OK. I've started and stopped a paper on metacognition, self-inference, and expected precision about a dozen times. I just feel conflicted about the nature of these papers and want to make a very circumspect argument without too much hype.
As everyone notes, we have way too many 'bayes glaze' review papers in glam mags making a bunch of claims for which there is no clear relationship to data or actual computational mechanisms.
It has gotten so bad, I sometimes see papers or talks where it feels like they took totally unrelated slides and plastered "prediction" or "prediction error" in random places.
This is unfortunate, and it's largely driven by the fact that these shallow reviews generate a bonkers amount of citations. It is a land rush to publish the same story over and over again just changing the topic labels.
I know people are excited about predictive processing, and I totally share that. And there is really excellent theoretical work being done. But there is also a lot of cynical stuff, and I worry that this speaks so much more loudly than the good, careful stuff.
In the past my theoretical papers in this area have been super dense and frankly a bit confusing in some aspects. I just wanted to try and really, really do due dilligence and not overstate my case.
But I do have some very specific theoretical proposals that I think are unique. I'm not sure why i'm all sharing this, but I think because it is always useful to remind people that we feel imposter syndrome and conflict at all career levels.
Specifically, I have some fairly straightforward ideas about how interoception and neural gain (precision) inter-relate, and also have a model i've been working on for years about how metacognition relates to expected precision.
I'm going to force myself to finally write these. I don't really care where they are published, it doesn't need to be a glamour review journal. I think I will probably preprint them on my blog, although not sure this is a good idea for purely theoretical work.
Further, I will try and hold to three key promises:
1) keep it simple. 1 key hypothesis/proposal per paper. Nothing grandiose.
2) specific, falsifiable predictions about behavioral & neurophysiological phenomenon, with no hand-waving
3) consider alternative models/views
1) keep it simple. 1 key hypothesis/proposal per paper. Nothing grandiose.
2) specific, falsifiable predictions about behavioral & neurophysiological phenomenon, with no hand-waving
3) consider alternative models/views
These papers *won't* be explicitly computational - although we have that under preparation as well - but will just try to make a single key point that I want to build on.
That is the idea. Now I need to go lock myself in a cabin for a few weeks and finally get these papers off my plate as they've been burning in my head for years. Where to submit them?
