Friday, May 25, 2018

The Role of Executive Functions in Reading Comprehension - excellent overview of major models of reading comprehension

The Role of Executive Functions in Reading Comprehension. Article or link.

Reese Butterfuss and Panayiota Kendeou


Our goal in this paper is to understand the extent to which, and under what conditions, executive functions (EFs) play a role in reading comprehension processes. We begin with a brief review of core components of EF (inhibition, shifting, and updating) and reading comprehension. We then discuss the status of EFs in process models of reading comprehension. Next, we review and synthesize empirical evidence in the extant literature for the involvement of core components of EF in reading comprehension processes under different reading conditions and across different populations. In conclusion, we propose that EFs may help explain complex interactions between the reader, the text, and the discourse situation, and call for both existing and future models of reading comprehension to include EFs as explicit components.

Keywords Executive functions . Reading comprehension . Discourse processes

This article includes an excellent summary of the major models of reading comprehension. This post includes that select material.

The Status of Executive Functions in Models of Reading Comprehension

Reading comprehension is one of the most complex and important cognitive activities humans perform (Kendeou et al. 2016). Given its importance and complexity, researchers have sought to understand reading comprehension via the development and specification of a multitude of models and frameworks that account for various processes and mechanisms of reading.

Generally, reading comprehension refers to the construction of a mental representation of what the text is about (Kintsch and V an Dijk 1978). Although most models of reading comprehension converge on this general idea, the processes and assumptions by which readers construct such representations differ across models and frameworks. It is also important to note that a unified, comprehensive model of reading comprehension has yet to be established. McNamara and Magliano (2009) reviewed and compared one set of models, which are concerned primarily with the construction of the mental representation during reading: The Construction-Integration Model (Kintsch 1988), the Structure-Building Framework (Gernsbacher 1991), the Resonance Model (Albrecht and O'Brien 1993), the Event-Indexing Model (Zwaan et al. 1995), the Causal Network Model (Trabasso et al. 1989), the Constructionist Theory (Graesser et al. 1994), and the Landscape Model (van den Broek et al. 1999). In this review, we investigate the status of EFs in each of these models.

Among this set of models, the Construction-Integration (CI) model (Kintsch 1988) is perhaps the most comprehensive, and it is considered the best approximation to a true theory of reading comprehension (Kendeou and O'Brien 2017). According to the CI model, comprehension is the result of two processes, construction and integration. Construction refers to the activation of information in the text and background knowledge. There are four potential sources of activation: the current text input, the prior sentence, background knowledge, and prior text. As this information is activated, it is connected into a network of concepts. Integration refers to the continuous spread of activation within this network until activation settles. Activation sources from the construction process are iteratively integrated, and only those concepts that are connected to many others are maintained in the network. At the completion of reading, the result is a complete network or a mental representation of what the text is about. This mental representation has been termed the situation model. Even though the initial model makes no explicit reference to EFs, in a subsequent revision, Kintsch (1998) included a suppression mechanism in the CI model by adopting inhibitory links. Specifically, the CI model relies on links between information units to promote an appropriate representation of a text and inhibit inappropriate representations. In this context, facilitatory links connect related information units, and inhibitory (or negative) links connect conflicting or inappropriate information units. Inhibitory links serve to suppress or inhibit inappropriate representations (Kintsch 1998).

The Structure-Building Framework (Gernsbacher 1991) describes comprehension as the result of three processes. The first process, laying a foundation, involves using initial information from a text to lay the groundwork for a mental representation to be constructed. The second process, mapping, involves mapping information from the text onto that foundation to create structures. The third process, shifting, involves a shift to begin building a new structure when readers are unable to map information onto an existing structure. Irrelevant information that does not cohere with a current structure is suppressed. Thus, within the Structure-Building Framework, the suppression mechanism attempts to account for individual differences in comprehension ability. Specifically, the model posits that if incoming information is related to the current structure, then activation of that information is enhanced, resulting in its incorporation into the current structure. When information is not related to the current structure, then activation to that information is suppressed, or, alternatively, readers may shift and use that information to begin building a new structure. The suppression mechanism is the result of readers' ability to inhibit irrelevant information. This ability moderates reading comprehension in that skilled readers have a strong suppression mechanism and can therefore suppress irrelevant information, whereas less-skilled readers lack a strong suppression mechanism. As a result, less-skilled comprehenders' poor suppression ability may lead them to shift too often, which impairs comprehension because more information is competing for limited resources.

