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Development of Mathematical Cognition: Neural Substrates and Genetic Influences, Volume 2 [Kõva köide]

Edited by (University of Virginia, Charlottesville, VA, USA), Edited by (National Institute of Child Health and Human Development, NIH, Rockville, MD, USA), Edited by (University of Missouri, Columbia, MO, USA)
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Development of Mathematical Cognition: Neural Substrates and Genetic Influences reviews advances in extant imaging modalities and the application of brain stimulation techniques for improving mathematical learning. It goes on to explore the role genetics and environmental influences have in the development of math abilities and disabilities.Focusing on the neural substrates and genetic factors associated with both the typical and atypical development of mathematical thinking and learning, this second volume in theMathematical Cognition and Learning series integrates the latest in innovative measures and methodological advances from the top researchers in the field.Provides details about new progress made in the study of neural correlates of numerical and arithmetic cognitionAddresses recent work in quantitative and molecular geneticsWorks to improve instruction in numerical, arithmetical, and algebraic thinking and learningInforms policy to help increase the level of mathematical proficiency among the general public

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"...an excellent book that should be on the desk of anyone who does research in numerical and mathematical cognition. In fact, I would recommend that any such person should obtain every volume in the 'Mathematical Cognition and Learning' series." --PsycCRITIQUES

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A helpful review of how contemporary brain imaging techniques and genetic methods can inform our understanding of mathematical cognitive development and ways to improve it.
Contributors xi
Foreword xiii
Preface xxv
1 Introduction: How the Study of Neurobiological and Genetic Factors Can Enhance Our Understanding of Mathematical Cognitive Development
Daniel B. Berch
David C. Geary
Kathleen Mann Koepke
Introduction
1(1)
Neurobiological Perspectives on Mathematical Cognitive Development
2(1)
Using Neuroimaging Methods to Study Children's Mathematical Development
2(1)
Mathematical Cognition and Development: Brain Structure and Function
3(4)
A Brief History
3(2)
The Developing Brain
5(2)
Brain Imaging Methods Used in Studying Mathematical Cognitive Development
7(2)
Criticisms of fMRI
9(3)
Reverse Inference
11(1)
How Brain Imaging Can Advance Cognitive Theorizing
12(1)
Behavioral and Neuro-Genetics of Mathematical Cognition
13(3)
Interpretive Challenges
16(2)
Behavioral Genetics in the Age of Molecular Genetics and Neuroscience
18(1)
Summary and Conclusions
19(1)
References
19(8)
Part I Neural substrates
2 Number Symbols in the Brain
Daniel Ansari
Introduction
27(2)
Which Brain Regions Are Engaged During the Processing of Numerical Symbols?
29(5)
Evidence from Comparison Tasks
29(1)
Response-Selection Confounds
30(1)
Evidence from fMRI Adaptation Studies
31(1)
Semantic or Perceptual Processing of Number Symbols in the IPS?
32(2)
Numerical Symbols in the Brain—Evidence from Developmental Studies
34(4)
Perceptual Representation of Number Symbols in the Brain
38(2)
Are Symbolic and Nonsymbolic Quantity Representations Linked in the Brain?
40(3)
Differences in Cardinal and Ordinal Processing of Number Symbols in the Brain
43(1)
Conclusions and Future Directions
44(2)
Acknowledgments
46(1)
References
46(5)
3 Neural and Behavioral Signatures of Core Numerical Abilities and Early Symbolic Number Development
Daniel C. Hyde
Yi Mou
Introduction
51(2)
Two Systems for Nonverbal Numerical Cognition
53(4)
Parallel Individuation System
53(1)
Approximate Number System
54(1)
Behavioral Evidence for Distinct Systems of Numerical Cognition
54(3)
The Cognitive Neuroscience of Two Core Systems of Number
57(8)
Establishing the Neural Signatures of Two Systems
57(4)
Distinct Brain Mechanisms of Two Systems
61(1)
Continuity in Neural Signatures over Development
62(1)
