Abstract
Procedural and perceptual learning are important processes involved in skill acquisition and the formation of expertise. This chapter provides an overview of recent research on the neuroscientific investigation of these different learning forms underlying the acquisition of skills. We focus on low-level processes in perception and motor control and how these low-level processes are improved by learning. Other forms of neural plasticity like adaptation, habituation, sensitization, conditioning and extinction are differentiated from procedural and perceptual learning. A brief introduction to the neuroanatomical basis of visual function is given. We next review the research on the cognitive neuroscience of these forms of learning with a focus on studies that use functional magnetic resonance imaging (fMRI). Recent results on dopaminergic and cholinergic processes underlying learning are discussed in the context of a top-down attention-gated model of perceptual learning. Finally an overview is given of research on skill acquisition and the implications of this research on the design of learning environments.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aeschbach, D., Cutler, A. J., & Ronda, J. M. (2008). A role for non-rapid-eye-movement sleep homeostasis in perceptual learning. The Journal of Neuroscience, 28(11), 2766–2772. doi:10.1523/JNEUROSCI.5548-07.2008.
Allen, M., Dietz, M., Blair, K. S., van Beek, M., Rees, G., Vestergaard-Poulsen, P., et al. (2012). Cognitive-affective neural plasticity following active-controlled mindfulness intervention. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, 32(44), 15601–15610.
Amiez, C., Neveu, R., Warrot, D., Petrides, M., Knoblauch, K., & Procyk, E. (2013). The location of feedback-related activity in the midcingulate cortex is predicted by local morphology. The Journal of Neuroscience, 33(5), 2217–2228.
Bakin, J. S., & Weinberger, N. M. (1996). Induction of a physiological memory in the cerebral cortex by stimulation of the nucleus basalis. Proceedings of the National Academy of Sciences of the United States of America, 93(20), 11219–11224.
Bao, S., Chan, V. T., & Merzenich, M. M. (2001). Cortical remodelling induced by activity of ventral tegmental dopamine neurons. Nature, 412(6842), 79–83.
Beer, A. L., Vartak, D., & Greenlee, M. W. (2013). Nicotine facilitates memory consolidation in perceptual learning. Neuropharmacology, 64, 443–451.
Bernard, J. A., & Seidler, R. D. (2013). Cerebellar contributions to visuomotor adaptation and motor sequence learning: An ALE meta-analysis. Frontiers in Human Neuroscience, 7, 27. doi:10.3389/fnhum.2013.00027.
Blakemore, C., & Campbell, F. W. (1969). On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images. The Journal of Physiology, 203(1), 237–260.
Cain, M. S., Landau, A. N., & Shimamura, A. P. (2012). Action video game experience reduces the cost of switching tasks. Attention, Perception, & Psychophysics, 74(4), 641–647.
Carew, T., Castellucci, V. F., & Kandel, E. R. (1979). Sensitization in Aplysia: Restoration of transmission in synapses inactivated by long-term habituation. Science (New York, NY), 205(4404), 417–419.
Carew, T. J., Walters, E. T., & Kandel, E. R. (1981). Classical conditioning in a simple withdrawal reflex in Aplysia californica. Journal of Neuroscience, 1(12), 1426–1437.
Carey, L., Macdonell, R., & Matyas, T. A. (2011). SENSe: Study of the Effectiveness of Neurorehabilitation on Sensation: A randomized controlled trial. Neurorehabilitation and Neural Repair, 25(4), 304–313.
Caspers, S., Zilles, K., Laird, A. R., & Eickhoff, S. B. (2010). ALE meta-analysis of action observation and imitation in the human brain. NeuroImage, 50(3), 1148–1167.
Castellucci, V. F., Carew, T. J., & Kandel, E. R. (1978). Cellular analysis of long-term habituation of the gill-withdrawal reflex of Aplysia californica. Science (New York, NY), 202(4374), 1306–1308.
