Lecture 4: Simulative, Projective, and Locality Assumptions (Turvey, 2019, Lectures on Perception)

This lecture is a brief history of the common assumptions made in theories of perception about how things 'over there' can cause us to have a given perceptual experience. The simulative and projective elements can be quickly dealt with; the big claim in this lecture is that the right notion of causation for perception is non-local, as it is in quantum mechanics. (Note: Turvey is not saying perception is a quantum process. He's just going to use it as a framing to explain what non-local causation is, and he will rely on the rigorous empirical testing it has passed in physics to say it is a viable notion of causation for a physical system.)

Lecture 3: Direct Perceiving, Indirect Perceiving (Turvey, 2019, Lectures on Perception)

In this lecture, Turvey provides a formal definition of what it means to claim a theory of perception is direct vs indirect. A theory of direct perception invokes lawfully specifying information, while all indirect theories invoke at least one mediating physiological or psychological process. Direct theories are allowed to discuss internal states, etc (Gibsonian neuroscience isn't a contradiction in terms), but these states are not allowed to alter information so it is no longer lawfully related to the environment. The big Turvey word we will learn about in this chapter is impredicative entailment - exciting! I'll also briefly point to some implications this chapter has for my recent papers with Sabrina on neuroscience and mechanism.

Lecture 2: Organism-Environment Dualism (Turvey, 2019, Lectures on Perception)

In this Lecture, Turvey lays out the organism-environment dualism that lies at the heart of pretty much all attempts to answer the question, how can an organism come to know about it's environment via perception? He discusses Descartes' mechanistic (mechanical) approach, and then pivots back to the idea that Composition, Environment, Structures (CES) systems are the only approach that can possibly cope with the nature of the problem. 

Lecture 1: What Kind of Systems Do We Study? (Turvey, 2019, Lectures on Perception)

The first thing to do is to characterise what it is we are studying when we are studying perception. Turvey states we are studying epistemic, intentional systems and spends this chapter explaining each term. He does the most work on system; intentional and epistemic are primarily just defined and noted as being features of the system we are going to have to engage with. 

As usual, I will try to efficiently review the key points and then add some reflections on what the chapter made me think about. 

Reading Group: Turvey (2019), Lectures on Perception

Michael Turvey runs a famously intense graduate level class on perception and action at CESPA. He has recently, finally, published a book of his lectures, in which he basically develops the ecological approach to perception-action from first principles. I've been reading the lectures in small bites (each one is a good 20 minute read to go through), but I've now been invited to a Zoom reading group with Noah Guzmán and Peter Zatka-Haas. This is awesome, as it's an excuse to do the next thing I wanted to do, which is to go back through the lectures in detail (20 minutes to read, a lifetime to digest!). 

This will take a while, but I plan to develop a series of posts, one lecture at a time, similar to what I've done with Chemero (2009) and what Sabrina has done with Gibson (1979) (see The Rough Guide for links). In each post, I will attempt to (concisely) summarise the key points from the lecture. At the end, I will reflect on what I've learned from the lecture, and connect it to issues in the literature. 

Turvey is a genuine gift to science, and these lectures are kind of amazing. Allons-y!

Links to posts

Lecture 1: What Kind of Systems Do We Study?

Lecture 2: Organism-Environment Dualism

Lecture 3: Direct Perceiving, Indirect Perceiving

Transfer of Learning a Novel Coordinated Rhythmic Movement

My PhD student Daniel Leach has just had his first paper accepted (preregistration, preprint, data & analysis files available here on the OSF) so it's way past time when I should blog this cool work. Danny and I have been developing methods, analyses and a theoretical framework to study learning and transfer of learning, and we have some interesting results (plus MANY more questions :) This post is about the first experiment just published; there's more to come!

We use coordinated rhythmic movement as our task; I've blogged this task in many posts and used this research programme as an example of theoretically driven, mechanistic modelling science. The basic form of the task is described here, the basic pattern of behavioural data is described here, and the model that implements our perception-action approach is described here. The main thing to know is that there are only a couple of rhythmic coordinations that are easy without training (0° and 180°), but other coordinations can be learned with feedback driven training. This gives us a simple model task that can serve as a window on perception-action mechanisms of skilled action and learning. 

The Task Dynamics of Angiogenesis

In the last two posts, I have laid out the proposal that endothelial cells seem to actively perceive their environments, and set out the details of the argument in favour of explicitly taking an ecological approach to understanding why they do what they do during angiogenesis. It's now time to develop that analysis more explicitly.

To do this, I will apply the 4 questions we proposed in Wilson & Golonka (2013) to the question of the endothelial cell behaviour.  These are

1. What is the task to be solved? 
2. What are the resources the organism has access to that might solve the task?
3. How might these resources get assembled so as to solve the task?
4. Do organisms actually do what you describe in Q3?

We gave some worked examples of this analysis in the 2013 paper, and have described how it drives my work on coordinated rhythmic movement (Golonka & Wilson, 2012, 2019). This will hopefully serve as another example.