Event Related Potentials (ERPs) in prognosis, diagnosis and rehabilitation of children with dyslexia
*Professor of Neuropsychology-Neurolinguistics, University of Thessaly, Greece
**Doctor of Clinical Neuropsychology, University of Thessaly, Greece

Developmental dyslexia affects 5 to 15% of the student population. It is diagnosed when literacy skills are much lower than those expected. One of the greatest difficulties that dyslexics have is to efficiently translate the written letters into the sounds that they represent. One of the suggested reasons for this phenomenon is the impaired low level auditory processing, which ultimately affects the phonological processing.

Different theories have emerged during the years about the origin of dyslexia, including the magnocellular hypothesis, the cerebral deficit hypothesis, the suggestions of hemispheric asymmetry, disturbances of working memory, deficits in visual and auditory processing, etc. Because of these neuropsychological deficits of reading disorder it is proposed that a good method in the assessment of children with dyslexia is Event Related Potentials (ERPs), a noninvasive tool that can provide data about the neuronal activity which is related to cognitive information processing.

This article’s aim is to review research studies available for the diagnosis of dyslexia in this electrophysio-logical technique. ERPs waveforms can provide unique insights into the nature of reading disorders and high-light quantitative and/or qualitative differences in information processing between normal and reading disabled children. Besides that, this article’s purpose is to summarize literature data on the prognosis of dyslexia in pre-school children and on the rehabilitation of cognitive deficits of children who have reading difficulties. All data will be used in a pilot study currently conducted by the Laboratory of Neuropsychology, University of Thessaly. Encephalos 2011, 48(3):118-127.

Key words: Event related potentials, dyslexia, brain activity.


Dyslexia as a reading problem is divided into two broad and clearly defined categories: acquired dyslexia and developmental dyslexia. Acquired dyslexia is characterized by a person's difficulty or inability to process written language. Acquired dyslexia differs from developmental dyslexia in this: it is a disorder in which reading skills had been fully acquired, but were lost or impaired as a result of brain injury in the lateral temporal lobe of the left hemisphere. In 1962 Geschwind1 distinguished three types of acquired dyslexia. The first type is characterized by serious inability to comprehend verbal and written language and difficulty producing orthographically correct writing. The second but less common type is characterized by clear inability to read and write. The third type is characterized by inability to read rather than to write. Out of these three forms of dyslexia, the latter resembles mostly developmental dyslexia. Extended research on the acquired form of dyslexia was carried out by Shallice & Warrington2 and Patterson & Marcel3. These researchers report cases of patients with acquired dyslexia who had great difficulty naming the letters of the alphabet or pronouncing orthographically incorrect pseudowords.

They classified the patients' reading errors into three basic categories: the first category included the so-called “visual errors” in which the reader confuses a letter or a word for another. The errors of converting graphemes into phonemes were placed in the second category, while the third category included semantic or etymological errors which resulted in the patient’s failure to read words he/she was presented with correctly. Given that developmental dyslexia has been studied by various researchers, different terms are employed for its classification. In the past, researchers supported two types of developmental dyslexia: a) visual dyslexia and b) auditory dyslexia. This wording stems from the researchers’ belief that dyslexia manifests as a result of disorders in the development of visual perception.

A few years later, Myklebust (1973)4, based on clinical neuropsychological studies, also maintained two basic types of dyslexia: a) visual and b) auditory. Three more were included in those two:

a. Dyslexia of inner language,
b. Auditory dyslexia and
c. Visual agnosia5.

Individuals experience visual dyslexia as a learning disability mainly through the visual channel. Obvious features include difficulty in identifying complex drawings, perception and reproduction of visual sequences and possible clumsiness in overall mobility.

