Components of Event-Related Potentials in studies of perceptual learning 101
Research assistant, Sirius University of Science and Technology, Moscow, Russia
PhD in Biology, Researcher, Sirius University of Science and Technology, Moscow, Russia
PhD in Psychology, Leading Researcher, Sirius University of Science and Technology, Moscow, Russia
Perceptual learning is defined by increased effectiveness of completing perceptual tasks as a result of experience or training. This review presents the analysis of changes in the components of event-related potentials (ERPs) after visual and auditory perceptual learning in humans. The use of the EEG method, which has a high temporal resolution, makes it possible to trace the spatio-temporal dynamics of changes in the functioning of the brain during learning, which remains hidden in behavioral experimental studies. A review of neurophysiological studies indicates that perceptual learning induces changes across all levels of cortical hierarchy, starting with the early sensory components of ERPs (C1) and ending with the later integrative components (N170, MMN, P2). We also analyzed the short-term and long-term effects of learning. The reviewed neurophysiological data can serve as the basis for the development of new approaches of effective learning, as well as for the objective evaluation of existing methodics by assessing neuronal dynamics at different stages of stimuli processing.
The reported study was funded by Russian Foundation for Basic Research (RFBR), project number 19-313-51039.
- Ivanitskii A. Sintez informatsii v klyuchevykh otdelakh kory kak osnova
sub"ektivnykh perezhivanii [Synthesis of information in key sections of the
cortex as the basis of subjective experiences]. Zhurnal vysshei nervnoi
deyatel'nosti = [Journal of Higher Nervous Activity], 1997. Vol. 47,
no. 2, pp. 209–225. (In Russ.).
- Rourke L. et al. A neural marker of medical visual expertise: implications
for training. Advances in Health Sciences Education, 2016. Vol. 21,
no. 5, pp. 953–966. DOI:10.1007/s10459-016-9712-7
- Alain C., Campeanu S., Tremblay K. Changes in Sensory Evoked Responses
Coincide with Rapid Improvement in Speech Identification Performance.
Journal of Cognitive Neuroscience, 2010. Vol. 22, no. 2,
pp. 392–403. DOI:10.1162/jocn.2009.21279
- Song Y. et al. An event-related potential study on perceptual learning in
grating orientation discrimination. NeuroReport, 2007. Vol. 18,
no. 9, pp. 945–948. DOI:10.1097/WNR.0b013e3281527795
- Atienza M., Cantero J.L., Dominguez-Marin E. The time course of neural
changes underlying auditory perceptual learning. Learning & Memory,
2002. Vol. 9, no. 3, pp. 138–150. DOI:10.1101/lm.46502
- Wisniewski M.G. et al. Auditory detection learning is accompanied by
plasticity in the auditory evoked potential. Neuroscience Letters, 2020.
Vol. 721, 5 p. DOI:10.1016/j.neulet.2020.134781
- Baumann S., Meyer M., Jäncke L. Enhancement of Auditory-evoked Potentials
in Musicians Reflects an Influence of Expertise but not Selective Attention.
Journal of Cognitive Neuroscience, 2008. Vol. 20, no. 12,
pp. 2238–2249. DOI:10.1162/jocn.2008.20157
- Bosnyak D.J., Eaton R.A., Roberts L.E. Distributed Auditory Cortical
Representations Are Modified When Non-musicians Are Trained at Pitch
Discrimination with 40 Hz Amplitude Modulated Tones. Cerebral Cortex,
2004. Vol. 14, no. 10, pp. 1088–1099.
- Busey T.A., Vanderkolk J.R. Behavioral and electrophysiological evidence
for configural processing in fingerprint experts. Vision Research, 2005.
Vol. 45, no. 4, pp. 431–448.
- Dering B., Hoshino N., Theirry G. N170 modulation is expertise driven:
evidence from word-inversion effects in speakers of different languages.
Future trends in the biology of language, 2013. 16 p.
- Opitz B. et al. Differential Contribution of Frontal and Temporal Cortices
to Auditory Change Detection: fMRI and ERP Results. NeuroImage, 2002.
Vol. 15, no. 1, pp. 167–174. DOI:10.1006/nimg.2001.0970
- Eimer M. The face-sensitive N170 component of the event-related brain
potential. In Calder A. [et al.] (eds.), The Oxford handbook of face
perception. OUP Oxford, 2011, pp. 329–344.
- Shahin A. et al. Enhancement of Neuroplastic P2 and N1c Auditory Evoked
Potentials in Musicians. The Journal of Neuroscience, 2003.
Vol. 23, no. 13, pp. 5545–5552.