Change in Core Numerical Processing over Development
63(2)
The Relationship Between Core Systems and Symbolic Number Abilities
65(5)
Approximate Number System and Symbolic Number and Mathematics Abilities
65(2)
The Relationship of Core Systems to Early Number Concept Development
67(3)
Conclusions
70(1)
Acknowledgments
71(1)
References
71(8)
4 A Neurodevelopmental Perspective on the Role of Memory Systems in Children's Math Learning
Vinod Menon
Introduction
79(2)
Development of Memory-Based Strategies in Children's Mathematics Learning
81(2)
Declarative Memory and Its Development
83(1)
Medial Temporal Lobe Memory System
83(2)
Memory Processes in the Context of Mathematics Learning
85(1)
Children Engage the MTL Memory System Differently than Adults
85(2)
Individual Differences in Children's Retrieval Strategy Use are Associated with the MTL
87(1)
Decoding Brain Activity Patterns Associated with Counting and Retrieval Strategies
88(3)
Hippocampal-Prefrontal Cortex Circuits and their Role in Children's Mathematics Learning
91(2)
Longitudinal Changes in MTL Response, Representations and Connectivity Associated with Memory-Based Retrieval
93(5)
Why Adults May not Rely on MTL Memory Systems for Mathematics Performance and Learning
98(1)
Conclusions
99(1)
Acknowledgments
100(1)
References
100(9)
5 Finger Representation and Finger-Based Strategies in the Acquisition of Number Meaning and Arithmetic
Ilaria Berteletti
James R. Booth
Introduction
109(1)
Fingers in Numerical and Arithmetic Processing
110(9)
The Role of Fingers and Finger Representation in Number Processing
110(2)
Neural Substrates for Hand and Number Processing
112(2)
Finger-Based Strategies and Finger Representation in Arithmetic
114(3)
Neural Substrates for Finger-Related Activation During Arithmetic Problem Solving
117(2)
Finger-Based Strategies and Operation-Specific Processes
119(9)
A Model Supporting Operation-Specific Processes
120(1)
Behavioral Evidence for Operation-Specific Processes
120(2)
Operation-Specific Neural Networks
122(1)
Operation-Specific Processes as a Consequence of Operation-Dependent Teaching Methods
123(1)
Operation-Dependent Finger-Related Activations
124(1)
Finger Counting, Cultural Influence, and Spatial-Numerical Relations
125(3)
Future Directions
128(4)
Conclusions
132(1)
References
132(9)
6 Neurocognitive Architectures and the Nonsymbolic Foundations of Fractions Understanding
Mark Rose Lewis
Percival G. Matthews
Edward M. Hubbard
Introduction
141(2)
Fundamental Limitations of the Human Cognitive Architecture
143(1)
A Competing View: The Ratio Processing System
144(1)
How the RPS May Influence Fraction Learning
145(3)
Emerging Behavioral and Neuroimaging Evidence for RPS Model Predictions
148(6)
Open Questions
154(1)
Charting the Development and Architecture of the RPS
154(1)
Leveraging the RPS to Support Fraction Learning
155(2)
RPS and Dyscalculia?
157(1)
Summary and Conclusions
158(1)
Acknowledgments
158(1)
References
159(6)
7 Developmental Dyscalculia and the Brain
Karin Kucian
Introduction
165(1)
Developmental Dyscalculia
166(20)
Diagnosis of Developmental Dyscalculia
168(2)
What Neuroimaging Is Telling Us about Developmental Dyscalculia
170(3)
Neuronal Correlates of Developmental Dyscalculia
173(3)
Deficient Functional Networks
176(5)
Abnormal Neuronal Macro- and Microstructures
181(4)
Neurometabolites
185(1)
Conclusions and Future Directions
186(2)
References
188(7)
8 Neurocognitive Components of Mathematical Skills and Dyscalculia
Wim Fias
Introduction
195(2)
Accessing Quantity Representations
197(3)
Working Memory: The Role of Serial Order
200(8)
Executive Functions
208(3)
Discussion and Conclusions
211(2)
References
213(6)
9 Individual Differences in Arithmetic Fact Retrieval
Bert De Smedt
Introduction
219(1)
Development and Measurement of Arithmetic Fact Retrieval
220(2)
Neurocognitive Determinants of Individual Differences in Arithmetic Fact Retrieval
222(8)
Numerical Magnitude Processing
224(3)
Phonological Processing
227(3)
Neural Correlates of Arithmetic Fact Retrieval
230(6)
Arithmetic Fact Retrieval in the (Developing) Brain
230(3)
Individual Differences in Brain Activity During Fact Retrieval
233(1)
Connections Between Areas of the Arithmetic Fact-Retrieval Network