The Resonance Model (Myers and O'Brien 1998) attempts to account for factors that influence the activation of information during comprehension, particularly information that is no longer active in working memory. The model emphasizes automatic, memory-based retrieval mechanisms as fundamental assumptions. Specifically, the model assumes that information in working memory serves as a signal to all of memory, which activates information that resonates with the signal. Elements resonate as a function of the number of features that overlap with the contents of working memory. Even though the model has not explicitly incorporated any EFs, O'Brien et al. (1995) found that suppression was involved in processes relevant to the Resonance Model. Specifically, O'Brien et al. found that when an anaphoric phrase reactivated more than one potential antecedent from the text, the selected target antecedent was strengthened in long-term memory, whereas potential, but non-target, antecedents that interfered with the target antecedent were suppressed.

The Event-Indexing Model (Zwaan et al. 1995) was developed as an attempt to account more fully for processes involved with situation model construction of narrative texts. It operates under the assumption that readers monitor and establish coherence along five dimensions of continuity, and thus situation model construction: time, space, causality, motivation, and agents. Thus, within the event-indexing model, EFs such as shifting attention from one dimension to another as well as updating the construction of the situation model account for individual differences in comprehension ability. For example, Bohn-Gettler et al. (2011) found that there are developmental differences in children's ability to monitor the shifts in each of these dimensions.

The Causal Network Model (Trabasso et al. 1989) accounts for how readers generate causal inferences and represent causality during reading. Causal inferences are at the core of building a coherent representation of a story. Narrative elements can be categorized as either settings, events, goals, attempts, outcomes, or reactions. Also, there are assumed to be four types of causal relations: enabling, psychological, motivational, and physical. The model also provided a discourse analysis tool, Causal Network Analysis, to identify the causal structure that underlies story constituents. Overall, the model accounts for the importance of causal relations in memory for the text, but makes no assumptions about specific EFs. The Constructionist theory (Graesser et al. 1994) attempts to account for factors that predict inference generation during reading. The theory emphasizes the role of top-down, strategic processes in the construction of meaning, what has been termed Bsearch after meaning.^ Three assumptions define search after meaning. The first is the reader goal assumption, which suggests that readers construct meaning in accordance with their reading goals. The second is the coherence assumption, which suggests that readers construct meaning at both local and global levels. The third is the explanation assumption, which suggests that readers are driven to construct meaning that explains events they read. Even though the theory makes no concrete assumptions about EFs, it is reasonable to assume that shifting attention likely exerts an influence on the top-down, strategic processes that govern search after meaning.

Lastly, the Landscape Model (van den Broek et al. 1999) simulates the fluctuation of concept activation during reading. The Landscape Model is similar to the CI Model in that it assumes the same four sources of activation. The model also includes two important mechanisms, cohort activation and coherence-based retrieval. Cohort activation assumes that when a concept is activated, all other concepts that are also activated become associated with it (McClelland and Rumelhart 1985). Coherence-based retrieval assumes that the activation of text elements is in accordance with the readers' standards of coherence. In turn, standards of coherence refer to readers' implicit or explicit criteria for comprehension. Even though the Landscape Model makes no concrete assumptions about EFs, it is reasonable to assume that shifting likely exerts an influence on readers' standards of coherence, directing attention to information that aligns with readers' standards.

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File under evidence-based instructional interventions: Studying and Constructing Concept Maps: a Meta-Analysis

Studying and Constructing Concept Maps: a Meta-Analysis. Article link.

Noah L. Schroeder, John C. Nesbit, Carlos J. Anguiano & Olusola O. Adesope

Abstract A concept map is a node-link diagram in which each node represents a concept and each link identifies the relationship between the two concepts it connects. We investigated how using concept maps influences learning by synthesizing the results of 142 independent effect sizes (n = 11,814). A random-effects model meta-analysis revealed that learning with concept and knowledge maps produced a moderate, statistically significant effect (g = 0.58, p < 0.001). A moderator analysis revealed that creating concept maps (g = 0.72, p < 0.001) was associated with greater benefit relative to respective comparison conditions than studying concept maps (g = 0.43, p < 0.001). Additional moderator analyses indicated learning with concept maps was superior to other instructional comparison conditions, and was effective across science, technology, engineering, and math (STEM) and non-STEM knowledge domains. Further moderator analyses, as well as implications for theory and practice, are provided.

