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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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“Neubauer and Fink (2009) also add that the cognitive performance is a function of the brain structure as well as of the functional interplay of different neural networks.”
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“…correlates of this model may be explained by the neural efficiency hypothesis of intelligence, which states that less activation in involved neural networks is correlated with increased cognitive performance (Haier et al., 1988; Neubauer & Fink, 2009; Brown et al., 2005; Meyler et al., 2007).”
Sex differences in mental rotation and cortical activation patterns: Can training change them?
Jaušovec, N., & Jaušovec, K. (2012) · Intelligence · doi:10.1016/j.intell.2012.01.005 · Cited by 40
“Even though there is no firm consensus about any particular brain–intelligence relation, most of the studies demonstrated a negative correlation between brain activity under cognitive load and intelligence (for review, Neubauer & Fink, 2009).”
BackgroundTest-retest reliability of emotion regulation networks using fMRI at ultra-high magnetic field
Berboth, S., Windischberger, C., Kohn, N., & Morawetz, C. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117917 · Cited by 40
Abellaneda‐Pérez, K., Potash, R. M., Pascual‐Leone, Á., & Sacchet, M. D. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105862 · Cited by 49
“The authors interpreted these brain activity changes underlying cognitive improvements within the context of the neural efficiency hypothesis (Neubauer and Fink, 2009).”
Medial Frontal White and Gray Matter Contributions to General Intelligence
Ohtani, T., Nestor, P. G., Sylvain Bouix, A., Saito, Y., Hosokawa, T., & Kubicki, M. R. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112691 · Cited by 61
Mitchell, B. L., Cuéllar-Partida, G., Grasby, K. L., Campos, A. I., Strike, L. T., Hwang, L., Okbay, A., Thompson, P. M., Medland, S. E., Martin, N. G., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116691 · Cited by 41
“, 2011) and neural network efficiency (Neubauer and Fink, 2009; Santarnecchi et al., 2014; Van Den Heuvel et al., 2009) have also been associated with general intelligence, highlighting potential functional mechanisms underlying individual variability in intelligence (Santarnecchi and Rossi, 2016).”
Deontological and Altruistic Guilt Feelings: A Dualistic Thesis
Mancini, F., & Gangemi, A. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.651937 · Cited by 40
“The authors suggested that this decreased activation may reflect patients’ cerebral efficiency, which results from their frequent exposure to DG feelings, known as the neuro efficiency hypothesis (Neubauer and Fink, 2009).”
BackgroundRicciardi, E., Handjaras, G., Bernardi, G., Pietrini, P., & Furey, M. L. (2012) · Neuropharmacology · doi:10.1016/j.neuropharm.2012.07.003 · Cited by 39
“…visual processing regions and frontal and parietal areas, together with the observed behavioral improvement, may reflect both a more efficient processing of task-significant stimuli and a reduction in the effort required to perform the task (Neubauer and Fink, 2009; Rypma and Prabhakaran, 2009).”
Fang, Q., Fang, C., Li, L., & Song, Y. (2022) · Journal of Exercise Science & Fitness · doi:10.1016/j.jesf.2022.04.001 · Cited by 47
van Ettinger-Veenstra, H., McAllister, A. M., Lundberg, P., Karlsson, T., & Engström, M. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00110 · Cited by 41
“High performing participants may find a moderate demand task not that cognitively demanding and have the possibility to process the information in a more efficient and less neural energy consuming way (Neubauer and Fink, 2009).”
BackgroundMethodWarbrick, T., Rosenberg, J., & Shah, N. J. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.12.075 · Cited by 41
GABA concentrations in the anterior temporal lobe predict human semantic processing
Jung, J., Williams, S. R., Nezhad, F. S., & Ralph, M. A. L. (2017) · Scientific Reports · doi:10.1038/s41598-017-15981-7 · Cited by 45
Wongupparaj, P., Sumich, A. L., Wickens, M., Kumari, V., & Morris, R. G. (2018) · Biological Psychology · doi:10.1016/j.biopsycho.2018.10.009 · Cited by 39
An fMRI study of scientists with a Ph.D. in physics confronted with naive ideas in science
Allaire‐Duquette, G., Foisy, L. B., Potvin, P., Riopel, M., Larose, M., & Masson, S. (2021) · npj Science of Learning · doi:10.1038/s41539-021-00091-x · Cited by 46
Scheffel, C., Graupner, S., Gärtner, A., Zerna, J., Strobel, A., & Dörfel, D. (2021) · Psychophysiology · doi:10.1111/psyp.13908 · Cited by 42
“It is assumed that after the WM training, participants put sustained effort in the ER task (cortical effort model) (Engen & Kanske, 2013; Neubauer & Fink, 2009; Schweizer et al., 2013).”
