Title Page

An MRI Study of the Relationship Between Human Neuroanatomy and Behavioral Ability

Paul Thomas Schoenemann

B.A. (University of California, Berkeley) 1986

M.A. (University of California, Berkeley) 1993

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Doctor of Philosophy

Anthropology

in the

GRADUATE DIVISION

of the

UNIVERSITY OF CALIFORNIA, BERKELEY

Committee in charge:

Professor Vincent M. Sarich

Professor William S.-Y. Wang

Professor F. Clark Howell

Professor Thomas F. Budinger

Spring 1997

Abstract

Hominid brain volume increased more than 3-fold in ~2.5 million years. From an evolutionary perspective, natural selection for one or more behavioral abilities is the most likely explanation. A large number of studies have demonstrated that brain volume is related to performance on standardized intelligence tests. The present study expands on this work in three important ways. First, a sibling-pair design is used, allowing for the calculation of independent within-family (WF) and between-family (BF) correlations. Second, a broader set of cognitive dimensions (specifically guided by an understanding of human evolution) is investigated. Third, neuroanatomical components are quantified from higher resolution 3D MR images (whole brain volume resolution of 1.3 mm3). The subject group consisted of 36 pairs of sisters.

The results for BF correlations between neuroanatomical and cognitive variables are consistent with previous MRI-based studies, but WF correlations are almost entirely negative or close to zero. The BF correlation of brain volume to the first principal component of 11 cogntive tests (1st PC) is r=0.46 (p<0.01), but the corresponding WF correlation is only r=-0.05 (NS). Social interest variables show a similar pattern, while throwing ability and maturation rate are unrelated to neuroanatomic variation both BF and WF.

This pattern is not easily explained by methodological or statistical artifacts. This study also shows that family differences in socio-economic status (SES) do not explain this pattern, because SES is not correlated with brain volume. It is therefore highly unlikely that the genetic correlation between neuroanatomy and behavior is zero. Possible explanations are: 1) Behavioral variability is genetically correlated only weakly with brain volume, precluding reliable detection in relatively small sample sizes; 2) The types of tests used might not assess behavior important for hominid brain evolution; 3) Within-family environmental effects (e.g., sibling competition) may mask any underlying genetic correlation. This is consistent with the finding that individuals more than four years apart from their sister show a correlation between brain volume and 1st PC of r=0.65 (p<0.023, N=12). Those closer in age only show a correlation of r=0.15 (NS, N=60). Furthermore, several cognitive tests are negatively correlated with WF age differences.

Table of Contents

Chapter 1: Introduction

Chapter 2: Human Neuroanatomical Evolution

2.1 Overall Brain Size

2.1.1 Brain Size Scaling

2.1.1.1 Causal Explanations of Brain to Body Size Scaling

2.1.1.2 Encephalization in Hominid Evolution

2.2 Grade Differences in Primate Brain Size

2.3 Other Aspects of Brain Evolution

2.3.1 Major Neuroanatomical Divisions

2.3.2 Cortical Areas

2.3.3 Sub-Cortical Areas

2.3.4 Spinal cord

2.3.5 Gray vs. White matter

2.3.6 Cortical folding

2.3.7 Functional Reorganization

2.3.7.1 Primary Visual Cortex and The Lunate Sulcus

2.3.7.2 Inferior Frontal Lobe

2.3.7.3 Cortical Asymmetry

2.4 Summary

Chapter 3: Evolutionary Explanations

3.1 Genetic Drift

3.2 Behavioral Benefits of Larger Brains

3.2.1 Brain size as an Indicator of the Complexity of Information Processing

3.2.2 Significant Behavioral Changes that Might Explain Hominid Brain Evolution

3.2.2.1 Evolution of Language

3.2.2.2 Social Ability as an Impetus to Brain Size Increase

3.2.2.3 Throwing, Hunting, and Spatial Ability

3.2.2.4 Diet and Human Evolution

3.2.2.5 Summary of Behavioral Changes Which Might Account for Hominid Brain Evolution

Chapter 4: Research into the Associations between Neuroanatomical Variation and Behavior

