Week 8- The Neurobiology of Intelligence

Common IQ tests (e.g. WAIS/WISC) and neurodivergence

• Some adjustments can be done

• Colourblind version of some tasks

• Visual/auditory versions

• In WAIS-V, clinician can skip some tasks

• However, tasks often applied without (all required) adjustments

• Neurodivergent individuals may be at a disadvantage

• Other populations (e.g. immigrants) may be as well

Wilson (2023) - Meta-Analysis

Data from 1,800 neurodivergent people (autism and ADHD) • Children and adults (WISC and WAIS)

• Autism performance: • Verbal and nonverbal reasoning: in typical range • Processing speed: ∼1 SD below the mean • WM: Slightly reduced

• ADHD performance: • Mostly at age-expected levels • WM: slightly reduced scores

Brain Size/IQ debate

Systematic review of published and unpublished studies. • 88 studies: 148 healthy and clinical mixed-sex samples (>8000 individuals). • Significant positive correlation (r = .24) between brain volume and IQ. • Generalised over age (children vs adults), IQ domain, Sex. • Evidence of publication bias in favour of studies showing strong positive correlations - with small and non-significant associations often omitted from reports.

CONCLUSIONS: >> the strength of the positive association of brain volume and IQ, although robust, has been overestimated in the literature. >> “While it is tempting to interpret this association in the context of human cognitive evolution and species differences in brain size and cognitive ability…it is not warranted to interpret brain size as an isomorphic proxy of human intelligence differences.”

correlation with number of nerons and iq

50 postmortem brains from Danish males (aged 20-52 years) for whom there was documentation of premorbid IQ (mean 94, SD 14). • Asked whether IQ correlates with the number of brain cells in the human neocortex or with brain weight?

• Found no correlation between IQ and number of brain cells.

• Only a weak correlation between IQ and brain weight

Sex differences, IQ and the brain.

On average, adult male brains have 10.8% larger total brain volume than women (Ruigrok et al., 2014).

• There is, on average, a 2.1 SD (or 131ml) difference.

• However, there is also a clear absence of sex differences in IQ (e.g. Dyliert et al., 2009; Flynn, 2012, Johnson et al., 2009).

• Hence, large brains do not necessarily translate in higher IQ in humans.

Voxel-based regional sex differences in grey matter volume

Women > Men in red and Men > Women in blue

so what do brain diffrenecs eman

• Changes in white matter as a result of learning an entirely new skill

learning juggling- whict matter changes in the skills

darwin barin evelution and cognative tasks

“No one, I presume, doubts that the large proportion which

the size of man’s brain bears to his body, compared to the

same proportion in the gorilla or orang, is closely related with

his higher mental powers”

farces galton

white higher educataed men havebiger brains

• raicsum

• sexsisum

• and classisim

con- barin iq depbate

• correlation if ral only contibuted to 2.1% of the population witch is negalable

london cabby testes

• chnagesin brain structures

• intensity inceraes in gary matter

geographical clustring

• diffrent contries have diffrent prpoformaces in taks

reasion for diffrenecs in countrys

• GDP

• gender effct- gender agps, womans opertunities

Do some people just have more

efficient brains?

• brain glucose activeity of teh barisn

• -.77,-.67,075

• highre metabolic rates

• do task more effcetivly

Brain Efficiency?

(PET)Haier et al. (1992aand b)

• Haier et al. (1992a): after learning

a complex visuo-spatial task (Tetris)

> decreased cerebral metabolism

after practice

• Haier et al. (1992b): after learning

to play Tetris > more pronounced

decreased in cerebral metabolism

in higher IQ participants (measured

using Raven’s Advanced

Progressive Matrices)

Haier and Benbow

(1995):

22 male and 22 female participants

- half high SAT-Maths Scores / and

half average SAT-Maths Scores

• During the PET scan, each participant

completed a new SAT-Maths test.

• Male Participants: significant

correlations between the math score

and glucose metabolism in the

temporal lobes bilaterally (middle,

inferior, and posterior; analogous to

BAs 20, 21, 22)

more activity - but becasue of task dificulty

ryman et al 2016 - frontal priatal gray matter and white matter effciacny

white matter effeciancy preicting intelligance

• White Matter Efficiency Differences:

• In male participants: no correlation with IQ

• In female participants: positive correlation with IQ

• Grey Matter Differences:

• In male participants: a significant positive relationship between

fronto-parietal grey matter region volumes and intelligence.

• In female participants: total grey matter volume did predict

intelligence in females, but a regionally specific contribution of the

fronto-parietal grey matter volume was not evident.

Ryman et al. (2016) 54

These results suggest that:

• Efficiency of white matter organization and the total grey matter

volume was predictive of intelligence in females.

• While intelligence was related primarily to a fronto-parietal grey

matter volume in males

Finn et al. (2015) Nature Neuroscience

• fMRI obtained from 126 participants.

• 6 imaging sessions/participant (mixture of rest and complex cognitive tasks).

• Explored functional connectivity patterns (across the whole brain and within

10 key networks).

• Key = focused on individual differences (i.e. didn’t average participants

together) > computed a connectivity analysis for each person individually

for each condition.

all neral activity is atable and each indidvidual has a ‘fingerprint of there own activity

Outcomes:

• Individual connectivity patterns were stable

across all six conditions

• Connectivity patterns in the frontoparietal

network were the most distinctive

• Connectivity profiles appeared to be able

to predict levels of fluid intelligence

(measured using matrix reasoning)

hair 2009

not all brains work in the same way

Connectotyping

A connectotype describes the distinct pattern of brain activity that

characterizes the way each person’s mind works and implies that mental

processes do not necessarily enlist identical neural pathways in every

person.

• Moreover, much of the variation in connectotypes tends to occur within

the brain’s most sophisticated networks i.e. in the higher order control

regions in frontal and parietal cortices.

• Connectotypes are stable over time, have been evidenced in adults and

children, and in both humans and in non-human primates.

• Connectotypes are familial e.g. the connectotypes of family members

resemble one another more than those of strangers.

• Connectotypes appear to also be heritableable