Do Markov Blankets Give Us Real Neural Parts?

In my last post, I laid out what I think the rules are for developing a mechanistic model of the neural scale contribution to behaviour. I ended there with a question: what counts as a real neural part? How can we successfully decompose neural activity supporting a given perception-action loop into parts? 

In this post, I want to discuss one potential option: the hypothesis that Markov blankets, a key feature of the free-energy principle approach to neuroscience, can identify and pick out real neural parts. I'll discuss some recent ecological critiques of Markov blankets and some potential answers to the challenges.

Mechanisms for Cognitive and Behavioural Science (#MechanismWeek 5)

This week we have reviewed what a mechanism is, various ways to model mechanisms, and talked about the kinds of functional and dynamical models cognitive science currently relies on. We then rejected the argument that cognitive science cannot have causal mechanistic models that refer to real parts and processes. We claim that if we ground our models at the ecological level of perceptual information, a truly mechanistic analysis is possible, and we walked through a causal mechanistic model of a perception-action task as proof of concept for our claims. Sabrina then presented these ideas this week at a mechanism conference in Warsaw to an audience that included Bechtel and Craver (with great success, hurray! :)

The message we want you to go home with after #MechanismWeek is this:

Despite the fact that psychology has been trucking on very-nicely-thank-you developing various kinds of functional models, these remain extremely limited in their explanatory scope and they are not moving us towards explanatory mechanistic models. We have demonstrated that explanatory, causal mechanistic modelling of cognitive and behavioural systems is possible, so long as that analysis is grounded at the level of ecological information. These models are powerful scientific tools for exploring and understanding the behaviour of systems, and if we can get them, we should definitely be trying to. 

The research programme for getting mechanistic models is that laid out in Bechtel & Abrahamsen (2010) who used the development of mechanistic models of circadian rhythms as an exemplar for cognitive science. That programme involves spending time empirically decomposing and localising the real parts and processes of that actual mechanism. This requires going into the mechanism at a useful level of analysis; if you are struggling to find real parts and processes, you might be working at the wrong level. Only once you know the composition and organisation of the mechanism do you try to model it, typically using dynamical equations containing terms serving as representations of each component, placed in the appropriate relation to one another.

We have risen to their challenge by identifying the ecological level of analysis as the correct place to ground our work, and by identifying a cognitive science model that parallels the biological exemplar. It is our hope that this work will help others move in the direction of mechanistic research and modelling in the cognitive and behavioural sciences, so that we all gain the many benefits of causal mechanistic explanations.

This work will form the centre piece of a large scale paper we are currently writing. We've posted this part of the work on the blog in part to stake a claim to this analysis, but also to try and garner useful feedback from interested parties. If you have questions, comments or feedback, please contact us by commenting on any relevant post (we'll see it, even if it's on an older post), emailing us or finding us on Twitter. 

Thanks for reading along with us! We hope you enjoyed #MechanismWeek :)

Mechanisms and Models of Mechanisms (#MechanismWeek 1)

In this first #MechanismWeek post, I will define a mechanism and briefly describe the kind of models of mechanisms you can build. I begin with various kinds of functional models (Cummins, 1975, 2001; Weiskopf, 2011). These either break capacities of systems into more coherent, easily studied sub-capacities (think of breaking memory into long term memory and short term memory as a simple example) or model them with components that may or may not be really implemented in the organism (e.g. geons, exemplars).

I will then introduce the idea of a dynamic causal mechanistic model (Bechtel & Abrahamsen, 2010) which attempt to map model components directly onto the real parts and processes of the mechanism at hand. The argument is that while functional models provide useful descriptions of mechanisms, they do not provide an explanation of that mechanism, and that only mechanistic models can explain.

Tasks from the First Person Perspective (A Purple Peril)

The great snare of the psychologist is the confusion of his own standpoint with that of the mental fact about which he is making his report. I shall hereafter call this the ‘psychologist’s fallacy’ par excellence.

William James, The Principles of Psychology

This is a video of a baby trying bacon for the first time. The baby gets really really excited, and everyone around him goes 'Ha! Babies love bacon as much as the rest of us, this is great!'. And everyone laughs and cheers.

Except here's the thing. I think what this baby really likes is making his loved ones laugh and cheer. The bacon is fine, but I don't think it's the magical experience his parents assume. They are making the psychologist's fallacy: mistaking what you think is going on for what the person is actually experiencing. (It's our fallacy because our subject matter makes us uniquely susceptible.)

When people come into our labs to take part in experiments, we present them with a situation that we have designed to elicit a specific behaviour from them, and that we manipulate in various ways in order to probe the makeup of that behaviour. We therefore think we know what the person is doing: they are doing the thing we asked them to do. However, this isn't necessarily true, and in order to figure out what our participants did and why, we need to consider how they experienced the experiment. In effect, doing our science right means taking the first person perspective of our participants when we formulate our explanations. 