Keywords Concept map . Knowledge map . Meta-analysis . cmap . kmap

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Saturday, May 19, 2018

The Relation between Intelligence and Adaptive Behavior: A Meta-Analysis 

Very important meta-analysis of AB IQ relation. Primary finding on target with prior informal synthesis by McGrew (2015)

The Relation between Intelligence and Adaptive Behavior: A Meta-Analysis   
Ryan M. Alexander 
Intelligence tests and adaptive behavior scales measure vital aspects of the multidimensional nature of human functioning. Assessment of each is a required component in the diagnosis or identification of intellectual disability, and both are frequently used conjointly in the assessment and identification of other developmental disabilities. The present study investigated the population correlation between intelligence and adaptive behavior using psychometric meta-analysis. The main analysis included 148 samples with 16,468 participants overall. Following correction for sampling error, measurement error, and range departure, analysis resulted in an estimated population correlation of ρ = .51. Moderator analyses indicated that the relation between intelligence and adaptive behavior tended to decrease as IQ increased, was strongest for very young children, and varied by disability type, adaptive measure respondent, and IQ measure used. Additionally, curvilinear regression analysis of adaptive behavior composite scores onto full scale IQ scores from datasets used to report the correlation between the Wechsler Intelligence Scales for Children- Fifth edition and Vineland-II scores in the WISC-V manuals indicated a curvilinear relation—adaptive behavior scores had little relation with IQ scores below 50 (WISC-V scores do not go below 45), from which there was positive relation up until an IQ of approximately 100, at which point and beyond the relation flattened out. Practical implications of varying correlation magnitudes between intelligence and adaptive behavior are discussed (viz., how the size of the correlation affects eligibility rates for intellectual disability).
Other Key Findings Reported
McGrew (2012) augmented Harrison's data-set and conducted an informal analysis including a total of 60 correlations, describing the distributional characteristics observed in the literature regarding the relation. He concluded that a reasonable estimate of the correlation is approximately .50, but made no attempt to explore factors potentially influencing the strength of the relation.
Results from the present study corroborate the conclusions of Harrison (1987) and McGrew (2012) that the IQ/adaptive behavior relation is moderate, indicating distinct yet related constructs. The results showed indeed that the correlation is likely to be stronger at lower IQ levels—a trend that spans the entire ID range, not just the severe range. The estimated true mean population is .51, and study artifacts such as sampling error, measurement error, and range departure resulted in somewhat attenuated findings in individual studies (a difference of about .05 between observed and estimated true correlations overall).
The present study found the estimated true population mean correlation to be .51, meaning that adaptive behavior and intelligence share 26% common variance. In practical terms, this magnitude of relation suggests that an individual's IQ score and adaptive behavior composite score will not always be commensurate and will frequently diverge, and not by a trivial amount. Using the formula Ŷ = Ȳ + ρ (X - X ̅ ), where Ŷ is the predicted adaptive behavior composite score, Ȳ  is the mean adaptive behavior score in the population, ρ  is the correlation between adaptive behavior and intelligence, X is the observed IQ score for an individual, and X ̅ is the mean IQ score, and accounting for regression to the mean, the predicted adaptive behavior composite score corresponding to an IQ score of 70, given a correlation of .51, would be 85 —a score that is a full standard deviation above an adaptive behavior composite score of 70, the cut score recommended by some entities to meet ID eligibility requirements. With a correlation of .51, and accounting for regression to the mean, an IQ score of 41 would be needed in order to have a predicted adaptive behavior composite score of 70. Considering that approximately 85% of individuals with ID have reported IQ scores between 55 and 70±5 (Heflinger et al., 1987; Reschly, 1981), the eligibility implications, especially for those with less severe intellectual impairment, are alarming. In fact, derived from calculations by Lohman and Korb (2006), only 17% of individuals obtaining an IQ score of 70 or below would be expected to also obtain an adaptive behavior composite score of 70 or below when the correlation between the two is .50. 
The purpose of this study was to investigate the relation between IQ and adaptive behavior and variables moderating the relation using psychometric meta-analysis. The findings contributed in several ways to the current literature with regard to IQ and adaptive behavior. First, the estimated true mean population correlation between intelligence and adaptive behavior following correction for sampling error, measurement error, and range departure is moderate, indicating that intelligence and adaptive behavior are distinct, yet related, constructs. Second, IQ level has a moderating effect on the relation between IQ and adaptive behavior. The correlation is likely to be stronger at lower IQ levels, and weaker as IQ increases. Third, while not linear, age has an effect on the IQ/adaptive behavior relation. The population correlation is highest for very young children, and lowest for children between the ages of five and 12. Fourth, the magnitude of IQ/adaptive behavior correlations varies by disability type. The correlation is weakest for those without disability, and strongest for very young children with developmental delays. IQ/adaptive behavior correlations for those with ID are comparable to those with autism when not matched on IQ level. Fifth, the IQ/adaptive correlation when parents/caregivers serve as adaptive behavior respondents is comparable to when teachers act as respondents, but direct assessment of adaptive behavior results in a stronger correlation. Sixth, an individual's race does not significantly alter the correlation between IQ and adaptive behavior, but future research should evaluate the influence of race of the rater on adaptive behavior ratings. Seventh, the correlation between IQ and adaptive behavior varies depending on IQ measure used—the population correlation when Stanford-Binet scales are employed is significantly higher than when Wechsler scales are employed. And eighth, the correlation between IQ and adaptive behavior is not significantly different between adaptive behavior composite scores obtained from the Vineland, SIB, and ABAS families of adaptive behavior measures, which are among those that have been deemed appropriate for disability identification. Limitations of this study notwithstanding, it is the first to employ meta-analysis procedures and techniques to examine the correlation between intelligence and adaptive behavior and how moderators alter this relation. The results of this study provide information that can help guide practitioners, researchers, and policy makers with regard to the diagnosis or identification of intellectual and developmental disabilities.