- Zhang G.-L. et al. ERP C1 is top-down modulated by orientation perceptual
learning. Journal of Vision, 2015. Vol. 15, no. 10,
pp. 1–11 DOI:10.1167/15.10.8
- Orduña I. et al. Evoked-potential changes following discrimination learning
involving complex sounds. Clinical Neurophysiology, 2012. Vol. 123,
no. 4, pp. 711–719. DOI:10.1016/j.clinph.2011.08.019
- Gauthier I., Tarr M.J. Becoming a “Greeble” Expert: Exploring Mechanisms
for Face Recognition. Vision Research, 1997. Vol. 37, no. 12,
pp. 1673–1682. DOI:10.1016/S0042-6989(96)00286-6
- van Zuijen T.L. et al. Grouping of Sequential Sounds—An Event-Related
Potential Study Comparing Musicians and Nonmusician. Journal of Cognitive
Neuroscience, 2004. Vol. 16, no. 2, pp. 331–338.
- Gottselig J.M. et al. Human Central Auditory Plasticity Associated With
Tone Sequence Learning. Learning & Memory, 2004. Vol. 11,
no. 2, pp. 162–171. DOI:10.1101/lm.63304
- Irvine D.R.F. et al. Irvine D.R.F. Auditory perceptual learning and
changes in the conceptualization of auditory cortex. Hearing Research,
2018. Vol. 366, pp. 3–16. DOI:10.1016/j.heares.2018.03.011
- Tremblay K.L. et al. Is the auditory evoked P2 response a biomarker of
learning? Frontiers in Systems Neuroscience, 2014. Vol. 8,
article ID 28, 13 p. DOI:10.3389/fnsys.2014.00028
- Koelsch S., Schröger E., Tervaniemi M. Superior pre-attentive auditory
processing in musicians. Neuroreport, 1999. Vol. 10, no. 6,
pp. 1309–1313. DOI:10.1097/00001756-199904260-00029
- Kuriki S., Kanda S., Hirata Y. Effects of Musical Experience on Different
Components of MEG Responses Elicited by Sequential Piano-Tones and Chords.
Journal of Neuroscience, 2006. Vol. 26, no. 15,
pp. 4046–4053. DOI:10.1523/JNEUROSCI.3907-05.2006
- Lütkenhöner B., Seither-Preisler A., Seither S. Piano tones evoke stronger
magnetic fields than pure tones or noise, both in musicians and non-musicians.
NeuroImage, 2006. Vol. 30, no. 3, pp. 927–937.
- Mankel K., Bidelman G.M. Inherent auditory skills rather than formal music
training shape the neural encoding of speech. Proceedings of the National
Academy of Sciences, 2018. Vol. 115, no. 51,
pp. 13129–13134. DOI:10.1073/pnas.1811793115
- Maurer U., Brandeis D., McCandliss B.D. Fast, visual specialization for
reading in English revealed by the topography of the N170 ERP response.
Behavioral and Brain Functions, 2005. Vol. 1, no. 13. 12 p.
- Shahin A. et al. Modulation of P2 auditory-evoked responses by the spectral
complexity of musical sounds. NeuroReport, 2005. Vol. 16,
no. 16, pp. 1781–1785. DOI:10.1097/01.wnr.0000185017.29316.63
- Fujioka T. et al. Musical Training Enhances Automatic Encoding of Melodic
Contour and Interval Structure. Journal of Cognitive Neuroscience, 2004.
Vol. 16, no. 6, pp. 1010–1021. DOI:10.1162/0898929041502706
- Kühnis J. et al. Musicianship boosts perceptual learning of
pseudoword-chimeras: an electrophysiological approach. Brain Topography,
2013. Vol. 26, no. 1, pp. 110–125.
- Virtala P. et al. Musicianship facilitates the processing of Western music
chords—An ERP and behavioral study. Neuropsychologia, 2014.
