Jill Kerper Mora

Neuroscience Research: The Reading Brain

In his book The Reading Brain (2009), French neurolinguist Stanislas Dehaene describes two pathways to the semantic region of the brain. One is through phonology of a word as decoded through orthography, the product of visual representations of language sounds (letters) being translated into sounds (in the brain) to render a pronounced word. The other pathway is where the visual image of the word is interpreted directly into meaning as a visual unit without “sounding out” the word. Dehaene proposes that these two pathways operate in the brain simultaneously, but one “gets there” to the semantic region before the other to trigger meaning.

We teachers must ask these questions:  What happens when there is no meaning for the word in the reader’s mental lexicon? Or what happens when the word cannot be understood because the word’s spelling alone does not provide a cue to its meaning within the sentence (context)? For example, the word “bow” has different meanings depending on how it is pronounced. Bowers and Bowers (2017) call words that can only be accurately decoded without reference to their meaning (semantics) “context-dependent” words. This is a term that describes 16% of words in English.

What should a teacher have an emergent reader do when s/he mispronounces the word incorrectly to render its correct meaning in the context of the sentence? Compare the meaning of b-o-w in these two sentences: “I took a bow at the end of my performance…” versus “He shot an arrow from his bow.” A teacher should cue the student to problem-solve this loss of comprehension by looking at the sentence and thinking of the context (language) where the word is used in order to comprehend its meaning. I have not seen any brain research that suggests that this sort of cueing disrupts brain functioning in any way, shape, or form.

Dual Route Models of Reading

Dehaene (2009) describes two parallel paths in the brain to word meaning. One is the spelling-to-sound route and the other is the direct-lexical route. Dehaene states that the route that the brain uses to determine the meaning of a word depends on the word’s relationship with its pronunciation of different types of words:

“These brain imaging results dovetail nicely with conclusions from a great many psychological studies of reading. Do we have to pronounce words mentally before we understand them? Or can we move straight from a letter string to it meaning and skip the pronunciation stage? Both may happen, but it all depends on the type of word.” (p. 115-116)

The spelling-to-sound route is taken in the brain by “… Infrequently used words and neologisms move along a phonological route that converts letter strings into speech sounds.”  The direct-lexical route is taken by “… “frequently used words, and those whose spelling does not correspond to their pronunciation, are recognized via a mental lexicon that allows us to access their identity and meaning.” (p. 104).

Dehaene identifies a “letterbox region” in the brain that processes visual information from words’ orthography for both routes of processing, which operate simultaneously and in parallel:

“The brain’s networks for meaning, however, are not limited to simply processing single words…. The process that allows our neurons to snap together and “make sense” remains utterly mysterious. We do know, however, that meaning cannot be confined to only a few brain regions and probably depends on vast arrays of neurons distributed throughout the cortex. All visual stimuli are channeled to the left letterbox region… This package of visual information is then shuttled on one of two main routes: one that converts it into sound, the other into meaning. Both routes operate simultaneously and in parallel–one or the other gets the upper hand, depending on the word’s regularity.” (p. 119)

There is a large body of research from neuroscience that supports the notion that processing of the meaning of written words can take dual routes in the brain depending on the reader’s familiarity with the meaning of the word. Yes, emergent readers need to be able to sound out the words of a text. Yes, readers must be taught how to sound out words, but teachers cannot assume that phonological decoding is the route in the reader’s brain that will “get the upper hand,” as Dehaene (2009) describes the process in the brain. The simultaneous phonological route and semantic route processing of a word or determine the “division of labor” between the reader’s brain’s use of grapheme-phoneme (orthographic) information and semantic knowledge. The brain of the reader determines the “primary route” to word meaning, not the teacher. An interpretation and implication of this research is support for teachers to guide students toward use of these dual routes to word meaning.

The neuroscience on reading in the brain has resulted in the reappraisal of models of reading. For example, Binder et al (2005: 678) make the following points about reading models to emphasize the possible neglect of the factor of semantics.

• Like the parallel dual-route model, the triangle model assumes that all words are processed by the entire system, so there should be no difference in activation patterns for regular and irregular words. Also, like the parallel dual-route model, the triangle model predicts little, if any, activation favoring nonwords over words, since all stimuli activate the orthographic and phonological units.
• Thus, the parallel dual-route and triangle models make very similar predictions about the effects of lexicality and regularity of pronunciation on brain activity. The principal difference between these models lies in whether the pronunciation of words is facilitated by word codes (the orthographic and phonological lexicons) or by semantic code.
• In the triangle model, on the other hand, these areas process semantic codes and might therefore be sensitive to concreteness/imageability, taxonomic category, prototypicality, level of specificity, and other semantic factors.
• The chief distinction between these theories lies in whether the indirect pathway to phonology is mediated by word codes or by semantic codes. The available evidence suggests that these regions are modulated by semantic factors … arguing for a semantic interpretation.

In a critique of current reading research and practice, David Share (2008) contends “… that the extreme ambiguity of English spelling–sound correspondence has confined reading science to an insular, Anglocentric research agenda addressing theoretical and applied issues with limited relevance for a universal science of reading.

According to Share, the dual route model of reading “…accounts for a range of English-language findings, but it is ill-equipped to serve the interests of a universal science of reading chiefly because it overlooks a fundamental unfamiliar-to-familiar and novice-to-expert dualism applicable to all words and readers in all orthographies.” 

