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Intelligence and neural efficiency
Abstract
We review research on the neural efficiency hypothesis of intelligence, stating that brighter individuals display lower (more efficient) brain activation while performing cognitive tasks [Haier, R.J., Siegel, B.V., Nuechterlein, K.H., Hazlett, E., Wu, J.C., Paek, J., Browning, H.L., Buchsbaum, M.S., 1988. Cortical glucose metabolic rate correlates of abstract reasoning and attention studied with positron emission tomography. Intelligence 12, 199-217]. While most early studies confirmed this hypothesis later research has revealed contradictory evidence or has identified some moderating variables like sex, task type, task complexity or brain area. Neuroscientific training studies suggest that neural efficiency also seems to be a function of the amount and quality of learning. From integrating this evidence we conclude that neural efficiency might arise when individuals are confronted with tasks of (subjectively) low to moderate task difficulty and it is mainly observable for frontal brain areas. This is true for easier novel cognitive tasks or after sufficient practice allowing participants to develop appropriate (efficient) strategies to deal with the task. In very complex tasks more able individuals seem to invest more cortical resources resulting in positive correlations between brain usage and cognitive ability. Based on the reviewed evidence we propose future empirical approaches in this field.
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“To exclude the effects of age, gender, intellectual ability and depression,31–33 we included these measures as regressors.”
From Ventral striatum dysfunction in children and adolescents with reactive attachment disorder: functional MRI study (2015) · cites this paper as [32]
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InfluentialAnterior insular cortex is a bottleneck of cognitive control
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EEG microstate features according to performance on a mental arithmetic task
Kim, K., Duc, N. T., Choi, M., & Lee, B. (2021) · Scientific Reports · doi:10.1038/s41598-020-79423-7 · Cited by 88
Cross-modal activation of auditory regions during visuo-spatial working memory in early deafness
Ding, H., Qin, W., Liang, M., Ming, D., Wan, B., Li, Q., & Yu, C. (2015) · Brain · doi:10.1093/brain/awv165 · Cited by 91
“In hearing subjects, working memory performance is mainly associated with activations in the lateral frontal and parietal regions and negative correlations between performance and activation are in line with the neural efficiency hypothesis (Neubauer and Fink, 2009).”
ResultSleep and Cortisol Interact to Support Memory Consolidation
Bennion, K. A., Steinmetz, K. R. M., Kensinger, E. A., & Payne, J. D. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht255 · Cited by 92
Assem, M., Blank, I., Mineroff, Z., Ademoğlu, A., & Fedorenko, E. G. (2020) · Cortex · doi:10.1016/j.cortex.2020.06.013 · Cited by 92
Speech‐perception training for older adults with hearing loss impacts word recognition and effort
Kuchinsky, S. E., Ahlstrom, J. B., Cute, S. L., Humes, L. E., Dubno, J. R., & Eckert, M. A. (2014) · Psychophysiology · doi:10.1111/psyp.12242 · Cited by 86
“…that, when faced with a challenging task, individuals who have sufficient perceptual and cognitive abilities are able to exert additional effort to perform successfully, and thus exhibit robust neural and pupillary responses (Neubauer & Fink, 2009; van der Meer et al., 2010; Zekveld et al., 2011).”
Tang, C. Y., Eaves, E. L., Ng, J., Carpenter, D. M., Mai, X., Schroeder, D. H., Condon, C. A., Colom, R., & Haier, R. J. (2010) · Intelligence · doi:10.1016/j.intell.2010.03.003 · Cited by 87
“Further, we present analyses separately for males and females to test whether the P-FIT areas differ in activation during the non-verbal n-back memory task andwhether inverse correlations consistent with brain efficiency may be stronger in males, as suggested by Neubauer and Fink (2009).”
BackgroundMethodPreusse, F., Elke, V. D. M., Deshpande, G., Krüeger, F., & Wartenburger, I. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00022 · Cited by 88
“, more efficient) cortical activity when performing a cognitive task (Haier et al., 1988; Neubauer and Fink, 2009b).”
