Evidence map›Paper›PMID 28812976›Full record

ArticleeLife2017

Learning and recognition of tactile temporal sequences by mice and humans.

Michael R Bale, Malamati Bitzidou, Anna Pitas, Leonie S Brebner, Lina Khazim, Stavros T Anagnou, Caitlin D Stevenson, Miguel Maravall

Abstract read
In one paragraph

Article in eLife, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Prediction of Choice from Competing Mechanosensory and Choice-Memory Cues during Active Tactile Decision Making.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019
    Article
  9. Review
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Michael R BaleSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.ORCID 0000-0002-5325-1992
Malamati BitzidouSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.ORCID 0000-0002-3726-9543
Anna PitasSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.
Leonie S BrebnerSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.ORCID 0000-0002-4540-2826
Lina KhazimSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.
Stavros T AnagnouSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.
Caitlin D StevensonSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.ORCID 0000-0003-4444-6402
Miguel MaravallSussex Neuroscience, School of Life Sciences, University of Sussex, Brighton, United Kingdom.ORCID 0000-0002-8869-7206

Funding

Medical Research Council MR/P006639/1
6 · The paper itself

Abstract

The world around us is replete with stimuli that unfold over time. When we hear an auditory stream like music or speech or scan a texture with our fingertip, physical features in the stimulus are concatenated in a particular order. This temporal patterning is critical to interpreting the stimulus. To explore the capacity of mice and humans to learn tactile sequences, we developed a task in which subjects had to recognise a continuous modulated noise sequence delivered to whiskers or fingertips, defined by its temporal patterning over hundreds of milliseconds. GO and NO-GO sequences differed only in that the order of their constituent noise modulation segments was temporally scrambled. Both mice and humans efficiently learned tactile sequences. Mouse sequence recognition depended on detecting transitions in noise amplitude; animals could base their decision on the earliest information available. Humans appeared to use additional cues, including the duration of noise modulation segments.

Indexed as

LearningPattern Recognition, PhysiologicalAcoustic StimulationAnimalsDecision MakingFingersHumansMiceTime FactorsVibrissaehead-fixedhumanmouseneurosciencesomatosensorystreamingtemporal codingvibrissaewhiskers

Identifiers

PMID28812976
PMCPMC5559268

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.