Effects of Orthographies in Models of Reading

Bowers and Bowers (2017) point out the following orthographic challenges attributable to English phonology and morphology:

• English spelling is based on morphology, etymology and phonology. Phonological challenges stem from 20 vowel phonemes represented by 5 vowel letters.
• Letter-sound correspondences often depend on the surrounding letters, which requires sub-lexical phonetic analysis. The sub-lexical route generates the wrong phonological transcription for 16% of 8,000 monosyllabic words.
• Only 84% of these monosyllabic words are regular. Common words are more irregular than less frequently used words. The different spellings of <to>, <too>, and <two> is an example of English spellings code for distinctions in meaning.
• English use consistent spellings across words with varied pronunciations. For example, the words pronunciations of the base <sign>: signal, signature, design, designate.
• Morphemic spelling is used to signal grammar and syntax. For example, the –ed ending for past tense is not a phonetic spelling. The –ed has three different pronunciations: pushed, shoved, shouted.
• Silent letters have a semantic function. For example, the single, silent <e> serves as an orthographic marker letter for the plural cancelling function in words like <please> or <nurse>.

Compare the complexities of English orthography to Spanish orthography based on the phonology and morphology of Spanish (Ardila & Cuetos, 2016): 

• The average length of Spanish words is 8.76 letters. 60% of all Spanish words have between 7 to 10 letters. The majority of Spanish words are three syllable words (trisílabas).
• 51% of the syllables in Spanish words are consonant-vowel CV syllables. 11% are vowel-consonant VC words. 88% of Spanish words are combinations of CV, CVC, V, or VC syllables.
• 75% of Spanish words are stressed on the second to the last syllable (palabras graves). 19% of Spanish words are stressed on the last syllable (palabras agudas).
• 3% of Spanish words are stressed on the third from the last syllable (palabras esdrújulas). Palabras esdrújulas always have a written accent mark over the stressed syllable.
• 95% of all Spanish nouns and adjectives are palabras graves that end in a vowel and are stressed on the next to the last syllable.

Neuroscience and Meaning Making

As researchers and as practitioners, it is important to recognize the concept of triangulation of data sources in research studies (Bellido-García, et al., 2022; Hoffman, Ralph & Woolhams, 2015). The extensive research base of miscue analysis performed on oral reading performance and then overlaid with eye movement data provides insights into how readers process text during meaning making (Goodman & Burke, 1973). A third point of triangulation is provided through neuroanatomical brain research that uses functional magnetic resonance imaging (fMRI) to identify activation of regions in the brain during reading (Hoffmann, et. al, 2015; Perfetti & Stafura, 2014; Sheriston et al., 2016).

“Dual-route models hold that all words can be read either via grapheme-to-phoneme rules or through access to orthographic and phonological lexica that are distinct from knowledge of word meaning. In contrast, the Triangle Model proposes that semantic knowledge plays an integral part in pronouncing words correctly. We were able to map specific elements of this cognitive model onto different cortical regions, thereby providing a direct link between cognitive theorizing and neural implementation. Specifically, we provide insights into the division of labor between semantic and phonological processes in supporting reading aloud, which has been a long-standing source of controversy among cognitive models. (p. E3719).

Neuroscientist Steven L. Strauss (2009; 2013) argues that fMRI is an inappropriate tool to study reading and dyslexia and that the neuroscientific study of reading and dyslexia needs to incorporate the psycholinguistic nature of meaning construction and its neuroanatomic foundation in cortical–subcortical circuitry. Strauss describes how the reader may not fixate on a word long enough to have fully visualized all of the letters the word contains. Letter–sound mappings differ significantly from what is assumed in fMRI-based research. Eye movement studies reveal that proficient readers do not fixate on fully one third of the words in a visual text display. Therefore, having the reader fixate again on a miscued word may result in more accurate decoding. The spatial and temporal resolution capacity of fMRI is adequate for identifying letter–sound brain regions, but not for identifying meaning-construction neuroanatomy.

Dr. Strauss, together with Ken Goodman and Eric Paulson (2009), claim that reading must be described within a meaning construction psychological paradigm. It is an executive process beyond the technical resolution capacity of fMRI. Its neuroanatomic basis lies in feed-forward cortical–subcortical tracts. Meaning-construction relies on psycholinguistic strategies far more efficient and effective than letter–sound conversion. Different conclusions from neuroscientists and neurolinguistics about the implications of brain research for the pedagogy of reading and writing instruction demand caution in making pronouncements and sweeping claims about what “the brain research says…” and argues against rejection or marginalization of bodies of scientific data that inform literacy instruction (van Heuven & Dijkstra, 2010). Paulson (2008) found that 20%-40% are not fixated on during oral reading performance and that the percentage of miscues made on fixated vs. non-fixated words is comparable. Consequently, he concluded that miscues were not attributable to “missed” or “skipped ” words. Rather, the eyes merely deliver raw data to the brain, while the brain decides what needs attending to in order to derive meaning from the text. This suggests that eye movements are largely controlled by the recognition of meaning in order to generate reliable inferences.

Following an explanation of the bottom-up processing theories and the top-down processing theories of reading in the brain, Strauss et al., (2009) state…

“… a meaning-centered, whole language model of reading is scientifically superior to the phonological processing model from the standpoint of neurobiology. As a scientific paradigm, whole language is based on a psycholinguistic model of the reading process, along with corresponding methods of classroom teaching and assessment. The model characterizes reading as an active process of meaning-construction brought about via the reader’s selective testing of meaning-based predictions against confirmatory or disconfirmatory textual and non-textual material. Confirmed predictions are incorporated into the reader’s expanding mental representation of meaning. Disconfirmed predictions are modified or discarded. Inconclusive predictions are tentative and await further confirmatory or disconfirmatory evidence … Neuroimaging findings are entirely consistent with the whole language model, and in no way distinguish the whole language model from the phonological processing model. (p. 022)

Neuroscientist Steven Strauss (2010) concludes that…

On the other hand, from the constructivist standpoint, the phonological processing model emphasizes biological aspects of reading to the exclusion of social, cultural, and certain psycholinguistic aspects. More problematically, the constructivists would argue that the biological emphasis in the phonological processing model is artificially narrow. It emphasizes specific brain localizations where certain processes occur, but not the global brain organization that explains why or how these processes occur… Neuroimaging cannot by itself decide the question of which cognitive functions play a role in reading and which do not. Only an independent theory of reading based on studies of reading behaviors and their patterns of development can adjudicate that. (p. 89) 

