Neural correlates of cognitive efficiency
Abstract
Since its inception, experimental psychology has sought to account for individual differences in human performance. Some neuroimaging research, involving complex behavioral paradigms, has suggested that faster-performing individuals show greater neural activity than slower performers. Other research has suggested that faster-performing individuals show less neural activity than slower performers. To examine the neural basis of individual performance differences, we had participants perform a simple speeded-processing task during fMRI scanning. In some prefrontal cortical (PFC) brain regions, faster performers showed less cortical activity than slower performers while in other PFC and parietal regions they showed greater activity. Regional-causality analysis indicated that PFC exerted more influence over other brain regions for slower than for faster individuals. These results suggest that a critical determinant of individual performance differences is the efficiency of interactions between brain regions and that slower individuals may require more prefrontal executive control than faster individuals to perform successfully.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
At a given level of task complexity, individuals with higher ability display more focal and less diffuse brain activity than those with lower ability.
“At a given level of task complexity, individuals with higher ability display more focal and less diffuse brain activity than those with lower ability”
From School Readiness and Self-Regulation: A Developmental Psychobiological Approach (2015) · cites this paper as Rypma et al. 2006
Cites
The processing-speed theory of adult age differences in cognition
Salthouse, T. A. (1996) · Psychological Review · doi:10.1037/0033-295x.103.3.403 · Cited by 5,568 · cited 3× · see citing works
“Additionally, it has been validated in correlational studies with other speeded-processing tasks, high-level cognitive and intelligence tests (Brebion et al., 2000; Salthouse, 1996a, b; Salthouse, 1992; Wechsler, 1981).”
BackgroundMethodInfluentialHemispheric asymmetry reduction in older adults: the HAROLD model
Cabeza, R. (2002) · Psychology and Aging · doi:10.1037/0882-7974.17.1.85 · Cited by 2,125 · see citing works
Immature Frontal Lobe Contributions to Cognitive Control in Children
Bunge, S. A., Dudukovic, N. M., Thomason, M. E., Vaidya, C. J., & Gabrieli, J. D. E. (2002) · Neuron · doi:10.1016/s0896-6273(01)00583-9 · Cited by 1,291 · cited 1× · see citing works
“Comparisons of neural activity differences in children and adults indicate frontal activation differences between these two groups ( Bunge et al., 2002 ).”
BackgroundAge differences in the frontal lateralization of verbal and spatial working memory revealed by PET
Reuter-Lorenz, P. A., Jonides, J., Smith, E. E., Hartley, A., Miller, A., Marshuetz, C., & Koeppe, R. A. (2000) · Journal of Cognitive Neuroscience · doi:10.1162/089892900561814 · Cited by 998 · see citing works
Processing speed as a mental capacity
Kail, R., & Salthouse, T. A. (1994) · Acta Psychologica · doi:10.1016/0001-6918(94)90003-5 · Cited by 850 · see citing works
Developmental change in speed of processing during childhood and adolescence
Kail, R. (1991) · Psychological Bulletin · doi:10.1037/0033-2909.109.3.490 · Cited by 673 · cited 1× · see citing works
“Similar results have been obtained with other kinds of tasks including letter-naming and memory search (e.g., Kail, 1988; 1991; Keating and Bobbitt, 1978).”