Cheng, K., Waggoner, R. A., & Tanaka, K. (2001). Human ocular dominance columns as revealed by high-field functional magnetic resonance imaging. Neuron, 32(2), 359–374.
Cross, E. S., Kraemer, D. J. M., Hamilton, A. F. de C., Kelley, W. M., & Grafton, S. T. (2009). Sensitivity of the action observation network to physical and observational learning. Cerebral Cortex (New York, NY: 1991), 19(2), 315–326.
Daniel, R., & Pollmann, S. (2010). Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning. The Journal of Neuroscience, 30(1), 47–55.
Draganski, B., & May, A. (2008). Training-induced structural changes in the adult human brain. Behavioural Brain Research, 192(1), 137–142.
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Neuroplasticity: Changes in grey matter induced by training. Nature, 427(6972), 311–312.
Egerton, A., Mehta, M. A., Montgomery, A. J., Lappin, J. M., Howes, O. D., Reeves, S. J., et al. (2009). The dopaminergic basis of human behaviors: A review of molecular imaging studies. Neuroscience & Biobehavioral Reviews, 33(7), 1109–1132.
Fahle, M. (2005). Perceptual learning: Specificity versus generalization. Current Opinion in Neurobiology, 15(2), 154–160.
Fahle, M., & Poggio, T. (Eds.). (2002). Perceptual learning (p. 2002). Cambridge, MA: MIT Press.
Fine, I., & Jacobs, R. A. (2002). Comparing perceptual learning tasks: A review. Journal of Vision, 2(2), 190–203.
Fitzgerald, M. B., & Wright, B. A. (2011). Perceptual learning and generalization resulting from training on an auditory amplitude-modulation detection task. The Journal of the Acoustical Society of America, 129(2), 898–906.
Frank, S. M., Reavis, E. A., Tse, P. U., & Greenlee, M. W. (2014). Neural mechanisms of feature conjunction learning: Enduring changes in occipital cortex after a week of training. Human Brain Mapping, 35, 1201–1211.
Gais, S., & Born, J. (2004). Low acetylcholine during slow-wave sleep is critical for declarative memory consolidation. Proceedings of the National Academy of Sciences of the United States of America, 101(7), 2140–2144. doi:10.1073/pnas.0305404101.
Gibson, E. (1963). Perceptual learning. Annual Review of Psychology, 14, 29–56.
Gopher, D., Well, M., & Bareket, T. (1994). Transfer of skill from a computer game trainer to flight. Human Factors, 36(3), 387–405.
Green, C. S., & Bavelier, D. (2003). Action video game modifies visual selective attention. Nature, 423(6939), 534–537.
Green, C. S., & Bavelier, D. (2012). Learning, attentional control, and action video games. Current Biology: CB, 22(6), R197–R206.
Greenlee, M. W., & Heitger, F. (1988). The functional role of contrast adaptation. Vision Research, 28(7), 791–797.
Groves, P. M., & Thompson, R. F. (1970). Habituation: A dual-process theory. Psychological Review, 77(5), 419–450.
Hasselmo, M. E. (2006). The role of acetylcholine in learning and memory. Current Opinion in Neurobiology, 16, 710–715.
Herzog, M. H., & Fahle, M. (1997). The role of feedback in learning a vernier discrimination task. Vision Research, 37(15), 2133–2141.
Higuchi, S., Holle, H., Roberts, N., Eickhoff, S. B., & Vogt, S. (2012). Imitation and observational learning of hand actions: Prefrontal involvement and connectivity. NeuroImage, 59(2), 1668–1683.
Hubel, D. H., & Wiesel, T. N. (1962). Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. The Journal of Physiology, 160, 106–154.
Hughson, A. L., & Boakes, R. A. (2009). Passive perceptual learning in relation to wine: Short-term recognition and verbal description. Quarterly Journal of Experimental Psychology (2006), 62(1), 1–8.
Jäncke, L., Koeneke, S., Hoppe, A., Rominger, C., & Hänggi, J. (2009). The architecture of the golfer’s brain. PLoS One, 4(3), e4785.
