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One of the much documented problems of Bayesian approaches to cognitive modeling is that there isn't much of a neural grounding. The NEF can be used to compute probabilistic computations with ease (see Chapter 9 of Neural Engineering), however have this been used in a published model before? Are there drawbacks that make merging the NEF with Bayesian modelling methods unfeasible in terms of resources required?

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    $\begingroup$ @chistiaan I would disagree, because it's still focused on neural approaches that only people on this site know and understand. It also takes into account biological plausibility and cognitive utility which aren't topics of CrossValidated. $\endgroup$ – Seanny123 Jun 1 '16 at 18:52
  • $\begingroup$ That's OK. Close-vote removed. It's just never going to be answered I'm afraid. Asking this on other, bigger sites grossly improves the chance of at least getting some feedback. $\endgroup$ – AliceD Jun 1 '16 at 19:01
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    $\begingroup$ It's an active area of research of my labmate, so it'll definitely be answered in a year or she isn't going to graduate $\endgroup$ – Seanny123 Jun 1 '16 at 19:02
  • $\begingroup$ I mean on this site. Then you can answer yourself. $\endgroup$ – AliceD Jun 1 '16 at 19:02

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