A Peek Inside the Reading Brain

Neural Processes Involved in Reading

For many adults, after learning to read in childhood and reading every day from then on, making meaning from marks on a page can feel as natural as breathing. But educators know that reading, and learning to read, is not that simple. Young, developing minds need careful instruction to build reading skills. Not every student learns at the same pace or requires the same supports, but each student does rely on complex neural processes to learn to read. Understanding exactly how the brain takes on this daunting task can help you, as an educator, make the most of every moment spent with students.

There’s an extensive amount of research on the cognitive processes involved in learning to read, and there’s still so much to learn. At the bottom of this blog, you’ll find a link to download an interactive eBook on the subject, with contributions from our Applied Learning Sciences team. To give you an overview of some of the most important research in the eBook, we’ve compiled a list. Here are just a few important facts we know about the neural activity and processes involved in reading that you can use to support your students with stronger instruction:

Reading is a complex, networked, and rapid set of processes.

When thinking about how cognitive science can inform instruction, it’s important to remember that the neural processes involved in reading are not simple to map out — a lot is happening in the brain at once, and it’s all too easy to oversimplify the activity in an attempt to understand it.

Reading involves areas throughout the entire brain.

For example, it might be easy to think of a single part of the brain at work when we read, but that’s not the case. The processes involved in reading require many parts of the brain, and multiple areas are working at once to achieve the complex tasks.

Developing those complex neural networks requires time and practice.

Students who are just learning to read haven’t developed the complex neural networks mentioned above. In order to achieve this, they need to undergo a positive cycle of practice, which involves reading more, wanting to read more, and being able to read more. This cycle helps build the neural circuitry and efficiencies found in proficient readers.

Extensive, explicit instruction in phonological awareness increases activation of brain areas needed for reading.

It’s important for young learners to continually read, but it’s also important for educators to provide instruction that is compatible with brain activity. Research has shown that a focus on phonics can go a long way in activating the parts of the brain required for expert reading.

Routine practice and instruction supports the development of automaticity.

Positive cycles of practice and extensive, explicit instruction in phonological awareness and phonics should ultimately build automaticity. This is key, because automaticity frees up cognitive capacity for skills required of readers down the road, like higher-order reading processes, such as comprehending complex, abstract text.

Not every child will need the same supports to learn to read.

Understanding all of these knowns in learning science research is important, but it’s also important to remember that not every student will need the same supports in their reading journey: students with language-based disabilities experience different challenges. Researchers have uncovered evidence of differences in both the structures and activity of various areas in the brain among some people with language-based disabilities.

For students who have dyslexia, extensive, direct, and systematic instruction in letters and their corresponding sounds will be especially effective.

Cognitive science can be particularly important when supporting students with language-based disabilities, because it can help us understand the science behind the roadblocks these students are facing in their reading experiences, and offer up solutions, such as extensive, direct, and systematic instruction.

Reading and writing draw on many of the same cognitive processes and areas of the brain.

Just like with reading instruction, an understanding of neural processes can also inform writing instruction. Research has shown that reading and writing are enhanced when taught simultaneously, in ways that support both processes. Writing can also contribute to the positive, self-reinforcing cycle of growth mentioned earlier.

For a deeper dive into each of the concepts listed above, in addition to more research around neural processes and reading, download the full interactive eBook here, or below:

For more on learning science, see:

References:

Barbey, A. K. (2017). Network neuroscience theory of human intelligence. Trends in cognitive sciences.

Berninger, V. W., Nielsen, K. H., Abbott, R. D., Wijsman, E., & Raskind, W. (2008). Writing problems in developmental dyslexia: Under-recognized and under-treated. Journal of school psychology, 46(1), 1–21.

Brown, W. E., Eliez, S., Menon, V., Rumsey, J. M., White, C. D., & Reiss, A. L. (2001). Preliminary evidence of widespread morphological variations of the brain in dyslexia. Neurology, 56(6), 781–783.

Buchweitz, A., Mason, R. A., Tomitch, L., & Just, M. A. (2009). Brain activation for reading and listening comprehension: An fMRI study of modality effects and individual differences in language comprehension. Psychology & neuroscience, 2(2), 111.

Dehaene, S. (2009). Reading in the brain: The new science of how we read. Penguin.

Erhard, K., Kessler, F., Neumann, N., Ortheil, H. J., & Lotze, M. (2014). Professional training in creative writing is associated with enhanced fronto-striatal activity in a literary text continuation task. NeuroImage, 100, 15–23.

Graham, S., & Hebert, M. (2010). Writing to read: Evidence of how writing can improve reading. Washington, DC: Alliance for Excellent Education.

Mishra, R., & Mohan, A. (2016). Developments in effective teaching strategies for students with dyslexia: A review of literature and research. IJAR, 2(6), 206–209.

Ness, M. K. (2016). Reading comprehension strategies in secondary content area classrooms: Teacher use of and attitudes towards reading comprehension instruction. Reading Horizons (Online), 55(1), 58.

Raschle, N. M., Chang, M., & Gaab, N. (2011). Structural brain alterations associated with dyslexia predate reading onset. Neuroimage, 57(3), 742–749.

Rello, L., Baeza-Yates, R., Dempere-Marco, L., & Saggion, H. (2013, September). Frequent words improve readability and short words improve understandability for people with dyslexia. In IFIP Conference on Human-Computer Interaction(pp. 203–219). Springer, Berlin, Heidelberg.

Rupley, W. H., Blair, T. R., & Nichols, W. D. (2009). Effective reading instruction for struggling readers: The role of direct/explicit teaching. Reading & Writing Quarterly, 25(2–3), 125–138.

Slavin, Robert E., Alan Cheung, Cynthia Groff, and Cynthia Lake. “Effective reading programs for middle and high schools: A best evidence synthesis.” Reading Research Quarterly 43, no. 3 (2008): 290–322.

Suggate, S. P. (2016). A meta-analysis of the long-term effects of phonemic awareness, phonics, fluency, and reading comprehension interventions. Journal of learning disabilities, 49(1), 77–96.

Torgesen, J. K., Houston, D. D., Rissman, L. M., Decker, S. M., Roberts, G., Vaughn, S., Wexler, J., Francis, D.J., Rivera, M.O. & Lesaux, N. (2017). Academic Literacy Instruction for Adolescents: A Guidance Document from the Center on Instruction. Center on Instruction.

Torgesen, Joseph K., Debra D. Houston, Lila M. Rissman, Susan M. Decker, Greg Roberts, Sharon Vaughn, Jade Wexler, David J. Francis, Mabel O. Rivera, and Nonie Lesaux.

Wehbe, L., Murphy, B., Talukdar, P., Fyshe, A., Ramdas, A., & Mitchell, T. (2014). Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses. PloS one, 9(11), e112575.

Yoncheva, Y. N., Wise, J., & McCandliss, B. (2015). Hemispheric specialization for visual words is shaped by attention to sublexical units during initial learning. Brain and language, 145, 23–33.