Furthermore, Strauss, Goodman and Paulson (2009) state the following: 

In order to better understand how contemporary neuroscience bears on models of the reading process, we therefore turned from neuroimaging studies to current research on how the cortical, “thinking” areas of the brain interact with the brain’s deeper, sensory processing structures. The emerging concepts from this research clearly indicate that the higher cortical structures control the transmission of information from the deeper structures…The psychological interpretation of this neuroanatomic arrangement is that the cortex selects evidence to confirm or disconfirm its predictions. It anticipates what will be seen and heard using knowledge stored in memory. Both this new neuroanatomical view and its psychological reflection are consistent with a transactional sociopsycholinguistic model of reading. Drawing on extensive comparisons of expected and observed responses from oral reading miscue studies, this model of reading emphasizes the fundamental importance of effective and efficient prediction and confirmation in the construction of meaning. Eye movement analysis, a widely used reading research tool for over a century, simultaneously supports the emerging neuroscientific view of cortical control and the meaning construction model of reading. Since the most conspicuous motor behavior in silent reading is eye movement, studying it allows us to “see” the silent reading process. When combined with miscue analysis from oral reading, it is clear that cortical instructions tell the eyes where to look for cues from the signal, lexico-grammatical, and semantic levels of language. We conclude that emerging neuroscience provides evidence for the meaning construction view of reading, and that the transactional socio-psycholinguistic character of reading is an instantiation of the memory-prediction model of brain function. (p. 021)

These researchers’ assessment of the findings the triangulation databases generated from miscue analysis research, eye movement research and neuroscience research, in my opinion, provide strong evidence to support instructional strategies and assessment procedures that address readers’ utilization of multiple subsystems of language (cueing system) in meaning making in oral and silent reading. Subsequently, Carreiras and colleagues (2014) affirm the legitimacy of this interpretation of neuroscience investigations on word recognition processes using a variety of increasingly sophisticated technological methods of data collection. 

“There is ample evidence that high-level information, such as phonological [80,81] morphological [82,83], and lexical information [84], influences very early aspects of the overall visual word recognition process. This evidence challenges the traditional claim of temporal and structural modularity, according to which printed words are principally identified on the basis of orthographic information alone in skilled readers (the underlying logic behind some researchers’ concept of the VWFA), with phonological and semantic information retrieved subsequently.” (p. 91)

Carreiras et al. (2014) also reiterate a number of outstanding questions that merit further investigation by neuroscientists such as how the interactivity and interconnectivity of visual word recognition processes are language-specific and how these processes work within the brain of bilingual and multilingual learners.   

A Neuroscience View of Language Processing in the Brain

There is a theoretical construct in neuroscience research termed “linguistic prediction” that describes how language is processed in the brain to achieve comprehension. Kroczek and Gunter (2017) give a description of the mechanism of prediction in comprehension of both speech and print:

Human nature strongly relates to making predictions in various domains of cognitive processing. In communication, more specifically the domain of language, predictions have been shown to affect the processing of phonological and visual word forms (but see), semantic categories, syntactic structure and event schemes. Importantly, they are tightly coupled to incoming information, as the difference between a top-down prediction and the actual input updates representations at higher hierarchical levels. By this mechanism, predictions remain adapted to the environment. For language, predictions are therefore shaped by language use itself. Language users can hence be described as experts with highly adapted predictions about the form and structure of their native language. These predictions mirror the rules and statistical regularities of the respective language and can be thought of as linguistic priors. (p. 1)

Mazoyer, et. al. (1993) explain the neural architecture of the cortical representation of speech by identifying processing systems into five categories of speech stimuli. 

To perceive and understand speech, one must deal with the acoustical, phonological, lexical, prosodic, syntactic and conceptual information conveyed by the signal. The purpose of our study is to evaluate the existence in the human brain, of specialized cerebral regions corresponding to these levels of linguistic analysis. (p. 468)

Finally, what view of the neural architecture of speech processing do our results imply? We believe that the speech processing system of the human brain is not organized, at the neural level, in a hierarchy of areas that successively and automatically come into play, whenever they receive an adequately structured stimulus. Rather, speech processing seems to imply the coordination of a network of areas, each of which may be specialized in one aspect of speech processing, but requires coherent support from the others in order to reach a high level of activation. (p. 476)

Heilbron et al. (2020) researched a hierarchy of linguistic predictions during natural language comprehension. They found that neural responses to speech are modulated by continuous linguistic predictions.

Theorists propose that the brain constantly generates implicit predictions that guide information processing. During language comprehension, such predictions have indeed been observed, but it remains disputed under which conditions and at which processing level these predictions occur. Here, we address both questions by analyzing brain recordings of participants listening to audiobooks, and using a deep neural network to quantify the predictions evoked by the story. We find that brain responses are continuously modulated by linguistic predictions. We observe predictions at the level of meaning, grammar, words, and speech sounds, and find that high-level predictions can inform low-level ones. These results establish the predictive nature of language processing, demonstrating that the brain spontaneously predicts upcoming language at multiple levels of abstraction. We first tested for evidence for linguistic prediction in general. We reasoned that, if the brain is constantly predicting upcoming language, neural responses to words should be sensitive to violations of contextual predictions, yielding “prediction error” signals which are considered a hallmark of predictive processing. (p. 1-2)

Brain research studies into signal processing systems, identified more commonly as language subsystems, reinforce the notion of “cueing systems” that have different, but mentally coordinated roles across regions of the brain, in speech comprehension as well as in comprehension of continuous text. Also see Goodman, Fries and Strauss (2016). 

Click here for a bibliography of neuroscience research studies on linguistic prediction.

