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Index
academic achievement influence of intelligence level, 19–21
achievement tests, 16–17
active reading for children effect on IQ, 154
adenine (A), 59
adoption studies, 41Denmark Adoption Studies of schizophrenia, 46–47
Sweden Adoption Study, 47
twin studies of intelligence, 46–50
aging and IQ score, 30–32
Alkire, Michael, 183
alleles of genes, 60
Alzheimer’s disease, 64, 156
amino acids, 59
analogy tests, 16
animal studies bridging animal and human research at the level of neurons, 175–179
aptitude tests, 16–17
Armed Forces Qualification Test (AFQT), 62
artificial intelligence (AI) based on human intelligence, 179–183
attention deficit hyperactivity disorder (ADHD), 156
autism, 2–3
autism research, 42
base pairs (nucleotides), 59, 60
BDNF (brain-derived neurotrophic factor), 62–63, 132
behavioral genetics, 41–42
Behaviorist view of human potential, 39
bell curve distribution of IQ scores, 13–15
Benbow, Camilla, 30, 77
bias in intelligence tests, 17–18
Big Data analysis, 60
Binet, Alfred, 12–13
Binet–Simon intelligence test, 12–13
bioinformatics, 60
Blank Slate view of human potential, 37, 39, 195
Bochumer Matrizen-Test (BOMAT), 144, 146–147, 148–149
boosting IQ, see increasing intelligence
Bouchard, Thomas, 50
brain activity evidence for individual differences, 76–79
multiple areas involved in intelligence, 76–79 See also fMRI; PET
brain-altering technologies, 158–162
brain anatomy Einstein’s brain, 79, 95–96 See also Brodmann Areas
brain efficiency and intelligence brain activity in low-IQ groups, 75–76
complexity of the concept, 110
effects of learning, 73–75
functional neuroimaging studies, 110
MEG studies, 112–117
PET studies, 71–76
brain imaging, see neuroimaging
BRAIN Initiative (Brain Research through Advancing Innovative Neurotechnologies), 166, 181
brain lesion patients evidence for brain networks, 106–107
brain mapping, 180–181
brain networks and intelligence, 100–110
connectivity analysis techniques, 100–110
default network, 100–101, 103
evidence from brain lesion patients, 106–107
homotopic connectivity, 103–104
rich club networks, 101
small-world networks, 101
brain proteins and IQ, 63
brain resilience after traumatic brain injury, 103
brain size and intelligence, 63size of brain regions and intelligence, 85
whole brain size/volume, 84–85
Brin, Sergey, 28
Brodmann Areas (BAs), 85–86, 101
Buchsbaum, Monte, 71
Burt, Sir Cyril twin studies, 46–50
Cajal, Santiago Ramon, xi
candidate gene studies, 58–59
CAT scan imaging of the brain, 69
Chabris, Christopher, 58–59, 141–142
CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), 64
chemogenetic technique, 178
CHIC (Childhood Intelligence Consortium), 61, 63
China commitment to molecular genetic research, 64–65
chromosomes, 59, 60
chronometric testing, 168
classical music claims for increasing intelligence, 139–143
Clemons, Alonso, 3
Clinton, Bill, 166
cognitive-enhancing (CE) drugs ethical issues, 157–158
cognitive segregation, 22
compensatory education programs, 42–45
complex traits three laws of heritability, 53
computer games claims for increasing intelligence, 150–153
computers Watson (IBM computer), 4, 11
consciousness and creativity, 183–192
Continuity Hypothesis, 53–54
correlations between mental ability tests, 5–9
effects of restricted range of scores, 33–34
creativity and consciousness, 183–192
Crick, Francis, 183
CRISPR/Cas9 method of genome editing, 164, 178
crystallized intelligence, 9–10
cytosine (C), 59
Database of Raising Intelligence (NYU) four meta-analyses, 153–155
de Geus, Eco J.C., 37
Deary, Ian, 30–32, 37
deep brain stimulation (DBS), 161–162
deGrasse Tyson, Neil, 1
Denmark Adoption Studies, 46–47
diffusion tensor imaging (DTI), 90
Discontinuity Hypothesis, 53–54
DNA analysis techniques, 56, 57–58, 60
double-helix structure, 59
sequencing, 60
technologies and methods, 41
Doogie strain of mice, 56–57
Down’s syndrome, 75–76
DREADD technique, 178
drugs ethical issues for cognitive enhancement (CE), 157–158
psycho stimulant drugs, 156
to boost intelligence, 155–158
DUF1220 brain protein subtypes and IQ, 63
Dutch twin study, 51, 52
early education effect on IQ, 154
education policy neuro-poverty and the achievement gap, 196–200
educational achievement influencial factors, 19–21
Einstein, Albert, 4, 9, 11Einstein’s brain, 95–96
electroconvulsive therapy (ECT), 159
emotional intelligence, 21
ENIGMA group, 134
environment and intelligence quantitative genetics studies, 50–56
shared and non-shared environmental factors, 51–53
three-component model, 51–53
epigenetics, 38, 39–40, 59
ethical issues cognitive enhancement, 157–158
eugenics, 30, 41
; everyday life functioning predictive validity of intelligence tests, 22–25
expertise, 22, 53–54
Facebook, 28, 180
factor analysis alternative models of intelligence, 9–10
concept, 7
mental ability tests, 5–9
fairness of intelligence tests, 17–18
FDG (fluorodeoxyglucose) PET, 70–71
fluid intelligence, 9–10, 143–150
fluorescent protein studies, 177
Flynn Effect, 49
fractional anisotropy (FA) studies, 128–, 131 See also diffusion tensor imaging
Frontal Dis-inhibition Model (F-DIM) of creativity, 189–190
frontotemporal dementia (FTD), 184–185, 189
functional literacy score and the challenges of daily life, 23–24
functional MRI (fMRI), 91–92
future of intelligence research, 166–168bridging animal and human research at the level of neurons, 175–179
challenges for the future, 200–201
chemogenetic technique, 178
chronometric testing, 168
cognitive neuroscience of memory and super-memory, 171–175
consciousness and creativity, 183–192
machine intelligence based on human intelligence, 179–183
neuro-poverty, 192–200
neuro-social–economic status, 192–200
optogenetic techniques, 177–178
public policy on neuro-poverty, 196–200
g-factor and savant abilities, 11
distinction from IQ, 10–11
heritability, 54–55
in alternative factor-analysis models, 9–10
influence on daily life functioning, 22–25
nature of, 10–11
reasons for myths about, 33–35
relationships to specific mental abilities, 5–9
The Neuroscience of Intelligence Page 33