The DOI matches its Crossref record; 149 of the 149 references it cites were found in a registry or an index.
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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Cites
The role of deliberate practice in the acquisition of expert performance
Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993) · Psychological Review · doi:10.1037/0033-295x.100.3.363 · Cited by 9,564
Shiffrin, R. M., & Schneider, W. (1977) · Psychological Review · doi:10.1037/0033-295x.84.2.127 · Cited by 7,335
Individual differences in working memory and reading
Daneman, M., & Carpenter, P. A. (1980) · Journal of Verbal Learning and Verbal Behavior · doi:10.1016/s0022-5371(80)90312-6 · Cited by 6,336
Controlled and automatic human information processing: I. Detection, search, and attention.
Schneider, W., & Shiffrin, R. M. (1977) · Psychological Review · doi:10.1037/0033-295x.84.1.1 · Cited by 5,902
Electroencephalography—Basic principles, clinical applications and related fields
(1982) · Journal of the Autonomic Nervous System · doi:10.1016/0165-1838(82)90067-4 · Cited by 3,449
Navigation-related structural change in the hippocampi of taxi drivers
Maguire, E. A., Gadian, D. G., Johnsrude, I. S., Good, C. D., Ashburner, J., Frackowiak, R. S. J., & Frith, C. D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.070039597 · Cited by 3,225
Working memory, short-term memory, and general fluid intelligence: A latent-variable approach.
Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. A. (1999) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.128.3.309 · Cited by 3,078
Intelligence: Knowns and unknowns.
Neisser, U., Boodoo, G., Bouchard, T. J., Boykin, A. W., Brody, N., Ceci, S. J., Halpern, D. F., Loehlin, J. C., Perloff, R., Sternberg, R. J., et al. (1996) · American Psychologist · doi:10.1037/0003-066x.51.2.77 · Cited by 2,913
Changes in grey matter induced by training
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004) · Nature · doi:10.1038/427311a · Cited by 2,373
On the Rate of Gain of Information
Hick, W. E. (1952) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470215208416600 · Cited by 2,279
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“Indeed, supporting an information integration efficiency hypothesis of intelligence (Jung and Haier, 2007; Neubauer and Fink, 2009; van den Heuvel et al., 2009), EEG findings have indicated that higher educated participants have on average a shorter path length than lower educated subjects…”
BackgroundThe neuroscience of human intelligence differences
Deary, I. J., Penke, L., & Johnson, W. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2793 · Cited by 1,038
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“Compensation”
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Barulli, D., & Stern, Y. (2013) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.08.012 · Cited by 1,006
Contemplating Mindfulness at Work: An Integrative Review
Good, D. J., Lyddy, C. J., Glomb, T. M., Bono, J. E., Brown, K. W., Duffy, M. K., Baer, R. A., Brewer, J. A., & Lazar, S. W. (2016) · Journal of Management · doi:10.1177/0149206315617003 · Cited by 1,043
“Considered as a whole, these results suggest that mindfulness increases cognitive capacity and flexibility, at least in part via its effects on attention.”
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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