Previous literature on neurobiology and intelligence largely focused on a “bigger is better” framework—larger cortical volumes showed reliable support for higher levels of intelligence. However, growing literature has been pointing to a different narrative: higher intelligence is also characterized by quick and efficient processing, also known as the neural efficiency hypothesis. This hypothesis adds nuance to neurobiological explanations for intelligence and has motivated further research into studying neuronal wiring in brain tissue—specifically the density and complexity of neuronal wiring.
In this paper, Genç et al. discuss their findings on how detailed structural features in the human brain correlates with intelligence using a diffusion MRI technique known as Neutrite Orientation Disperson and Density Imaging (NODDI). NODDI has proved capable of reliably estimating neural density and neural orientation in human brains in vivo, matching histological conditions closely. More specifically, the researchers focused on studying brain tissue structure across three different environments: intra-neurite, extra-neurite, and cerebrospinal fluid environments. Intelligence metrics were obtained from matrix reasoning tests, specifically the BOMAT and PMAT tests.
There were two main groups in their study, one of which comprised data taken from the Human Connectome Project and was used as validation. Although the groups were largely similar—both groups comprised healthy adults aged between 18-40 years old and were approximately equal in gender ratio—the study design differed in the matrix reasoning tests assigned to participants.
At the whole brain level, the researchers results can be summed up into two main findings. Firstly, there was significant, weak positive correlation between cortical volume and intelligence—this was expected as it conformed with previous literature. However, a significant, weak negative correlation between both neural density and neurite orientation and intelligence was also observed. Both groups agree on these results even after controlling for confounders.
Although the latter result contradicts the “bigger is better” narrative, it can be explained by early childhood and learning-induced synaptic plasticity—strengthening or weakening of neural connections over time. During early childhood (and up to one’s early twenties), there is a loss of connections between neurons in non-stimulated brain regions for the purposes of learning and memory. The same phenomena occurs during learning in adult brains too, though to a lesser extent.
At the single brain region level, this finding can be explained by faster and more efficient neuronal processing. Less resources are consumed when only activating relevant neurons; fewer connections imply a more organized and focused circuitry, improving the processing speed and signal-to-noise ratio. These results are further supported by early EEG studies which reveal focused cortical activation when problem-solving among high-IQ individuals. In contrast, the general population reveals more distributed and widespread cortical activation when solving the same task.
In summary, the work by Genç et al. provides biological evidence in support of the neural efficiency hypothesis. Larger brains with sparse and organized dedritic arbor increase computation power and speed and are more resource-efficient, providing a neurobiological basis for higher intelligence.
References
Genç, E., Fraenz, C., Schlüter, C., Friedrich, P., Hossiep, R., Voelkle, M. C., Ling, J. M., Güntürkün, O., & Jung, R. E. (2018). Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence. Nature Communications, 9(1), 1905. https://doi.org/10.1038/s41467-018-04268-8
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