Application of Neuroscience to Biliteracy Instruction

Dehaene (2009:104) identifies two pathways to word recognition: The spelling-to-sound route and the direct-lexical route. The distinction between the two pathways is based on the word that is being decoded. “Infrequently used words and neologisms move along a phonological route that converts letter strings into speech sound… Frequently used words, and those whose spelling does not correspond to their pronunciation, are recognized via a mental lexicon that allows us to access their identity and meaning.” There are three aspects of a word: 1) el léxico fonológico, which refers to the word as it is pronounced in oral language 2) el léxico ortográfico, or the word as it is spelled or encoded through letter-sound correspondence and spelling patterns, and 3) el léxico semantic, which is the meaning the word conveys in its function as a name or label for an object or concept. This is called the Triangle Model of reading (Dehaene, 2014).

The Triangle Model provides a framework for planning and implementing phonics instruction in Spanish and English to ensure that the teacher address the three aspects of a word during instruction, while avoiding working with words in isolation and out of context (Cevoli, et al., 2022; Coltheart, 2006; Liversedge et al., 2012). This contextualized teaching is effective because often the semantics (meaning) of a word resides in its function within a syntactic structure of a sentence. For example, consider the difference in meaning between these two phrases: Un hombre pobre; un pobre hombre. The positioning of the noun before the adjective versus the adjective before the noun determines the meaning of the word “pobre.” Syntax occurs at the phrase and the sentence levels, which make the isolated word undefined in the mental lexicon of the reader. Consequently, a common word may be semantically context dependent. 

Wong, et al. (2016) and Fedeli, et al. (2021) explain the impact of different types of learning experiences on the networking of the bilingual brain. In a comprehensive review of the literature on experiences and the bilingual brain, Wong and colleagues (2016) make this observation: “While the general language network may be similar across languages and even between languages used within a bilingual individual, there appear to be more variations in the way these subnetworks for the component processes are engaged and assembled. For instance, simultaneous acquisition of reading in two orthographies lends itself to divergent pathways for reading in each language, whereas sequential reading acquisition gives rise to largely overlapping reading circuits in both languages. (p. 3)

Wong, et al. (2016) explain that cognitive models of brain activity differentiate knowledge forms or representations of language that are processed in different regions of the brain. For example, these researchers found that language processes that involve more declarative memory rather than more rule-like aspects of language are processed in different cerebral zones. Vocabulary knowledge and word phonology both involve arbitrary mappings between word labels and their meanings. This contrasts with syntax and grammatical knowledge that constitute procedural forms of memory that involve rule-based learning. Consequently, neuroimaging finds clusters of activity related to various language tasks, indicating cluster-to-function subnetworks related to metalinguistic processing. Further, Wong and colleagues assert that these neural structure and function relationships in the brain are affected by one’s linguistic experiences.

The distinction is made in this neuroscience research between declarative (“knowing that”) and procedural (“knowing how”) knowledge. Declarative knowledge is defined as factual knowledge, whereas procedural knowledge is defined as the knowledge of specific functions and procedures to perform a complex process, task, or activity. An implication of these findings from neuroscience is that teachers must recognize that their understanding of how linguistic tasks in reading comprehension are processed in the brain should prompt them to be skeptical of policy proposals regarding the use or non-use of instructional strategies that may not reflect full and accurate research evidence of differentiated brain functions. This is especially true for prohibitions against guiding emergent readers in the use of multiple cueing systems: grapho-phonic, semantics and syntax. Knowledge for performing each of these linguistic acts is processed in different brain regions, each of which needs to be developed for learners to achieve competency in literacy.

Teachers cannot determine how the brain of an individual student processes text. It is unwise for teachers to adopt or fail to utilize a certain instructional strategy based on a belief that they can determine which pathways in the brain a students should use for making meaning from text. This is why policies restricting teachers’ use of certain feedback and guidance during oral reading with students or as assessment tools are counterproductive. See for example the proposed bans on “three-cueing” strategies being promoted by certain proponents of the Science of Reading through state legislative initiatives. Such policies are not based on science.

Fedeli, et al. (2021) draw this conclusion from their research: “Whereas input leads to activation of a single language system in monolinguals, in individuals who speak (or sign) in two languages both systems are simultaneously activated in production and comprehension automatically. L2 Exposure, L2 Proficiency, and L2 AoA (in interaction with Exposure) differentially affected the structural organization of linguistic pathways and the communication between regions relevant for language control. These results are in line with established brain models of dual-language representation and monitoring.” (p. 104978)

The issue in teaching for transfer in biliteracy development then becomes the analysis to distinguish between the concepts and literacy skills that are universal across the languages and are therefore transferable, and the concepts and skills that are language specific (Dufour & Kroll, 1993; Kroll & Stewart, 1994). A sequence of instruction for initial Spanish literacy is based on the regularities of the grapheme-phoneme (letter-sound) relationships in Spanish orthography (Dehaene, 2015). Priority is given in instruction to teaching letters and letter-sound correspondences that are more frequent and more regular before teaching the more usual, less regular, and more complex letter-sound relationships.

