Dyscalculia: What Causes Dyscalculia?

Table on contents:

Successful intervention is dependent on finding the cause or causes of a problem. Most problems can only be solved if one knows their causes. A disease such as pellagra took the lives of thousands in the Southern States of America during the early part of the twentieth century. Today, pellagra is virtually unknown because we know that it is caused by a vitamin B3 deficiency. A viable point of departure would therefore be to ask the question, “What causes dyscalculia?”


While the environment plays a role — poor teaching or environmental deprivation, for example — there is also strong evidence for a genetic basis. For example, if one twin has dyscalculia there is a 58% likelihood that his/her identical twin and a 39% chance that a non-identical twin will also be dyscalculic. The link also exists between dyscalculics’ parents and siblings: around half of all the first-degree family members of a dyscalculic also have dyscalculia (mothers, 67%; fathers, 41%; brothers, 53%; sisters, 52%), and 43% of the second-degree relatives. This prevalence is around tenfold higher than expected for the general population. However, there are no gender differences (Kadosh & Walsh, 2007). 

If one twin has dyscalculia there is a 58% likelihood that his/her identical twin and a 39% chance that a non-identical twin will also be dyscalculic.

Although some causes of dyscalculia have a genetic origin, and environmental factors play an important role, cognition mediates brain-behavior relationships and therefore offers a sufficient level of explanation for the development of principled interventions. We thus need to understand the cognitive difficulties that underpin math failure, regardless of whether their origin is constitutional or environmental (Elliott & Grigorenko, 2014).

Cognitive skills that matter

Research has shown that attention; visual and auditory processing; visual, visuospatial, and working memory; and logical thinking are important foundational skills of math.

– Visual and auditory processing

Making comparisons of likeness and difference is nearly impossible for the person with processing (also called perceptual) deficits, and for this reason processing deficits frequently impact not only performance in reading, but math as well. Mercer (1997) identified three basic problem areas in the perceptual field that affect performance in mathematics: figure-ground differentiation, discrimination, and spatial orientation.

Figure-ground problems may cause difficulties in keeping individual problems separate from each other. The student may lose his place on a worksheet, confuse problem numbers with digits in the problem itself, or not finish the problem, etc.

Visual discrimination problems tend to cause inversions in number recognition, confusion among coins, confusion among operation symbols, confusion between the hands of the clock, and the like.

Auditory discrimination problems cause confusion in oral counting and among endings of number words, such as /fourteen/, /forty/, etc.

Spatial problems may cause reversals and affect the ability to write problems horizontally or vertically, to understand before-after concepts, to understand the importance of directionality which, in turn, could affect regrouping, and to align rows of numbers with varying digits. Additionally, the child may have problems putting decimals in the right place, using the number line, understanding positive and negative integers, etc. Also affected is the ability to tell time, to understand geometry, and any other mathematical concepts which have to do with spatial and temporal orientations and relationships.

– Visual memory

One hundred seventy-one children with a mean age of 10.08 years participated in a study by Kulp et al. This study, conducted at the Ohio State University College of Optometry in 2004 was designed to determine whether or not performance on tests of visual perception and visual memory could predict the children with poor current achievement in mathematics. Controls for age and verbal cognitive ability were included in all regression analyses because the failure to control for verbal ability has been a criticism of some literature investigating the relation between visual and academic skills.

Kulp et al. concluded: “visual perceptual ability, and particularly visual memory, should be considered to be amongst the skills that are significantly related to mathematics achievement.”

– Visuospatial memory

Szűcs and team (2013) of the University of Cambridge, UK set out to compare various potential theories of dyscalculia in more than a thousand 9-year-old children. The researchers found that children with dyscalculia showed poor visuospatial memory performance. For example, they performed poorly when they had to remember the locations of items in a spatial grid. In addition, dyscalculic children’s ability to resist distraction from irrelevant information was also weak. For example, on a task where they had to choose which of two animals was larger in real life they performed poorly when the real-life larger animal was smaller in its display size.

The findings challenge the notion that dyscalculia is characterized by problems with a specialized ‘number sense’ because this number sense was intact in this sample of children with dyscalculia.

– Working memory

Several studies have shown that children with mathematical difficulties underperform on tests of various aspects of working memory, while others found no differences between children with dyscalculia and typically developing children on working memory measures (Price & Ansari, 2013).

