Cited by 878Cognitive Abilities and TestingNeural and Behavioral Psychology StudiesCreativity in Education and Neuroscience

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Intelligence and neural efficiency

Neubauer, Aljoscha C., Fink, Andreas·2009·Neuroscience & Biobehavioral Reviews

DOI 10.1016/j.neubiorev.2009.04.001

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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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Background
High Neural Efficiency in Unconscious Perceptual Processing among Table Tennis Athletes: An Event-Related Potential Study
Shi, J., Huang, H., Nasrallah, F. A., & Li, A.-M. (2024) · Brain Sciences · doi:10.3390/brainsci14080756 · Cited by 8
“Given that these studies utilized different experimental tasks, the inconsistency in their findings may indicate that the complexity and characteristics of these tasks influence the outcomes [11].”
Result
Computerized cognitive training enhances cognitive function in Alzheimer’s disease by downregulating Ruminococcus-TMAO pathway
Zhang, W., Song, J., Zhong, F., Yu, W., Qin, Z., Yang, Z., Liu, J., Wang, X., Chen, L., Lü, W., et al. (2025) · Journal of Translational Medicine · doi:10.1186/s12967-025-07209-4 · Cited by 8
“Increased FC between certain ROIs might reflect the reactivation of previously underutilized areas, while decreased FC could signify reduced compensatory engagement of atypical brain regions, suggesting a shift towards more efficient neural processing [37].”
Efficiency: an underlying principle of learning?
Commins, S. (2017) · Reviews in the Neurosciences · doi:10.1515/revneuro-2017-0050 · Cited by 11
“, may all affect efficiency to different degrees Individuals that are more intelligent have a greater efficiency in brain use after training compared to those with less intelligence (Neubauer et al., 2004; Neubauer and Fink, 2009) Older adults that show good memory performance often have extra neural activation compar…”
BackgroundResult
Command, Leadership, Intelligence and Management (CLIM): A Proposed Theory for Improved Strategic Leadership
Keeton, W. (2018) · FIIB Business Review · doi:10.1177/2319714518792788 · Cited by 8
Performance Gains in an Open Skill Video-Game Task: The Role of Neural Efficiency and Neural Proficiency
Filho, E., Husselman, T.-A., Zugic, L., Penna, E. M., & Taneva, N. (2022) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-022-09553-3 · Cited by 7
Neural oscillation amplitude in the frontal cortex predicts esport results
Minami, S., Watanabe, K., Saijo, N., & Kashino, M. (2023) · iScience · doi:10.1016/j.isci.2023.106845 · Cited by 8
“The activation of the frontal cortex represents centralization.(9,10,13) In contrast to high frequencies, previous studies have shown a negative correlation between the blood oxygenation level-dependent signal and power changes at low frequencies (8–30 Hz) arising from cortical areas.”
Result
Toward precision brain health: accurate prediction of a cognitive index trajectory using neuroimaging metrics
Spence, J. S., Turner, M. P., Rypma, B., D’Esposito, M., & Chapman, S. B. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad435 · Cited by 8
Investigating robust associations between functional connectivity based on graph theory and general intelligence
Metzen, D., Stammen, C., Fraenz, C., Schlüter, C., Johnson, W., Güntürkün, O., DeYoung, C. G., & Genç, E. (2024) · Scientific Reports · doi:10.1038/s41598-024-51333-y · Cited by 11
Efficient motor control: how can less be more?
Mazzoni, P. (2008) · The Journal of Physiology · doi:10.1113/jphysiol.2008.160135 · Cited by 8
“Neural efficiency has long been investigated in relationship to human intelligence (Vernon, 1993), but these studies have been fraught with the long list of potential confounding factors (task complexity, use of strategy, past experience) associated with the study of such a complex measure of…”
Background
The role of fluid intelligence and learning in analogical reasoning: How to become neurally efficient?
Dix, A., Wartenburger, I., & van der Meer, E. E. (2016) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2016.07.019 · Cited by 9
Touching the elephant: The search for fluid intelligence
Wasserman, T. H., & Wasserman, L. D. (2017) · Applied Neuropsychology Child · doi:10.1080/21622965.2017.1317489 · Cited by 8
