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  1. Embed this notice
    Nicole Rust (nicolecrust@neuromatch.social)'s status on Wednesday, 31-Jan-2024 10:39:55 JST Nicole Rust Nicole Rust

    Thoughts on these provocative ideas (about how research in psychology should proceed)?

    The last author tipped me off to this one. Curious to hear impressions.

    Beyond Playing 20 Questions with Nature: Integrative Experiment Design in the Social and Behavioral Sciences

    https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4284943

    (also here, behind the BBS paywall: https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/abs/beyond-playing-20-questions-with-nature-integrative-experiment-design-in-the-social-and-behavioral-sciences/7E0D34D5AE2EFB9C0902414C23E0C292)

    The dominant paradigm of experiments in the social and behavioral sciences views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment’s specific conditions. According to this view, which Alan Newell once characterized as “playing twenty questions with nature,” theory is advanced one experiment at a time, and the integration of disparate findings is assumed to happen via the scientific publishing process. In this article, we argue that the process of integration is at best inefficient, and at worst it does not, in fact, occur. We further show that the challenge of integration cannot be adequately addressed by recently proposed reforms that focus on the reliability and replicability of individual findings, nor simply by conducting more or larger experiments. Rather, the problem arises from the imprecise nature of social and behavioral theories and, consequently, a lack of commensurability across experiments conducted under different conditions. Therefore, researchers must fundamentally rethink how they design experiments and how the experiments relate to theory. We specifically describe an alternative framework, integrative experiment design, which intrinsically promotes commensurability and continuous integration of knowledge. In this paradigm, researchers explicitly map the design space of possible experiments associated with a given research question, embracing many potentially relevant theories rather than focusing on just one. The researchers then iteratively generate theories and test them with experiments explicitly sampled from the design space, allowing results to be integrated across experiments. Given recent methodological and technological developments, we conclude that this approach is feasible and would generate more-reliable, more-cumulative empirical and theoretical knowledge than the current paradigm—and with far greater efficiency.

    In conversation about a year ago from neuromatch.social permalink

    Attachments


    • Embed this notice
      Nicole Rust (nicolecrust@neuromatch.social)'s status on Wednesday, 31-Jan-2024 10:39:48 JST Nicole Rust Nicole Rust
      in reply to
      • Ulrike Hahn
      • jonny (good kind)
      • Peter Moleman

      @MolemanPeter @UlrikeHahn @jonny
      My read is that the emerging evidence supports the brain at the edge of chaos hypothesis. For instance, it's the only regime where recurrent neural networks work. I summarize some of that work here:
      https://www.thetransmitter.org/systems-neuroscience/is-the-brain-uncontrollable-like-the-weather/

      In conversation about a year ago permalink

      Attachments

      1. Domain not in remote thumbnail source whitelist: www.thetransmitter.org
        Is the brain uncontrollable, like the weather?
        The brain may be chaotic. Does that mean our efforts to control it are doomed?
    • Embed this notice
      Peter Moleman (molemanpeter@neuromatch.social)'s status on Wednesday, 31-Jan-2024 10:39:49 JST Peter Moleman Peter Moleman
      in reply to
      • Ulrike Hahn
      • jonny (good kind)

      @NicoleCRust @UlrikeHahn @jonny
      @NicoleCRust
      Beggs started out to think the cortex works at the edge of chaos. But that appeared not to be tenable. Not for the cortex, but more so for processes at the subcortical level.
      Beggs JM (2022): The cortex and the critical point: understanding the power of emergence. Cambridge, Massachusetts, The MIT Press.

      In conversation about a year ago permalink
      Nitin Pai repeated this.
    • Embed this notice
      Nicole Rust (nicolecrust@neuromatch.social)'s status on Wednesday, 31-Jan-2024 10:39:50 JST Nicole Rust Nicole Rust
      in reply to
      • Ulrike Hahn
      • jonny (good kind)

      @UlrikeHahn @jonny
      Fascinating! I’m working to flesh out a good analogy for this line of thought. Are you thinking of something maybe chaotic, like the weather? Where small changes to initial conditions have inpredictable long term effects?

