specific critical periods ofdevelopment, e.g. fetal alcohol syndrome. Many cognitive defects have beenshown to correlate with abnormalities in brain structure.24o Organic Brain Damage may result from a head injury, and this damage often
results in sclerosis that disrupts neural flows underlying Brain Integration (e.g.
hippocampal sclerosis and subsequent epilepsy are often associated with learning
disorders).
o Genetic Factors affecting Brain Integration are often genes that code for specificalleles for specific enzymes involved in maintaining normal levels ofneurotransmitters or receptors in brain circuits.25 Deficiencies in either
neurotransmitters or receptors will compromise Brain Integration, and have
behavioural consequences. This is both the basis of much ADHD behaviour andthe justification for drug use to ameliorate these behaviours.26
Other genes may code for alleles that affect fatty acid metabolism and utilisation,
especially in maintaining neuronal membrane stability and function. This affects
predominately physical co-ordination and reading.27
o Diet and nutritional deficiencies may also compromise brain function and result inloss of Brain Integration. Diets rich in fast or junk foods often create marginal
nutritional deficiencies that may disrupt brain function, and often contain various
preservatives and additives, like the azo-food dye tartrazine, that may cause a
total loss of brain integration in sensitive individuals28.
Indeed, the misbehaviour and academic performance of children and young adults
have been shown to improve significantly with diet change or nutritional
supplementation29, and several recent books have discussed this aspect of
behaviour and learning problems30.
o Environmental factors such as electromagnetic fields emitted from man-madeelectronic equipment and Geopathic stress from distortions in the earth’s
electromagnetic fields may affect the brain integration of sensitive individuals andresult in learning problems. 31

Loss of Brain Integration and Compensation
When Brain Integration is lost via disruption of the most efficient neural pathways and/or
centres, either by organic damage or by functional inhibition of cortical or subcortical functions due
to outputs from survival centres in the brain, specific conscious functions dependent upon thisintegration is also disrupted. The overt loss of conscious function is, however, often far less than thedegree of interference with underlying functions might suggest because the brain is a master atcompensation and will automatically compensate for these disrupted flows by using other areas of
the brain, both conscious and subconscious to produce the most efficient processing possible.
Thus, even children with considerable organic brain damage will often establish compensatoryneurological patterns of activity to produce varying levels of function in spite of massive disruptionof neural pathways underlying normal function, e.g. children with cerebral palsy may learn to walkand talk. It is indeed this tremendous compensatory capacity of the brain that allows even highly
disintegrated brains to produce some degree of function, however, the level of dysfunction controls
the degree of compensation. Thus, the greater the degree of dysfunction present, the lesscompensation that is possible.
If the disruption of integrated function is at the more basal levels of integration, the ability tocompensate for the resulting dysfunction is much more limited than if the loss of integration is at ahigher level of processing because all higher levels of processing are dependent upon the quality ofthe data integrated at earlier levels of processing. For instance, while damage to an early componentof vision, say the retina or optic nerve totally disrupts sight, damage and hence loss of integration in
the V3 area of the occipital cortex may leave the image fully intact, but disrupt only colour vision.
When the highest levels of cortical integration are disrupted directly or lower level cortical or
subcortical functions underlying these higher cortical functions are disrupted, we may lose thecapacity to “think” in certain ways. For instance, we may maintain Gestalt creative abilities (e.g. begood at art and design), but lose the ability to perform even simple mathematics because of the lossof the ability to abstract (e.g. are hopeless at maths). Specific Learning Disorders result from theloss of integration in of higher-level cortical functions or lower-level subconscious cortical or
subcortical functions supporting these higher-level functions directly activated by consciousness.
Children and adults suffering Specific Learning Disorders usually know what they need to do,often even how to do it (e.g. I want to spell this word, so I need to sequence the letters andremember this sequence). But they just cannot activate the necessary subcortical and corticalprocessing to do what they know how and want to do consciously because of loss of integration atsome level of neural processing required to do this function. When this loss of Brain Integration
affects their ability to read, spell, write or do mathematics, it results in SLDs. However, they will
still attempt to perform these functions, but in some compensated way. For instance, a child thatcannot spell words correctly (that is, visually in English), still attempts to spell words, but usingphonetics to compensate for the “mind’s eye” image he/she cannot create.
Because the level at which the integration is disrupted is unknown to the consciousness andcompensation is largely subconscious and automatic, a person with Specific Learning Disorders isonly aware that some function is difficult or not possible to perform, but not why this is so. Mostoften Brain Integration is lost in subconscious functions that were never accessible to ourconsciousness in the first place.

SYNOPSIS OF THE RESULTS OF LEAP STUDIES TO DATE:
There have only been a few controlled studies of the effectiveness of LEAP to resolve learning
problems because funding for studies involving Energetic Medicine are very limited as for any“new” technique that is outside the current Paradigm. Below are the summary results of the LEAP
studies done to date. The first two of these are unpublished research done as part of a degree in
Psycho-physiology at Swinburne University, and the other is a fully controlled study of the effectsof the LEAP program on children with identified Specific Learning Difficulties (SLDs) from an
Israeli School for Children with SLDs. The results of the Israeli study are in preparation for
submission to the International Journal of Learning Disabilities.

Swinburne LEAP Studies:
Two studies were undertaken at Swinburne University: One was a study of the differences incortical processing, Digit Span and Reading Comprehension between adults with ADD and theother was a Controlled Study of the affects of application of the LEAP program to children who had
identified SLDs.
Swinburne Study 1: Effect of the Learning Enhancement Advanced Program (LEAP) on
Cortical Activity, Auditory Short-term Memory Performance and Reading Comprehension.
by Susan Mc Crossin, B App Sc (Hons), Swinburne University