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Thursday, May 17, 2018

Interactive Metronome study: Clapping in time parallels literacy and calls upon overlapping neural mechanisms in early readers

Clapping in time parallels literacy and calls upon overlapping neural mechanisms in early readers

Annals of the New York Academy Of Science. Article link here.

Link to complete paper at IM site.

Silvia Bonacina Jennifer Krizman Travis White‐Schwoch Nina Krau


The auditory system is extremely precise in processing the temporal information of perceptual events and using these cues to coordinate action. Synchronizing movement to a steady beat relies on this bidirectional connection between sensory and motor systems, and activates many of the auditory and cognitive processes used when reading. Here, we use Interactive Metronome, a clinical intervention technology requiring an individual to clap her hands in time with a steady beat, to investigate whether the links between literacy and synchronization skills, previously established in older children, are also evident in children who are learning to read. We tested 64 typically developing children (ages 5–7 years) on their synchronization abilities, neurophysiological responses to speech in noise, and literacy skills. We found that children who have lower variability in synchronizing have higher phase consistency, higher stability, and more accurate envelope encoding—all neurophysiological response components linked to language skills. Moreover, performing the same task with visual feedback reveals links with literacy skills, notably processing speed, phonological processing, word reading, spelling, morphology, and syntax. These results suggest that rhythm skills and literacy call on overlapping neural mechanisms, supporting the idea that rhythm training may boost literacy in part by engaging sensory‐motor systems.

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Wednesday, May 16, 2018

MindHub Pub #3: WJ IV Norm-Based and Supplemental Clinical Test Groupings for “Intelligent” Intelligence Testing with the WJ IV

I am pleased to announce the availability of MindHub Pub #3 (WJ IV Norm-Based and Supplemental Clinical Test Groupings for "Intelligent" Intelligence Testing with the WJ IV).  Click the link to view or download.

The material in this document is based on my work during the development of the WJ IV as well as significant post-WJ IV publication analyses.  I have been completing considerable post-WJ IV data analysis in response to questions on listservs and to develop advanced and clinical interpretation information for convention presentations and workshops.  In the past I had the luxury of time to write professional books re: clinical "intelligent" intelligence testing with the WJ (1986) and WJ-R (1984).  I was unable to find time for the WJ III nor the WJ IV.  So much to little time.

