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Biological Influences on Intelligence

Biological Influences on Intelligence

Intelligence is often thought to be linked to brain size, but the relationship is more complex than that. While brain size does correlate modestly with some abilities, like verbal skills, the connection is weaker for others, such as spatial reasoning. Other factors, like brain structure, also play crucial roles. For instance, despite Einstein's smaller-than-average brain, his parietal cortex, which is involved in spatial reasoning, was 15% wider, suggesting that neural density might matter...

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Updated: May 6, 2026

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Structural inequality and temporal brain dynamics across diverse samples.

Sandra Baez^1,2,3, Hernan Hernandez⁴, Sebastian Moguilner^4,5

¹Departamento de Psicología, Universidad de los Andes, Bogota, Colombia.

Clinical and Translational Medicine

|October 3, 2024

Summary

This summary is machine-generated.

Structural income inequality significantly impacts brain dynamics, influencing neural activity more than individual factors. This highlights the need to consider societal structures in neuroscience and public policy.

Keywords:

EEG brain dynamics cognition demographics individual differences structural income inequality

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Published on: March 21, 2019

Area of Science:

Neuroscience
Socioeconomics
Public Health

Background:

Structural income inequality, the uneven distribution of income across regions, may influence brain structure and function.
The specific impact of structural income inequality on brain dynamics and the mediating roles of demographics and cognition are not well understood.

Purpose of the Study:

To investigate the effect of structural income inequality on electrophysiological brain dynamics.
To determine the influence of demographic and cognitive factors on these associations.

Main Methods:

Assessed the impact of the Gini coefficient (a measure of income inequality) on electroencephalography (EEG) metrics.
Analyzed resting-state EEG data from 1394 healthy individuals across 10 countries, considering age, sex, and education.
Examined complexity, power spectral, aperiodic components, and graph-theoretic measures of brain activity.

Main Results:

Structural income inequality systematically predicted brain dynamics, acting as a more significant determinant than individual factors.
Complexity and aperiodic activity metrics effectively captured the effects of income inequality on brain function.
Age and cognition were identified as key predictors following the influence of inequality, with observed changes including less complex signals and reduced alpha/beta power.

Conclusions:

Findings challenge neuroscience's focus on individual factors, emphasizing the importance of structural determinants.
Results suggest a biological embedding of structural income inequality and support neuroscience-informed public policies to address societal inequalities.