Bayesian just-so stories in psychology and neuroscience.

By Jeffrey S. Bowers, Colin J. Davis. 2012

405 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology

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In Cognitive Neuroscience

In Developmental and Educational Psychology

Citations in the corpus

Assessing the Role of the ‘Unity Assumption’ on Multisensory Integration: A Review (2017, background): “Some, for instance, have argued that Bayesian models simply re-express the cognitive model in mathematical language (see Murphy, 1993; Jones and Love, 2011; Bowers and Davis, 2012).”
From cognitivism to autopoiesis: towards a computational framework for the embodied mind (2016, background): “…(interoceptive or otherwise) are subject to a variety of critiques; which charge for example that they constitute circular/tautological reasoning (Bowers and Davis 2012), are unfalsiﬁable (Wiese 2014), and are merely convenient post-hoc or ‘just-so’ explanations (see Jones and Love 2011 for…”
A Bayesian observer model constrained by efficient coding can explain 'anti-Bayesian' percepts (2015, background): “By rewriting equation (14) in terms of this expansion, we find that”
Grandmother cells and localist representations: a review of current thinking (2017, background): “…psychology are often further removed from neuroscience, as these theories tend to be developed at a computational level of analysis that specify the goals and problems that people face with little consideration algorithmic, let alone the neural, underpinnings of behaviour (Bowers & Davis, 2012).”
Probabilistic brains: knowns and unknowns (2013, background): “Experimentally, this is a potential pitfall of the probabilistic approach: many data sets can be used to support the claim that humans are optimal, as long as one uses the appropriate cost function (or prior distribution) 85 .”
Troubles with Bayesianism: An introduction to the psychological immune system (2018, background): “For critiques of Bayesianism because of its connection to optimality, see Jones & Love, 2011; Elqayam & Evans, 2011; Bowers & Davis, 2012.”
Noise as a Resource for Computation and Learning in Networks of Spiking Neurons (2014, background): “[75] J. S. Bowers and C. J. Davis, ‘‘Bayesian just-so stories in psychology and neuroscience,’’ Psychol.”
Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic (2015, background): “There are several interesting features of this program — not least that there is no stopping criterion, which would concern critics of rational models (Bowers & Davis, 2012; Jones & Love, 2011) — but our focus here will be on Step 3.”