Large and fast human pyramidal neurons associate with intelligence
- Vrije Universiteit Amsterdam, Netherlands
- University of Antwerp, Belgium
- Stichting Epilepsie Instellingen Nederland (SEIN), Netherlands
- VU Medical Center, Netherlands
Abstract
It is generally assumed that human intelligence relies on efficient processing by neurons in our brain. Although grey matter thickness and activity of temporal and frontal cortical areas correlate with IQ scores, no direct evidence exists that links structural and physiological properties of neurons to human intelligence. Here, we find that high IQ scores and large temporal cortical thickness associate with larger, more complex dendrites of human pyramidal neurons. We show in silico that larger dendritic trees enable pyramidal neurons to track activity of synaptic inputs with higher temporal precision, due to fast action potential kinetics. Indeed, we find that human pyramidal neurons of individuals with higher IQ scores sustain fast action potential kinetics during repeated firing. These findings provide the first evidence that human intelligence is associated with neuronal complexity, action potential kinetics and efficient information transfer from inputs to output within cortical neurons.
Data availability
Numerical data for fall figures are available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.83dv5j7 (doi number 10.5061/dryad.83dv5j7).All customized Matlab scripts used for physiological data analysis are available at https://github.com/INF-Rene/Morphys
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Data from: Large and fast human pyramidal neurons associate with intelligenceDryad Digital Repository, 10.5061/dryad.83dv5j7.
Article and author information
Author details
Natalia A Goriounova
Funding
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VENI grant)
- Natalia A Goriounova
H2020 European Research Council (Human Brain Project)
- Huib D Mansvelder
Fonds Wetenschappelijk Onderzoek (G0F1517N)
- Michele Giugliano
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VICI grant)
- Huib D Mansvelder
H2020 European Research Council (ERC StG)
- Huib D Mansvelder
H2020 European Research Council (Human Brain Project)
- Michele Giugliano
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All procedures were performed with the approval of the Medical Ethical Committee of the VU University Medical Centre (2012/362), and in accordance with Dutch license procedures and the Declaration of Helsinki. Written informed consent was provided by all subjects for data and tissue use for scientific research. All data were anonymized.
Copyright
© 2018, Goriounova et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Large and fast human pyramidal neurons associate with intelligence
eLife 7:e41714.
https://doi.org/10.7554/eLife.41714
Further reading
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Larger neurons seem to lead to higher IQs.
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- Neuroscience
Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development (ABCD) dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology (p) factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the p factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples and robust to variations in analytical parameters. Although model parameters yielded statistically significant brain–behavior associations in unseen data, generalizability of the model was rather limited for all three latent components (r change from within- to out-of-sample statistics: LC1within = 0.36, LC1out = 0.03; LC2within = 0.34, LC2out = 0.05; LC3within = 0.35, LC3out = 0.07). Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.