Jäncke, L., Langer, N., & Hänggi, J. (2012). Diminished whole-brain but enhanced peri-sylvian connectivity in absolute pitch musicians. Journal of Cognitive Neuroscience, 24(6), 1447–1461.
Kahnt, T., Grueschow, M., Speck, O., & Haynes, J.-D. (2011). Perceptual learning and decision-making in human medial frontal cortex. Neuron, 70(3), 549–559.
Karni, A., & Sagi, D. (1991). Where practice makes perfect in texture discrimination: Evidence for primary visual cortex plasticity. Proceedings of the National Academy of Sciences of the United States of America, 88(11), 4966–4970.
Karni, A., & Sagi, D. (1993). The time course of learning a visual skill. Nature, 365(6443), 250–252.
Karni, A., Tanne, D., Rubenstein, B. S., Askenasy, J. J., & Sagi, D. (1994). Dependence on REM sleep of overnight improvement of a perceptual skill. Science (New York, NY), 265(5172), 679–682.
Karni, A., Meyer, G., Jezzard, P., Adams, M. M., Turner, R., & Ungerleider, L. G. (1995). Functional MRI evidence for adult motor cortex plasticity during motor skill learning. Nature, 377(6545), 155–158.
Kassubek, J., Schmidtke, K., Kimmig, H., Lücking, C. H., & Greenlee, M. W. (2001). Changes in cortical activation during mirror reading before and after training: An fMRI study of procedural learning. Brain Research. Cognitive Brain Research, 10(3), 207–217.
Kilgard, M. P., & Merzenich, M. M. (1998). Cortical map reorganization enabled by nucleus basalis activity. Science (New York, NY), 279(5357), 1714–1718.
Kim, J., Lee, H. M., Kim, W. J., Park, H. J., Kim, S. W., Moon, D. H., et al. (2008). Neural correlates of pre-performance routines in expert and novice archers. Neuroscience Letters, 445(3), 236–241.
Koepp, M. J., Gunn, R. N., Lawrence, A. D., Cunningham, V. J., Dagher, A., Jones, T., et al. (1998). Evidence for striatal dopamine release during a video game. Nature, 393(6682), 266–268.
Kühn, S., Romanowski, A., Schilling, C., Lorenz, R., Mörsen, C., Seiferth, N., et al. (2011). The neural basis of video gaming. Translational Psychiatry, 1, e53.
Kyndt, E., Onghena, P., Smet, K., & Dochy, F. (Accepted). Employees’ learning intention: Comparing low- and high-qualified employees. International Journal of Educational and Vocational Guidance.
Lee, B. B., Martin, P. R., & Grünert, U. (2010). Retinal connectivity and primate vision. Progress in Retinal and Eye Research, 29(6), 622–639.
Lee, H., Voss, M. W., Prakash, R. S., Boot, W. R., Vo, L. T. K., Basak, C., et al. (2012). Videogame training strategy-induced change in brain function during a complex visuomotor task. Behavioural Brain Research, 232(2), 348–357.
LeVay, S., Wiesel, T. N., & Hubel, D. H. (1980). The development of ocular dominance columns in normal and visually deprived monkeys. The Journal of Comparative Neurology, 191(1), 1–51.
Levi, D. M., & Li, R. W. (2009). Perceptual learning as a potential treatment for amblyopia: A mini-review. Vision Research, 49(21), 2535–2549.
Li, R., Polat, U., Makous, W., & Bavelier, D. (2009). Enhancing the contrast sensitivity function through action video game training. Nature Neuroscience, 12(5), 549–551.
Löwel, S., Schmidt, K. E., Kim, D. S., Wolf, F., Hoffsümmer, F., Singer, W., & Bonhoeffer, T. (1998). The layout of orientation and ocular dominance domains in area 17 of strabismic cats. European Journal of Neuroscience, 10(8), 2629–2643.