Metalinguistic Learning in the Bilingual Brain

Research into the acquisition of Spanish literacy affirms the constructs that are investigated and validated through studies of learners’ neurological processing of Spanish text. Cuetos and Suárez-Coalla (2009) describe the operation of the two pathways in the brain for processing words in Spanish text as compared to English text, noting the impact of the transparency of the orthography of the two languages: 

The relationship between written words and their pronunciation varies considerably among different orthographic systems, and these variations have repercussions on learning to read. Children whose languages have deep orthographies must learn to pronounce larger units, such as rhymes, morphemes, or whole words, to achieve the correct pronunciation of some words. However, children whose languages have transparent orthographies need only learn to pronounce graphemes to be able to read any word. In this study, the reading evolution of Spanish-speaking children was investigated for the purpose of discovering when and for what types of stimuli lexical information is used in Spanish. Five- to 10-year-old children were presented with lists of stimuli in which lexicality, frequency, and length were manipulated. The results in terms of reading accuracy and speed showed that the influence of stimulus length is great in the early grades and later diminishes, and just the opposite is the case for lexicality and frequency. These data suggest that reading acquisition in Spanish constitutes a continuum that ranges from phonological recoding to the use of lexical strategies, and that this transition is made at a very early stage, at least for the most frequent words. (p. 583)

This variability in orthographic systems has important effects on reading strategies: whereas readers of transparent systems can read each letter without having to attend to the whole word, readers of deep systems often find themselves obligated to consider the word as a whole to arrive at the correct pronunciation. (p. 583) However, despite the simplicity of the Spanish orthography, and even though Spanish speakers can read using only grapheme–phoneme correspondence, there is considerable evidence that they also use units larger than the grapheme… readers of transparent languages also read many words globally for speed and efficiency. (p. 584)

English-speaking children must develop intermediate representations between the grapheme and the word (i.e., rhymes, syllables, morphemes) to be able to deal with the irregularities of the system. As the self-teaching hypothesis has shown (Share, 1995), when the child correctly reads a word over and over again, she ends up forming a representation of that word in her orthographic lexicon, whether or not she has acquired all the grapheme–phoneme rules. Likewise, the reading of constantly repeated groups of letters involves forming representations of those groups of graphemes. Over time, the increased frequency of experience in phonological coding, together with an expanding set of words that the learner has encountered and coded, support the child’s capacity to grasp useful regularities about spelling patterns and spelling–sound mappings, which entail collections of letters. (p. 586)

The change in the types of errors children make as they advance from grade to grade confirms this progressive switch from sublexical to lexical reading. In keeping with this theory, and taking into account the characteristics of the Spanish language, words can be successfully decoded from a very early age, which makes it possible to get information about their orthographic form, enabling at least the most frequent words to enter the orthographic lexicon. Therefore, the existence and use of orthographic representations probably begins to develop from very early on, alongside sublexical reading for unknown words and pseudo words. The lexical route begins to develop rapidly, but the sublexical route is not abandoned. We are speaking, therefore, of a developmental progression that does not have specific stages characterized by a single process, but rather one in which both processes coexist, are functional, and are used depending on the characteristics of the stimulus to be read. (p. 593-4)

The implications of these findings from neuroscience for biliteracy instruction are that Spanish phonics instruction is essential for developing reading fluency and comprehension, while also recognizing that phonological processing and orthographic mapping together develop dual routes for word recognition. The research from Spanish-speaking countries into “el cerebro lector” confirm the differences between literacy acquisition in Spanish that must be taken into account when educators make decisions regarding  instructional approaches for Spanish-English literacy learners.

Neurological Effects of Bilingual Language Exposure

Kovelman and colleagues (2008a) describe the relationship between reading and language development as a function of age of first intensive, systematic, and maintained bilingual language exposure. These researchers’ findings include the following: 

“Early bilingual exposure is best for dual language reading development, and it may afford such a powerful positive impact on reading and language development that it may possibly ameliorate the negative effect of low SES on literacy. Young bilingual children exposed to two languages from birth achieve each and every major linguistic milestone in their one language, on the same time table as their other language, and both languages proceed on the identical time table as observed in the monolingual child.” (p. 204)

To be clear, the specific ages of first bilingual exposure that we study correspond to major periods of brain development that have been linked to key language and cognitive milestones and sensitivities in child development… Particular brain changes enable the child to be better capable of processing, storing, and remembering information in their environment and thus to better direct and control their thoughts and behaviors (p. 205)

Our goal is to explore the relationship between reading and language development as a function of age of first intensive, systematic, and maintained bilingual language exposure. Multiple aspects of bilingual language competence are considered in this investigation, including phonological, semantic, and morphosyntactic development. Metalinguistic awareness has been shown to develop faster and more effectively in young bilinguals as compared to young monolinguals. Bilinguals learning to read in their two languages might also have an advantage in grasping the symbolic nature of sound-to-letter correspondence, as a plethora of sounds in their two languages corresponds in a very multifaceted manner to their two writing systems. The researchers’ findings are suggestive of the possibility that bilingual children who receive at least some formal and systematic reading instruction in of BOTH their languages will have a phonological advantage over their monolingual peers schooled in English only, and that this bilingual phonological advantage can persist into grade 1. Thus, bilingual reading instruction alone in itself might be an important factor in boosting phonological awareness competence.” (p. 206)

Kovelman, et. al. (2008a) found an advantage for bilingual learners who had exposure to both languages before age three. This advantage manifested as monolingual-levels of literacy competence in both languages during students’ progression through elementary school grades. The researchers observed a strong relationship between the cumulative score of bilingual language competence, expression, proficiency, including multiple aspects of semantic, morphological and syntactic production, and reading competence. Their findings support the idea that language competence as a whole correlates with reading proficiency. 

Furthermore, in another study, Kovelman et al. (2008b) found what they call a “bilingual neural signature” in the brain. 