ResultDistinct basal ganglia territories are engaged in early and advanced motor sequence learning
Lehéricy, S., Benali, H., Van de Moortele, P.-F., Pélégrini-Issac, M., Waechter, T., Ugurbil, K., & Doyon, J. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0502762102 · Cited by 634 · see citing works
Newman, S. D., Carpenter, P. A., Varma, S., & Just, M. A. (2003) · Neuropsychologia · doi:10.1016/s0028-3932(03)00091-5 · Cited by 400 · see citing works
Age-related differences in the functional connectivity of the hippocampus during memory encoding
Grady, C. L., McIntosh, A. R., & Craik, F. I. M. (2003) · Hippocampus · doi:10.1002/hipo.10114 · Cited by 277 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Competition between functional brain networks mediates behavioral variability
Kelly, A. M. C., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.008 · Cited by 1,287 · see citing works
Self-citationSchool Readiness and Self-Regulation: A Developmental Psychobiological Approach
Blair, C., & Raver, C. C. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-010814-015221 · Cited by 1,240 · see citing works
Intelligence: New findings and theoretical developments
Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F., & Turkheimer, E. (2012) · American Psychologist · doi:10.1037/a0026699 · Cited by 968 · see citing works
Intelligence and neural efficiency
Neubauer, A. C., & Fink, A. (2009) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2009.04.001 · Cited by 878 · see citing works
Large-scale brain systems in ADHD: beyond the prefrontal–striatal model
Castellanos, F. X., & Proal, E. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.11.007 · Cited by 831 · see citing works
Turken, U., Whitfield-Gabrieli, S., Bammer, R., Baldo, J. V., Dronkers, N. F., & Gabrieli, J. D. E. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.057 · Cited by 500 · see citing works
Ding, W.-N., Sun, J.-H., Sun, Y.-W., Chen, X., Zhou, Y., Zhuang, Z.-G., Li, L., Zhang, Y., Xu, J.-R., & Du, Y.-S. (2014) · Behavioral and Brain Functions · doi:10.1186/1744-9081-10-20 · Cited by 294 · see citing works
Dong, G., DeVito, E. E., Du, X., & Cui, Z. (2012) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2012.02.001 · Cited by 289 · see citing works
Top-down regulation of default mode activity in spatial visual attention
Wen, X., Liu, Y., Yao, L., & Ding, M. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4939-12.2013 · Cited by 150 · see citing works
Cholinergic augmentation modulates visual task performance in sleep-deprived young adults
Chuah, L. Y. M., & Chee, M. W. L. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4045-08.2008 · Cited by 118 · see citing works
Neural effects of short-term training on working memory
Buschkuehl, M., Hernandez-Garcia, L., Jaeggi, S. M., Bernard, J. A., & Jonides, J. (2014) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-013-0244-9 · Cited by 117 · see citing works
Multiple Biological Pathways Link Cognitive Lifestyle to Protection from Dementia
Valenzuela, M. J., Matthews, F. E., Brayne, C., Ince, P., Halliday, G., Kril, J. J., Dalton, M. A., Richardson, K., Forster, G., & Sachdev, P. S. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.07.036 · Cited by 100 · see citing works
Tarter, K. D., Simanek, A. M., Dowd, J. B., & Aiello, A. E. (2014) · The Journal of Infectious Diseases · doi:10.1093/infdis/jit616 · Cited by 78 · see citing works
Effects of processing speed training on cognitive functions and neural systems
Takeuchi, H., & Kawashima, R. (2012) · Reviews in the Neurosciences · doi:10.1515/revneuro-2012-0035 · Cited by 67 · see citing works
Evidence for reduced efficiency and successful compensation in older adults during task switching
Hakun, J. G., Zhu, Z., Johnson, N. F., & Gold, B. T. (2015) · Cortex · doi:10.1016/j.cortex.2014.12.006 · Cited by 51 · see citing works
The Effects of Working Memory Training on Brain Activity
Nęcka, E., Gruszka, A., Hampshire, A., Sarzyńska-Wawer, J., Anicai, A.-E., Orzechowski, J., Nowak, M., Wójcik, N., Sandrone, S., & Soreq, E. (2021) · Brain Sciences · doi:10.3390/brainsci11020155 · Cited by 23 · see citing works
- Authors
- Rypma, B., Berger, J. S., Prabhakaran, V., Martin Bly, B., Kimberg, D. Y., Biswal, B. B., & D'Esposito, M.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Temple University (US)
- Johns Hopkins University (US)
- Hospital of the University of Pennsylvania (US)
- University of Medicine and Dentistry of New Jersey (US)
- Corresponding author
- Rypma, Bart
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2006-11
- Volume
- 33
- Issue
- 3
- Pages
- 969-979
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2017185691
- Cited by
- 334
- References
- 9
- Citations by year
- 2026: 9 · 2025: 14 · 2024: 13 · 2023: 10 · 2022: 10 · 2021: 10 · 2020: 12 · 2019: 12 · 2018: 23 · 2017: 17 · 2016: 16 · 2015: 23 · 2014: 31 · 2013: 26 · 2012: 21
- FWCI
- 7.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (R03MH061636, MH61636)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Keywords
- individual differences in performance, cognitive efficiency, prefrontal cortex, parietal cortex, executive function, brain network interactions
- MeSH terms
- Adolescent, Adult, Algorithms, Brain Mapping, Cognition, Data Interpretation, Statistical, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neurons, Psychomotor Performance, Reaction Time
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
