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Can the error detection mechanism benefit from training working memory? A comparison between dyslexics and controls—an ERP study

Scientific publication on skills enhancement in dyslexic university students

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Original Name: Can the error detection mechanism benefit from training the working memory? A comparison between dyslexics and controls—an ERP study.

Authors: Tzipi Horowitz-Kraus1, Zvia Breznitz.

  • 1. The Edmond J. Safra Brain Research Center for the Study of Learning Disablilities, Faculty of Education, University of Haifa, Israel.

Journal: PloS ONE (2009), vol. 4 (9): 1-10.

References to this article (APA style):

  • Horowitz-Kraus, T. & Breznitz, Z. (2009). Can the error detection mechanism benefit from training the working memory? A comparison between dyslexics and controls--an ERP study. PloS ONE, 4, 1-10.

Study Conclusion

CogniFit's personalized cognitive training has been able to improve cognitive function in college students with dyslexia through an intervention of 24 sessions of 10-15 minute with this program. Digit span from 9.84±3.15 to 10.79±3.03 (p<. 01); Working memory from -. 58±. 61 to -. 42±. 69 (p<. 01).

Study Summary

Given the existing relationship between working memory and error detection, we wanted to test the changeability of working memory in adults with dyslexia as a result of training, and the impact of training on error detection.

For this purpose, 27 university students with dyslexia and 32 student controls participated in the study. The behavior and evoked potentials Event-Related Potential (ERP) were measured before, just after and 6 months after training. The training consisted of 24 sessions of CogniFit Personalized Cognitive Training, focusing on the skills related to the Working memory.

After the evaluations, it was observed that, although both groups improved with CogniFit training, the increase was significantly bigger in the reading group with dyslexia (digit span increased from 9.84±3.15 to 10.79±3.03). This training also increased the number of words read correctly per minute by 14.73%. An increase in working memory and in the amplitude of the ERN component (Error-Related Negativity, a negative wave that appears after making an error) showed that training also produced changes in brain activity.

From all this, it is clear that increasing the capacity of the working memory with CogniFit personalized training it is possible to retain larger units of information in the system, allowing a more efficient error detection.

Context

Dyslexia is a learning disorder that affects the ability to acquire reading. People with this disorder have difficulties in detecting errors when reading written material and, in addition, tend to make mistakes during reading. Adults with dyslexia who have compensated for their difficulties continue to have a large number of errors in reading, fluency, and less working memory than people without the disorder. This can have consequences in academic, work and personal areas, making it difficult for them to do so on a daily basis. Between 10 and 15% of the world's population suffers from dyslexia, making it a very common disorder.

  • Evoked Potentials: These mistakes during reading seem to be regulated by an error detection mechanism, which we can identify by evoked potentials (ERP) that appear at 0-160 milliseconds after giving an erroneous or correct answer: the negative component ERN (related to errors) and the negative component CRN (opposed to the previous one), respectively. Working memory is a sub-component of the information processing system, but with limited capacity. Brain plasticity is maintained during adulthood and can be favored through training. Therefore, through cognitive training, it is possible to stimulate brain plasticity to increase the capacity of our working memory. CogniFit is a cognitive training tool with a solid scientific validation that allows you to apply this training.

The hypothesis is that CogniFit cognitive training should increase both the working memory and the amplitude of the ERN component in dyslexic participants.

Methodology

Participants

This study included 61 university students (27 of them had dyslexia and 34 were control group. Groups were matched by age. In addition, they were found to have similar non-verbal intelligence scores (measured by the Raven Progressive Matrix Test). All of them were middle-class, speaking Hebrew as their native language, skillful, with healthy or corrected eyesight and without hearing problems. Nor had they suffered from any neurological or emotional disorders or attention deficit (measured through Test D2). They were paid volunteers and signed the consent form. Those with dyslexia were diagnosed during their childhood and contacted by the student support service at Haifa University. The controls contacted through an ad on the university campus bulletin board.

Evaluation and design

The following variables were assessed:

  • Decoding capacity (through the one-minute test of words and pseudo-words).
  • Verbal fluency (Read aloud test).
  • Reading comprehension (Silent reading test with 15 closed-ended questions).
  • Short term memory (with the WAIS-III Subtest "Span of digits").
  • Verbal Memory (Opposites Tests).
  • Short term visual memory (remember digits in correct and reverse order displayed on the screen).
  • Short term auditory memory (remember digits in correct and inverse order presented through the headphones).
  • Short term memory in cross mode (numers were displayed on the screen and in the headphones).

These evaluations were carried out three times:

  • Previousto training.
  • Just aftertraining
  • Six months after training.

Statistical analysis

Several statistical analyses were performed:

  • T Tests to confirm there were no significant differences between groups.
  • A repeated measures ANOVA (2x3) for each experimental measurment.
  • A repeated measures MANOVA (2x2x3) for electrophysiological measurements.

Results and conclusions

Data from statistical analysis indicated that both groups improved working memory and reading with CogniFit training, although the improvement was greater in people with dyslexia. There was also an improvement in readability and error detection after CogniFit work memory training.

From all this information we can extract that, on the one hand, adults with dyslexia can also improve their reading ability despite having lower brain plasticity than children. On the other hand, the data points to the relationship between the ERN component (error detection) and working memory. In addition, this data confirms that cognitive training produces changes to the brain. Finally, it was also found that personalized CogniFit cognitive training can improve the working memory of people with dyslexia, which can also produce a benefit in their reading capacity and, therefore, in diverse areas of their lives.

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