“Presently, most developmental psycholinguistic research with young children supports the view that young bilinguals are developing two differentiated linguistic systems from early in infancy…Thus, the present study provides neural evidence suggesting that there may be a functional separation of a bilingual’s two languages in one brain based on the formal linguistic properties of each given languages.” (p. 166)

“As such, in our participants, their bilingual brains honored the grammatical distinction between their two languages. Thus, although adult bilinguals may show behavioral evidence of cross-linguistic interference (Hernandez et al., 1994), early bilinguals with extensive dual-language exposure may, nonetheless, develop predominantly differentiated representations for each of their languages in one brain. That the bilinguals showed processing differences in English versus Spanish, which were specifically predicted from differences in the linguistic structures typical of English versus Spanish, lends support to the hypothesis that bilinguals can develop two differentiated, monolingual-like, linguistic systems in one brain.” (p. 165)

This developmental psycholinguistic research has important implications for biliteracy/dual language programs, as well as for English medium educators of multilingual learners. Notably, these research findings affirm the value of additive perspectives on bilingualism and biliteracy development. One aspect of bilingualism in the brain that these researchers noted is that the neural functions in the brain in the bilingual’s two languages is based on the formal linguistic properties of the given language. This evidence supports approaches to multilingual learner instruction that differentiate between universal, transferrable literacy skills that apply equally to both languages, as opposed to skills that are language-specific and text-specific. See the Common Core Standards Linguistic Augmentation (San Diego County Office of Education, 2012) for elaborate of the transferability and non-transferability of literacy skills and metalinguistic knowledge for Spanish and English language arts instruction.  

Vocabulary and Concepts in the Bilingual Brain 

Researchers propose two predominant hypotheses about lexical and conceptual representations: One theory is called the word association hypothesis that proposes that a direct association in established between words in two languages. Another theory, called the concept mediation hypothesis is that the connection between the two languages is via an underlying conceptual system through which bilinguals have “lexical access” to words and their meanings (Peña, Kester & Sheng, 2022; Schwartz & Kroll, 2006). The implications of these two theories about how bilingual learners access their knowledge of word meanings in two languages is that if either or both theories are true, both vocabulary learning and concept learning must be addressed through effective instruction. Another factor is the frequency of exposure to words as a determiner of the strength of the associative networks in each of the learners’ languages (Li & Clariana, 2019; Roxbury, et al, 2014). The brain research also supports the notion that there are distinct cerebral regions where Spanish semantics are stored in memory and another where English semantics are stored in a mental lexicon. The mental lexicon or collection of concept units of each language is activated to comprehend text by recognizable phonological (sounds) and orthographic (spellings) representations that the reader identifies by mapping language features onto print.

The implication of this brain activity for dual language teachers is that pathways to access the semantic storage regions must be created through appropriate multilingual instruction. In addition, pathways linking the Spanish and English semantic regions for bilingual learners to take advantage of their full linguistic and conceptual repertoires (Taylor, Rastle & Davis, 2013). When bilingual learners’ vocabulary in both languages is considered, their total vocabulary size is generally comparable to the total vocabulary size of their monolingual peers (Patterson & Pearson, 2022). Researchers also report findings that suggest that bilinguals have a greater brain memory capacity for words because they engage a wider cross-linguistic activation of the lexico-semantic system and use more effective encoding strategies. They have a propensity to make associations at the conceptual level because they have extensive experience directly associating word forms from their two languages. Bilingual learners also develop more skill in the automatic monitoring context as a source of information for clues to novel words (Francis, et al., 2019). 

Educational Neuroscience: Research and Ethical Concerns

In an enlightening and informative treatise of the role of educational neuroscience, Hruby (2012) warns against potential methodological and ethical concerns in efforts to bridge between research in the neurosciences and research, theory and practice in education. Hruby identifies three areas of concern: Intellectual coherence, mutually informing and respected scholarly expertise, and an ethical commitment to the moral implications and obligations shared within educational research generally. Hruby highlights the need for intellectual coherence and precision in definition of technical terms to preserve the logical warrants by which educational implications of neuroscientific findings are drawn from empirical data. He states the following: “Detailing descriptions of the brain alongside descriptions of favoured teaching practices does nothing to enhance, let alone demonstrate, the efficacy of those practices… References to the brain is apparently meant to imply research-demonstrated efficacy, but the only warrant for suggesting such research demonstrated efficacy of a method is citation of research on said method’s efficacy.” (p. 4-5) The same can be said about claims of “ineffectiveness” of a method, approach or strategy, where no clear definition of the construct is provided, nor is a body of descriptive and/or empirical studies cited to support the claim. This is the very problem addressed in this critique of the claims made under a “patina of scientific certainty” by advocates of the Science of Reading (Yaden, Reinking, & Smagorinsky, 2021: S123). Yaden and colleagues also state this conclusion about SoR: 

“Specifically, those who assume, or even claim, that there is a settled SOR, especially one that dictates unequivocally how reading should be taught for all students, are not operating in the spirit, or within the accepted interpretive tradition and practice, of science… We believe that considering split and relational metatheories reveals the limitations of the SOR movement’s narrow consideration of what factors and influences explain reading and learning to read. It also underscores the manner in which the SOR movement’s view of science and its valorization of quantitative, experimental methods not only are dismissive of critical contextual variables but also generalize from their own data in questionable ways. Specifically, we conclude that viewing science as an accumulation of quantifiable empirical data and unqualified inductive generalizations embeds a number of problems that undermine any claims from that perspective to having exclusive authority in understanding reading and guiding reading instruction. These include the issues that the SOR, as we suggested in the introduction, relies on a limited conception of science, ignores relevant environmental factors, and uncritically accepts experimentation as the only valid approach to social science inquiry in literacy.” (p. S126)

One authority on the challenges facing the emerging field of educational neuroscience from a decade ago who offers wise guidance is Dr. George G. Hruby, Associate Research Professor and Executive Director, Collaborative Center for Literacy Development, University of Kentucky. Hruby (2012) states the following: 

“In this paper, I (Hruby) suggest that to be a worthy field of educational research, educational neuroscience will need to address three issues: intellectual coherence, mutually informing and respected scholarly expertise, and an ethical commitment to the moral implications and obligations shared within educational research generally.

“Educational neuroscientists should hold their educational colleagues to high standards regarding the application of neuroscience to theory, research, and practice; provide tutelage and guidance wherever possible; and demonstrate an interest in the base of research, theory, and practice already abundant in fields of teacher education and practice. Unfortunately, pioneers of educational neuroscience have not always been careful in characterizing educational research to the general public. Rather, they have often ignored the copious research base in education or not given much credit to its efforts when communicating the promise of neuroscience. As a result, no doubt unwittingly, they have propagated some myths themselves.”