Mathematical skills and knowledge

Landerla et al. (2004) concluded that dyscalculia is the result of specific disabilities in basic numerical processing, rather than the consequence of deficits in other cognitive abilities.

There are many things in mathematics that the learner must learn to do, like, for example, the skills of counting, adding and subtracting, multiplication and division, applying place value and fractions, and reading time. There is much in math that one simply has to know and therefore has to learn, for example, many terms, definitions, symbols, theorems, and axioms. These are all things that the learner must know, not things that he must know how to do. A child, who does not know what a sphere is, will have to guess when confronted by twelve objects and the question, “Which of the above objects have the same shape as a sphere?”

How does math anxiety contribute to dyscalculia?

Mathematics anxiety (henceforth, referred to as ‘math anxiety’), is a negative reaction to math associated with negative emotions. Ashcraft and Faust (1994) define math anxiety as a feeling of tension, helplessness, mental disorganization and dread produced when one is required to manipulate numbers or to solve mathematical problems.

Reasons for math anxiety are usually classified as environmental, personal, or cognitive. Environmental causes can include negative experiences in math classes or with particular math teachers. Personal causes include low self-esteem, lack of confidence, and the influence of previous negative experiences with mathematics. Cognitive causes involve innate characteristics, being either low intelligence or simply poor cognitive abilities in mathematics (Rubinsten and Tannock, 2010). Math anxiety may influence students’ choices of courses in school and careers. Math anxiety can be specific: students may experience stress about particular math situations rather than all math situations. Math anxiety can be global: feel incompetent in all math situations and dislike all aspects of mathematics intensely. Extreme cases may lead to a phobia of mathematics and mathematical devices.

Math anxiety is distinguishable from other types of anxiety symptoms (i.e., math anxiety can exist in the absence of more general anxiety traits); and has a direct and deleterious effect on underlying cognitive processes as the individual performs a math task. This is especially true for individuals with dyscalculia — they may experience intense fear, which may cause an inability to learn math concepts and skills or perform well on math tests (Rubinsten and Tannock, 2010).

Brain differences

A study by Kadosh et al. (2007) found strong evidence that dyscalculia is caused by malformations in the right parietal lobe. Using neuronavigated transcranial magnetic stimulation (TMS) to stimulate the brain, scientists were able to bring about dyscalculia in normal subjects for a short time while the subjects completed a math task that involved comparing two digits, one larger in physical size than the other and the other larger numerically. For example, the subjects compared a 2 and a 4. The 2 was in a larger font than the 4 and subjects had to decide which digit was numerically larger.

The effect of TMS lasted only a few hundred milliseconds in the subjects and was brought on just at the point when the subject had to evaluate the numbers and decide which had the greater value or which was physically bigger. The test was designed to measure the subjects’ automatic processing of numbers and was rolled out to both people with the dysfunction and those without it.

The researchers found that non-dyscalculic participants displayed dyscalculic-like behavior in number processing only during TMS-induced neuronal activity disruptions to the right intraparietal sulcus. These findings were further validated by testing participants suffering from developmental dyscalculia. The results of the dyscalculic group reproduced the behavioral results obtained in non-dyscalculic volunteers during right parietal TMS, but not after left parietal TMS or sham stimulation.

A study by McCaskey et al. (2020) concluded that dyscalculia is accompanied by reduced gray and white matter volumes in number-related brain areas.

It should be noted, however, that brain differences do not equal brain disorders (Protopapas & Parrila, 2018):

Differences in brains are certain to exist whenever differences in behavior exist, including differences in ability and performance. Therefore, findings of brain differences do not constitute evidence for abnormality; rather, they simply document the neural substrate of the behavioral differences.

It should also be noted that the brain is plastic. New connections can form and the internal structure of the existing synapses can change. New neurons, also called nerve cells, are constantly being born, particularly in the learning and memory centers. Approximately 700 new neurons are daily being formed in the brain. Neurons die each day too, keeping the overall number more or less balanced, with a slow loss of cells as we age (Spalding, 2015). A person who becomes an expert in a specific domain will have growth in the areas of the brain that are involved with their particular skill.

The human brain is a powerhouse; the human brain has put a man on the moon, created the silicon chip that can do billions of calculations per second, invented red, yellow, and green lights to control millions of people in traffic every day and — believe it or not — found ways to see what goes on inside itself. The human brain itself tells us that it is most certainly capable of overcoming learning obstacles like dyscalculia, despite genetic influences and brain differences.