I have presented early versions of this material at conventions and workshops.  However, I never felt comfortable with the final product.  The most important reason for not distributing widely was my knowledge that the CHC model was in the process of responding to new research and insights--to be published this fall 2018 in a chapter by Joel Schneider and myself.  I only wanted this"supplemental grouping strategy" worksheet material (ala, Dr. Alan Kaufman's shared ability approach to test interpretation) to be made available once the revised CHC model had been described.  This event will occur this August with the publication of our chapter.  An early visual-graphic overview of the chapter, presented in a nifty animated YouTube video was released at this blog approximately a week ago.

So...enjoy the material.  This is not a book or article--more of a detailed PPT presentation.  It should be understandable to clinicians familiar with the WJ IV, CHC theory, and Kaufman's "intelligent" intelligence test interpretation approach.

Below is a sample worksheet--for Gc related tests.  Click on images to enlarge.

Higher intelligence related to more efficiently organized brains-bigger/larger/more not always better

Click on image to enlarge

Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Article link.

Erhan Genç, Christoph Fraenz, Caroline Schlüter, Patrick Friedrich, Rüdiger Hossiep, Manuel C. Voelkle, Josef M. Ling, Onur Güntürkün, & Rex E. Jung


Previous research has demonstrated that individuals with higher intelligence are more likely to have larger gray matter volume in brain areas predominantly located in parieto-frontal regions. These findings were usually interpreted to mean that individuals with more cortical brain volume possess more neurons and thus exhibit more computational capacity during reasoning. In addition, neuroimaging studies have shown that intelligent individuals, despite their larger brains, tend to exhibit lower rates of brain activity during reasoning. However, the microstructural architecture underlying both observations remains unclear. By combining advanced multi-shell diffusion tensor imaging with a culture-fair matrix-reasoning test, we found that higher intelligence in healthy individuals is related to lower values of dendritic density and arborization. These results suggest that the neuronal circuitry associated with higher intelligence is organized in a sparse and efficient manner, fostering more directed information processing and less cortical activity during reasoning.

From discussion

Taken together, the results of the present study contribute to our understanding of human intelligence differences in two ways. First, our findings confirm an important observation from previous research, namely, that bigger brains with a higher number of neurons are associated with higher intelligence. Second, we demonstrate that higher intelligence is associated with cortical mantles with sparsely and well-organized dendritic arbor, thereby increasing processing speed and network efficiency. Importantly, the findings obtained from our experimental sample were confirmed by the analysis of an independent validation sample from the Human Connectome Project25

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Tuesday, May 08, 2018

Gates, Zuckerberg team up on new education initiative

Gates, Zuckerberg team up on new education initiative

From Education, a Flipboard topic

Tech moguls Bill Gates and Mark Zuckerberg said Tuesday they will team up to help develop new technologies for kids with trouble learning — an…

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NEUROSCIENCE & SOCIETY: Ethics, Law, and Technology Confrence - Neuroethics & Law Blog

NEUROSCIENCE & SOCIETY: Ethics, Law, and Technology Confrence - Neuroethics & Law Blog

NEUROSCIENCE & SOCIETY: Ethics, Law, and Technology Confrence

NEUROSCIENCE & SOCIETY: Ethics, Law, and Technology
24-25 August 2018
Sydney, NSW, Australia

Advances in brain scanning and intervention technologies are transforming our ability to observe, explain, and influence human thought and behaviour. Potential applications of such technologies (e.g. brain-based pain detection in civil lawsuits, medications to help criminal offenders become less impulsive, prediction of future behaviour through neuroimaging) and their ethical, clinical, legal, and societal implications, fuel important debates in neuroethics. However, many factors beyond the brain – factors targeted by different emerging technologies – also influence human thought and behaviour. Sequencing the human genome and gene-editing technologies like CRISPR Cas-9 offer novel ways to explain and influence human thought and behaviour. Analysis of data about our offline and online lives (e.g. from fitness trackers, how we interact with our smartphone apps, and our social media posts and profiles) also provide striking insights into our psychology. Such intimate information can be used to predict and influence our behaviour, including through bespoke advertising for goods and services that more effectively exploits our psychology and political campaigns that sway election results. Although such methods often border on manipulation, they are both difficult to detect and potentially impossible to resist. The use of such information to guide the design of online environments, artifacts, and smart cities lies at the less nefarious – and potentially even socially useful and morally praiseworthy – end of the spectrum vis à vis the potential applications of such emerging "moral technologies".