“I (Hruby) conclude that educational neuroscience is more than a hybrid patchwork of individual interests constituting a study area, and is perhaps ready to stand as a legitimate field of educational inquiry. It will not be accepted as such, however, nor should it be, unless the need to demonstrate a capacity for consistent intellectual coherence, scholarly expertise, and ethical commitment is met.”

We educators of multilingual learners draw our effective practices from a rich and comprehensive knowledge base that is frequently marginalized and ignored in the rhetoric of the Science of Reading. We must raise our collective voice as an interpretive community of researchers, teacher educators and practitioners to express our concerns and to protect the intellectual integrity and ethical focus of our multidisciplinary research that informs our practice. 

Below please find citations of research studies to support the information about neuroscience research and the bilingual brain. Thank you for your attention. I invite your feedback and comments. JKM

References

Ardila, A., & Cuetos, F. (2016). Applicability of dual-route reading models to Spanish. Psicothema, 28(1), 71-75. https://doi.org/10.7334/psicothema2015.103

Binder, J. R., Medler, R. D., Conant, L. L., & Liebenthal, E. (2005). Some neurophysiological constraints on models of word naming. Neuroimage, 27(2005), 677-693. https://doi.org/10.1016/j.neuroimage.2005.04.029

Bowers, J. S., & Bowers, P. N. (2017). Beyond phonics: The case for teaching children the logic of the English spelling system. Educational Psychologist, 52(2), 124-141. https://doi.org/10.1080/00461520.2017.1288571

Castles, A., Rastle, K., & Nation, K. (2018). Ending the Reading Wars: Reading acquisition from novice to expert. Psychological Science, 19(1), 5-51. https://doi.org/10.1177/1529100618786959

Cevoli, B., Watkins, C., & Rastle, K. (2022). Prediction as a basis for skilled reading: Insights from modern language models. Royal Society Open Science, 9(211837), 1-12. https://doi.org/10.1098/rsos.211837

Coltheart, M. (2006). Dual route and connectionist models of reading: An overview. London Review of Education, 4(1), 5-17.

Compton-Lilly, C. F., Mitra, A., Guay, M., & Spence, L. K. (2020). A confluence of complexity: Intersections among reading theory, neuroscience and observations of young readers. Reading Research Quarterly, 55(S1), S185-S195. https://doi.org/10.1002/rrq.348

Cuetos, F., & Suárez-Coalla, P. (2009). From grapheme to word in reading acquisition in Spanish. Applied Psycholinguistics, 30(2009), 583-601.

Dehaene, S. (2015). Aprender a leer: De las ciencias cognitivas al aula [Learning to read: From the cognitive sciences to the classroom]. Siglo Veintiuno Editores.

Dehaene, S. (2014). El cerebro lector [The reading brain]. Siglo Veintiuno Editores.

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

Dehaene, S., & Dehaene-Lambertz, G. (2016). Is the brain prewired for letters? Nature Neuroscience, 19(9), 1192-1193.

Deniz, F., Nunez-Elizalde, A. O., Huth, A. G., & Gallant, J. L. (2019). The representation of semantic information across human cerebral cortex during listening versus reading is invariant to stimulus modality. Journal of Neuroscience, 39(39), 7722-7736.

Dufour, R., & Kroll, J. F. (1993). Matching words to concepts in two languages: A test of the concept mediation model of bilingual representation. Memory & Cognition, 23(2), 166-180.

Ebe, A. (2008). What eye movement and miscue analysis reveals about the reading process of young bilinguals. In A. D. Flurkey, E. J. Paulson, & K. S. Goodman (Eds.), Scientific realism in studies of reading (pp. 131-149). Routledge.

Fedeli, D., Del Maschio, N. S., Simone, Rothman, J., & Abutalebi, J. (2021). The bilingual structural connectome: Dual-language experiential factors modulate distinct cerebral networks. Brain and Language, 220(104978), 1-11.

Fedorenko, E., Blank, I. A., Siegelman, M., & Mineroff, Z. (2020). Lack of selectivity for syntax relative to word meanings throughout the language network. Cognition, 203(104348), 1-24.

Francis, W. S., Strobach, E. N., Penalver, R. M., Martínez, M., Gurrola, B. V., & Soltero, A. (2019). Word-context associations in episodic memory are learned at the conceptual level: Word frequency, bilingual proficiency, and bilingual status effects on source memory. Journal of Experimental Psychology Learning, Memory, and Cognition, 45(10), 1852-1871.

Frost, R. (2012). Towards a universal model of reading. Behavioral and Brain Sciences, 35, 263-329. https://doi.org/10.1017/S0140525X11001841

Goodman, K., Fries, P. H., & Strauss, S. L. (2016). Reading‒The grand illusion: How and why people make sense of print. Routledge.

Heilbron, M. A., Kristijan, Schoffelen, J.-M., Hagoot, P., & de Lange, F. P. (2022). A heirarchy of linguistic predictions during natural language comprehension. PNAS Neuroscience Psychological and Cognitive Sciences, 119(32), e2201968119. https://doi.org/10.1073/pnas.2201968119

Hoffman, P., Ralph, M. A. L., & Woollams, A. M. (2015). Triangulation of the neurocomputational architecture underpinning reading aloud. PNAS Journal Proceedings of the National Academy of Sciences, 112(28), E3719-E3728. https://doi.org/https://doi.org/10.1073/pnas.1502032112

Hruby, G. G. (2012). Three requirements for justifying an educational neuroscience. British Journal of Educational Psychology, 82, 1-23.

Hruby, G. G., & Goswami, U. (2011). Neuroscience and reading: A review for reading education researchers. Reading Research Quarterly, 46(2), 156-172.