Vol. 61, pp. 247–258. DOI:10.1016/j.neuropsychologia.2014.06.028
- Nikjeh D.A., Lister J.J., Frisch S.A. Preattentive Cortical-Evoked
Responses to Pure Tones, Harmonic Tones, and Speech: Influence of Music
Training. Ear and Hearing, 2009. Vol. 30, no. 4,
pp. 432–446. DOI:10.1097/AUD.0b013e3181a61bf2
- Civile C. et al. Perceptual learning and inversion effects: Recognition of
prototype-defined familiar checkerboards. Journal of Experimental
Psychology: Animal Learning and Cognition, 2014. Vol. 40, no. 2,
pp. 144–161. DOI:10.1037/xan0000013
- Wu D. et al. Perceptual Learning at Higher Trained Cutoff Spatial
Frequencies Induces Larger Visual Improvements. Frontiers in Psychology,
2020. Vol. 11, article ID 265, 9 p.
- Bao M. et al. Perceptual Learning Increases the Strength of the Earliest
Signals in Visual Cortex. Journal of Neuroscience, 2010. Vol. 30,
no. 45, pp. 15080–15084. DOI:10.1523/JNEUROSCI.5703-09.2010
- Ahmadi M. et al. Perceptual learning induces changes in early and late
visual evoked potentials. Vision Research, 2018. Vol. 152,
pp. 101–109. DOI:10.1016/j.visres.2017.08.008
- Reinke K.S. et al. Perceptual learning modulates sensory evoked response
during vowel segregation. Cognitive Brain Research, 2003. Vol. 17,
no. 3, pp. 781–791. DOI:10.1016/S0926-6410(03)00202-7
- Qu Z., Song Y., Ding Y. ERP evidence for distinct mechanisms of fast and
slow visual perceptual learning. Neuropsychologia, 2010. Vol. 48,
no. 6, pp. 1869–1874. DOI:10.1016/j.neuropsychologia.2010.01.008
- Ritter W., Simson R., Vaughan Jr H.G. Event-Related Potential
Correlates of Two Stages of Information Processing in Physical and Semantic
Discrimination Tasks. Psychophysiology, 1983. Vol. 20, no. 2,
pp. 168–179. DOI:10.1111/j.1469-8986.1983.tb03283.x
- Rossion B., Curran T., Gauthier I. A defense of the subordinate-level
expertise account for the N170 component. Cognition, 2002. Vol. 85,
no. 2, pp. 189–196. DOI:10.1016/S0010-0277(02)00101-4
- Sheehan K.A., McArthur G.M., Bishop D.V.M. Is discrimination training
necessary to cause changes in the P2 auditory event-related brain potential to
speech sounds? Cognitive Brain Research, 2005. Vol. 25, no. 2,
pp. 547–553. DOI:10.1016/j.cogbrainres.2005.08.007
- Shiu L., Pashler H. Improvement in line orientation discrimination is
retinally local but dependent on cognitive set. Perception &
Psychophysics, 1992. Vol. 52, no. 5, pp. 582–588.
- Alain C. et al. Sleep-dependent neuroplastic changes during auditory
perceptual learning. Neurobiology of Learning and Memory, 2015.
Vol. 118, pp. 133–142. DOI:10.1016/j.nlm.2014.12.001
- Ding Y. et al. Specificity and generalization of visual perceptual learning
in humans: an event-related potential study. NeuroReport, 2003.
Vol. 14, no. 4, pp. 587–590.
- Schneider P. et al. Structural and functional asymmetry of lateral Heschl’s
gyrus reflects pitch perception preference. Nature neuroscience, 2005.
Vol. 8, no. 9, pp. 1241–1247. DOI:10.1038/nn1530
- Su J., Tan Q., Fang F. Neural correlates of face gender discrimination
learning. Experimental brain research, 2013. Vol. 225, no. 4,
pp. 569–578. DOI:10.1007/s00221-012-3396-x
- Tanaka J. W., Curran T. A Neural Basis for Expert Object Recognition.
Psychological Science, 2001. Vol. 12, no. 1, pp. 43–47.
- Fort A. et al. Task-dependent activation latency in human visual
extrastriate cortex. Neuroscience Letters, 2005. Vol. 379,
no. 2, pp. 144–148. DOI:10.1016/j.neulet.2004.12.076
- Kühnis J. et al. The encoding of vowels and temporal speech cues in the
auditory cortex of professional musicians: An EEG study.
Neuropsychologia, 2013. Vol. 51, no. 8, pp. 1608–1618.
- Rossion B. et al. The N170 occipito-temporal component is delayed and
enhanced to inverted faces but not to inverted objects: an electrophysiological
account of face-specific processes in the human brain [Elektronnyi resurs].
Neuroreport, 2000. Vol. 11, no. 1, pp. 69–72. URL:
- Tong Y., Melara R.D., Rao A. P2 enhancement from auditory discrimination
training is associated with improved reaction times. Brain Research,
2009. Vol. 1297, pp. 80–88. DOI:10.1016/j.brainres.2009.07.089
- Doniger G.M. et al. Visual Perceptual Learning in Human Object Recognition
Areas: A Repetition Priming Study Using High-Density Electrical Mapping.
NeuroImage, 2001. Vol. 13, no. 2, pp. 305–313.
- Yin R.K. Looking at upside-down faces. Journal of Experimental
Psychology, 1969. Vol. 81, no. 1, pp. 141–145.