234(2)
Conclusions and Future Directions
236(2)
References
238(7)
10 Transcranial Electrical Stimulation and the Enhancement of Numerical Cognition
Amar Sarkar
Roi Cohen Kadosh
Introduction
245(5)
A Brief History
246(1)
tES Today
247(1)
The Forms of tES
248(2)
Principles and Limitations of tES Experiments
250(5)
Placebo Effects
251(1)
Online and Offline Effects: Single Session and Training Studies
251(1)
Depth of Stimulation
252(1)
Choosing the Brain Region
252(1)
Size, Number, and Placement of the Electrodes
253(2)
Choosing the Type of Stimulation
255(1)
Evidence of tES-Induced Enhancement of Numerical Cognition
255(18)
Numerosity
255(5)
Symbolic and Magnitude Processing
260(7)
Arithmetic Operations
267(5)
All or Null? The Case of Nonsignificant Results
272(1)
Evidence of tES-Induced Enhancements in Dysfunctional Numerical Cognition
273(6)
Mathematics Anxiety
273(3)
Dyscalculia
276(3)
The To-Do List
279(6)
Cognitive Cost
279(1)
Transfer Effects
280(2)
Individual Differences
282(2)
Ecological Validity
284(1)
Conclusions
285(1)
References
286(13)
Part II Genetic Influences
11 Individual Differences in Mathematics Ability: A Behavioral Genetic Approach
Stephen A. Petrill
Yulia Kovas
Introduction
299(1)
Introduction to Quantitative Genetics
300(3)
Etiology of Individual Differences in Mathematics
303(3)
Etiology of the Links between Mathematics Ability and Other Traits
306(6)
Multivariate Genetic Designs
306(1)
Etiology of Relationships between Mathematics and Reading as well as Language-Related Skills
307(1)
Origin of Relationships between Mathematics and Spatial Ability
308(1)
Etiology of Relationships among Mathematical Subskills
309(1)
Overlap in Genetic Influences on Academic Subjects
309(1)
Genetic Effects Specific to Mathematics
310(1)
Etiology of Relationships between Mathematical Ability and Related Affective Factors
311(1)
Mathematical Development
312(1)
Molecular Genetic Studies of Mathematics
313(1)
Neurobiological Mechanisms
314(3)
Conclusions
317(1)
Acknowledgment
317(1)
References
317(8)
12 Genetic Syndromes as Model Pathways to Mathematical Learning Difficulties: Fragile X, Turner, and 22q Deletion Syndromes
Michele M.M. Mazzocco
Andrea I. Quintero
Melissa M. Murphy
Michael McCloskey
Introduction
325(3)
Why Focus on Fragile X, Turner, and 22q Deletion Syndromes to Study MLD?
326(1)
Contributions of Syndrome Research to Understanding MLD
327(1)
Syndromes as Models of MLD
328(20)
Fragile X Syndrome
328(1)
Turner Syndrome
329(1)
Chromosome 22q11.2 Deletion Syndrome
329(1)
MLD Frequency and Severity in Children with Fragile X, Turner, or 22q11.2 Deletion Syndromes
330(1)
Correlates as Indicators of Pathways to or Subtypes of MLD: Contributions and Limitations
331(1)
Correlates as Indicators of MLD Specificity in Fragile X, Turner, and 22q11.2DS
332(10)
Models of Relations Between Math, Executive Function, and Attention
342(3)
Syndrome Models Contribute to Understanding Neuro-Correlates of MLD
345(3)
Conclusions
348(2)
Acknowledgments
350(1)
References
350(9)
Index 359
Daniel B. Berch is Professor of Educational Psychology and Applied Developmental Science at the University of Virginias Curry School of Education. Prior to this position, he was Associate Dean for Research and Faculty Development at the Curry School. Before coming to the University of Virginia, Professor Berch served as Associate Chief of the Child Development and Behavior Branch at the National Institute of Child Health and Human Development, NIH. His previous federal service included a year spent as a Senior Research Associate at the U. S. Department of Education, advising the Assistant Secretary for Educational Research and Improvement. Professor Berch is a cognitive developmental psychologist with interests ranging from the development of numerical cognition and mathematical learning disabilities (MLD) to evolutionary perspectives on education. He has published articles on childrens magnitude representations, the development of number sense, and the role of working memory in MLD. He is senior editor of the book, Why is math so hard for some children? The nature and origins of mathematical learning difficulties and disabilities (co-edited by Michele Mazzocco).