“These conclusions have been supported by research suggesting that neural efficiency also seems to be a function of the amount and quality of learning related to the task being attempted (Neubauer & Fink, 2009).”
Background
Genetic Taster Status as a Mediator of Neural Activity and Swallowing Mechanics in Healthy Adults
Dietsch, A. M., Westemeyer, R. M., Pearson, W. G., & Schultz, D. H. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.01328 · Cited by 8
“while performing cognitive tasks than lower intelligence individuals (Haier et al., 1992; Neubauer and Fink, 2009).”
Background
EEG-based intelligent system for cognitive behavior classification
Anoor, M. M., Jahidin, A. H., Arof, H., & Ali, M. S. A. M. (2020) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-190955 · Cited by 8
“Such ﬁndings are valid as it shows conformity with both Neural Efﬁciency Hypothesis [4] and Alpha Suppression Theory [7].”
Temporal regularity of cerebral activity at rest correlates with slowness of reaction times in intellectual disability
Palix, J., Giuliani, F., Sierro, G., Brandner, C., & Favrod, J. (2020) · Clinical Neurophysiology · doi:10.1016/j.clinph.2020.04.174 · Cited by 8
General Intelligence Is Associated with Working Memory-Related Functional Connectivity Change: Evidence from a Large-Sample Study
Takeuchi, H., Taki, Y., Nouchi, R., Yokoyama, R., Kotozaki, Y., Nakagawa, S., Sekiguchi, A., Iizuka, K., Hanawa, S., Araki, T., et al. (2020) · Brain Connectivity · doi:10.1089/brain.2020.0769 · Cited by 8
“Among these ﬁndings, the associations between lower task-induced activation and greater intelligence are partly consistent with the neural efﬁciency theory, which suggests lower prefrontal activity during tasks of low to moderate difﬁculty (Neubauer and Fink, 2009).”
Psychological power alters cognitive efficiency
Lin, E., Freydefont, L., & Schmid, P. C. (2021) · Psychophysiology · doi:10.1111/psyp.13773 · Cited by 9
Intelligence and Creativity from the Neuroscience Perspective
Jauk, E. (2018) · Cambridge University Press eBooks · doi:10.1017/9781316556238.024 · Cited by 8
Diffusion-Weighted Imaging of Intelligence
Genç, E., & Fraenz, C. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108635462.014 · Cited by 8
The effort investment theory of power
Schmid, P. C. (2021) · Journal of Applied Social Psychology · doi:10.1111/jasp.12823 · Cited by 9
fNIRS-derived neurocognitive ratio as a biomarker for neuropsychiatric diseases
Akın, A. (2021) · Neurophotonics · doi:10.1117/1.nph.8.3.035008 · Cited by 9
Using electroencephalography to explore neurocognitive correlates of procedural proficiency: A pilot study to compare experts and novices during simulated endotracheal intubation
Toy, S., Ozsoy, S., Shafiei, S. B., Antonenko, P., & Schwengel, D. A. (2022) · Brain and Cognition · doi:10.1016/j.bandc.2022.105938 · Cited by 8
A proposed integration of the expert performance and individual differences approaches to the study of elite performance
Kaufman, S. B. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00707 · Cited by 8
“Brain imaging studies support the idea that people who do well on tests of cognitive ability use fewer brain resources to solve novel and complex problems (Haier et al., 1992; Neubauer and Fink, 2009; Van den Heuvel et al., 2009; Deary et al., 2010; Prabhakaran et al., 2011).”
Background
Putting the temporal resolution power (TRP) hypothesis to a critical test: Is the TRP-g relationship still more fundamental than an optimized relationship between speed of information processing and g?
Pahud, O., Rammsayer, T. H., & Troche, S. J. (2018) · Intelligence · doi:10.1016/j.intell.2018.08.002 · Cited by 8
Boom Chack Boom—A multimethod investigation of motor inhibition in professional drummers
Schlaffke, L., Friedrich, S., Tegenthoff, M., Güntürkün, O., Genç, E., & Ocklenburg, S. (2019) · Brain and Behavior · doi:10.1002/brb3.1490 · Cited by 8
“…in the area of intelligence research the so-called neural efficiency hypothesis of intelligence has been brought forward, assuming that especially in rather simple tasks trained individuals show lower and therefore, more efficient brain activations (Genç et al., 2018; Neubauer & Fink, 2009).”
Background
Decoding auditory deprivation: resting-state fMRI insights into deafness and brain plasticity
Kumar, U., & Dhanik, K. (2024) · Brain Structure and Function · doi:10.1007/s00429-023-02757-1 · Cited by 8
