An Extension of the Procedural Deficit Hypothesis from Developmental Language Disorders to Mathematical Disability

The development of simple addition problem solving in children: Reliance on automatized counting or memory retrieval depends on both expertise and problem size

In an experiment, 98 children aged 8 to 9, 10 to 12, and 13 to 15 years solved addition problems with a sum up to 10. In another experiment, the same children solved the same calculations within a sign priming paradigm where half the additions were displayed with the "+" sign 150 ms before the addends. Therefore, size effects and priming effects could be considered conjointly within the same populations. Our analyses revealed that small problems, constructed with addends from 1 to 4, presented a linear increase of solution times as a function of problem sums (i.e., size effect) in all age groups. However, an operator priming effect (i.e., facilitation of the solving process with the anticipated presentation of the "+" sign) was observed only in the group of oldest children. These results support the idea that children use a counting procedure that becomes automatized (as revealed by the priming effect) around 13 years of age. For larger problems and whatever the age group, no size or priming effects were observed, suggesting that the answers to these problems were already retrieved from memory at 8 to 9 years of age. For this specific category of large problems, negative slopes in solution times demonstrate that retrieval starts from the largest problems during development. These results are discussed in light of a horse race model in which procedures can win over retrieval.

Contributions of Lower Structures to Higher Cognition: Towards a Dynamic Network Model

Researchers often attribute higher cognition to the enlargement of cortical regions throughout evolution, reflecting the belief that humans sit at the top of the cognitive pyramid. Implicitly, this approach assumes that the subcortex is of secondary importance for higher-order cognition. While it is now recognized that subcortical regions can be involved in various cognitive domains, it remains unclear how they contribute to computations essential for higher-level cognitive processes such as endogenous attention and numerical cognition. Herein, we identify three models of subcortical-cortical relations in these cognitive processes: (i) subcortical regions are not involved in higher cognition; (ii) subcortical computations support elemental forms of higher cognition mainly in species without a developed cortex; and (iii) higher cognition depends on a whole-brain dynamic network, requiring integrated cortical and subcortical computations. Based on evolutionary theories and recent data, we propose the SEED hypothesis: the Subcortex is Essential for the Early Development of higher cognition. According to the five principles of the SEED hypothesis, subcortical computations are essential for the emergence of cognitive abilities that enable organisms to adapt to an ever-changing environment. We examine the implications of the SEED hypothesis from a multidisciplinary perspective to understand how the subcortex contributes to various forms of higher cognition.

Understanding Mathematical Learning Disorder in Regard to Executive and Cerebellar Functioning: a Failure of Procedural Consolidation

A burgeoning body of literature in pediatric neuropsychological assessment suggests executive functioning is the foundation of many procedural learning skills as mediated by cerebellar processing. Given the neuropsychological necessity of intact procedural learning ability for efficient academic learning, the accurate identification of what we have termed “procedural consolidation deficit” (PCD) may be an underpinning of mathematical learning disorder (MLD). Thus, one aim of the present study was to perform an exploratory correlational analysis between performance on pediatric neuropsychological tasks of procedural learning and a classification of MLD. The second aim was to utilize regression analysis of measures of procedural learning for predicting a clinically useful classification of MLD. Results revealed a significant correlation between performance on tasks of procedural learning and a classification of MLD. The follow-up regression model yielded the most predictive variables in identifying individuals with MLD, which included: (a) WISC-V Coding; (b) first administration of Trail Making Test Part B; (c) slope across five serial administrations of Trail Making Test Part B. The model was highly significant and had a classification accuracy for MLD of 87.4%. Results suggest performance on procedural learning tasks significantly predict a classification of MLD. Theoretical and clinical implications are discussed.