Introduction:
Previous studies (Silberstein et al., 1995) had demonstrated that a recently developed sophisticatedtype of EEG, Steady State Visual Evoked Potential (SSVEP), was capable of generating maps ofcortical activity sensitive to cognitive processes. In SSVEP there are transient reductions in
amplitude that appear to index regional increases in cortical activity associated with theperformance of a cognitive task. Because it is possible to estimate the amplitude of the SSVEP
using as little as 1 to 5 seconds of recorded activity, this technique was chosen to investigatechanges in brain activity associated with attentional and decision-making cognitive tasks.
The Learning Enhancement Acupressure Program (LEAP) has been developed empirically since1985 and has been applied to the improvement of specific learning problems on several thousand
subjects with generally excellent results. The LEAP treatment employs a specific acupressure
protocol to improve brain functions (Krebs & McCrossin, 1994) that has been empiricallydemonstrated to reproducibly improve various learning dysfunctions including deficit Digit Spanability and poor reading comprehension.
Pre and post-testing of subjects undergoing the LEAP protocol with WISC-R has shown marked
improvement on all of the subtests (Paphazy, unpublished data). Improvement was consistently
seen even on visuo-spatial subtests like Block Design which had not previously been observed tochange over time, regardless of considerable periods of remedial treatment. Block design is often
considered to be a measure of innate intelligence as it tests spatial reasoning not affected byacquired verbal knowledge.
After LEAP treatment some subjects have shown an increase in the Block Design task from aprevious ranking in the 25th percentile of same aged children to the 75th percentile and changes to
as high as the 99.6 percentile have been recorded. Changes of equal magnitudes have been
observed on all subtests, for instance from the 1st to the 50th percentile ranking on the Digit Span
subtest.
In those cases where improvement was not observed or was marginal, either on several or on only aspecific subtest, neurological assessment demonstrated varying degrees of organic brain damage inalmost all cases (Dr. Graeme Jackson, personal communication). The damage observed varied from

developmental problems such as neuronal migration problems, temporal lobe epilepsy, hypoxic
damage resulting from birth difficulties or traumatic injury such as blows to the head.
In this study the five (5) adult subjects ranged in age from 18 to 44 years (mean 30, S.D. 10). No
subject had a history of epilepsy or any type of organic brain damage, both of which may be
associated with such deficit digit spans as an adult.
Although the SSVEP activity maps for both tasks, Attention Primed and Decision-making, varied indetail between subjects, similar patterns were observed for both types of tasks. Prior to the LEAP
treatment, all subjects showed predominately occipito-parietal lobe activity with little or no frontal
lobe activity during the decision-making task, characteristic of people with ADD. While thesepeople still made decisions, they were not made upon the basis of careful consideration of “cause
and effect”, but rather upon “impulsive” partial processing initiating a reaction to stimuli presented.
Following the LEAP treatment, there was now a very different pattern of areas of activation. All
subjects now showed increased bilateral activation of the frontal lobes, the areas involved inconscious higher-level rational evaluation of the data and the lowest levels of cortical activity in theoccipito-parietal lobes during decision-making. (Figure 1)
Figure 1. SSVEP Maps of typical subjects Before and After LEAP treatment. Degree of stippling
indicates degree of activity. Before treatment subjects with learning difficulties showed the mostactivity in the occipital lobes when performing attentional and decision-making tasks. After
treatment the cortical activity now switched to the frontal lobes on the same attentional anddecision-making tasks, the same areas active when normal subjects perform these tasks.

Before LEAP
Treatment

After LEAP
Treatment

Digit Span:
The Digit Span subtest of the WISC-R was used as a measure of short-term memory, retrieval anddistractibility (Horn, 1985; Reynolds & Kaufman, 1985). This subtest of the WISC-R is a measure of
the auditory short-term memory processing and freedom from distractibility, where a subject repeats averbally presented sequence of random numbers. The span or number of digits that can be accurately
reported varies with age, varying from 3 forwards and 0 backwards for a 4 year old to 6 forwards and 5
backwards of an average adult. Deficit digit span is when the subject recalls fewer digits forwards
and/or backwards than is average for their age (Horn, 1985; Reynolds & Kaufman, 1985).

The Forwards task requires predominately basal short-term memory functions of the hippocampus,
while the Backwards task requires the additional step in working memory of the frontal lobes tocreate an image which is then simply “read” backwards. Not surprisingly, people with deficit
Backwards digit span have difficulty spelling and remembering their times tables because bothtasks are heavily dependent upon creating an image in your “mind’s eye”. This image must then be
stable enough for the brain to make a “picture” of it, and then store this picture in Eidetic Memory
or Picture Memory of the occipital lobes. Spelling or remembering your times tables is then simply

“recalling” into consciousness the picture of the word or the answer to the times tables and“reading” this recalled information.
Before the LEAP treatment the digit spans all subjects were well below the adult average of 6
forwards and 5 backwards, with all but one below the average for a 10-year old. The Post-test digitspans of all subjects improved dramatically and now ranged from 7 forwards and 6 backwards to ashigh as 8 forwards and 8 backwards (Figure 2).
Figure 2. Digit Span scores for subjects before and after LEAP treatment. In all cases theforwards and backwards Digit Span increased significantly following the LEAP treatment.

Reading Comprehension:
Reading comprehension is the ability to recall information about what was read shortly after reading it.
Reading comprehension often does not vary directly with reading speed, as both slow and fast readers
may demonstrate good or poor comprehension of what was read. Poor reading comprehension isexpressed by the inability to recall much of the detail of what was read or to confuse or confabulate thestoryline or information presented by the author. Subjects with normal reading comprehension caneasily recall greater than 90% of the material read when tested within a few minutes of reading it.
Individuals with poor comprehension can generally recall less than 50% and may recall almost nothing.

All subjects were asked to read standard passages from the Neale Analysis of Reading and thentested for their reading comprehension. Reading comprehension showed equally remarkable
improvements. The percentage of reading comprehension on the Neale Reading Analysis before
treatment varied from 62.5% to 37.5% with one case of zero percent comprehension as this subject
was unable to answer a single question correctly on the material read. The Post-test assessments
showed that after the LEAP Treatment reading comprehension After the LEAP treatment forlearning difficulties all subjects scored 100% on reading comprehension.
SwinburneStudy 2: The Effect of Acupressure Treatment on Measures of Cognitive Ability,
Standard Intelligence Test Scores and Reading Comprehension for Children with Learning
Difficulties. By Susan J. McCrossin, B.App. Sci. Hons. (Psychology & Psychophysiology), Swinburne University
Measures of Cognitive Ability:
Cattell (1963) defined intelligence as comprising of two distinct aspects: ‘fluid’ and ‘crystallised’
intelligence. Fluid intelligence is the capacity to perform abstract reasoning which involves ‘native’
intelligence and is thought to be unaffected by formal education. This includes the ability to solve
puzzles, memorise a series of arbitrary items such as words or numbers, as well as the ability to change
problem solving strategies easily and flexibly. Crystallised intelligence, on the other hand, comprises ofabilities that depend on knowledge and experience or the amount of stored factual knowledge, such as
vocabulary and general informational knowledge (Murphy & Davidshofer, 1994).
In the current study, subjects’ performance on the Inspection Time, which is a cognitive task measuring
fluid intelligence, was compared before and after acupressure treatment designed to improve mental
ability. Tests that are believed to measure Crystallised intelligence were not used as knowledge of facts

is accumulated over a number of years and would not be expected to change substantially over the shorttime frame of the study.