In reading, a visually dyslexic child tends to confuse word or letter pairs which have a visual similarity or mirror correspondence between them. This was attributed to poor visual memory which fails to perceive words as visual wholes; in turn, this failure was held responsible for the difficulty in learning the correct position and orientation of letters. As a result of these functional deficits, children find it hard to recognize words rapidly. They usually treat all words as if confronted with for the first time, which justifies the view that those individuals have a restricted sight vocabulary. Therefore, they have difficulty in reading words as a whole and they rather process words analytically using the process of analysis and synthesis, which helps them read even pseudowords. There is abundant body of research on the mechanisms of reading and spelling and Boder’s6 work clearly stands out. Based on the clinical-training analysis of reading and spelling errors, she distinguished three subtypes of reading disability, which form the following dyslexic types:

a) the dysphonetic type is characterized by an inability to process sound-symbol relationships,
b) the dyseidetic  type is characterized by an inability to visualize words when reading to the point that reading becomes fluent and
c) the mixed type (dysphonetic-dyseidetic) or alexic that combines difficulties of the two previous types4.

Currently, various imaging techniques enable Clinical Neuropsychology to provide prognosis, assessment and rehabilitation of Specific Learning Disabilities and, primarily, dyslexia. This article focuses on Event-Related Potentials (ERPs), an electrophysiological technique that assesses how long it takes the brain to process stimuli that activate its cognitive functions and how this processing is effected. ERPs represent the simultaneous activation of electrical fields associated with the activity of large populations of neurons. This activity volume conducts to the scalp surface, and is configured in such a way that their individual electrical fields summate to yield a dipolar field (a field with positive and negative charges). ERPs reflect changes in the brain's electrical activity in response to a discrete stimulus or event. They are normally collected after the presentation of repeated stimuli. In general, electrical activity recording occurs at about 100 ms or more before stimulus presentation and continues over a period of 500-2,000 ms after its termination.

Each trial is generally averaged in order to eliminate background noise that is not related to the targeted stimulus. As a result of averaging, the noise goes to 0 and the positive and negative waveforms recorded correspond to different neural and perceptual/cognitive operation7. The first studies using ERPs in patients with psychiatric disorders were carried out in the mid-1960s8. During those studies, ERPs were evoked from patient responses to somatosensory stimuli. About the same period of time, Samuel Sutton9 discovered the P300 waveform. This discovery confirmed the view that ERPs are affected by the psychological state and cognitive ability of an individual. This waveform, and the majority of the evoked potential components, drew its name from its positive voltage potential and the 300 ms post-stimulus. The Ρ300 waveform was first used in the assessment of higher cognitive functions of individuals as they became older. ERP components are evoked in response to auditory and visual stimuli. Furthermore, most components are detected after the presentation of the target stimulus (oddball) in different stages of the cognitive functions activated by the brain to respond to the particular stimulus. In fact, it should be noted here that most ERP components can be detected even during the presentation of standard stimuli. However, the ERP components lack clarity and, as a result, they are mostly used to verify the results of an oddball stimulus.

ERP Components

The Ν100 waveform

The N100 is a negative-going evoked potential, which occurs when the individual is vigilant, roughly at 100 milliseconds, as the brain’s response to repeated auditory stimuli. In fact, we could argue that it is the brain’s spontaneous post-stimulus reaction10.

The Ν200 waveform

The Ν200 waveform typically occurs at a latency of 180-325 milliseconds post-stimulus (visual or auditory). It is a negative-going evoked potential that is generated as a result of separating stimuli (visual or auditory) to which the subject is asked to respond. This potential is usually evoked in response to the classic oddball. In other words, the subject is called upon to recognize two kinds of stimuli which are barely different. What’s more, one stimulus is presented more frequently than the other. The N200 should be elicited during the presentation of the less frequent stimulus. Furthermore, the N200 waveform is evoked before the subject’s brain becomes aware of the unexpected stimulus. Thus, it measures the brain’s spontaneous reaction to the stimulus. This waveform cannot be detected in small children11.