NEXT: Page 5: Intervention

Edublox offers live online tutoring to students with dyscalculia. Our students are in the United States, Canada, Australia, New Zealand, and elsewhere. Book a free consultation to discuss your child’s math learning needs.

Key takeaways

Authored by Susan du Plessis (B.A. Hons Psychology; B.D.) who has 30+ years’ experience in the LD field.
Medically reviewed by Dr. Zelda Strydom (MBChB) on May 21, 2021.
Next review due: May 21, 2023.

References and sources:

Ashcraft, M. H., & Faust, M. W. (1994). Mathematics anxiety and mental arithmetic performance: An exploratory investigation. Cognition Emotion 8, 97-125.

Elliott, J. G., & Grigorenko, E. L. (2014). The dyslexia debate. Cambridge: Cambridge University Press.

Hornigold, J. (2015). Dyscalculia pocketbook. Alresford, Hampshire: Teachers’ Pocketbooks.

Kadosh, R. C., & Walsh, V. (2007). Dyscalculia. Current Biology, 17(22).

Kadosh, R. C., Kadosh, K. C., Schuhmann, T., Kaas, A., Goebel, R., Henik, A., & Sack, A. T. (2007). Virtual dyscalculia induced by parietal-lobe TMS impairs automatic magnitude processing. Current Biology, 17(8), 689–693. 

Kere, J. (2014). The molecular genetics and neurobiology of developmental dyslexia as model of a complex phenotype. Biochemical and Biophysical Research Communications452(2), 236-243. https://doi.org/10.1016/j.bbrc.2014.07.102

Kulp, M. T. et al. (2004). Are visual perceptual skills related to mathematics ability in second through sixth grade children? Focus on Learning Problems in Mathematics, 26(4), 44-51.

Landerl, K., Bevan, A., & Butterworth, B. (2004). Developmental dyscalculia and basic numerical capacities: A study of 8-9-year-old students. Cognition, 93, 99-125.

Levy L. M., Reis I. L., & Grafman J. (1999). Metabolic abnormalities detected by 1H-MRS in dyscalculia and dysgraphia. Neurology, 53, 639-641.

McCaskey, U., von Aster, M., O’Gorman, R., & Kucian, K. (2020). Persistent differences in brain structure in developmental dyscalculia: A longitudinal morphometry study. Frontiers in Human Neuroscience14, 272. https://doi.org/10.3389/fnhum.2020.00272

Mercer, C. D. (1997). Students with learning disabilities, 5th ed. Upper Saddle River, NJ: Merrill.

Price, G., & Ansari, D. (2013). Dyscalculia: Characteristics, causes, and treatments. Numeracy, 6(1).

Protopapas, A., & Parrila, R. (2018). Is Dyslexia a Brain Disorder? Brain sciences, 8(4). https://doi.org/10.3390/brainsci8040061

Rubinsten, O., & Tannock, R. (2010). Mathematics anxiety in children with developmental dyscalculia. Behavioral and Brain Functions  6, 46. https://doi.org/10.1186/1744-9081-6-46

Shalev, R. S. (2007). Prevalence of developmental dyscalculia. In D. B. Berch & M. M. M. Mazzocco (Eds.), Why is math so hard for some children? The nature and origins of mathematical learning difficulties and disabilities (pp. 49–60). Baltimore, MD: Paul H. Brooks Publishing Co.

Siegel, L. S., & Ryan, E. B. (1989). The development of working memory in normally achieving and subtypes of
learning disabled children. Child Development, 60, 973–980.

Spalding K. L., Bergmann O., Alkass K., Bernard S., Salehpour M., Huttner H.B., … Frisén J. (2013). Dynamics of hippocampal neurogenesis in adult humans. Cell153(6), 1219-1227.

Stein, J. (2018). The magnocellular theory of developmental dyslexia. In T. Lachmann, & T. Weis (Eds.). Reading and dyslexia (pp. 97-128). Cham, Switzerland: Springer.

Szűcs, D., Devine, A., Soltesz, F., Nobes, A., & Gabriel, F. (2013). Developmental dyscalculia is related to visuo-spatial memory and inhibition impairment. Cortex49(10), 2674-2688. https://doi.org/10.1016/j.cortex.2013.06.007