BackgroundInfluentialEngström, M., Landtblom, A., & Karlsson, T. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00140 · Cited by 92
“This pattern is similar to the notion of neural efficiency, as proposed by Neubauer and Fink (2009).”
MethodCamfield, D., Scholey, A. B., Pipingas, A., Silberstein, R. B., Kras, M., Nolidin, K., Wesnes, K. A., Pase, M. P., & Stough, C. K. K. (2011) · Physiology & Behavior · doi:10.1016/j.physbeh.2011.11.013 · Cited by 84
“According to the neural efficiency hypothesis of intelligence, participants who are more intelligent develop more efficient strategies to deal with the tasks that are of low–moderate difficulty, and this is evidenced by a lower level of brain activation [32].”
BackgroundResultShort-term training in the Go/Nogo task: Behavioural and neural changes depend on task demands
Benikos, N., Johnstone, S. J., & Roodenrys, S. J. (2012) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2012.12.001 · Cited by 90
“Jodo and Inoue (1990) found that Go reaction time and Nogo P3 latency were significantly shortened after six days of practice (200 trials per day) - in line with previous theoretical viewpoints suggesting more efficient processing with training (Neubauer and Fink, 2009).”
ResultThalamo‐striato‐cortical determinants to fatigue in multiple sclerosis
Engström, M., Flensner, G., Landtblom, A., Ek, A., & Karlsson, T. (2013) · Brain and Behavior · doi:10.1002/brb3.181 · Cited by 83
Basic functional trade-offs in cognition: An integrative framework
Giudice, M. D., & Crespi, B. J. (2018) · Cognition · doi:10.1016/j.cognition.2018.06.008 · Cited by 86
“In a previous section, we noted that IQ correlates with the integrity of white matter fibers; the resulting increase in overall efficiency likely contributes to explain why higher IQ predicts better cognitive performance but lower energetic consumption in the brain (Neubauer & Fink, 2009).”
The neural correlates of memory encoding and recognition for own-race and other-race faces
Herzmann, G., Willenbockel, V., Tanaka, J. W., & Curran, T. (2011) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.07.019 · Cited by 77
Geary, D. C. (2018) · Psychological Review · doi:10.1037/rev0000124 · Cited by 80
De Bellis, M. D., Hooper, S. R., Chen, S. D., Provenzale, J. M., Boyd, B. D., Glessner, C. E., MacFall, J. R., Payne, M. E., Rybczynski, R., & Woolley, D. P. (2015) · Development and Psychopathology · doi:10.1017/s0954579415000942 · Cited by 75
“Because higher IQ participants demonstrate a linear relationship with neural efficiency compared with lower IQ participants (Neubauer & Fink, 2009), and cortical thickness in this study participants’ age and IQ range (average to high average) show linear associations (Shaw et al., 2006), IQ group…”
ResultThe link between callosal thickness and intelligence in healthy children and adolescents
Eileen Luders, A., Thompson, P. M., Narr, K. L., Zamanyan, A., Chou, Y., Gutman, B. A., Dinov, I. D., & Toga, A. W. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.09.083 · Cited by 73
“” The current findings with respect to the corpus callosum possibly imply that more intelligent individuals (at least during childhood and adolescence) possess more efficient neuronal networks (Haier et al., 1988; Li et al., 2009; Neubauer and Fink, 2009).”
The development and malleability of executive control abilities
Hsu, N. S., Novick, J. M., & Jaeggi, S. M. (2014) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2014.00221 · Cited by 78
Association of Structural Global Brain Network Properties with Intelligence in Normal Aging
Fischer, F. U., Wolf, D. G. F., Scheurich, A., & Fellgiebel, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0086258 · Cited by 72
A Scaffold for Efficiency in the Human Brain
Burzynska, A. Z., Garrett, D. D., Preuschhof, C., Nagel, I. E., Li, S., Bäckman, L., Heekeren, H. R., & Lindenberger, U. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1426-13.2013 · Cited by 70
“Many functional neuroimaging studies suggest that better performers require less brain activity (relative to baseline) to successfully perform a task of a given difficulty level (Neubauer and Fink, 2009).”