Mednick, S., Nakayama, K., & Stickgold, R. (2003). Sleep-dependent learning: A nap is as good as a night. Nature Neuroscience, 6(7), 697–698. doi:10.1038/nn1078.
Molenberghs, P., Cunnington, R., & Mattingley, J. B. (2012). Brain regions with mirror properties: A meta-analysis of 125 human fMRI studies. Neuroscience & Biobehavioral Reviews, 36(1), 341–349.
Mollon, J. D., & Danilova, M. V. (1996). Three remarks on perceptual learning. Spatial Vision, 10(1), 51–58.
Moreno, M. M., Linster, C., Escanilla, O., Sacquet, J., Didier, A., & Mandairon, N. (2009). Olfactory perceptual learning requires adult neurogenesis. Proceedings of the National Academy of Sciences, 106(42), 17980–17985.
Muellbacher, W., Ziemann, U., Wissel, J., Dang, N., Kofler, M., Facchini, S., et al. (2002). Early consolidation in human primary motor cortex. Nature, 415(6872), 640–644.
Nomoto, K., Schultz, W., Watanabe, T., & Sakagami, M. (2010). Temporally extended dopamine responses to perceptually demanding reward-predictive stimuli. The Journal of Neuroscience, 30(32), 10692–10702.
Nyberg, L., Eriksson, J., Larsson, A., & Marklund, P. (2006). Learning by doing versus learning by thinking: An fMRI study of motor and mental training. Neuropsychologia, 44(5), 711–717.
Pavlov, I. P. (1927). Conditioned reflexes: An investigation of the physiological activity of the cerebral cortex (G. V. Anrep, Trans.). London: Oxford University Press.
Pérès, M., van de Moortele, P. F., Pierard, C., Lehericy, S., Satabin, P., Le Bihan, D., & Guezennec, C. Y. (2000). Functional magnetic resonance imaging of mental strategy in a simulated aviation performance task. Aviation, Space, and Environmental Medicine, 71(12), 1218–1231.
Poggio, T., Fahle, M., & Edelman, S. (1992). Fast perceptual learning in visual hyperacuity. Science, 256(5059), 1018–1021.
Poldrack, R. A. (2002). Neural systems for perceptual skill learning. Behavioral and Cognitive Neuroscience Reviews, 1(1), 76–83.
Poldrack, R. A., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (1998). The neural basis of visual skill learning: An fMRI study of mirror reading. Cerebral Cortex (New York, NY: 1991), 8(1), 1–10.
Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. A., Lamantia, A. S., McNamara, J. O., & Williams, M. (2004). Neuroscience (3rd ed.). New York: Sinauer Press.
Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. A., & Lamantia, A. S. (2008). Neuroscience (4th ed.). New York: Sinauer Press.
Robertson, E. M. (2004). Skill learning: Putting procedural consolidation in context. Current biology: CB, 14(24), R1061–R1063.
Roelfsema, P. R., van Ooyen, A., & Watanabe, T. (2010). Perceptual learning rules based on reinforcers and attention. Trends in Cognitive Sciences, 14(2), 64–71.
Rokem, A., & Silver, M. A. (2010). Cholinergic enhancement augments magnitude and specificity of visual perceptual learning in healthy humans. Current Biology: CB, 20(19), 1723–1728.
Sagi, D. (2011). Perceptual learning in vision research. Vision Research, 51(13), 1552–1566.
Sagi, Y., Tavor, I., Hofstetter, S., Tzur-Moryosef, S., Blumenfeld-Katzir, T., & Assaf, Y. (2012). Learning in the fast lane: New insights into neuroplasticity. Neuron, 73(6), 1195–1203.
Schlaug, G., Jäncke, L., Huang, Y., & Steinmetz, H. (1995). In vivo evidence of structural brain asymmetry in musicians. Science (New York, NY), 267(5198), 699–701.