Inspection Time:
Savage (1970, cited in Deary & Stough, 1996) suggested that individual differences in intellectual
ability may be attributable largely to the speed of intake of visual information processing. A currently
used measure of the speed of visual information processing is Inspection Time (IT), an estimate of thestimulus presentation time (in milliseconds) which a subject requires to correctly respond 80% of thetime (Deary, 1993; Deary & Stough, 1996). IT has been found to be highly correlated (-0.8 to -0.9)
with performance IQ as measured by the Wechsler Adult Intelligence Scale - Revised (WAIS-R)(Nettelbeck & Lally, 1976; Lally & Nettelbeck, 1977). Although more recent studies suggest that the
IT-IQ correlation may be closer to 0.5 (Nettelbeck, 1987).
Normal scores for control groups on the IT test range between 55 and 120 milliseconds (msec) withscores higher than 100msec considered low normal (Tsourtos et al., 1995). All subjects in both theControl and Treatment groups were low normal or very slow in their performance on the IT Pre-test. On
the Post-test the Control group remained unchanged, while in the LEAP treatment group all individuals
improved with those who scored above 140 milliseconds on the pre-test improving their IT scores themost. (Figure 2)

ScoresFigure 2. Pre-test and Post-test Inspection Time Scores for the Treatment Group.

350
300
250
200
150
100
50
0

Pre-test
Post-test

1

2

3

4

5

6

7

8

9

Subjects
Digit Span:
The Digit Span subtest of the WISC-R was used as a measure of short-term memory, retrieval anddistractibility (Horn, 1985; Reynolds & Kaufman, 1985). This subtest of the WISC-R is a measure of
the auditory short-term memory processing and freedom from distractibility, where a subject repeats averbally presented sequence of random numbers. The span or number of digits that can be accurately
reported varies with age, varying from 3 forwards and 0 backwards for a 4 year old to 6 forwards and 5
backwards of an average adult. Deficit digit span is when the subject recalls fewer digits forwards
and/or backwards than is average for their age (Horn, 1985; Reynolds & Kaufman, 1985).

The Forwards task requires predominately basal short-term memory functions of the hippocampus,
while the Backwards task requires additional working memory processing in the frontal lobes tocreate an image which is then simply “read” backwards. Not surprisingly, people with deficit
Backwards digit span have difficulty spelling and remembering their times tables, both tasks
heavily dependent upon creating an image in your “mind’s eye”.

All subjects demonstrated deficit age-specific digit span varying from near average at 6 forwards,
but a deficit and 4 backwards compared to the average of 6 forwards and 5 backwards to highly
deficit digit spans at 5 forwards and 3 backwards.
After LEAP treatment the digit spans all subject’s were above the adult average of 6 forwards and 5
backwards. The Post-test digit spans of all subjects ranged from 7 forwards and 6 backwards to ashigh as 8 forwards and 8 backwards (Figure 3a & b).

ScoresFigure 3a. Digit Span Scores for the Non Treatment Group at the Pre-test (B) and Post-test (A) of
the Study. * Zero backwards as subject could not understand concept of reversing digits.

8
7
6
5
4
3
2
1
0

B

1

A B A

2

*

B A

B

3

4

A B A B

5

6

A B A

7

B A

8

B A

9

Subjects
Forwards Before Backwards BeforeForwards After Backwards After

Figure 3b. Digit Span Scores for the LEAP® Treatment Group at the Pre-test (B) and Post-test(A) of the Study.

7

Scores

6
5
4
3
2
1
0

B

1

A B A

2

B A

3

B

A

4

B A

5

B

6

A

B A

7

B A

8

B A B A

9

10

Subjects
Forwards Before Backwards BeforeForwards After Backwards After

Reading Comprehension Task:
Reading comprehension is the ability to recall information about what was read shortly after reading it.
Reading comprehension may not very with reading speed, as both slow and fast readers may
demonstrate good or poor comprehension of what was read. Poor reading comprehension is expressedby the inability to recall much of the detail of what was read or to confuse or confabulate the storyline orinformation presented by the author. Subjects with normal reading comprehension can easily recall
greater than 90% of the material read when tested within a few minutes of reading it. Individuals withpoor comprehension can generally recall less than 50% and may recall almost nothing.

All subjects were asked to read standard passages from the Neale Analysis of Reading and thentested for their reading comprehension. The percentage of reading comprehension on the before
treatment varied from 62.5% to 37.5% with one case of zero percent comprehension as this subject
was unable to answer a single question correctly on the material read. After the LEAP treatment forlearning difficulties all subjects scored between 85 and 100% on reading comprehension (Figure 4a& b).