Subcortical Cognition: The Fruit Below the Rind

Cognitive neuroscience has highlighted the cerebral cortex while often overlooking subcortical structures. This cortical proclivity is found in basic and translational research on many aspects of cognition, especially higher cognitive domains such as language, reading, music, and math. We suggest that, for both anatomical and evolutionary reasons, multiple subcortical structures play substantial roles across higher and lower cognition. We present a comprehensive review of existing evidence, which indeed reveals extensive subcortical contributions in multiple cognitive domains. We argue that the findings are overall both real and important. Next, we advance a theoretical framework to capture the nature of (sub)cortical contributions to cognition. Finally, we propose how new subcortical cognitive roles can be identified by leveraging anatomical and evolutionary principles, and we describe specific methods that can be used to reveal subcortical cognition. Altogether, this review aims to advance cognitive neuroscience by highlighting subcortical cognition and facilitating its future investigation. Expected final online publication date for the Annual Review of Neuroscience, Volume 45 is July 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Mathematics Disability vs. Learning Disability: A 360 Degree Analysis

A fundamental issue for research in mathematics disability (MD) and reading disability (RD) is: If these disabilities are clearly distinct, why is there so high a level of comorbidity, together with the converse; if these disabilities are so similar, why are there clear differences in underlying causes and aetiology? In order to address this puzzle, we introduce the “360 degree analysis” (360DA) framework and apply it to the overlap between RD and MD. The 360DA process starts by analyzing the issue from four perspectives: theoretical, developmental, affective, and pedagogical. Under 360DA, these analyses are then integrated to provide insights for theory, and for individual assessment and support, together with directions for future progress. The analyses confirm extensive similarities between arithmetic and reading development in terms of rote learning, executive function (EF), and affective trauma, but also major differences in terms of the conceptual needs, the motor coordination needs, and the methods of scaffolding. In terms of theory, commonalities are interpreted naturally in terms of initial general developmental delay followed by domain-independent affective trauma following school failure. Dissociations are interpreted in terms of cerebellar vs. hippocampal learning networks, sequential vs. spatial processing, and language vs. spatial scaffolding, with a further dimension of the need for accurate fixation for reading. The framework has significant theoretical and applied implications.

The benefit of assessing implicit sequence learning in pianists with an eye-tracked serial reaction time task

Playing piano professionally has been shown to benefit implicit motor sequence learning. The aim of the current study was to determine whether this advantage reflects generally enhanced implicit sequence learning unrelated to pianists' higher motor and/or visual-motor coordination abilities. We examined implicit sequence learning using the ocular serial reaction time (O-SRT) task, a manual-free eye-tracked version of the standard SRT, in 29 pianists and 31 controls. Reaction times (RT) and correct anticipations (CA) of several phases describing implicit sequence learning were analyzed. Furthermore, explicit sequence knowledge was compared between the groups, and relationships between implicit sequence learning with explicit sequence knowledge or demographic measures were evaluated. Pianists demonstrated superiority in all critical phases of implicit sequence learning (RT and CA). Moreover, pianists acquired higher explicit sequence knowledge, and only in pianists was explicit sequence knowledge related to implicit sequence learning. Our results demonstrate that pianists' superiority in implicit sequence learning is due to a higher general implicit sequence learning ability. Hence, we can exclude that higher motor and/or visual-motor coordination abilities are related to pianists' higher implicit sequence learning. Furthermore, the significant relationship of implicit sequence learning and explicit sequence knowledge suggests that pianists either used explicit strategies to support implicit sequence learning, had better explicit access to sequence knowledge, or both.

Hand preference and Mathematical Learning Difficulties: New data from Greece, the United Kingdom, and Germany and two meta-analyses of the literature

Increased rates of atypical handedness are observed in neurotypical individuals who are low-performing in mathematical tasks as well as in individuals with special educational needs, such as dyslexia. This is the first investigation of handedness in individuals with Mathematical Learning Difficulties (MLD). We report three new studies (N = 134; N = 1,893; N = 153) and two sets of meta-analyses (22 studies; N = 3,667). No difference in atypical hand preference between MLD and Typically Achieving (TA) individuals was found when handedness was assessed with self-report questionnaires, but weak evidence of a difference was found when writing hand was the handedness criterion in Study 1 (p = .049). Similarly, when combining data meta-analytically, no hand preference differences were detected. We suggest that: (i) potential handedness effects require larger samples, (ii) direction of hand preference is not a sensitive enough measure of handedness in this context, or that (iii) increased rates of atypical hand preference are not associated with MLD. The latter scenario would suggest that handedness is specifically linked to language-related conditions rather than conditions related to cognitive abilities at large. Future studies need to consider hand skill and degree of hand preference in MLD.