BackgroundExercise Intensity Influences Prefrontal Cortex Oxygenation during Cognitive Testing
Moriarty, T. A., Bourbeau, K., Bellovary, B. N., & Zuhl, M. (2019) · Behavioral Sciences · doi:10.3390/bs9080083 · Cited by 78
“Likewise, higher cortical activity occurring along with a decrease in cognitive function may indicate reduced neural efficiency, and highlights greater neural input required for a given cognitive task [12].”
BackgroundAssociation between sleep duration and intelligence scores in healthy children.
Geiger, A., Achermann, P., & Jenni, O. G. (2010) · Developmental Psychology · doi:10.1037/a0019679 · Cited by 73
“In this framework, psychometrically assessed IQ scores have been associated with several physiological variables such as glucose metabolism rate and an electroencephalographic measure, the event-related desynchronization (Neubauer & Fink, 2009).”
Individual differences in the learning potential of human beings
Stern, E. (2017) · npj Science of Learning · doi:10.1038/s41539-016-0003-0 · Cited by 102
Sex differences in the IQ-white matter microstructure relationship: A DTI study
Dunst, B., Benedek, M., Koschutnig, K., Jauk, E., & Neubauer, A. C. (2014) · Brain and Cognition · doi:10.1016/j.bandc.2014.08.006 · Cited by 73
Self-citationA preliminary study of the effects of working memory training on brain function
Stevens, M. C. G., Gaynor, A. M., Bessette, K. L., & Pearlson, G. D. (2015) · Brain Imaging and Behavior · doi:10.1007/s11682-015-9416-2 · Cited by 80
“…effect of WM load was found before WM training, which could indicate either reduced need to engage this region at higher loads after training (e.g., greater Befficiency^ (Haier et al. 1992; Neubauer and Fink 2009), or consistently greater activation after training, regardless of task demands.”
BackgroundIndividual differences in the neural basis of causal inferencing
Prat, C. S., Mason, R. A., & Just, M. A. (2010) · Brain and Language · doi:10.1016/j.bandl.2010.08.004 · Cited by 71
“In general, among healthy participants who can perform a task, higher cognitive abilities are indexed by less (more focal distribution or lower intensity) brain activation (see Neubauer and Fink (2009) for a review).”
BackgroundThe Athlete’s Brain: Cross-Sectional Evidence for Neural Efficiency during Cycling Exercise
Ludyga, S., Gronwald, T., & Hottenrott, K. (2015) · Neural Plasticity · doi:10.1155/2016/4583674 · Cited by 71
“a more efficient cortical function [3].”
(2013) · The MIT Press eBooks · doi:10.7551/mitpress/9780262019583.001.0001 · Cited by 69
Kruschwitz, J., Waller, L., Daedelow, L. S., Walter, H., & Veer, I. M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.018 · Cited by 71
Frischkorn, G. T., Schubert, A., & Hagemann, D. (2019) · Intelligence · doi:10.1016/j.intell.2019.05.003 · Cited by 77
Metadata
- Authors
- Neubauer, A. C., & Fink, A.
- Affiliations
- University of Graz (AT)
- Corresponding author
- Neubauer, Aljoscha C.
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 33
- Issue
- 7
- Pages
- 1004-1023
- ISSN
- 0149-7634 (ISSN-L)
- OpenAlex
- W2072541188
- Cited by
- 878
- References
- 149
- Citations by year
- 2026: 115 · 2025: 69 · 2024: 49 · 2023: 60 · 2022: 63 · 2021: 65 · 2020: 48 · 2019: 58 · 2018: 50 · 2017: 40 · 2016: 45 · 2015: 42 · 2014: 39 · 2013: 37 · 2012: 32
- FWCI
- 40.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neuroscience & Biobehavioral Reviews (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Creativity in Education and Neuroscience
- Keywords
- neural efficiency hypothesis, intelligence, brain activation, cognitive task difficulty, frontal cortex, cortical glucose metabolism, cognitive training, learning, moderators, abstract thinking, attention
- MeSH terms
- Brain, Brain Mapping, Cognition, Female, Humans, Intelligence, Male, Models, Neurological, Practice, Psychological, Professional Competence, Sex Characteristics
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