Percent

Figure 4a. Reading Comprehension Scores for the Non Treatment Group at the Pre-test and Posttest of the Study.
* Six-year-old subject unable to read.
80
70
60
50
40
30
20
10
0

Pre-test
Post-test

1

2

3

4

5

6

7

8

9

Subjects

Figure 4b. Reading Comprehension Scores for the LEAP® Treatment Group at the Pre-test andPost-test of the Study. * 16-year-old subject unable to read.
** 11-year-old subject able to read a few small words.
100

Percent8060Pre-test

40

Post-test

20
0
1

2

3

4

5

6

7

Subjects

8

9

10

The Efficacy of LEAP Acupressure Treatment for the Treatment of SpecificLearning Disabilities: A Controlled Study.
By Dr. Toba Frankel, Haifa University and Dr. Charles T. Krebs, Melbourne Applied Physiology,
Pty Ltd, In Preparation for submission to the International Journal of Learning Disabilities.
Introduction:
Thirty-two children from a school for children with Learning Disabilities in Jerusalem where
randomly assigned to two experimental groups and matched for gender, age and types of learning
disabilities. All children had been diagnosed as being Dyslexic, ADD, or ADHD, and half of bothgroups were taking Ritalin. All children were Pre-tested on a variety of tests from functional tests
for speed of visual and auditory processing and speed of visual decision-making to tests for memory
and learning such as the Wide Range Assessment of Memory and Learning (WRAML) and theDyslexia Screening Test, to behavioural tests for ADD and ADHD as well as subtests of theWechsler Intelligence Test for Children (WISC-revised) assessing academic performance.
In total thirty-two (32) separate Pre-tests were given each subject, and each subject was then Posttested between four (4) and eight (8) months after the initial Pre-tests. The Control Group was Pretested, and then received only normal remediation available through the school, while the LEAP
Treatment Group received on average of 11.5 hours of acupressure treatment over the first twoweeks following assessment by two different LEAP practitioners. Following the initial LEAP
treatment, the LEAP Group then received normal remediation available through the school.
None of the Control Group who were only Pre-tested and then received normal remediation showed
any significant change on the Post-testing. In contrast, subjects in the LEAP Treatment Group
showed statistically significant improvement between the Pre- and Post-tests in Twenty-nine (29) of
the 32 assessments performed, a truly remarkable result. Below are presented summary data on anumber of academically and behaviourly relevant tests.
Speed of Visual & Auditory Processing:
The Visual and Auditory Order Thresholds are tests involving speed of visual and auditory intake,measured as the smallest interval between 2 stimuli necessary to accurately determine which of thetwo stimuli (left or right) was perceived first. These tests showed highly significant improvements
between the before and after results for the experimental group with t-score analysis (p< .001); andshowed no significant improvement for the control group. (Figure 5 & 6)
Figure 5. Visual Order Threshold: Pre- & Post-tests for the Control Group (Group 1) and the
LEAP Treatment Group (Group 2).

percentiles

Visual Order Threshold
60
50
40
30
20
10
0

48.44

17.27

14.5

8
1

2
GroupsbeforeafterFigure 6. Auditory Order Threshold: Pre- & Post-tests for the Control Group (Group 1) and the
LEAP Treatment Group (Group 2).

Percentile

Auditory Order Threshold
60
50
40
30
20
10
0
1

2
Groupsbeforeafter

Speed of Visual Decision-making:Inspection Time (IT) is a basic measure of how long a subject needed to inspect the data before they
could make a correct decision 80% of the time. The more rapidly you can extract information fromvisual data, the more rapidly you can process this data at higher levels of processing, which isprobably why individuals with the fastest IT scores also score highly on IQ tests. As in the previous
Swinburne Study, IT showed no significant improvement in the Control Group and a statisticallysignificant improvement following the LEAP Treatment. (Figure 7)
Figure 7. Inspection Time: Remained the same in the Pre- & Post-tests for the Control Group,
but improved significantly in the LEAP Treatment Group.

Milliseconds

Inspection Time
350
300
250
200
150
100
50
0
1

2
Groupsbeforeafter

By random chance, the LEAP Treatment Group happened to have several individuals who had
extremely low ITs before treatment which lowered the overall LEAP Group average. In fact severalof the LEAP Group had ITs in the low range for normal individuals, and thus could not improveafter treatment, but all other subjects in the LEAP Group showed enormous improvement with the
LEAP Group twice as fast after treatment than before.

Stroop Test: Executive Control of Impulse.
The Stroop Test is a very simple test: the subject is shown the name of a colour, say yellow, but theword is coloured blue. The rules of the test state that you must state the name of the colour written
on the screen, not the colour of the word. However, colour is processed much more rapidly thanreading the word, so the impulse is to say the colour of the word rather than the name of the word.
Thus, the Stroop Test is a relative measure of executive control of brain function as the subject must
inhibit their initial impulse – to say the colour they see, in order to follow the rules – state the nameof the colour written on the screen.
Figure 8 shows that the Pre-tests scores are quite similar for the two groups. The Post-test scores
however show almost no improvement for the Control Group, but enhanced executive control for
the LEAP Group. This indicates that these people were now much improved at inhibiting theirimpulsive reactions by using frontal lobe to follow the rules. These results synchronise nicely with
the SSVEP data showing the shift to frontal lobe activation during decision-making (Fig. 1).
Figure 8. Stroop Test: The Control Group showed no significant improvement, while the LEAP
Treatment Group went from deficit to normal in performance of this executive control task. (ex =Experimental LEAP Treatment Group, co = Control Group)

words

Stroop
25
24
23
22
21
20
19
18

24.31

20.38

20
19.09

beforeafter
exbeforeafter
coReading Comprehension Task:
Reading comprehension is the ability to recall information about what was read shortly after reading it.
Reading comprehension may not very with reading speed, as both slow and fast readers may
demonstrate good or poor comprehension of what was read. Poor reading comprehension is expressedby the inability to recall much of the detail of what was read or to confuse or confabulate the storyline orinformation presented by the author. Subjects with normal reading comprehension can easily recall
greater than 90% of the material read when tested within a few minutes of reading it. Individuals withpoor comprehension can generally recall less than 50% and may recall almost nothing.

All subjects were asked to read standard passages from the Esther Tovli's Hebrew Reading
Comprehension Passages and Reading Speed and then tested for their reading comprehension. The
percentage of reading comprehension varied in the Control Group, as one six year old child that
could not read effectively at the time of the Pre-test had begun to read by the time of the Post-test 6
months later. Also several other Control subjects now comprehended more of what they read, whileothers comprehended less on the Post-tests. In the Post-tests, all of the LEAP Treatment Groupnow had a reading comprehension between 70% and a 100% with every subject significantly
improving their reading comprehension (Figure 9a & b).