MethodThe Role of NREM Sleep Instability in Child Cognitive Performance
Bruni, O., Kohler, M. J., Novelli, L., Kennedy, D., Lushington, K., Martin, J., & Ferri, R. (2012) · SLEEP · doi:10.5665/sleep.1824 · Cited by 43
Neural Dynamics of Improved Bimodal Attention and Working Memory in Musically Trained Children
Kausel, L., Zamorano, F. J., Billeke, P. B., Sutherland, M. E., Larraín-Valenzuela, J., Stecher, X., Gottfried Schlaug, A., & Aboitiz, F. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.554731 · Cited by 37
“Evidence has suggested that this phenomenon also seems to be a function of the amount and quality of learning; this means that the specialization of functioning is reached over time (Neubauer and Fink, 2009).”
BackgroundNeural Contributions to Reduced Fluid Intelligence across the Adult Lifespan
Mitchell, D. J., Mousley, A., Shafto, M. A., Cam-CAN, & Duncan, J. (2022) · Journal of Neuroscience · doi:10.1523/jneurosci.0148-22.2022 · Cited by 41
“This is consistent with evidence that exercise may support cognition by improving the efficiency of neural function (Neubauer and Fink, 2009; Voss et al., 2011).”
BackgroundGeiger, A., Achermann, P., & Jenni, O. G. (2010) · Progress in brain research · doi:10.1016/b978-0-444-53702-7.00010-5 · Cited by 37
Lucas, M., Wagshul, M. E., İzzetoğlu, M., & Holtzer, R. (2018) · The Journals of Gerontology Series A · doi:10.1093/gerona/gly131 · Cited by 41
Schubert, A., Nunez, M. D., Hagemann, D., & Vandekerckhove, J. (2018) · Computational Brain & Behavior · doi:10.1007/s42113-018-0021-5 · Cited by 39
“…2010; 2011; Schmiedek et al. 2007; Schubert et al. 2015), cognitive neuroscience researchers have characterized the time course of information processing and identified structural and function neural correlates of cognitive abilities(Basten et al. 2015; Neubauer and Fink 2009; Jung and Haier 2007).”
BackgroundAlpha Band Resting-State EEG Connectivity Is Associated With Non-verbal Intelligence
Zakharov, I., Олеговна, Т. А., Adamovich, T., Kovas, Y. V., & Malykh, S. B. (2020) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2020.00010 · Cited by 39
“Later these results were extended to more types of brain activity measures (EEG, fMRI and so on) and different types of tasks (see Neubauer and Fink, 2009 for review).”
BackgroundRiečanský, I., & Katina, S. (2010) · Neuroscience Letters · doi:10.1016/j.neulet.2010.07.017 · Cited by 37
“Such a result would fit with the evidence that neural efficiency holds for tasks with low to moderate difficulty, which are solved quickly using already settled strategies [7,27].”
BackgroundKim, J., Chey, J., Kim, S.-E., & Kim, H. (2015) · Neuroscience Research · doi:10.1016/j.neures.2014.12.009 · Cited by 36
Heiland, E. G., Tarassova, O., Fernström, M., English, C., Ekblom, Ö. B., & Ekblom, M. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.719509 · Cited by 35
Li, C., & Tian, L. (2014) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3850 · Cited by 34
Mendes, A. J., Pacheco‐Barrios, K., Lema, A., Gonçalves, Ó. F., Fregni, F., Leite, J., & Carvalho, S. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.11.002 · Cited by 36
Occupational Solvent Exposure and Brain Function: An fMRI Study
Tang, C. Y., Carpenter, D. M., Eaves, E. L., Ng, J., Ganeshalingam, N., Weisel, C. P., Qian, H., Lange, G., & Fiedler, N. L. (2011) · Environmental Health Perspectives · doi:10.1289/ehp.1002529 · Cited by 39
“This hyper activity is assumed to be an indicator of local compensatory function: The less “efficient” brain region has to work harder (showing increased blood flow) to perform the same task, as has been shown in studies of normal cognition and intelligence (Haier 1993; Neubauer and Fink 2009).”
Background
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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