Statistical Learning and Language Impairments: Toward More Precise Theoretical Accounts

Statistical-learning (SL) theory offers an experience-based account of typical and atypical spoken and written language acquisition. Recent work has provided initial support for this view, tying individual differences in SL abilities to linguistic skills, including language impairments. In the current article, we provide a critical review of studies testing SL abilities in participants with and without developmental dyslexia and specific language impairment and discuss the directions that this field of research has taken so far. We identify substantial vagueness in the demarcation lines between different theoretical constructs (e.g., “statistical learning,” “implicit learning,” and “procedural learning”) as well as in the mappings between experimental tasks and these theoretical constructs. Moreover, we argue that current studies are not designed to contrast different theoretical approaches but rather test singular confirmatory predictions without including control tasks showing normal performance. We end by providing concrete suggestions for how to advance research on SL deficits in language impairments.

Gender Differences in Connectome-based Predictions of Individualized Intelligence Quotient and Sub-domain Scores

Scores on intelligence tests are strongly predictive of various important life outcomes. However, the gender discrepancy on intelligence quotient (IQ) prediction using brain imaging variables has not been studied. To this aim, we predicted individual IQ scores for males and females separately using whole-brain functional connectivity (FC). Robust predictions of intellectual capabilities were achieved across three independent data sets (680 subjects) and two intelligence measurements (IQ and fluid intelligence) using the same model within each gender. Interestingly, we found that intelligence of males and females were underpinned by different neurobiological correlates, which are consistent with their respective superiority in cognitive domains (visuospatial vs verbal ability). In addition, the identified FC patterns are uniquely predictive on IQ and its sub-domain scores only within the same gender but neither for the opposite gender nor on the IQ-irrelevant measures such as temperament traits. Moreover, females exhibit significantly higher IQ predictability than males in the discovery cohort. This findings facilitate our understanding of the biological basis of intelligence by demonstrating that intelligence is underpinned by a variety of complex neural mechanisms that engage an interacting network of regions-particularly prefrontal-parietal and basal ganglia-whereas the network pattern differs between genders.

The Neurocognition of Developmental Disorders of Language

Developmental disorders of language include developmental language disorder, dyslexia, and motor-speech disorders such as articulation disorder and stuttering. These disorders have generally been explained by accounts that focus on their behavioral rather than neural characteristics; their processing rather than learning impairments; and each disorder separately rather than together, despite their commonalities and comorbidities. Here we update and review a unifying neurocognitive account—the Procedural circuit Deficit Hypothesis (PDH). The PDH posits that abnormalities of brain structures underlying procedural memory (learning and memory that rely on the basal ganglia and associated circuitry) can explain numerous brain and behavioral characteristics across learning and processing, in multiple disorders, including both commonalities and differences. We describe procedural memory, examine its role in various aspects of language, and then present the PDH and relevant evidence across language-related disorders. The PDH has substantial explanatory power, and both basic research and translational implications.