Figure 9a. Reading Comprehension: Pre-test and Post-test Scores for the Control Group.
* One six-year-old subject unable to read at time of Pre-test.
Reading Comprehension
Controls
100

percent of correct responses

90

90

85

80

75

70

90

75
65

60

55
50

50

60

55

50

80

75

50

50

40
30

after

36

30

20

15

10
0

before

15

0

10

0

1

2

3

4

5

6

7

8

9

10

11

subjects

Figure 9b. Reading Comprehension: Pre-test and Post-test Scores for the LEAP Treatment
Group.
* Two six-year-old subjects unable to read at time of Pre-test.
Reading Comprehension

percentage of correct responses

100

95

90
80

80

70

70

60

75

100
90

100100

90

80

75 75

70

95 95

70

68

100
95
90

65

60 60

before

50
40

40

30

30

20

after

40

20

25

20

10
0

0
1

0
2

3

4

5

6

7

8

9 10 11 12 13 14 15 16

subjects

Dyslexia Screening Test
Another factor in reading comprehension is speed and accuracy of decoding. This was tested by two
subtests of the Dyslexia Screening Test and both of these also showed a significant improvement;
Nonsense Passage (p<.05), and One Minute Reading Subtest (p<.05).
Back Span, the reverse digit memory subtest of the Dyslexia Screening Test showed a significant
improvement (p<.001), supporting the highly statistically significant results in Backwards Digit
Span on the WISC-R test in the Swinburne study (Fig. 3b).

The Dyslexia Screening Test At Risk Quotient is based on the mean of only the problematic scaled
scores, and At Risk Quotient showed a highly statistically significant improvement (p<.001)
compared to the control group. This suggests that just 11.5 hours of LEAP treatment moved thesechildren from being At Risk of demonstrating Dyslexia to no longer demonstrating strong dyslexic
tendencies.
Wide Range Test of Memory and Learning
The Wide Range Test of Memory and Learning (WRAML) is a series of subtests predominately
assessing memory and learning. While the Control Group showed no change between the Pre- andpost-tests, the LEAP Treatment Group showed statistically significant improvement in each one ofits subtests, Story Memory (p<.05), Design Memory (p<.001), Verbal Learning (p= 0.56, Picture
Memory (p<.001), and Symbolic Working Memory (p<.05); and when tested by a Cronbach's
Alpha of .800, showed a high reliability.
Conners' Rating Scales of Behaviour:
The Conner’s Rating Scale of Behaviour is a standard rating scale of ADHD behaviours. It has
three primary Indices: The Parents and Teachers Scales, the DSM Index and the Global Index.
In addition to the tests of processing and cognitive functioning presented above, the Conners' Rating
Scales of Behaviour show very positive results. The Conner's ADHD Index for the Parent Scales
was statistically significant between LEAP Group compared with the Control Group (p<.05), eventhough the Teacher’s ADHD Index was not quite statistically significant (p< 0.58). However, boththe DSM Index (p<.05) and the Global Index (p<0.55) as well as the Conner's ADHD Global Index
for the Teacher Scales (p<.05) showed that the LEAP Treatment had a significant effect on ADHD
behaviours for a majority of the children in the LEAP Group. Interestingly, of the original eight (8)children on Ritalin at the onset of the study, four (4) were totally off Ritalin at the end of the study
and no longer displayed ADHD behaviours. All eight (8) of the children on Ritalin at the onset ofthe study in the Control Group were still on Ritalin at the end of the study.
Conners' Continuous Performance Test:
In contrast to the overt significant improvement in the ADHD Indices given above, the Conners'
Continuous Performance Test showed no statistically significant improvement for the LEAP Groupon this ADHD task. Even though there was no statistical significance between the Control and
LEAP Groups on this task, the Confidence Index of being ADHD was lower for all but one child in
the Post-tests in the LEAP Group, while few of the children in the Control Group reduced their
Confidence Index of being ADHD over the course of the study.
WISC-R Subtests: Coding, Block Design and Arithmetic.
Coding is a test for visual short-term memory, eye-hand co-ordination and visual search strategy,
clearly all important functions for academic success. This important function showed no significant
improvement in the Control Group, but a highly statistically significant improvement following the
LEAP acupressure treatment (p<0.001).
The Block Design subtest is considered an assessment of the innate visuo-spatial reasoning ability
as it requires no verbal knowledge and is largely dependent upon fluid intelligence. This is one areaof function that invariably improves significantly in clinical practice as you can watch the child
improve in this task. Visuo-spatial reasoning underlies much of our thinking and is important inproblem-solving. Thus the highly significant improvement on the Post-test in the LEAP Treatment
Group (p<0.001) compared to the Control Group supports these clinical observations. Interestingly
the Wechsler's Block Design and WRAML's Design Memory show inter-test reliability with asignificant Pearson Correlation for the LEAP Treatment Group versus a lack of correlation in theControl Group.

Arithmetic is clearly a foundation academic skill that is often difficult for most children withlearning difficulties. This is partly because many of these children have great difficulty with
abstraction, a purely Logic function underlying all mathematical processing. Again the remarkable
improvement displayed by the LEAP Group compared to the Control Group (p<0.001) suggest that
the LEAP Treatment has huge potential to assist children overcome their Learning Disabilities.
Academic Performance: Cause of Improvement.
To note that significant improvements in high level academically important functions like reading
comprehension occurred does not offer any explanation as to why they occurred? However, becauseof the large number of tests from basal functions to high-level cortical processing used in this study,
it is possible to understand why these changes occurred, in fact why they would have had to occur!
Reading comprehension is one of the highest level academic functions dependent upon many levelsof coherent, integrated processing from the brainstem to the frontal lobes. If processes at any levelare poorly integrated or poorly accessed, then reading comprehension will suffer.
In the LEAP Treatment Group, all children showed poorly integrated functions from the most basal
level of speed visual processing through speed of visual decision-making to auditory and visual
short-term memory to working memory of the frontal lobes. Reading comprehension is especiallydependent upon the higher level working memory functions of self-monitoring and drawing
inferences from what was read to fully understand the meaning of what was read, because with outmeaning there can be no comprehension.
Since the speed of visual processing (Visual Order Threshold), the speed of visual decision-making(Inspection Time), auditory and visual short-term memory (Digit Span & Coding) and working
memory (WRAML) all improved statistically significantly individually, reading comprehension
dependent upon these individual processes must improve statistically significantly!