Schlegel, A. A., Rudelson, J. J., & Tse, P. U. (2012). White matter structure changes as adults learn a second language. Journal of Cognitive Neuroscience, 24(8), 1664–1670.
Schmidt-Wilcke, T., Rosengarth, K., Luerding, R., Bogdahn, U., & Greenlee, M. W. (2010). Distinct patterns of functional and structural neuroplasticity associated with learning Morse code. NeuroImage, 51(3), 1234–1241.
Seitz, A. R., & Watanabe, T. (2003). Psychophysics: Is subliminal learning really passive? Nature, 422(6927), 36.
Seitz, A., & Watanabe, T. (2005). A unified model for perceptual learning. Trends in Cognitive Sciences, 9(7), 329–334.
Steele, C. J., Scholz, J., Douaud, G., Johansen-Berg, H., & Penhune, V. B. (2012). Structural correlates of skilled performance on a motor sequence task. Frontiers in Human Neuroscience, 6, 289.
Sutton, R. S., & Barto, A. G. (1998). Reinforcement learning. Cambridge, MA: MIT Press.
Tang, K., Staines, W. R., Black, S. E., & McIlroy, W. E. (2009). Novel vibrotactile discrimination task for investigating the neural correlates of short-term learning with fMRI. Journal of Neuroscience Methods, 178(1), 65–74.
Tricomi, E., Delgado, M. R., McCandliss, B. D., McClelland, J. L., & Fiez, J. A. (2006). Performance feedback drives caudate activation in a phonological learning task. Journal of Cognitive Neuroscience, 18(6), 1029–1043.
Tsushima, Y., Sasaki, Y., & Watanabe, T. (2006). Greater disruption due to failure of inhibitory control on an ambiguous distractor. Science (New York, NY), 314(5806), 1786–1788. doi:10.1126/science.1133197.
Tsushima, Y., Seitz, A. R., & Watanabe, T. (2008). Task- irrelevant learning occurs only when the irrelevant feature is weak. Current Biology, 18(12), 516–517.
Ungerleider, L. G., Doyon, J., & Karni, A. (2002). Imaging brain plasticity during motor skill learning. Neurobiology of Learning and Memory, 78(3), 553–564.
Wan, X., Takano, D., Asamizuya, T., Suzuki, C., Ueno, K., Cheng, K., et al. (2012). Developing intuition: Neural correlates of cognitive-skill learning in caudate nucleus. The Journal of Neuroscience, 32(48), 17492–17501.
Watanabe, T., Náñez, Y., & Sasak, S. (2001). Perceptual learning without perception. Nature, 413, 844–848.
Webster, M. A., Kaping, D., Mizokami, Y., & Duhamel, P. (2004). Adaptation to natural facial categories. Nature, 428(6982), 557–561.
Werner, J. S. & Chalupa, L. M. (Eds.). (2013). The new visual neurosciences. Cambridge, MA: MIT Press.
Wiesel, T. N., & Hubel, D. H. (1963). Single-cell responses in striate cortex of kittens deprived of vision in one eye. Journal of Neurophysiology, 26, 1003–1017.
Wright, M. J., Bishop, D. T., Jackson, R. C., & Abernethy, B. (2011). Cortical fMRI activation to opponents’ body kinematics in sport-related anticipation: Expert-novice differences with normal and point-light video. Neuroscience Letters, 500(3), 216–221.
Yotsumoto, Y., Sasaki, Y., Chan, P., Vasios, C. E., Bonmassar, G., Ito, N., et al. (2009). Location-specific cortical activation changes during sleep after training for perceptual learning. Current Biology, 19(15), 1278–1282.
Zatorre, R. J., Perry, D. W., Beckett, C. A., Westbury, C. F., & Evans, A. C. (1998). Functional anatomy of musical processing in listeners with absolute pitch and relative pitch. Proceedings of the National Academy of Sciences of the United States of America, 95(6), 3172–3177.
Suggested Readings
Fahle, M., & Poggio, T. (Eds.). (2002). Perceptual learning (p. 2002). Cambridge, MA: MIT Press.