I take this idea primarily from Louise Barrett's excellent book, Beyond the Brain: How Body & Environment Shape Animal and Human Minds (which I reviewed here). The first couple of chapters spend a lot of time talking about anthropomorphism, and why it's a problem. To be honest, when I read the book I didn't quite know why Louise started with this. But over time, I've realised what an extraordinarily powerful point it is and we now talk about all the time. 

Peril Proposal: The psychologist's fallacy is real, but the ecological approach to understanding task dynamics and the information they create offers a useful framework for avoiding it while we science.

Dynamic Mechanistic Explanations in Radical Embodied Cognitive Science

I'm on my way back from an enactivist/embodiment conference in Warsaw. I gave a talk (slides) in which I argued that in order to make theories of distributed/embodied cognition work, you have to have something like a theory of ecological information as the glue to hold it all together. All the talks I saw that discussed any kind of plan for distributing cognition were missing this piece and desperately needed it, so I'm hoping the talk will make people realise this tool exists and can help. Drop me a line if you would like any help!

I argued specifically that information lets us propose mechanistic explanations for distributed cognitive systems. We recently came across the philosophical literature on what mechanisms are and how to make them, and it seemed immediately clear that we should be doing this (and that we already are; see below). 

It turns out, though, that some of the radical camp (specifically Chemero and Silberstein) don't think we can have distributed cognition mechanisms, but that this is ok because we still get explanations out of our dynamical models. 

This post will briefly review what dynamic mechanistic explanation is and why they are so useful (Bechtel & Abrahamsen, 2010). I'll briefly summarise the radical opposition to mechanisms, point out their answer doesn't work, then talk an example that shows we can have radical dynamic mechanistic explanatory models without giving anything up. The trick, as ever, will be to rely heavily on information as the component part that allows cognitive mechanisms to extend out over body and environment. 

Embodying Culture: My ongoing conversation with Soliman & Glenberg

Would a formal reply make me this guy?

I've been exchanging views with Art Glenberg and his colleagues about a paper he published recently in Frontiers. I reviewed it, had reservations but eventually let it through, then published my concerns as a commentary on the original paper. Soliman and Glenberg (2014; S&G) then replied to my reply which I didn't know about until I noticed the commentary had a citation in my Google Scholar profile. 

I could simply publish a reply to their reply, but to be honest I'm not sure it's worth it; it feels a little too much like arguing on the internet. I'll link to this in the comments section of the Frontiers page, however, and if people think it's worth the DOI then I'll write this reply up as a formal submission. I'd be interested to hear from you all on this.

The short version of my reply is that in the process of dodging my criticism they concede it applies to them, and they swerve into a literature that doesn't help. I do think they've applied some serious and valuable consideration to the details of their proposal, though, so I think this has been a useful process.

Connecting the conceptual dots in embodied cognition

UPDATE 9 June 2015: We published this critique. 

Around about the time we published our embodied cognition paper, we also reviewed a paper for that research topic, which happened to be an example of the conceptualisation hypothesis  style of 'embodied' cognition we aren't all that impressed by.

We had serious reservations about the paper (detailed below) and did not think it should be published. After several rounds of trying and failing to get the authors to acknowledge the problem, we withdrew from the review and the editor, Dermot Lynott then decided to side with the other reviewers (who had identified the same problem we had but who didn't think it was a fatal flaw). The paper (Dijkstra, Eerland, Zijlmans & Post, 2012) was therefore published.

A while back I drafted a commentary laying out the problems with this paper; the full text is here. The motivation for a comment was the same as for the one I wrote for Soliman et al (2014); this style of embodiment does not tackle the hard questions about mechanism that are crucial for an embodied account and this is a big problem. I cannot decide if the commentary is worth publishing; this paper is not that important, although it is a good example of this major issue for 'grounded' embodied cognition. Any thoughts on this would be welcome.

Does action scaling predict 'the embodiment of culture'? (No.)

I recently reviewed a paper for Frontiers by Arthur Glenberg and colleagues called 'Sensory motor mechanisms unify psychology: the embodiment of culture' (Soliman, Gibson & Glenberg, 2014). This is part of an ongoing research topic on embodied cognition run by Guy Dove. Once the paper had been published, I took the opportunity to write up my main remaining problem with the paper as a commentary piece (Wilson, 2014) and I'd like to review that here (and also please see my comment at the end about my role here as reviewer). Go download the paper, though, I worked hard to produce a focused critique in the 1000 word limit and I think it went well.

Glenberg and colleagues are trying to develop a broad embodied framework that can encompass both traditional hunting grounds like perception and action but also 'higher order' cognition like social cognition and culture. I admire the effort but to my mind this is grounded cognition, not embodied and so this is not an approach I'd endorse. I like to review papers like this though because it's healthy to have an adversarial reviewer who tries not to be evil (I promise!), and because I also like to keep myself informed about the work I'm rejecting so that I don't start fighting straw men.