John Morrison

I am currently working on two projects. The first is an attempt to understand the brain from an abstract perspective. Physics and economics provide helpful models of what I'm aiming for. When trying to understand a thermodynamic system, it’s often better to abstract away from the activities of individual molecules, and instead focus on more global features, such as pressure and temperature. When trying to understand an economic system, it’s often better to abstract away from the activities of individual consumers, and instead focus on more global features, such as inflation and gross domestic product. Likewise, when trying to understand brains, it’s often useful to abstract away from activities of individual neurons, and instead focus on more global features, such as representation and inference. This is particularly true when trying to understand how our brains enable us to successfully interact with our environment. Unfortunately, whereas we have precise and uniform definitions of pressure, temperature, inflation, and gross domestic product, there are no widely accepted definitions of representation and inference. Perhaps as a result, it is far less clear how to map representations and inferences onto brain activity. It is also far less clear what neuroscientists mean when they use these terms, because they often use them in loose and contradictory ways. The overall goal of this project is to develop a useful and precise framework for attributing representations and inferences to the brain, especially when they involve probabilities.

This project builds on past research on conscious perception. In one line of research, I argued that our conscious perceptions involve probabilities. I called this view Perceptual Confidence. I am now expanding my focus to include unconscious neural representations and the probabilistic inferences that rely on them. In another line of research, I argued that our conscious perceptions of color properties, such as redness, depend on our representations of the differences and similarities between objects, thereby reversing the traditional order of explanation. I called this view Perceptual Structuralism. I am now expanding my focus to include unconscious neural representations of other properties, such as orientation. In a new strand of research, I am trying to assess the extent to which artificial networks shed light on our own representations and inferences.

The second project is about the foundations of Spinoza's metaphysics. It's an attempt to unravel his claims about minds, bodies, God, and their essences. In past research, I argued for new interpretations of Spinoza's basic notions, namely causation, conception, and inherence. I also argued that Spinoza would reject the Indiscernibility of Identicals in response to a puzzle of identity over time, and that this is the key to understanding his view of the mind's relation to the body. I am now trying to understand his view of essences.