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  Long-term implicit memory for sequential auditory patterns in humans

Bianco, R., Harrison, P. M. C., Hu, M., Bolger, C., Picken, S., Pearce, M. T., et al. (2020). Long-term implicit memory for sequential auditory patterns in humans. eLife. doi:10.7554/eLife.56073.

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 Creators:
Bianco , Roberta1, Author
Harrison, Peter M. C.2, Author           
Hu, Mingyue1, Author
Bolger, Cora1, Author
Picken, Samantha1, Author
Pearce, Marcus T2, 3, Author
Chait, Maria1, Author
Affiliations:
1UCL Ear Institute, University College London, London, United Kingdom, ou_persistent22              
2School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom, ou_persistent22              
3Department of Clinical Medicine, Aarhus University, Denmark, ou_persistent22              

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 Abstract: Memory, on multiple timescales, is critical to our ability to discover the structure of our surroundings, and efficiently interact with the environment. We combined behavioural manipulation and modelling to investigate the dynamics of memory formation for rarely reoccurring acoustic patterns. In a series of experiments, participants detected the emergence of regularly repeating patterns within rapid tone-pip sequences. Unbeknownst to them, a few patterns reoccurred every ~3 min. All sequences consisted of the same 20 frequencies and were distinguishable only by the order of tone-pips. Despite this, reoccurring patterns were associated with a rapidly growing detection-time advantage over novel patterns. This effect was implicit, robust to interference, and persisted for 7 weeks. The results implicate an interplay between short (a few seconds) and long-term (over many minutes) integration in memory formation and demonstrate the remarkable sensitivity of the human auditory system to sporadically reoccurring structure within the acoustic environment.

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Language(s): eng - English
 Dates: 2020-05-18
 Publication Status: Published online
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.7554/eLife.56073
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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X