At this year's Neuroscience & Society conference we will investigate the ethical, clinical, legal, and societal implications of a wide range of moral technologies that target factors beyond, as well as within, the brain, in order to observe, explain, and influence human thought and behaviour. Topics will include, but are not limited to:

  • cognitive and moral enhancement
  • neurolaw and neuro-evidence
  • brain-computer interfaces
  • neuro-advertising
  • neuromorphic engineering and computing
  • mental privacy and surveillance
  • social media and behaviour prediction/influence
  • implicit bias and priming
  • technological influences on human behaviour
  • nudging, environment and technology design, and human behaviour
  • artificial intelligence and machine learning
  • technology and the self
  • (neuro)technology and society

We invite abstracts from scholars, scientists, technology designers, policy-makers, practitioners, clinicians and graduate students, interested in presenting talks or posters on any of the above or related topics.

Abstracts of 300 words should be emailed to Cynthia Forlini <> in Microsoft Word format by Thursday, 31 May 2018. Submissions will be peer reviewed, and authors of successful submissions will be notified via email by Friday, 15 June 2018.

In addition to keynote presentations (to be announced shortly), contributed talks, and a poster session, the conference program will also include three sessions on the following topics:

  • highlights from- and information about enhancements to the Australian Neurolaw Database
  • book symposium on Neuro-Interventions and The Law: Regulating Human Mental Capacity
  • panel on the topic of remorse
For enquiries about matters other than abstract submission, please email Adrian Carter <> or Jeanette Kennett <>
Neuroscience & Society is supported by the ARC Centre of Excellence for Integrative Brain Function Neuroethics Program, and the Centre for Agency Values and Ethics at Macquarie University.

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

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Sunday, May 06, 2018

The salience brain network and personality (self-directedness; cognitive control)


A prevailing topic in personality neuroscience is the question how personality traits are
reflected in the brain. Functional and structural networks have been examined by functional and structural magnetic resonance imaging, however, the structural correlates of functionally defined networks have not been investigated in a personality context. By using the Temperament and Character Inventory (TCI) and Diffusion Tensor Imaging (DTI), the present study assesses in a sample of 116 healthy participants how personality traits proposed in the framework of the biopsychosocial theory on personality relate to white matter pathways delineated by functional network imaging. We show that the character trait self-directedness relates to the overall microstructural integrity of white matter tracts constituting the salience network as indicated by DTI-derived measures. Self-directedness has been proposed as the executive control component of personality and describes the tendency to stay focused on the attainment of long-term goals. The present finding corroborates the view of the salience network as an executive control network that serves maintenance of rules and task-sets to guide ongoing behavior.

Click here for info regarding one of the better brain network overview articles by Bressler and Menon.

Click on image to enlarge

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Research suggests that Gq acquired knowledge has distinct neuro basis from other types of semantic knowledge (Gc)

Thanks to my colleague Joel Schneider for making me aware of this article which provides support for Gq acquired knowledge systems being distinct from Gc (as per CHC theory)

Cortical circuits for mathematical knowledge: evidence for a major subdivision within the brain's semantic networks

Cite this article: Amalric M, Dehaene S. 2017
Cortical circuits for mathematical knowledge: evidence for a major subdivision within the brain's semantic networks. Phil. Trans. R. Soc. B373: 20160515.

Marie Amalric and Stanislas Dehaene


Is mathematical language similar to natural language? Are language areas used by mathematicians when they do mathematics? And does the brain comprise a generic semantic system that stores mathematical knowledge alongside knowledge of history, geography or famous people? Here, we refute those views by reviewing three functional MRI studies of the representation and manipulation of high-level mathematical knowledge in professional mathematicians. The results reveal that brain activity during professional mathematical reflection spares perisylvian language-related brain regions as well as temporal lobe areas classically involved in general semantic knowledge. Instead, mathematical reflection recycles bilateral intra-parietal and ventral temporal regions involved in elementary number sense. Even simple fact retrieval, such as remembering that ‘the sine function is periodical' or that ‘London buses are red', activates dissociated areas for math versus non-math knowledge. Together with other fMRI and recent intra-cranial studies, our results indicated a major separation between two brain networks for mathematical and non-mathematical semantics, which goes a long way to explain a variety of facts in neuroimaging, neuropsychology and developmental disorders. This article is part of a discussion meeting issue ‘The origins of numerical abilities'.

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