The Ρ300 waveform

This is the most studied ERP component. It is a positive-going evoked potential that occurs at a latency of roughly 300 ms post-stimulus. This waveform is a postsynaptic potential in the cortex. Various neurotransmitters and cerebral structures play a major role in its elicitation. It was already noted that the first ERP component that was found in 1965 by S. Sutton and his colleagues8. They had described the ERP component as an electrophysiological measurement that could be used as a promising tool for assessing psychological disorders. Whether the P300 waveform is elicited or not depends upon the degree of attention and the effort made by the individual to identify the differences between the physical attributes of a stimulus12. Auditory, visual and somatosensory stimuli can be used to measure this waveform. Put simply, this waveform offers information on how all higher cognitive functions13 - memory, learning, attention, vigilance and perception14 – are performed and activated.

ΜΜΝand LDN waveforms

The Μismatch Negativity (MMN) waveform was discovered by R. Näätänen and his colleagues back in 197815. This waveform reflects the response of the brain to an unexpected change in a sequence of stimuli. More specifically, the brain has retained the stimulus in its memory which, during the trial, is replaced by another without cue. At that particular time, an ΜΜΝ response is elicited. Overall, this waveform specializes in assessing the subject's mnemonic function16. In fact, the MMN is elicited irrespective of attention, as in the case of the P300 waveform; therefore, it is considered that it can also be used to assess infant memory. At this point, we should note that MMN in infants and small children is typically followed by a negative-going slow-developing evoked potential, the LDN waveform. The Late Discriminative Negativity (LDN) waveform usually occurs after 600 milliseconds and is associated with the child's effort to detect novelty within a sequence of standard stimuli17,18.

Event-Related Potentials in the prognosis of dyslexia

Disability in reading acquisition, as previously suggested, may be attributed to various reasons. Luckily, these difficulties can be detected long before the child reaches the age when it must develop reading skills, and there are various methods to use to that end. Although certain reading problems are attributed to difficulties in comprehending instructions based on which we read or are due to lack of experience, several researchers maintain that developmental dyslexia has a genetic basis. Developmental dyslexia is considered to be the result of a difficulty in phonological acquisition, which can manifest itself as a difficulty in storing and producing phonemes of phonemes, letters and words.

It is widely accepted that many children who will develop symptoms of dyslexia have problems pretty early in their life. Several researchers believe that the most appropriate age to predict dyslexia is 3 years old. At that age, language development problems can occur and this is the first indication that the acquisition of reading skills is likely to be delayed. In fact, traditional neuropsychological trials used to detect dyslexia in pre-school children lack sensitivity and important omissions are often found, thus, rendering its timely detection difficult. As a result, contemporary research pursues the detection of this learning disability by using brain activity imaging techniques. Cerebral activity is associated with the processes of language comprehension and processing, such as ERPs with presentation of auditory stimuli. Several researchers believe that measuring brain activity with the use of this technique is quite useful since it can discover differences among children who may or may not develop difficulties in reading skills acquisition later. At the same time, this technique allows us to achieve a prognosis in the development of dyslexia judging by the way that certain brain regions function.

Research to this direction has begun for one more reason. It is widely accepted that the sooner dyslexia is diagnosed – as well as any learning disability or psychological disorder - the easier and more permanently it can be addressed by introducing the appropriate therapeutic scheme as a result of brain plasticity. Therefore, research on detecting early signs of dyslexia by using ERPs has shifted to studying children whose one or both parents have dyslexia. Again, there is sound research evidence that some forms of dyslexia are genetically inherited, thus, children with dyslexic parents or close relatives who are dyslexic have more chances of developing this disability19,20. These various studies facilitate the detection of factors that can lead to genetically and not environmentally based dyslexia.

A reasonable method of examining these factors would be to present auditory stimuli associated with phonological types of the words which are most likely to be missed by children with this problem. Nevertheless, quite a few researchers have argued that the study of these functions is too complex; this is because it requires very small children to respond to tests that only later they will be able to manage, as they require concentration and/or problem-solving skills. As a result, scientists use easier tests to which children with dyslexia are expected to have difficulty with responding to. Thus, ERPs can be an extremely handy tool given that their result does not depend upon the aforementioned limitations which we normally come across in traditional diagnostic tools for learning disabilities. Instead, they serve as a reliable assessment tool for young children because they use simple examination methods and their result is influenced solely by brain activity. Moreover, using ERPs to assess newborns is extremely successful in diagnosing the language skills they will develop later. A research conducted by Guttorm and his colleagues in 200121 revealed that an LDN waveform was elicited at a latency of 540-630 ms  in newborns at risk of dyslexia when presented with the auditory stimulus which included meaningless syllables (ba/ga etc.).