Summary: The LEAP Acupressure Program offers an Effective Long-term Solution to
Addressing the Correction of Specific Learning Disabilities for most Children and Adults.
From the data presented above as well as thousands of successful clinical outcomes both in my own
practice and feedback from LEAP Practitioners around the world (LEAP is now taught in 10
countries), it would appear that the LEAP program provides one possible solution to resolving
Specific Learning Disabilities on a long-term basis. In the Israeli study, the children were treatedwith the LEAP program, but not re-tested for on average of six months following treatment.
Improvements that have persisted for six (6) months can be considered permanent, because LEAP
corrects the basic Brain Integration problems underlying the symptoms of learning and memory
dysfunction, rather than attempting to treat the symptom. On the strength of the data above, it would
appear that a trial of the LEAP Program is warranted in the Victorian Schools.
References:
1. Kussmaul, cited in Kolb, B & Whishaw, I Q, Fundamentals of Human Neuropsychology, 3rd Ed. W.H.
Freeman & Co, New York, p.778, 1990.
2. Berlin, as cited in Kolb, B & Whishaw, I Q, Fundamentals of Human Neuropsychology, 3rd Ed. W.H.
Freeman & Co, New York, p.778, 1990.
3. Kolb, B & Whishaw, I Q . Fundamentals of Human Neuropsychology (3rd ed.). New York: W H
Freeman & Co, 1990.
4. Geschwind, N. & Galaburda, A.M., Cerebral Lateralization, Cambridge, MA: The MIT Press, 1985
Galaburda et al, Planum temporale asymmetry, reappraisal since Geschwind and Levitsky,
Neuropsychologia, 25:853-868, 1987.
Duffy, F H, McAnulty, G B & Schachter, S C. Brain Electrical Activity Mapping. . In N Geschwind &A M Galaburda (eds.) Cerebral Dominance (pp. 53-74). Cambridge, Massachusetts, USA: Harvard
University Press, 1995.

5. Fawcett, A. Dyslexia: a personal view. In A Fawcett, & R Nicolson (Eds.), Dyslexia in children.
Hemel Hempstead, UK: Harvester Wheatsheaf, 1994.
6. Fawcett, A. ibid.
7. Aiken, L R. Assessment of Intellectual Functioning (2nd ed). New York: Plenum Press, 1996.
8. Aiken, L R. ibid
9. Rutter, M. & Yule, W., The concept of specific reading retardation. J. Child Psych & Psychiatry 16:181197, 1975.
10. Gaddes, W. H. Prevalence estimates and the need for definition of learning disabilities. In: R.M. Knights& D.J., eds. The Neuropsychology of Learning Disorders. Baltimore: University Park Press, 1976.
11. Kolb, B & Whishaw, I Q. Fundamentals of Human Neuropsychology (3rd ed), 1990.
12. Kolb, B & Whishaw, I Q. ibid.
13. Kolb, B & Whishaw, I Q. ibid.
14. Hughes, J.R. Electroencephalographic and neurophysiological studies in dyslexia. In: A.K. Benton & D.
Pearl, eds. Dyslexia: An appraisal of Current Knowledge. New York: Oxford University Press, 1978.
15. Farrow, M. et al. Prefrontal & parietal deficits in ADHD suggested by Brain Electrical Activity during
Children performing the AX-CPT. Ed. Develp. Psych. 13:59-68, 1996.
16. Kolb, B & Whishaw, I Q. Fundamentals of Human Neuropsychology (3rd ed), 1990.
Baving, L., Laucht, M. & Schmidt, M.H. Atypical frontal brain activity in ADHD: preschool andelementary school boys and girls. J. Am. Acad. Child Adolesc. Pyschiatry 38(11):1363-1371, 1999.
17. Douglas, V.I. Perceptual and cognitive factors as determinants of learning disabilities: A review chapter
with special emphasis on attentional factors. In: R.M. Knights & D.J., eds. The Neuropsychology of
Learning Disorders. Baltimore: University Park Press, 1976.
18. Serfontein, G . The Hidden Handicap. Sydney, Australia: Simon & Schuster, 1990.
19. Damasio, A R . Descartes’ Error: Emotion, Reason and the Human Brain. New York: Grosset/Putnam,
1994.
Nunez, P.L. Neocortical Dynamics and Human EEG Rhythms. Oxford University Press, New York, NY,
1995.
20. Krebs, C.T. & McCrossin, S.J. Learning Enhancement Advanced Program (LEAP). Melbourne:
Melbourne Applied Physiology, 1994.
21. Damasio, A R. Descartes’ Error: Ibid. p.94, 1994.
22. Kandel, E.R. Brain and Behavior. In Kandel, E.R., Schwartz, J.H. & Jessell, T.M. (eds) Principles of
Neural Science. 3rd ed. Appleton & Lange, Norwalk, CN. pp.997-1008, 1991.
Kupfermann, I. Learning and Memory. In Kandel, E.R., Schwartz, J.H. & Jessell, T.M. (eds) Principles
of Neural Science. 3rd ed. Appleton & Lange, Norwalk, CN. pp.997-1008, 1991.
Damasio, A. Descartes’ Error. Emotion, Reason and the Human Brain, 1994.
Restak, R.N. The Modular Brain. Touchstone Book, New York, NY. 1995.

23. Krebs, C.T. & Brown, J. A Revolutionary Way of Thinking. From a Near Fatal Accident to a New
Science of Healing. Hill of Content Publishing, Melbourne, Australia, pp.246-271, 1998.
24. Goldberg, E. The Executive Brain. Frontal Lobes and the Civilized Mind. Oxford University Press, New
York, pp.113-135 & pp.139-150, 2001.
25. Blum, K. et al. Allelic association of human dopamine D2 receptor genes in alcoholism. J. Am. Med.
Assoc. 263:2055-2060, 1990.
Blum, K. et al. Prolonged P300 latency in a neuropsychiatric population with the D2 dopamine receptor
A1 allele. Phramocogenetics, 4:313- 322. 1994.
Miller, D. & Blum, K. Overload: Attention Deficit Disorder and the Addictive Brain. Andrews &McMeel, Kansas City, MO, pp.38-39, 1996.p.60-61, 1996.
Aldridge, S. Seeing Red & Feeling Blue. The New Understanding of Mood and Emotion. .Arrow Books,
London, pp. 137- 138. 2001.
26. Safer, D J & Krager, J M (1988). A survey of medication treatment for hyperactive/inattentive students.
JAMA, 260, 15, 2256-2258.