Purves, D., Augustine, G. J., Fitzpatrick, D., Hall, W. A., & Lamantia, A. S. (2008). Neuroscience (4th ed.). New York: Sinauer Press.
Acknowledgements
The author would like to thank Sebastian M. Frank (Dartmouth College) for his critical and helpful comments. The author also acknowledges funding support from the Federal Ministry for Education and Research (BMBF, Project “Brain Plasticity and Perceptual Learning”) and the German Research Council (DFG, FOR 1075, Project GR988/22-2).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Glossary
- 11C-raclopride positron emission tomography
-
A brain imaging technique involving the radioactive isotope 11C combined with raclopride to label dopaminergic brain regions.
- Anterior cingulum
-
Cortical area in medial prefrontal cortex thought to process various aspects of attention and executive control.
- Caudate nucleus
-
A component of the subcortical basal ganglia involved in motor control, learning, memory and other forms of cognition.
- Cholinesterase inhibitor
-
Or acetylcholinesterase inhibitor is a chemical substance that inhibits acetylcholinesterase enzyme from breaking down acetylcholine thereby increasing cholinergic transmission.
- Extrastriate visual cortex
-
Secondary visual cortex beyond the striate (stripped) cortex representing area 17 (containing primary visual cortex).
- fMRI
-
Functional magnetic resonance imaging, a non-invasive, in-vivo brain imaging technique.
- Fusiform gyrus
-
Part of the ventral visual cortex involved in object and face recognition.
- LGN
-
Lateral geniculate nucleus of the thalamus involved in visual processing with magno-, parvo- and koniocellular layers.
- Laminae I–VI
-
Six layers of the neocortex, where lamina I borders the pia mater and lamina VI the white matter.
- Mid-cingulate/paracingulate cortex
-
Parts of the cingular cortex in the medial neocortex.
- Nucleus accumbens
-
A dopaminergic structure in the midbrain thought to be involved in reward processing.
- Nucleus basalis
-
Nucleus basalis of Meynert: a group of neurons in the substantia innominate in the basal forebrain involved in cholinergic innervation of the cortex.
- Occipito-temporal cortex
-
Part of the ventral visual pathway at the junction between the occipital and temporal lobes.
- OC
-
Optic chiasma, a location in the brain where the optic nerves partially bifurcate.
- Physostigmin
-
A cholinesterase inhibitor that acts by interfering with the metabolism of acetylcholine.
- REM
-
Rapid-eye-movement sleep, a form of paradoxical sleep in which the person executes rapid eye movements during dream-like states.
- RSVP
-
Rapid serial presentation task, a visual task involving the presentation of a rapid sequence of images containing two or more targets that require a motor response from the participant.
- SN
-
Substantia nigra, a brain structure in the midbrain involved in motor control and reward processing.
- SWS
-
Slow-wave sleep, stage 3 to 4 of (deep) sleep that is associated of low frequency EEG delta waves.
- VBM
-
Voxel-based morphometry, a data analysis technique that determines statistical differences in grey and white matter voxel intensities. Used to measure cortical grey and white matter thickness.
- Ventral striatum
-
Part of the basal ganglia involving the nucleus accumbens, the olfactory tubercle, as well as the caudate nucleus and putamen.
- VTA
-
Ventral tegmentum area, a dopaminergic structure in the midbrain involved in dopaminergic innervation and control of attention.
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Greenlee, M.W. (2014). The Neuronal Base of Perceptual Learning and Skill Acquisition. In: Billett, S., Harteis, C., Gruber, H. (eds) International Handbook of Research in Professional and Practice-based Learning. Springer International Handbooks of Education. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8902-8_12
Download citation
DOI: https://doi.org/10.1007/978-94-017-8902-8_12
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-017-8901-1
Online ISBN: 978-94-017-8902-8
eBook Packages: Humanities, Social Sciences and LawEducation (R0)