Sequence learning in the human brain: A functional neuroanatomical meta-analysis of serial reaction time studies

Sequence learning underlies numerous motor, cognitive, and social skills. Previous models and empirical investigations of sequence learning in humans and non-human animals have implicated cortico-basal ganglia-cerebellar circuitry as well as other structures. To systematically examine the functional neuroanatomy of sequence learning in humans, we conducted a series of neuroanatomical meta-analyses. We focused on the serial reaction time (SRT) task. This task, which is the most widely used paradigm for probing sequence learning in humans, allows for the rigorous control of visual, motor, and other factors. Controlling for these factors (in sequence-random block contrasts), sequence learning yielded consistent activation only in the basal ganglia, across the striatum (anterior/mid caudate nucleus and putamen) and the globus pallidus. In contrast, when visual, motor, and other factors were not controlled for (in a global analysis with all sequence-baseline contrasts, not just sequence-random contrasts), premotor cortical and cerebellar activation were additionally observed. The study provides solid evidence that, at least as tested with the visuo-motor SRT task, sequence learning in humans relies on the basal ganglia, whereas cerebellar and premotor regions appear to contribute to aspects of the task not related to sequence learning itself. The findings have both basic research and translational implications.

How Lifestyle Factors Affect Cognitive and Executive Function and the Ability to Learn in Children

In today's research environment, children's diet, physical activity, and other lifestyle factors are commonly studied in the context of health, independent of their effect on cognition and learning. Moreover, there is little overlap between the two literatures, although it is reasonable to expect that the lifestyle factors explored in the health-focused research are intertwined with cognition and learning processes. This thematic review provides an overview of knowledge connecting the selected lifestyle factors of diet, physical activity, and sleep hygiene to children's cognition and learning. Research from studies of diet and nutrition, physical activity and fitness, sleep, and broader influences of cultural and socioeconomic factors related to health and learning, were summarized to offer examples of research that integrate lifestyle factors and cognition with learning. The literature review demonstrates that the associations and causal relationships between these factors are vastly understudied. As a result, current knowledge on predictors of optimal cognition and learning is incomplete, and likely lacks understanding of many critical facts and relationships, their interactions, and the nature of their relationships, such as there being mediating or confounding factors that could provide important knowledge to increase the efficacy of learning-focused interventions. This review provides information focused on studies in children. Although basic research in cells or animal studies are available and indicate a number of possible physiological pathways, inclusion of those data would distract from the fact that there is a significant gap in knowledge on lifestyle factors and optimal learning in children. In a climate where childcare and school feeding policies are continuously discussed, this thematic review aims to provide an impulse for discussion and a call for more holistic approaches to support child development.

Is there a prediction network? Meta-analytic evidence for a cortical-subcortical network likely subserving prediction

Predictive coding is an increasingly influential and ambitious concept in neuroscience viewing the brain as a 'hypothesis testing machine' that constantly strives to minimize prediction error, the gap between its predictions and the actual sensory input. Despite the invaluable contribution of this framework to the formulation of brain function, its neuroanatomical foundations have not been fully defined. To address this gap, we conducted activation likelihood estimation (ALE) meta-analysis of 39 neuroimaging studies of three functional domains (action perception, language and music) inherently involving prediction. The ALE analysis revealed a widely distributed brain network encompassing regions within the inferior and middle frontal gyri, anterior insula, premotor cortex, pre-supplementary motor area, temporoparietal junction, striatum, thalamus/subthalamus and the cerebellum. This network is proposed to subserve domain-general prediction and its relevance to motor control, attention, implicit learning and social cognition is discussed in light of the predictive coding scheme. Better understanding of the presented network may help advance treatments of neuropsychiatric conditions related to aberrant prediction processing and promote cognitive enhancement in healthy individuals.

Are specific learning disorders truly specific, and are they disorders?

Specific learning disorders, such as dyslexia and dyscalculia, are frequently studied to inform our understanding of cognitive development, genetic mechanisms and brain function. In this Opinion Paper, we discuss limitations of this research approach, including the use of arbitrary criteria to select groups of children, heterogeneity within groups and overlap between domains of learning. By drawing on evidence from cognitive science, neuroscience and genetics, we propose an alternative, dimensional framework. We argue that we need to overcome the problems associated with a categorical approach by taking into account interacting factors at multiple levels of analysis that are associated with overlapping rather than entirely distinct domains of learning. We conclude that this research strategy will allow for a richer understanding of learning and development.