Wolraich, M L, Lindgren, S, Stromquist, A, Milich, R, Davis, C & Watson, D. Stimulant medication use
by primary care physicians in the treatment of attention deficit hyperactivity disorder. Pediatrics, 86, 1,
95-101. 1990.
Barkley, R A, DuPaul, G J & McMurray, M B. (1991). Attention deficit disorder with and without
hyperactivity: Clinical response to three dose levels of methylphenidate. Pediatrics, 87, 519-531.
Barkly, R.A. ADHD and the Nature of Self-Control. The Guilford Press, New York, 1997.
27. Conner, W.E. & Neuringer, M. The effects of N-3 fatty acid deficiency and repletion upon fatty acidcomposition and function of brain and retina. In Biological Membranes: Alteration in Membrane
Structure and Function. Alan R.: Liss Inc. New York, pp.275-294, 1988.
Stordy, J. Benefit of DHA supplement to dark adaptation in dyslexia. Lancet, 346:385, 1995.
Stordy, J. Dark adaptation and motor skills: docosahexaenoic acid and dyslexia. Am. J. Clin. Nutr.
Supplement, 1997.
28. Ward, N.I. et al. The influence of the chemical additive tartrazine on the zinc status of hyperactive
children - a double blind placebo controlled study. J. Nutr. Med 1:51-57, 1990.
Hannuksela, M. et al. Hypersensitive reactions to food additives. Allergy 42(Nov): 561-575, 1987.
David, T.J. Reactions to dietary tartrazine. Arch. Disease Childhood 62:119-122, 1987.
Buist, R. Food Chemical Sensitivity. What It is and How to Cope with It. Harper & Rowe Publishing,
Sydney, pp.193-196, 1986.
Salamy, J. et al. Physiological changes in hyperactive children following ingestion of food additives.
Intl. J. Neuroscience 16:241-246, 1982.
29. Schoenthaler, S.J. et al. Institutional Nutritional Policies and Criminal Behaviour”. Nutrition Today p.21
May/June, 1985
Schoenthaler, S.J. et al. The impact of a low food additive and sucrose diet on academic performance in
803 New York City Public schools. Intl.. J. Biosocial Res. 8(2): 185-195, 1986.
Schoenthaler, S.J. et al. Malnutrition and maladaptive behaviour: Two correlational analyses and adouble blind placebo controlled challenge in five states. In Essman W.B. (ed.) Nutrients and Brain
Function. Basil, Switzerland: Karger, p.198-218, 1987.
30. Rapp, D. Is This Your Child’s World. Bantam Books, New York, 1996.
***Other References not yet located!
31. Becker, R.O. Cross Currents. The Perils of Electropollution and the Promise of Electromedicine. Jeremy
P. Tarcher, Inc. Los Angeles p.174-176, 1990.
Coghill, R. Electrohealing. The Medicine of the Future. Thorsons, London. p.83, 1992.
32. Krebs, C.T. & Brown, J. A Revolutionary Way of Thinking. From a Near Fatal Accident to a New
Science of Healing. Chap. 8, Hill of Content Publishing, Melbourne, 1998.
33. Kendall, H.O. & Kendall, F.P. Muscle Testing and Function. Williams & Williams, Baltimore, MD,
1949.
Kendall, F..P. & Kendall McCreary, E. Muscle Testing and Function. 3rd Edition, Williams &Williams, Baltimore, MD, 1983.
34. Walther, D.S. Applied Kinesiology. Vol.1. Basic procedures and Muscle Testing. Systems D.C., Pueblo,
CO, pp.220-223, 1981.
Walther, D.S. Applied Kinesiology. Synopsis. D.C., Pueblo, CO, 1988.
35. Krebs, C.T. & Brown, J. A Revolutionary Way of Thinking. From a Near Fatal Accident to a New
Science of Healing. Chapters 2 & 12, Hill of Content Publishing, Melbourne, 1998.
36. Walther, D.S. Applied Kinesiology. Vol.1. Basic procedures and Muscle Testing. Systems D.C., Pueblo,
CO, pp.220-223, 1981.
Walther, D.S. Applied Kinesiology. Synopsis. D.C., Pueblo, CO, 1988.
37. Krebs, C.T. & McCrossin, S.J. Learning Enhancement Advanced Program (LEAP). Melbourne:
Melbourne Applied Physiology, 1994.
38. Krebs, C.T. & Brown, J. A Revolutionary Way of Thinking, 1998.
39. Levy, S.L. & Lehr, C. Your Body Can Talk. The Art and Application of Clinical Kinesiology. Hohm
Press, Prescott, Az, pp.4-5, 1996.