“…occipital regions, both implicated in cognitive and visual processing (Cavanna and Trimble 2006; Wandell et al. 2007), might reflect a reconfiguration of neural networks in these areas, possibly due to altered cognitive dynamics or streamlined visual processing pathways (Neubauer and Fink 2009).”
Early life brain network connectivity antecedents of executive function in children born preterm
Derbie, A. Y., Altaye, M., Wang, J., Allahverdy, A., He, L., Tamm, L., & Parikh, N. A. (2025) · Communications Biology · doi:10.1038/s42003-025-07745-1 · Cited by 7
Brain working memory network indices as landmarks of intelligence
Khodaei, M., Laurienti, P. J., Dagenbach, D., & Simpson, S. L. (2023) · Neuroimage Reports · doi:10.1016/j.ynirp.2023.100165 · Cited by 8
“…theory was later disputed in a review stating that while early task-based studies align with this hypothesis, recent studies have cast doubt on this hypothesis or have identified that some variables like gender, task type, and task complexity can affect this relationship (Neubauer and Fink, 2009).”
Working memory and processing speed abilities are related to habituation and change detection in school-aged children: An ERP study.
Charlebois-Poirier, A.-R., Lalancette, È., Agbogba, K., Fauteux, A., Knoth, I. S., & Lippé, S. (2023) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2023.108616 · Cited by 7
Cognitive Brain Training, Video Games, and Creativity
Vartanian, O. A., & Beatty, E. L. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-801462-2.00009-6 · Cited by 9
The correlation between intelligence, creativity and the parameters of sensorimotor integration in children of different ages
Nikolaeva, E. I., Novikova, A., & Vergunov, E. G. (2018) · Psychology in Russia State of Art · doi:10.11621/pir.2018.0206 · Cited by 7
Adolescent Psychopathic Traits Negatively Relate to Hemodynamic Activity within the Basal Ganglia during Error-Related Processing
Maurer, J. M., Steele, V. R., Vincent, G. M., Rao, V., Calhoun, V. D., & Kiehl, K. A. (2019) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-019-00560-3 · Cited by 9
Brain Responses to Passive Sensory Stimulation Correlate With Intelligence
Horwitz, A., Klemp, M., Horwitz, H., Thomsen, M. D., Rostrup, E., Mortensen, E. L., Osler, M., Lauritzen, M., & Benedek, K. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00201 · Cited by 7
‘Delaying’ a saccade: Preparatory phase cortical hemodynamics evince the neural cost of response inhibition
Tari, B., Shirzad, M., Badcock, N. A., Belfry, G. R., & Heath, M. D. (2021) · Brain and Cognition · doi:10.1016/j.bandc.2021.105808 · Cited by 7
ABBaH teens: Activity Breaks for Brain Health in adolescents: study protocol for a randomized crossover trial
Heiland, E. G., Kjellenberg, K., Tarassova, O., Fernström, M., Nyberg, G., Ekblom, M., Helgadóttir, B., & Ekblom, Ö. B. (2022) · Trials · doi:10.1186/s13063-021-05972-5 · Cited by 8
“This suggests that after performing physical activity, efficiency in performing the cognitively demanding task increases so that less resources are required [39].”
Background
Psychological resilience and neurodegenerative risk: A connectomics‐transcriptomics investigation in healthy adolescent and middle‐aged females
Petrican, R., Fornito, A., & Jones, N. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119209 · Cited by 7
Community‐based high‐intensity cycling improves disease symptoms in individuals with Parkinson's disease: A six‐month pragmatic observational study
Rosenfeldt, A. B., Koop, M. M., Penko, A. L., Hastilow, K., Zimmerman, E. M., Schindler, D., & Alberts, J. L. (2022) · Health & Social Care in the Community · doi:10.1111/hsc.14049 · Cited by 7
“…74% of classes, a cycling cadence of 76 or greater was associated with greater improvements in MDS-UPDRS III than those who cycled at a slower cadence. healthy adults and individuals with PD, support the concept that high cadence training may facilitate neural efficiency (Neubauer & Fink, 2009 ).”

Authors: Neubauer, A. C., & Fink, A.
Affiliations: University of Graz (AT)
Corresponding author: Neubauer, Aljoscha C.
ORCID: 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)
DOI: 10.1016/j.neubiorev.2009.04.001
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
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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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