Modulation of striatum based non-declarative and medial temporal lobe based declarative memory predicts academic achievement at university level

BACKGROUND

There is a dearth of research on the roles of non-declarative (implicit) learning linked to the striatum and declarative (explicit) learning associated with the medial temporal lobes as predictors of academic attainment.

METHODS

Participants were 120 undergraduate students, studying Psychology or Engineering, who completed several long-term memory tests.

RESULTS

There was a significant interaction between the groups (Psychology or Engineering) and task type (declarative or non-declarative): Engineers performed better at declarative and psychologists at non-declarative learning. Furthermore, non-declarative but not declarative learning scores were significant correlates of academic achievement (r = 0.326, p < .05). Moreover, competitive modulation (activation of non-declarative learning in conjunction with deactivation of declarative learning) was a significant predictor of future academic achievement in both psychology (r = 0.264, p < .05) and Engineering (r = 0.300, p < .05) groups.

CONCLUSIONS

The results confirm that these declarative and non-declarative systems interact competitively and that the extent of this competition may have implications for understanding educational attainment.

Disentangling Neural Sources of Problem Size and Interference Effects in Multiplication

Multiplication is thought to be primarily solved via direct retrieval from memory. Two of the main factors known to influence the retrieval of multiplication facts are problem size and interference. Because these factors are often intertwined, we sought to investigate the unique influences of problem size and interference on both performance and neural responses during multiplication fact retrieval in healthy adults. Behavioral results showed that both problem size and interference explained separate unique portions of RT variance, but with significantly stronger contribution from problem size, which contrasts with previous work in children. Whole-brain fMRI results relying on a paradigm that isolated multiplication fact retrieval from response selection showed highly overlapping brain areas parametrically modulated by both problem size and interference in a large network of frontal, parietal, and subcortical brain areas. Subsequent analysis within these regions revealed problem size to be the stronger and more consistent "unique" modulating factor in overlapping regions as well as those that appeared to respond only to problem size or interference at the whole-brain level, thus underscoring the need to look beyond anatomical overlap using arbitrary thresholds. Additional unique contributions of interference (beyond problem size) were identified in right angular gyrus and subcortical regions associated with procedural processing. Together, our results suggest that problem size, relative to interference, tends to be the more dominant factor in driving behavioral and neural responses during multiplication fact retrieval in adults. Nevertheless, unique contributions of both factors demonstrate the importance of considering the overlapping and unique contributions of each in explaining the cognitive and neural bases of mental multiplication.

Specific learning disability in mathematics: a comprehensive review

Math skills are necessary for success in the childhood educational and future adult work environment. This article reviews the changing terminology for specific learning disabilities (SLD) in math and describes the emerging genetics and neuroimaging studies that relate to individuals with math disability (MD). It is important to maintain a developmental perspective on MD, as presentation changes with age, instruction, and the different models (educational and medical) of identification. Intervention requires a systematic approach to screening and remediation that has evolved with more evidence-based literature. Newer directions in behavioral, educational and novel interventions are described.

Is procedural memory enhanced in Tourette syndrome? Evidence from a sequence learning task

Procedural memory, which is rooted in the basal ganglia, underlies the learning and processing of numerous automatized motor and cognitive skills, including in language. Not surprisingly, disorders with basal ganglia abnormalities have been found to show impairments of procedural memory. However, brain abnormalities could also lead to atypically enhanced function. Tourette syndrome (TS) is a candidate for enhanced procedural memory, given previous findings of enhanced TS processing of grammar, which likely depends on procedural memory. We comprehensively examined procedural learning, from memory formation to retention, in children with TS and typically developing (TD) children, who performed an implicit sequence learning task over two days. The children with TS showed sequence learning advantages on both days, despite a regression of sequence knowledge overnight to the level of the TD children. This is the first demonstration of procedural learning advantages in any disorder. The findings may further our understanding of procedural memory and its enhancement. The evidence presented here, together with previous findings suggesting enhanced grammar processing in TS, underscore the dependence of language on a system that also subserves visuomotor sequencing.