4.1 Hypotheses about the Functional Organization of the Brain

4.2 A Key Functional Area: The Frontal Lobes

4.3 The Meaning of Variation within Modern Human Populations

4.4 Attempts to Find Behavioral Correlates of Neuroanatomical Variation within Species

4.4.1 Evidence from Non-Human Species

4.4.2 Evidence in Humans

4.4.2.1 Clinical Populations

4.4.2.2 Studies of Normal Individuals

4.4.2.3 Potentially Inconsistent Evidence

Chapter 5: Rationale of this Study

5.1 Limitations of Previous Studies

5.2 Contribution of the Present Research

5.2.1 Within-Family Correlations as a Test of Causality

5.2.1.1 Height/IQ and Myopia/IQ Associations: Test Cases

5.2.1.2 Brain size/IQ Studies of Between- versus Within-family Correlations

5.2.2 Expanding the Variety of Cognitive Dimensions Addressed

5.2.2.1 Prefrontal tests.

5.2.2.2 Additional linguistic tests

5.2.2.3 Throwing accuracy
5.2.2.4 Social dimensions

5.2.3 Expanding the Neuroanatomical Subdivisions Addressed

5.2.4 What is the Effect of Increasing Brain Size on Maturation-Rate?

5.2.5 Additional Variables of Interest

5.2.6 Increasing MRI Spatial Resolution

5.3 Summary of Research Goals

Chapter 6: Experimental Procedures

6.1 General Study Design

6.2 Subject Selection

6.2.1 Who , Why, and How Many

6.2.2 Inclusion/Exclusion Criteria

6.2.3 Subject Recruitment

6.2.4 Consent Process and Documentation

6.2.5 Procedures

6.2.5.1 Data Collection

6.2.5.2 Methods of Data Analysis

Chapter 7: Results

7.1 Anthropometric Variables

7.2 Neuroanatomical Variables

7.3 Cognitive Variables

7.4 Between-family Correlations of Cognitive Tests with Neuroanatomical Features

7.5 Within-family Correlations of Cognitive Tests with Neuroanatomical Features

7.6 Sociality

7.7 Rate of Maturation

7.8 Throwing Accuracy

7.9 Methodological Issues

7.9.1 Reliability Differences and Restriction of Range

7.9.2 Empirical Relationship Between Variance Differences and the Differences in the Size of Correlations

7.9.3 Randomization Studies

7.9.4 Consistency Across Subsets of Data

7.9.5 A Note About Age Correction

7.9.6 Summary of Methodological Issues

7.10 Mean Differences in Behavioral Variables Between Larger- and Smaller-Brained Siblings

7.11 Linguistic Variables

Chapter 8: Discussion

8.1 Explanations for Lack of Within-Family Correlations

8.1.1 Between-Family Environmental Effects

8.1.2 Cross-Assortative Mating

8.1.3 Within-Family Environmental Effects

8.2 Implications for Hominid Brain Evolution

8.2.1 Other Cognitive Dimensions of Interest

8.2.2 How Strong Does the Association Need to Be?

8.3 Sex Differences

8.4 Grey-White Matter Contrast and the Structure of the Brain

8.5 Possible Physiological Explanations of Brain Size Increases

8.6 Linguistic Tasks

8.7 Summary

Chapter 9: Future Research

Appendix A: Comparative and Fossil Data Tables

Table 1: Cranial Capacities and Dates for Selected Fossil Specimens (Modified Slightly from Falk 1987a)

Table 2: Brain sizes, body sizes, encephalization quotients, and 'extra brain mass' in 95 mammals (including 52 primates) and 1 reptile

Table 3: Estimated cranial capacity and body size of fossil hominids, extant pongids and Homo sapiens.

Appendix B: Questionnaire and Cognitive Test Details

Subject Questionnaire

Raven's Progressive Matrices (RAVEN) Instructions to Subjects

Simple Reaction Time test (SRT)

Instructions to Subjects

Object Identification Reaction Time test (OBJECT-ID)

Instructions to Subjects

Sequence of Test Trials

Sentence Verification test (SENTENCE-VERIF and SYNTAX)

Instructions to Subjects

Construction of the Sentences

Order of Appearance of Test Sentences:

Mental Rotation Reaction Time Test (MRT)

Instructions to Subjects

Wisconsin Card Sort Test - computerized adaptation (WCST)

Instructions Given to Subjects

Appendix C: Zero-order and Intraclass Correlations for the Variables Used in this Study

Zero-order Correlations

Among All 72 Individuals:

Between- and Within-family Zero-Order Correlations (N=36):

Intraclass Correlations:

Between-family Basic Statistics

Within-family Basic Statistics

Appendix D: MRI and Cognitive Testing Subject Consent Forms

MRI Consent Form

Cognitive Testing Consent Form

Appendix E: Line Drawings of the Human Brain

Lateral view

Superior view

Medial (mid-saggital) view

Inferior view

Bibliography

List of Figures

Figure 2.1	Cranial capacity in fossil hominids over time
Figure 2.2	General relationship of body to brain size in mammals
Figure 2.3	Cranial capacity and body size in fossil hominids
Figure 2.4	Cerebral cortex volume and percent white matter in mammals
Figure 2.5	Gray and white matter cerebral volumes in mammals
Figure 2.6	Corpus callosum to brain size in 3 orders of mammals

