The formation of learning sets.
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?
Harlow (1949) found that monkeys adapted their learning strategies after sufficiently many interactions with tasks that shared a common structure, showing a learning-to-learn effect.
“He found that they adapted their learning strategies after sufficiently many interactions with tasks that shared a common structure, thereby showing a learning-to-learn effect.”
From Meta-learned models of cognition (2024) · cites this paper as Harlow, 1949
Cited by
Sorted by citations
Absorptive Capacity: A New Perspective on Learning and Innovation
Cohen, W. M., & Levinthal, D. A. (1990) · Administrative Science Quarterly · doi:10.2307/2393553 · Cited by 35,728 · see citing works
Generalized expectancies for internal versus external control of reinforcement.
Rotter, J. B. (1966) · Psychological Monographs: General and Applied · doi:10.1037/h0092976 · Cited by 21,937 · see citing works
Human-level concept learning through probabilistic program induction
Lake, B. M., Salakhutdinov, R., & Tenenbaum, J. B. (2015) · Science · doi:10.1126/science.aab3050 · Cited by 2,817 · see citing works
Building machines that learn and think like people
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x16001837 · Cited by 2,550 · see citing works
Getting formal with dopamine and reward
Schultz, W. (2002) · Neuron · doi:10.1016/s0896-6273(02)00967-4 · Cited by 2,574 · see citing works
Neuroscience-Inspired Artificial Intelligence
Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017) · Neuron · doi:10.1016/j.neuron.2017.06.011 · Cited by 1,557 · see citing works
Schemas and Memory Consolidation.
Tse, D., Langston, R. F., Kakeyama, M., Bethus, I., Spooner, P. A., Wood, E. R., Witter, M. P., & Morris, R. G. M. (2007) · Science · doi:10.1126/science.1135935 · Cited by 1,244 · see citing works
Neuronal Reward and Decision Signals: From Theories to Data
Schultz, W. (2015) · Physiological Reviews · doi:10.1152/physrev.00023.2014 · Cited by 1,126 · see citing works
What Is a Cognitive Map? Organizing Knowledge for Flexible Behavior
Behrens, T. E. J., Muller, T. H., Whittington, J. C. R., Mark, S., Baram, A. B., Stachenfeld, K. L., & Kurth-Nelson, Z. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.002 · Cited by 1,055 · see citing works
Reinforcement learning, fast and slow
Botvinick, M., Ritter, S., Wang, J. X., Kurth-Nelson, Z., Blundell, C., & Hassabis, D. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.02.006 · Cited by 667 · see citing works
Motor Development: Embodied, Embedded, Enculturated, and Enabling
Adolph, K. E., & Hoch, J. E. (2019) · Annual Review of Psychology · doi:10.1146/annurev-psych-010418-102836 · Cited by 580 · see citing works
Learning to reinforcement learn
Wang, J. X., Kurth-Nelson, Z., Tirumala, D., Soyer, H., Leibo, J. Z., Munos, R., Blundell, C., Kumaran, D., & Botvinick, M. (2016) · arXiv · doi:10.48550/arxiv.1611.05763 · Cited by 579 · see citing works
Human replay spontaneously reorganizes experience
Liu, Y., Dolan, R. J., Kurth-Nelson, Z., & Behrens, T. E. J. (2019) · Cell · doi:10.1016/j.cell.2019.06.012 · Cited by 497 · see citing works
Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making
Collins, A., & Koechlin, E. (2012) · PLoS Biology · doi:10.1371/journal.pbio.1001293 · Cited by 558 · see citing works
“—that is, active representations of behavioral strategies stored in long-term memory—for driving action”
BackgroundBrain plasticity through the life span: Learning to learn and action video games
Bavelier, D., Green, C. S., Pouget, A., & Schrater, P. (2012) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-060909-152832 · Cited by 541 · see citing works
Working memory training involves learning new skills
Gathercole, S. E., Dunning, D. L., Holmes, J., & Norris, D. (2019) · Journal of Memory and Language · doi:10.1016/j.jml.2018.10.003 · Cited by 225 · see citing works
“Finally, the approach is clearly differentiated from theories of cognitive training which assume that benefits might arise from “learning to learn” (Bavelier et al., 2012; Harlow, 1949).”