Interestingly, when the values recorded within the time frame of LDN elicitation originated from the right cerebral hemisphere, these children would develop language acquisition impairments at the age of 2.5 years old, and when these values originated from the left cerebral hemisphere, this indicated that these children would manifest difficulties in memorizing sounds of words at the age of 5. These results with the use of the LDN waveform were confirmed later in 2004 by a similar study by Friedrich and his colleagues22 in which 2-month old infants were assessed. During a research23 children aged 12-36 months old who had been born in families where one or both parents with dyslexia were examined against age-matched controls. This research revealed statistically significant differences in Ρ150, Ν250 and ΜΜΝ latencies. As a rule, scientists avoid using these waveforms in combination with ERPs when the children under study are of a very small age. The following table shows the alterations in Ν250 latency timing in children at risk of developing dyslexia compared to the control group. As regards the MMN amplitude, smaller responses over the right as well as over the left cerebral hemisphere of the frontal lobe, the frontocentral region, the brain centre and the temporal lobe were seen in children at risk of dyslexia. While the MMN amplitude in the temporal and occipital lobe was smaller, differences were not statistically significant.

In his study, Stein24 reports that, although spontaneous brain reactions triggered by the auditory stimulus have no difference in latency (50 ms) among children at risk of dyslexia and their age-matched controls, they do differ in amplitude. Children at risk of dyslexia, in particular, showed no amplitude in the waveform response. This waveform was named Ρ50 and was actually perceived when the ERP methods were streamlined. In addition, scientists believe that the Ρ200 amplitude reflects the reading difficulties that an individual is expected to face when having this learning disorder.

Lastly, the research conducted in 200725 by Näätänen and his colleagues who assessed children whose one and/or both parents suffered from dyslexia is considered very important. The children participating in the study were observed from 2 until they reached 10 years old. The children who showed symptoms of developmental dyslexia had an LDN response in the interval from 715-755 ms, whereas children free of symptoms had an LDN response in the time period from 590-625 ms. In fact, this discrepancy was more evident in the right cerebral hemisphere. Finally, a growing body of literature suggests the use of the LDN waveform for the prognosis of dyslexia in ages 3.5-5.5 years and maintains that children with an LDN response of approximately 600 ms over the right temporal lobe are expected to develop better language skills26.

To sum up, it is easily understood that the developments in ERP recording enable us not only to assess if a child is suffering from dyslexia but also if it is at risk of developing the disorder. This is highly important since we are given the opportunity to intervene in children of younger age where we can apply the principles of brain plasticity.

Brain region Ν250 in children
with history of dyslexia
Ν250 in children
without history of dyslexia
Statistically significant difference3
Left frontal lobe 307 ms 266 ms 0.02
Right frontal lobe 305 ms 264 ms 0.01
Left frontocentral region 288 ms 269 ms 0.09
Right frontocental region 277 ms  262 ms 0.02
Left brain centre 279 ms 269 ms 0.02
Right brain centre 274 ms 273 ms 0.80
Left temporal lobe 267 ms 298 ms 0.12
Right temporal lobe 278 ms 292 ms 0.27
Left temporal lobe 309 ms 324 ms 0.14
Right sincipital lobe 315 ms 321 ms 0.41
Left occipital lobe 288 ms 331 ms 0.06
Right occipital lobe 287 ms 328 ms 0.04
3A value is statistically significant when p<0.05 