      The exceedingly simple logistic equation behaves in this way.
      https://en.m.wikipedia.org/wiki/Logistic_map
      In it’s chaotic regime, start it at 0.2 and it will do one thing; start it at 0.20000001 and it will do the same thing for awhile but diverge. If this simple equation does that, why not the brain?

      But the weather is chaotic and we’ve figured it out insofar as we have equations that can predict it in the near term and we understand why it’s chaotic. I think your point is along the lines of: the equivalent of the 7 equations for weather prediction will be harder to find for the brain. I’m trying to pinpoint: why might we think that, exactly? Because there are likely hundreds? Or they are of a different type?

      (No doubt we all agree that a good first step that needs to be made is acknowledging the brain is a dynamical system upfront. We haven’t tried much of that - how far will it take us?)

      In conversation about a year ago permalink

      Attachments

      1. Domain not in remote thumbnail source whitelist: upload.wikimedia.org
        Logistic map
        The logistic map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often referred to as an archetypal example of how complex, chaotic behaviour can arise from very simple nonlinear dynamical equations. The map was popularized in a 1976 paper by the biologist Robert May, in part as a discrete-time demographic model analogous to the logistic equation written down by Pierre François Verhulst. Mathematically, the logistic map is written where xn is a number between zero and one, which represents the ratio of existing population to the maximum possible population. This nonlinear difference equation is intended to capture two effects: reproduction, where the population will increase at a rate proportional to the current population when the population size is small, starvation (density-dependent mortality), where the growth rate will decrease at a rate proportional to the value obtained by taking the theoretical "carrying capacity" of the environment less the current population.The usual values of interest for the parameter r are those in the interval...
    • Embed this notice
      Ulrike Hahn (ulrikehahn@fediscience.org)'s status on Wednesday, 31-Jan-2024 10:39:52 JST Ulrike Hahn Ulrike Hahn
      in reply to
      • jonny (good kind)

      @NicoleCRust @jonny ? a better way to put this: I was a bit surprised by this paper given the authors because it slightly reads ‘piecemeal dustbowel empiricism didn’t work lets do dustbowl empiricism harder’. I take the fundamental problem of psych. to be the inherent flexibility of human responding. Change the context slightly, get a different response. So there’s gazillions of little paradigms that devolved into ‘it depends’. What we haven’t learned is what a meaningful theory is given that.

      In conversation about a year ago permalink
    • Embed this notice
      Ulrike Hahn (ulrikehahn@fediscience.org)'s status on Wednesday, 31-Jan-2024 10:39:53 JST Ulrike Hahn Ulrike Hahn
      in reply to
      • jonny (good kind)

      @NicoleCRust @jonny 2/2 that’s basically what the paper is saying though not in those words, and there is a sense in which that seems obviously right. The limitation I see is that I think the relevant “parameter space” for human behav. exp. is fundamentally not like the parameter space of my stylised ABM. I mostly do scenario based exp. - I can change experimental materials in infinite ways which are not ordered. We can’t chart this space in the way they envision - it’s all much much harder

      In conversation about a year ago permalink
    • Embed this notice
      Ulrike Hahn (ulrikehahn@fediscience.org)'s status on Wednesday, 31-Jan-2024 10:39:55 JST Ulrike Hahn Ulrike Hahn
      in reply to
      • jonny (good kind)

      @NicoleCRust @jonny my personal take is that this paper has an important point but not a solution, because the full scale of the problem is (to my mind) still not fully grasped. To explain: imagine you are trying to understand a little agent-based model you have. It’s a complex dynamical system, so you can’t just pick out a few random parameter combinations and form local theories and hope to come up with deep understanding. You need to systematically explore the parameter space 1/2

      In conversation about a year ago permalink

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