Among other honors, he received the NIH Award of Merit, was elected Fellow of the American Psychological Associations Division of Experimental Psychology, served as an ex officio member of the U.S. Department of Educations National Mathematics Advisory Panel commissioned by President George W. Bush, was elected to the Evolution Institutes Scientific Advisory Board (and chairs its Education Subcommittee), was appointed to the AIM Academys Research Advisory Board, and served as a member of the Professional Advisory Board of the National Center for Learning Disabilities for six years. During the past several years, Professor Berch has been working on the implications of evolutionary theory for educational research and practice, publishing a book chapter on instructing evolved minds, serving as one of the Evolution Institutes primary organizers of a 2013 conference on evolutionary perspectives in educational research funded by the American Educational Research Association, and is co-author (with David Geary) of an article entitled Evolutionary Approaches to Understanding Childrens Academic Achievement” to be published in Wileys forthcoming online reference work, Emerging Trends in the Social and Behavioral Sciences.

David C. Geary is a cognitive developmental and evolutionary psychologist at the University of Missouri. He has wide ranging interests but his primary areas of research and scholarly work are childrens mathematical cognition and learning and Darwins sexual selection as largely but not solely related to human sex differences.

Professor Geary directed a 10-year longitudinal study of childrens mathematical development from kindergarten to ninth grade, with a focus on identifying the core deficits underlying learning disabilities and persistent low achievement in mathematics. The study was funded by the National Institutes of Health (US), including through a MERIT award to professor Geary. One result has been the identification of the school-entry number knowledge that predicts economically-relevant mathematical competencies in adolescence. As a follow-up, professor Geary is directing a second longitudinal study, funded by the National Science Foundation (US), to identify the preschool quantitative competencies that predict this school-entry number knowledge. Professor Geary has also published conceptual and theoretical articles on individual differences in childrens mathematical learning, as well as a book published by the American Psychological Association, Childrens mathematical development (1994); recently translated into Korean. Professor Geary has also contributed to applied and policy related work on this topic, serving, for instance, on the Presidents National Mathematics Advisory Panel, and chairing its learning processes task group.

Professor Gearys interests in evolution are reflected in two of his other books published by the American Psychological Association, The origin of mind: Evolution of brain, cognition, and general intelligence (2005), and Male, female: The evolution of human sex differences (1998, 2010 second edition). The corresponding empirical work ranges from the study of changes in brain volume during hominid evolution to human mate choices to hormonal responses to simulated (video game) competition. Professor Gearys current interests in this area follow from several of his collaborative studies on the effects of prenatal toxin exposure on sex differences in cognition and behavior in mice. Specifically, traits related to Darwins sexual selection are often exaggerated relative to other traits. These would include, for example, the bright plumage of the males of many species of bird that in turn is a good indicator of their behavioral and genetic health. These traits are particularly sensitive to environmental disruption, even in healthy individuals. Professor Gearys in progress book, The evolution of vulnerability, is focused on these traits in humans and how they can be used to identify at-risk populations and individuals.

Kathleen Mann Koepke, Ph.D., is Director of the Math and Science Cognition and Learning, Development & Disorders Program in the Child Devlopment and Behavior Branch (CDBB) of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Rockville, MD (kmk@nih.gov).

Dr. Mann Koepke oversees a research program focused on developing and supporting research and training initiatives to increase knowledge relevant to the development of math and science cogniton, reasoning, knowledge, and abilities, both in animals and in humans from birth through all years of formal education in diverse learners with and without disabilities. This research focus recently lead to her serving as co-Guest Editor of a special journal issue regarding the co-occurrence of math and reading disabilities (Mann Koepke, K and Miller, B. (Eds.) At the Intersection of Math & Reading Disabilities. Journal of Learning Disabilities. 2013: 46(6)).

She is a lifecourse developmental cognitive neuroscientist/psychologist with a passion to serve the cognitively challenged and/or disabled via promoting new and innovative basic research and theoretically-grounded evidence-based intervention strategies to maximuze function. Dr. Mann Koepke has served in the Division of Extramural Programs across the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), and now NICHD, overseeing research on cognitive and neurological development and disorders, including neurobiological, behavioral and caregiving research foci. She has served on numerous federal and national committees aimed at advancing research and services for young learners and persons with cognitive and/or physical disability or differences, co-authoring numerous calls for new research to close significant gaps, as well as peer-reviewed publications. Prior to coming to NIH, she was faculty in Neurology (Psychology) at Washington University-St. Louis School of Medicine where she managed the universitys Alzheimers Disease Research Center (supported in part by grant P50AG05681), and served as Director of its Education Core and its Rural Outreach Satellite. While there, expanding on her enthusiasm for the use of newly developed technologies as tools for cognition, she developed and regularly contributed to the first-ever freely available web-based online educational support system for anyone interested in Alzheimers disease (AD) and for formal and informal dementia patient caregivers; the cite has garnered numerous national and international awards. This early online educational service has been used & replicated around the globe as a model for online disease/disabilty-focused educational support service.