Event-Related Potentials as a tool for the diagnosis of dyslexia

As mentioned earlier, dyslexia is a reading acquisition disorder which generates from difficulty to process oral and written language and the way they relate to one another. Developmental dyslexia is considered to originate from disorder in phonological skills associated with language acquisition, storing and use of phonology. This is evident when a child begins to conquer the letter-sound relationship. ERPs have been widely used in the diagnosis of dyslexia. Using electrophysiological techniques, scientists are able to identify brain regions responsible for the genesis of dyslexia, differences in the activation of cerebral hemispheres as well as differences in the activation of cerebral lobes. The features of ERP waveforms mostly used are amplitude and latency. In terms of latency, emphasis is placed on evoked waveforms in the time period of 100-500 ms. Studies which assess dyslexic children and witness groups using long latency waveforms – also called ERP components – employing auditory or language stimuli have played an important role in identifying cognitive processes associated with language acquisition27. The ERP components evoked by auditory stimuli, likely to demonstrate the differences between dyslexic and control groups, are the Ν100, ΜΜΝ and Ρ300 waveforms.

A large number of scientists28-30 have spotted differences in the latency and amplitude of the N100 waveform. Νeville and colleagues31 found discrepancies in the hemispheric dominance of dyslexic groups as against controls. The N100 waveform showed a decreased amplitude and prolonged latency in the left cerebral hemisphere of children with reading disability. Not surprisingly, the discrepancies were more evident when the auditory stimulus used was words and not tones. Apart from the N100 waveform, the N200 waveform is also used to assess dyslexic children. This waveform shows reduced amplitude and prolonged latency in children with reading difficulties32.

Another important waveform used in diagnosing dyslexia is the MMN. ΜΜΝ responds to different stimuli which appear to be located in different regions of the auditory cortex. Therefore, if MMN is not evoked, this is probably due to auditory memory problems or deficits in recognition of auditory stimuli. The MMN has the strong advantage that it can be used for an independent careful measurement of auditory awareness. Several researchers33,34 observed statistically significant differences in MMN latency between dyslexic children and normal readers. A recent research35 revealed a prolonged latency of the MMN waveform when the stimulus presented was verbal. On the contrary, when tones were used as an auditory stimulus, no statistically significant differences were reported among dyslexic children and the control group.

In a number of papers the P300 waveform of the ERPs is used  to evaluate the brain deficits present in dyslexic children. This is justified by the fact that this waveform can record the cognitive disabilities of these children, such as memory, attention, vigilance, perception and learning. According to several researchers, the P300 waveform shows an increased amplitude in dyslexic children36-38 as well as in slow readers. In a more recent research it was revealed that the P300 waveform has an increased latency in dyslexic adults as compared to the control group39. Furthermore, during the same research, participants with dyslexia had decreased latency times over the right hemisphere as opposed to the left. The cerebral hemispheres of the adult participants, though, were activated in the opposite direction. The important thing about this research is the use of an auditory language stimulus. Furthermore, a number of neuropsychological studies using ERPs25,40,41,42 suggested anincrease inP300 wave latency in dyslexic children. In fact, researchers argue that this latency has a negative impact on their academic performance.

Moreover, according to a research conducted at the Neuropsychology laboratory of the University of Thessaly, the Ρ300 waveform had an increased latency in children with reading difficulties. What’s more, the cerebral hemispheres of dyslexics were activated in the opposite direction to those of the control group. In dyslexic children, in particular, the Ρ300 waveform was evoked at a shorter latency from the right cerebral hemisphere, whereas in the control group the P300 waveform was evoked more quickly in the left cerebral hemisphere43.

On the contrary, according to a research by Holcomb, Ackerman and Dykman44, dyslexic children showed a reduced latency in P300 waveform compared to against the control group both on presentation of auditory and visual stimuli.

Event-Related Potentials as a tool for the rehabilitation of dyslexia

Before going into the research data on efforts to intervene in dyslexic children, we need to explain the role of ERPs in rehabilitation of dyslexia. The importance of this method lies in the fact that it can offer reliable results in terms of the therapeutic scheme followed. Each individual is unique; this means that, when treating any dysfunction, despite the reliability and effectiveness of the therapeutic scheme, we need to constantly evaluate each individual in order to establish if it helps them or how we can change it to increase their performance.