Figure 5.1	Hypothetical causal links between SES, brain anatomy, and behavior
Figure 5.2	Theoretical independence of between and within family associations

Figure 6.1	Gaussian curve fitting on pixel intensity probability density functions

Figure 7.1	Association of BRAINVOL to RAVEN with family relationships indicated
Figure 7.2	Between family relationship of BRAINVOL to RAVEN
Figure 7.3	Relationship of proportion of variance to differences in size of correlation
Figure 7.4	Randomization study histograms

Figure 8.1	Comparison of older and younger sibling relationships between brain volume and general cognitive performance
Figure 8.2	Examples of negative within-family relationships between age and cognitive tests

Figure E.1	Landmarks and features of the lateral surface of the human brain
Figure E.2	Landmarks and features of the superior surface of the human brain
Figure E.3	Landmarks and features of the medial surface of the human brain
Figure E.4	Landmarks and features of the inferior surface of the human brain

List of Tables

Table 2.1	Comparison of brain sizes between the great apes and humans, controlling for body weight
Table 2.2	Encephalization quotients of different neuroanatomical components based on non-human anthropoid primate trends with respect to body weight
Table 2.3	Encephalization quotients of different neuroanatomical components based on non-human anthropoid primate trends with respect to brain volume

Table 6.1	Age data
Table 6.2	Schooling and socio-economic status
Table 6.3	Neuroanatomical variables
Table 6.4	Cognitive tests
Table 6.5	Handedness data
Table 6.6	Sociality indicators
Table 6.7	Menarche
Table 6.8	Throwing accuracy
Table 6.9	Amount of exercise
Table 6.10	Anthropometric data
Table 6.11	Test reliabilities

Table 7.1	Between family correlations among anthropometric variables
Table 7.2	Within family correlations among anthropometric variables
Table 7.3	Between family correlations among neuroanatomic variables
Table 7.4	Within family correlations among neuroanatomic variables
Table 7.5	Between family correlations of anthropometric and neuroanatomic variables
Table 7.6	Within family correlations of anthropometric and neuroanatomic variables
Table 7.7	Between family correlations among cognitive variables
Table 7.8	Within family correlations among cognitive variables
Table 7.9	Between family correlations of cognitive to neuroanatomic variables
Table 7.10	Between family correlations of neuroanatomic measures with cogntive 1st PC, and partial correlations with cogntive variables controlling for 1st PC
Table 7.11	Within family correlations of cognitive to neuroanatomic
Table 7.12	Within family correlations of neuroanatomic measures with cogntive 1st PC, and partial correlations with cogntive variables controlling for 1st PC
Table 7.13	Between family correlations of neuroanatomic to sociality measures
Table 7.14	Within family correlations of neuroanatomic to sociality measures
Table 7.15	Between family correlations of sociality with cognitive variables
Table 7.16	Within family correlations of sociality with cognitive variables
Table 7.17	Between and within family correlations of MENARCHE with neuroanatomic variables
Table 7.18	Between and within family correlations of THROW (throwing accuracy) with neuroanatomic variables
Table 7.19	Estimated effect of range-restriction and reliability differences on the largest associations with BRAINVOL found in this study
Table 7.20	Average within-family differences for the cognitive variables in this study
Table 7.21	Average within-family differences for the First PC, and the other cognitive variables controlling for First PC
Table 7.22	Average within-family differences for MENARCHE, THROW, and sociality measures
Table 7.23	Average within-family differences for the cognitive variables in this study grouped by within-family BRAINVOL differences
Table 7.24	Average within-family differences for the First PC and the other cognitive variables controlling for First PC grouped by within-family BRAINVOL differences
Table 7.25	Average within-family differences for MENARCHE, THROW, and sociality variables grouped by within-family BRAINVOL differences
Table 7.26	Between and within family associations between SYNTAX and six possible correlates of past exposure to esoteric syntax