Kovelman, I., Baker, S. A., & Petitto, L. (2008a). Age of first bilingual language exposure as a new window into bilingual reading development. Bilingualism: Language and Cognition, 11(2), 203-223.

Kovelman, I., Baker, S. A., & Petitto, L. (2008b). Bilingual and monolingual brains compared: A functional magnetic resonance imaging investigation of syntactic processing and a possible “neural signature” of bilingualism. Journal of Cognitive Neuroscience, 20(1), 153-169.

Kroczek, L. O. H., & Gunter, T. C. (2017). Communicative predictions can overrule linguistic priors. Scientific Reports, 7, 17581. DOI:10.1038/s41598-017-17907-9

Kroll, J. F., & Stewart, E. (1994). Category interference in translation and picture naming: Evidence for asymmetric connections between bilingual memory representations. Journal of Memory and Language, 33, 149-174.

Liversedge, S. P., Blythe, H., & Drieghe, D. (2012). Beyond isolated word recognition. Behavioral and Brain Sciences, 35(5), 293-294.

Li, P., & Clariana, R. B. (2019). Reading comprehension in L1 and L2: An integrative approach. Journal of Neurolinguistics, 50, 94-105. https://doi.org/10.1016/j.jneuroling.2018.03.005

Li, P., & Grant, A. (2015). Second language learning success revealed by brain networks. Bilingualism: Language and Cognition, 19(4), 657-664.

Marks, R. A., Satterfield, T., & Kovelman, I. (2022). Integrated multilingualism and bilingual reading development. In J. MacSwan (Ed.), Multilingual perspectives on translanguaging (pp. 201-223). Multilingual Matters.

Mazoyer, B. M., Tzourio, N., Frak, V., Sytota A, Murayama, N., Levrier, O., Salamon, G., Dehaene, S., Cohen, L., & Mehler, J. (1993). The cortical representation of speech. Journal of Cognitive Neuroscience, 5(4), 467-479.

Patterson, J. L., & Pearson, B. Z. (2022). Bilingual lexical development, assessment, and intervention. In B. A. Goldstein (Ed.), Bilingual language development and disorders in Spanish-English speakers (Third ed., pp. 119-148). Brookes Publishing.

Paulson, E. J. (2008). Miscues and eye movements: Functions of comprehension. In A. D. Flurkey, E. J. Paulson, & K. S. Goodman (Eds.), Scientific realism in studies of reading (pp. 247-264). Routledge.

Peña, E. D., Kester, E. S., & Sheng, L. (2022). Semantic development in Spanish-English bilinguals. In B. A. Goldstein (Ed.), Bilingual language development and disorders in Spanish-English speakers (Third ed., pp. 149-170). Brookes Publishing.

Perfetti, C. A., & Stafura, J. (2014). Word knowledge in a theory of reading comprehension. Scientific Studies of Reading, 18(1), 22-37.

Rastle, K. (2012). Rethinking phonological theories of reading. The Behavioral and Brain Sciences, 35(5), 303-304. https://doi.org/10.1017/s0140525x12000246

Roxbury, T., McMahon, K., & Copland, D. (2014). An fMRI study of concreteness effects in spoken word recognition. Behavioral and Brain Function, 10(34), 1-14.

Schwartz, A. I., & Kroll, J. F. (2006). Bilingual lexical activation in sentence context. Journal of Memory and Language, 55(2006), 197-212.

Share, D. L. (1995). Phonological recoding and self-teaching: sine qua non of reading acquisition. Cognition, 55, 151-218.

Sheriston, L., Critten, S., & Jones, E. (2016). Routes to reading and spelling: Testing the predictions of dual-route theory. Reading Research Quarterly, 51(4), 403-417.

Strauss, S. L. (2005). The linguistics, neurology, and politics of phonics: Silent “E” speaks out. Lawrence Erlbaum.

Strauss, S. L. (2013). We need a paradigm shift in research on reading and dyslexia: Fundamental problems with fMRI studies of written language processing. Journal of the Neurological Sciences, 333, e579-e628.

Strauss, S. L. (2010). Neuroscience and dyslexia. In A. A. McGill-Franzen, Richard L. (Ed.), Handbook of reading disability research (pp. 79-90). Routledge Taylor & Francis Group.

Strauss, S. L. (2005). The linguistics, neurology, and politics of phonics: Silent “E” speaks out. Lawrence Erlbaum.

Strauss, S. L., Goodman, K. S., & Paulson, E. J. (2009). Brain research and reading: How emerging concepts in neuroscience support a meaning construction view of the reading process. Educational Research and Review, 4(2), 021-033.

Strauss, S. L., & Altweger, B. (2007). The logographic nature of English alphabetics and the fallacy of direct intensive phonics instruction. Journal of Early Childhood Literacy, 7(3), 299-319. https://doi.org/10.1177/1468798407083664

Taylor, J. S. H., Rastle, K., & Davis, M. H. (2013). Can cognitive models explain brain activation during word and pseudoword reading? A meta-analysis of 36 neuroimaging studies. Psychological Bulletin, 139(4), 966-791. https://doi.org/10.1037/a0030266

van Heuven, W., & Dijkstra, T. (2010). Language comprehension in the bilingual brain: fMRI and ERP support for psycholinguistic models. Brain Research Reviews. https://doi.org/10.1016/j.brainresrev.2010.03.002

Wong, B., Yin, B., & O’Brien, B. (2016). Neurolinguistics: Structure, function, and connectivity in the bilingual brain. BioMed Research International, Article ID 7069274, 22. https://doi.org/http://dx.doi.org/10.1155/2016/7069274

Yaden, D. B., Reinking, D., & Smagorinsky, P. (2021). The trouble with binaries: A perspective on the Science of Reading. Reading Research Quarterly, 56(S1), S119-S129.