ERPs make this possible since we are able to compare the subject’s divergence waveform amplitude and/or latency from the values taken from the control group. As a result, we do not evaluate treatment exclusively on the basis of behavioural data that may take long to collect or may be due to transient effects; instead, we use more permanent data which reveal how and when certain dysfunctional brain regions are activated as a result of the specific learning disorder.

Thus, Kujala and colleagues45 have made a tentative assessment of an audiovisual program for the treatment of dyslexia with the use of Event-Related Potentials and in particular, the ΜΜΝ waveform. They used this particular waveform because it is elicited irrespective of the subject’s attention, the separation of auditory stimuli and the subject’s motor reaction during the presentation of oddballs. Upon completing the audiovisual training, dyslexic children had an MMN waveform time window of 225-275 ms, whereas before rehabilitation, the MMN waveform was recorded at 400-450 ms. Therefore, it is easily understood that this program helped children overcome their learning disability  through the development of their memory skills.

Furthermore, according to a research by Santos and colleagues46 the rehabilitation of 10 dyslexic children was evaluated after they attended a training focused on phonological rehabilitation. During evaluation, the children were presented with auditory stimuli, sentences where the last word sounded identically but was semantically different. During the evaluation process, while dyslexic children showed a statistically significant reduced latency in Ρ300 waveform, no such pattern was found in controls. Apparently, this is due to their failure to detect the semantic differences in the auditory stimuli. After three months of attending the rehabilitation program, there were no statistically significant differences in the Ρ300 waveform latency. In other words, dyslexic children detected the semantic differences and their change in neural activity was so marked that there were no differences from the controls.


Reviewing the literature, it is evident that the Event-Related Potentials serve as a reliable tool for the prognosis, diagnosis and rehabilitation of dyslexia. What’s more, neuronal anomalies which are the causes behind the genesis of dyslexia may be recorded by this electrophysiological tool. It is highly encouraging, however, that this imaging technique offers reliable results for the prognosis of dyslexia in particularly young ages. On the basis of the principles of brain plasticity, when intervention is applied, it is possible for these groups to considerably reduce the reading deficits once these children reach the age they are expected to master reading skills.47

Event-Related Potentials also play a substantial role in the diagnosis of dyslexia. Ν100 and Ν200 waveforms show increased latency and increased amplitude in dyslexic children and adults as opposed to normal readers. Increased ΜΜΝ and P300 wave latency are recorded in most studies. In addition, the disordered hemispheric dominance manifested by hyperactivity of the right cerebral hemisphere or hypoactivity of the left are clear indicators for the diagnosis of this disorder. At this point, we should stress the fact that these findings agree with existing neuropsychological theories on the causes of dyslexia. It appears that Ν100, Ν200 and ΜΜΝ waveforms are strong indicators of the difficulty in acoustic processing which could restrict the accuracy of phonological representations considered to be the main deficits of dyslexics25.

Moreover, the longer P300 latency demonstrates higher cognitive function disorders present in dyslexic children, such as proper allocation of attention, decoding, processing, memorization and, successful response to auditory stimuli. What’s more, the disordered hemispheric dominance seems to confirm the classic neuropsychological theory of Geschwind1 regarding hemispheric asymmetry and callosal conditions. Our review would not be complete had we not emphasized that ERPs and, especially MMN waveform can essentially contribute in the assessment of the rehabilitation program. In particular, the proper detection of diagnostic inaccuracies may help in choosing the suitable training program. Besides, each individual has a unique personality; therefore, disorders of the cerebral activity of dyslexics differ.

The ERPs help us quantify deficits and, thus, assess the improvement of a child with reading difficulties before identifying the results of rehabilitation in their behaviour. Thus, we can tailor rehabilitation programs according to the causes of dyslexia26. In turn, this not only reduces the duration of intervention, which is crucial in child’s development, but also rehabilitation is based on the changes in neuronal activity, which in turn increases maintenance of behaviour changes.


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