40. Utt, R. D. Utt, R. Applied Physiology Acupressure Formatting for Brain Physiology. Applied Physiology
Publishing, Tucson, AZ, 1991.
41. Paphazy, J. Unpublished data from children who pre- and post-tested with the WISC-R before and after
they received the LEAP® treatment from 1986 to 1991.
McCrossin, S. The Effect of Acupressure Treatment on Standard Intelligence Test Scores and Reading
Comprehension for Children with Learning Difficulties. Unpublished Honours Thesis, Swinburne
University, Melbourne, Australia, November, 1996.
42. Lezak, M D (1995). Neuropsychological Assessment. (3rd ed.), New York: Oxford University Press.
43. McCrossin, S. The Effect of Acupressure Treatment on Standard Intelligence Test Scores and Reading
Comprehension for Children with Learning Difficulties. Unpublished Honours Thesis, Swinburne
University, Melbourne, Australia, November, 1996.
44. Kaptchuk, T.J. Chinese Medicine. The Web that has no Weaver. Ryder, London, 1983.
Gerber, R. Vibrational Medicine. Bear & Company, Santa Fe, New Mexico, pp.176-177, 1988.
45. Senelar, R. & Auziech, O. Histophysiologie du point d’acupuncture. Acupuncture et Médecine
Traditionnelle Chinois, Paris. Encyclopedic des Médecine Naturelles, 1B-2C, 1989.
Niboyet, J-E-H. Nouvelles constalations un les proprietés électrique des points chinois. Bulletin de laSociété de’Acupuncture, Vol.4 (30), 1938.
Roppel, R.M. & Mitchell, F. Jr. Skin points of anomalously low electric resistance: current voltage
characteristics and relationships to peripheral stimulation therapies. J. Am. Osteopathic Assoc.,
746:877-878, 1975.
Hyvarien, J. & Karlson, M. Low resistance skin points that may coincide with acupuncture locations.
Medical Biology 55:88-94, 1977.
Helms, J.M. Acupuncture Energetics. A Clinical Approach for Physicians. Medical Acupuncture
Publishers, Berkeley, CA, pp.26-27, 1995.
46. Niboyet, J.E.H. La Moindre Resistance à l’Electricite de surfaces punctiformes et de trajets catanes
concordant avec les points et meridiens, bases de l’Acupuncture, Marseille. Thése de Sciences, 1963.
Reichmanis, M. et al. Electrical correlates of acupuncture points. IEEE Trans, Biomed, Eng. BME
22:533-535, 1975
Helms, J.M. Acupuncture Energetics……… pp.20-21, 1995.
47. Porkert, M. The Theoretical Foundations of Chinese Medicine. The MIT Press, Cambridge, MA, p.4376, 1974.
Kaptchuk, T.J. Chinese Medicine. The Web that has no Weaver. Ryder, London, 1983.
Maciocia, G. The Foundations of Chinese Medicine. Churchill Livingstone, London, pp.15-34, 1989.
Xinnong, Cheng (chief ed) Chinese Acupuncture and Moxibustion. Foreign Language Press, Beijing,
China, p.1-2, 1987.
The 20th Century French scholar/diplomat George Soulié de Morant studied acupuncture in China with
Chinese masters between 1901-1917. Upon his return to France, he taught clinical applications ofacupuncture to French physicians and introduced acupuncture theory of the classical texts to the French
and European medical community through his truly monumental three volume text L’Acuponcture
Chinoise (Chinese Acupuncture) in 1939, 1941 & 1955. It was Soulié de Morant that introduced theterms “meridian” and “energy” to the West from his translation of the terms “Jing” and “Ch’i” or “Qi”
from traditional Chinese texts.
48. Zhongfang, L, Qingshu, C, Shuping, C & Zhenjing, H (1989). Effect of electro-acupuncture of“Neiguan” on spontaneous discharges of single unit in amygdaloid nucleus in rabbits. Journal of
Traditional Chinese Medicine, 9(2), 144-150.
49. Bucinskaite, V, Lundeberg, T, Stenfors, C, Ekblom, A, Dahlin, L & Theodorsson, E (1994). Effects ofelectro-acupuncture and physical exercise on regional concentrations of neuropeptides in rat brain.
Brain Research 666, 128-132.
50. Qian-Liang, L (1989). Research on strengthening cerebral function and improving intelligence.
International Journal of Oriental Medicine, Vol 14, 227-232.
51. Abad-Alegria, F, Galve, J A & Martinez, T (1995b). Changes of cerebral endogenous evoked potentials
by acupuncture stimulation: A P300 Study. American Journal of Chinese Medicine, Vol. XXIII, 2, 115119.

52. Cho. Z.H. et al. New findings of the correlation between acupoints and corresponding brain cortices
using f-MRI. Proc. Nat. Acad. Sci. 95: 2670- 2673, 1998.
Cho, Z.H. et al. Functional Magnetic Resonance Imaging of the brain in the investigation of acupuncture.
In: Clinical Acupuncture – Scientific Bases. Springer (Ed. by G. Stux and R. Hammershlag), Berlin,
Germany, pp. 83- 96, 2000.
53. Hui. K.K.S. et al. Acupuncture modulates the limbic system and subcortical gray structures of the humanbrain: Evidence from f-MRI studies in normal subjects. Human Brain Mapping 9:13-25, 2000.
54. Utt, R. Applied Physiology Acupressure Formatting for Brain Physiology. Applied Physiology
Publishing, Tucson, AZ, 1991.
55. Krebs, C T & McCrossin, S J. Learning enhancement advanced program (LEAP). Melbourne:
Melbourne Applied Physiology. 1994.
56. Tobar, Hugo. Brain Formatting, Accessing, Stress, Consciousness and Awareness. Brain Conference,
Internationaler Kinesiologie Kongress, Kirchzarten, Germany, 6- 8 Sept. 2002.
57. Jones, J..P, So, C.S., Kidney, D.D. & Saito, T. Evaluation of Acupuncture using f-MRI and Untrasonic
Imaging. Abstract, 20th Annual Meeting of the Society For Scientific Exploration, La Jolla, California,
June 7- 9, 2001.
58. Helms, J.M. Acupuncture Energetics. A Clinical Approach for Physicians. Medical Acupuncture
Publishers, Berkeley, CA, pp.26-27, 1995.
Maciocia, G. The Foundations of Chinese Medicine. Churchill Livingstone, London, pp.15-34, 1989.
Xinnong, Cheng (chief ed) Chinese Acupuncture and Moxibustion. Foreign Language Press, Beijing,
China, p.1-2, 1987.
59. McCrossin, S. The Effect of Acupressure Treatment on Standard Intelligence Test Scores and Reading
Comprehension for Children with Learning Difficulties. Unpublished Honours Thesis, Swinburne
University, Melbourne, Australia, November, 1996.
60. Paphazy, J. Unpublished data from children who pre- and post-tested with the WISC-R before and after
they received the LEAP® treatment from 1986 to 1991.
61. Lezak, M.D. Neuropsychological Assessment. 3rd ed. Oxford University Press, 1995.
62. Paphazy, J. Unpublished data from children who pre- and post-tested with the WISC-R before and after
they received the LEAP® treatment from 1986 to 1991.
63. McCrossin, S. Changes in SSVEP topography, digit span performance and reading comprehension in
response to acupressure treatment. Unpublished major research thesis, Swinburne University,
Melbourne, Australia, October, 1995.

64. Jackson, G. Personal communication, June 1990- July 1993.