MethodPractice makes perfect: entrepreneurial-experience curves and venture performance
Toft-Kehler, R., Wennberg, K., & Kim, P. H. (2014) · Journal of Business Venturing · doi:10.1016/j.jbusvent.2013.07.001 · Cited by 216 · see citing works
Braun, D. A., Mehring, C., & Wolpert, D. M. (2010) · Behavioural Brain Research · doi:10.1016/j.bbr.2009.08.031 · Cited by 210 · see citing works
Deaner, R. O., van Schaik, C. P., & Johnson, V. (2006) · Evolutionary Psychology · doi:10.1177/147470490600400114 · Cited by 212 · see citing works
The study of animal metacognition
Smith, J. D. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.06.009 · Cited by 203 · see citing works
The extraction and integration framework: A two-process account of statistical learning
Thiessen, E. D., Kronstein, A. T., & Hufnagle, D. G. (2013) · Psychological Bulletin · doi:10.1037/a0030801 · Cited by 202 · see citing works
Meta-learning in natural and artificial intelligence
Wang, J. X. (2021) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2021.01.002 · Cited by 171 · see citing works
The comparative study of metacognition: Sharper paradigms, safer inferences
Smith, J. D., Beran, M. J., Couchman, J. J., & Coutinho, M. V. C. (2008) · Psychonomic Bulletin & Review · doi:10.3758/pbr.15.4.679 · Cited by 151 · see citing works
Adolph, K. E., & Robinson, S. R. (2015) · Handbook of Child Psychology and Developmental Science · doi:10.1002/9781118963418.childpsy204 · Cited by 135 · see citing works
On the formation of psychological traits
Anastasi, A. (1970) · American Psychologist · doi:10.1037/h0029767 · Cited by 128 · see citing works
Model averaging, optimal inference, and habit formation
FitzGerald, T. H. B., Dolan, R. J., & Friston, K. J. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00457 · Cited by 121 · see citing works
Toward the neural implementation of structure learning
Tervo, D. G. R., Tenenbaum, J. B., & Gershman, S. J. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2016.01.014 · Cited by 106 · see citing works
Porter, J. N., Olsen, A. S., Gurnsey, K., Dugan, B. P., Jedema, H. P., & Bradberry, C. W. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.5426-10.2011 · Cited by 97 · see citing works
Assessment of intradimensional/extradimensional attentional set-shifting in rats
Tait, D. S., Bowman, E. M., Neuwirth, L. S., & Brown, V. J. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.02.013 · Cited by 66 · see citing works
Radulescu, A., Shin, Y. S., & Niv, Y. (2021) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-092920-120559 · Cited by 63 · see citing works
Orientation toward humans predicts cognitive performance in orang-utans
Damerius, L. A., Forss, S. I. F., Kosonen, Z. K., Willems, E. P., Burkart, J. M., Call, J., Galdikas, B. M. F., Liebal, K., Haun, D. B. M., & van Schaik, C. P. (2017) · Scientific Reports · doi:10.1038/srep40052 · Cited by 53 · see citing works
Visual discrimination of species in dogs (Canis familiaris)
Autier-Dérian, D., Deputte, B. L., Chalvet-Monfray, K., Coulon, M., & Mounier, L. (2013) · Animal Cognition · doi:10.1007/s10071-013-0600-8 · Cited by 49 · see citing works
From remembering to reconstruction: The transformative neural representation of episodic memory.
Xue, G. (2022) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2022.102351 · Cited by 49 · see citing works
Naïve to expert: Considering the role of previous knowledge in memory
Alonso, A., van der Meij, J., Tse, D., & Genzel, L. (2020) · Brain and Neuroscience Advances · doi:10.1177/2398212820948686 · Cited by 46 · see citing works
Meta-learned models of cognition
Binz, M., Dasgupta, I., Jagadish, A. K., Botvinick, M., Wang, J. X., & Schulz, E. (2024) · Behavioral and Brain Sciences · doi:10.1017/s0140525x23003266 · Cited by 38 · see citing works
A neural circuit architecture for rapid learning in goal-directed navigation
Dan, C., Hulse, B. K., Kappagantula, R., Jayaraman, V., & Hermundstad, A. M. (2024) · Neuron · doi:10.1016/j.neuron.2024.04.036 · Cited by 51 · see citing works
“82 Here, we show how inductive biases that are likely learned over evolutionary time-scales can be inferred directly from an animal’s behavior.”
BackgroundNeri, F., Smeralda, C. L., Momi, D., Sprugnoli, G., Menardi, A., Ferrone, S., Rossi, S., Rossi, A., Di Lorenzo, G., & Santarnecchi, E. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.598410 · Cited by 27 · see citing works
A neural circuit architecture for rapid behavioral flexibility in goal-directed navigation
Dan, C., Hulse, B. K., Kappagantula, R., Jayaraman, V., & Hermundstad, A. M. (2021) · doi:10.1101/2021.08.18.456004 · Cited by 51 · see citing works
The HexMaze: A Previous Knowledge Task on Map Learning for Mice
Alonso, A., Bokeria, L., van der Meij, J., Samanta, A., Eichler, R., Lotfi, A., Spooner, P., Navarro Lobato, I., & Genzel, L. (2021) · eneuro · doi:10.1523/eneuro.0554-20.2021 · Cited by 13 · see citing works
Learning-to-learn in the age of generative AI: a scoping review and conceptual framework
Schorr, I., Bardach, L., Bühler, B., & Kasneci, E. (2026) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2026.100575 · Cited by 3 · see citing works
- Authors
- Harlow, H. F.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Harlow, Harry F.
- Venue
- Psychological Review
- Published
- 1949
- Volume
- 56
- Issue
- 1
- Pages
- 51-65
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2092387347
- Cited by
- 1,959
- References
- 0
- Citations by year
- 2026: 26 · 2025: 45 · 2024: 54 · 2023: 45 · 2022: 68 · 2021: 59 · 2020: 68 · 2019: 54 · 2018: 39 · 2017: 41 · 2016: 32 · 2015: 37 · 2014: 23 · 2013: 29 · 2012: 28
- FWCI
- 26.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Review (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Keywords
- learning sets, associative learning, stimulus-response associations
- MeSH terms
- Humans, Learning
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