Table 8.1	Between family correlations of SES with neuroanatomic variables
Table 8.2	Within-family correlations of cognitive to neuroanatomic variables for sibling pairs that differ by less than four years in age (N=30)
Table 8.3	Within-family correlations of cognitive to neuroanatomic variables for sibling pairs that differ by more than four years in age (N=6)
Table 8.4	Average within-family differences for the cognitive variables grouped by within-family age differences
Table 8.5	Average within-family differences for the First PC and the other cognitive variables controlling for First PC, grouped by within-family age differences
Table 8.6	Average within-family differences for MENARCHE, THROW, and sociality variables grouped by within-family age differences
Table 8.7	Within-Family Correlations Between Cognitive Tests and Age at Testing

Acknowledgments

    This dissertation would not have happened without the help of a huge number of people. The most important being my wife, Reina A. Wong, who carried the family on her back at various times while I worked on this project, and helped in numerous other ways. Equally important were the subjects themselves, who agreed to give me hours of their time and undergo such extensive testing and MR imaging in the name of science (and a small fee).
    Dr. Vince Sarich has, over the years, literally reshaped how I see the world; he more than anyone else has been my intellectual mentor. He also played a crucial role in securing funding for this project. Dr. William Wang has also been extremely influential, and I consider his linguistics seminars to be the highlights of my graduate education. I owe him gratitude for kindling my interest in the evolution of language, and for allowing me the space and support to pursue questions relating to this most curious and magical feature of human behavior. Dr. Arthur Jensen provided the inspiration, pointed me toward funding, and provided invaluable statistical and methodological advice on all aspects of this project. He was also a gold mine of references to important work on individual differences in cognitive abilities, and provided me with copies of several tests and other materials which were used in this study. I doubt it would have been accomplished without his help at crucial times. Although he was not officially a member of my committee, he probably provided more help than anyone. Dr. F. Clark Howell, through his graduate seminars, allowed me to explore the interesting questions in physical anthropology. Dr. Thomas Budinger sought me out at a crucial time in this project and provided me with the computational tools and advice crucial to the analysis of the MRI data. He also prodded me to look at my data in new ways. I admire his drive and ambition as a scientist, and his open-mindedness to interesting questions of all kinds. Dr. Sundar Amartur kindly showed me how to use his gaussian-curve-fitting program. Dr. Sarah Nelson also deserves special mention for sponsoring my project, without any benefit to herself, at the UCSF Magnetic Resonance Science Center, and for providing crucial advice concerning the human subjects protocol. Her help at crucial times was essential. Frank Miele deserves special mention for tirelessly keeping this project on track even when I was sure the train had derailed. He was a crucial part of the whole project, and I cannot thank him enough for all his help.
    A number of people provided advice at various times and in various ways. Nancy Poole and Jane Sprouse advised me on cognitive tests and how best to give them. They also helped me obtain copies of several of the tests used in this study. Babak Razani showed me many of the intricacies of VIDAª, helped me formalize my MRI quantification methodology, and helped rename files so that I was blind to the subjectÕs scan while segmenting them. Xia Teng also helped in various ways during segmenting. The MRI technologists at the MRSC: Gary Ciciriello, Evelyn Proctor, and Niles Bruce, treated the subjects (and myself) with care, graciousness, humor, and professionalism that put us at ease and were crucial to the success of this project. Gary Ciciriello particularly helped above and beyond the call in several instances. Margaret Lobo made MRI scheduling and administrative work a pleasure. Pam Streitfeld lent me her skinfold calipers and put me in touch with Dr. Pat Crawford and Beverley Barnes, who took the time to train me in their use. Dr. Tim White lent me a scale, along with an anthropometer. Dr. Arthur Shimamura provided confirmatory advice on prefrontal tests. Dr. David Lohman gave crucial advice on spatial ability testing. Dr. Lee Willerman talked to me about his pioneering MRI study of brain size and IQ. Dr. Robert Schultz provided specific details about how I might replicate his study of gray/white matter image contrast and its relationship to IQ. Drs. Philip Vernon and Robert Zatorre both helped with advice on various details of this project. Drs. Fred Johnson and David Rowe also helped me with various statistical questions.
    Among my friends, Dr. Karen Schmidt, Dr. John Allen, (soon to be Dr.) Manuel Lizzaralde and John Dolan provided me with a intellectual stimulation and friendship that helped sustain me through this long journey. The most important people, however, were my two children, Daniel and Maria, who endured me through this whole process, and who, along with Reina, provided me with a reason to keep going. I also would like to thank all my parents, of all kinds, for their unwavering support and their encouragement at all the right times.
    This research was supported by grants from the Alexis de Tocqueville Institute, the Robert H. Lowie Graduate Scholarship program at the University of California at Berkeley, and the Charles Atwood Kofoid Fellowship for graduate study in Anthropology at the University of California at Berkeley.