Tom Stafford

@tomstafford

Cognitive Scientist at the University of Sheffield, UK - - - Research: - - - Writing:

Sheffield, United Kingdom
idiolect.org.uk
Joined January 2008
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  1. Pinned Tweet
    1 Jul 2015

    For argument's sake: evidence that reason can change minds my essays on the power of argument, OUT NOW as an ebook!

    10 replies 56 retweets 202 likes
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  2. Retweeted
    Jul 12

    Looking for a lovely talented person to come and do a PhD with us :) Could you spread the word?

    2 replies 26 retweets 11 likes
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  3. Jul 12

    Complex Human Data Summer School Melbourne, Australia. December 15-20, 2019. Awesome programme. Apply:

    2 retweets 4 likes
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  4. Jul 11

    Thread

    Smart, honest, experienced researchers produce massively varied, and often unreliable, analyses of data from a basic memory paradigm. Yikes!
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  5. Jul 11

    Update, co-author Nathan Evans is on Twitter :

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  6. Jul 11

    cc

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  7. Jul 11

    They cite Logan's instance theory for the concurrent emergence hypothesis, but I don't know enough about instance theory. Can you comment if that's fair ?

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  8. Jul 11

    Also related: Bebko et al (2005) which argues against the controlled-automatic continuum and in favour of a "concurrent emergence hypothesis" (i.e. habit *and* flexibility).

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  9. Jul 11

    Related: Automatic behaviour: Efficient not mindless Saling & Phillips (2007)

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  10. Jul 11

    "chunks, which are supposed to enjoy the most extreme automatization, appear to save little or no time overall (the time savings problem)"

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  11. Jul 11

    "the proportion of actions within a chunks is stable across expertise and expert sequences are generally more varied" (ie chunking and flexibility co-exist)

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  12. Jul 11

    Using data from 3,330 StarCraft 2 players, and showing that, although chunking definitely occurs during skill acquisition, chunking is more than mere automatisation (i.e. speeding of habits at the cost of flexibility)

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  13. Jul 11

    Classic motor chunking theory fails to account for behavioural diversity and speed in a complex naturalistic task new from Joseph J. Thompson and colleagues, in PlosOne

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  14. Jul 11

    Related: Evidence Accumulation Models: Current Limitations and Future Directions new preprint from Nathan Evans &

    2 replies 2 retweets 5 likes
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  15. Jul 11

    (e.g. some other process could be changing which isn't captured by the model but which the model best fits by adjusting the sensitivity parameter)

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  16. Jul 11

    Caveat #2: In a sense the model fitting only arbitrates between two possibilities: changes in response bias and/or sensory sensitivity. The model says the data are better fit by an increased sensitivity, but what that means in the mind/brain is less clear

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  17. Jul 11

    Caveat: Fitting decision models isn't a precise science, so interpretation of them should be correspondingly cautious (see today's earlier thread )

    Assessing theoretical conclusions with blinded inference to investigate a potential inference crisis in press at Advances in Methods and Practices in Psychological Science , from Jeffrey Starns and many collaborators
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  18. Jul 11

    Data and analysis scripts available at the OSF project page (using the German servers for data storage - righteous!)

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  19. Jul 11

    This a) puts our social lives at the heart of our perceptual-cognitive machinery b) connects social and perceptual decision making via reinforcement learning theory

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  20. Jul 11

    But that's not what they found. Instead the sensitivity/drift rate was affected. What the Germar & Mojzisch result suggests is that learning what other people believe actually changes what you *perceive*.

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  21. Jul 11

    The decision model they use already has a term to capture response bias - if other people's responses alter participant decisions they should - you'd expect - affect this parameter.

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