Week 8 Flashcards

1
Q

Francis Galton and the study of Head/Brain Sizes

A
  • Measured the heads of Cambridge University students
  • Found that those 19yo with degrees had larger heads
  • Assumed that head sizes had a correlation to intelligence
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2
Q

2005 Meta-Analysis on Brain Size

A
  • Found there were small correlations between the brain size and IQ
  • Supports the idea that individual differences in brain size may lead to individual differences in intelligence but the evidence is not strong
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3
Q

2015 Meta-Analysis on Brain Size

A
  • Found an overall significant positive correlation between brain sizes and IQ scores
  • Small correlation (smaller than 2005’s)
  • Found evidence of publication bias (small and non-significant associations often omitted)
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4
Q

Is there a correlation between the number of brain cells, brain weight, and IQ?

(postmortem brains from Danish males)

A
  • 50 postmortem brains from Danish males (20-52yo) for whom there was documentation of premorbid IQ
  • IQ test from army
  • Asked whether IQ correlated with the number of brain cells in the human neocortex or with brain weight?
  • Found no correlation between IQ and no of brain cells
  • Found weak correlation between IQ and brain weight
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5
Q

Brain Size/IQ Debate: Sex Differences

A
  • On average, adult male brains have 10.8% total brain volume larger than women
  • However there is also a clear absence of sex differences in IQ
  • Hence, large brains do not necessarily translate to higher IQ in humans
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6
Q

Specific Brain Structures and their Link to Intelligence in Different Genders

A

in Men:
- Higher IQ correlates with more gray matter in posterior sensory integration areas

in Women:
- Higher IQ scores associated with more gray and white matter in frontal language areas

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7
Q

What do brain differences mean?

(Jugglers)

A
  • Two groups of healthy young adults
  • One of these groups had weekly juggling sessions for 6 weeks
  • Found that there were white matter differences in the juggling group relative to non-jugglers
  • These changes were in the region related to reaching and grasping in the periphery of vision
  • Shows that there are changes in the white matter of the brain as a result of learning an entirely new skill
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8
Q

Navigation-related Structural Change in the Hippocampi of Taxi Drivers

A
  • Individuals who successfully acquired the knowledge required of black cab drivers has larger posterior hippocampi
  • The more time you spend as a London taxi driver, the more change you see in this region (increased volume)
  • Recall that hippocampus plays a large role in memory, including spatial navigation
  • ## One big difference between those who succeeded and failed was the amount of time spent training to acquire the spatial knowledge
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9
Q

Global Determinants of Navigation Ability (Sex Differences)

A
  • Globally, men outperform women in spatial navigation and abilities
  • When they account for both GDP (and the countries’ economic and political opportunities, wellbeing, education for women), they both significantly predict a country’s estimates
  • More gender equality = Less gender differences in spatial abilities
  • How they perform in spatial abilities correlate to academic performance?
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10
Q

2019 UK Biobank Study

A
  • 44-81yo (M= 63)
  • Looked at correlations between ‘g’ and brain volume, cortical thickness, white matter integrity and white matter intensities
  • Showed that grey and white matter accounted for more than double the g variance in older p than in middle-age p
  • Older age = 13.6% and Middle-age = 5.4%
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11
Q

Explain grey matter

A

Consists of neuronal cell bodies

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12
Q

Explain cortical thickness

A

The thickness of the brain’s grey matter

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13
Q

Explain white matter

A

The connecting network of axons (or ‘wires) in the brain

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14
Q

Explain white matter integrity

A

A measure of the health of the white matter connections

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15
Q

Explain white matter hyperintensities

A

Scars in the brain’s connections

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16
Q

Neural Efficiency Theory

A
  • Argues that intelligence is linked to more efficient use of the cortex
17
Q

Study on Neural Efficiency

A
  • Argues that people who have higher IQ require less brain activity to perform a task
  • A PET study
  • Inverse correlation between glucose metabolism in the brains of individuals who scored higher on the Ravens matrices
  • Later did another study on cerebral metabolism
  • Complex visual spatial task (tetris)
  • After learning tetris, there was an overall decrease in cerebral metabolism (larger decrease in those with higher IQs)
18
Q

Brain Efficiency, SAT Scores and Sex Differences

A
  • Male and female participants with half high SAT scores and half average SAT scores
  • During the PET scan, each participant completed a new SAT test

Male:
- Significant correlations between the math scores and glucose metabolism in the temporal lobes bilaterally

Female:
- No correlations

19
Q

How Fronto-Parietal Grey Matter and White Matter Efficiency Differentially Predict Intelligence in Males and Females

A
  • Male and female young adults were asked to perform various subsets of intelligence scales
  • Looked at the structural differences - some measures of white matter efficiency
  • Found that there was a link between white matter efficiency and intelligence

Male:
- No correlation between white matter efficiency differences and IQ
- Significant positive relationship between fronto-parietal grey matter volumes and intelligence

Female:
- Positive correlation between white matter efficiency differences and IQ
- Total grey matter volume did predict intelligence BUT a regionally specific contribution of the fronto-parietal grey matter was not evident

20
Q

fMRI Study on Nature Neuroscience

A
  • 6 imaging sessions/participant (mixture of rest and complex cognitive tasks
  • Explored functional connectivity patterns (across the whole brain and within 10 key networks); Looked to see whether they were stable in performing each of the different tasks and in rest
  • Found stability over the conditions; Connectivity patterns in frontoparietal network were UNIQUE to the individuals; Connectivity profiles appeared to predict levels of fluid intelligence
21
Q

Explain fluid intelligence

A
  • The figuring out component of intelligence
  • Perceptual reasoning, Working memory, Processing speed
22
Q

Explain crystallised intelligence

A
  • More to do with the outcome of figuring something out
  • Verbal comprehension
23
Q

Explain Connectotyping

A
  • Describes the distinct pattern of brain activity that characterises the way each person’s mind works
  • Implies that mental processes do not necessarily enlist identical neural pathways in every person
24
Q

Where would we find much of the variation relating to connectotypes of the brain?

A
  • Tends to occur within the brain’s most sophisticated networks
  • i.e. In the higher order control regions in frontal and parietal cortices
25
Q

What are the characteristics of connectotypes?

A
  • Stable over time
  • Evidences in adults and children; Evident in humans and non-human primates
  • Familial (e.g. family members have similar connectotypes)
  • Heritable