Russ and I discuss cognitive ontologies – the “parts” of the mind and their relations – as an ongoing dilemma of how to map onto each other what we know about brains and what we know about minds. We talk about whether we have the right ontology now, how he uses both top-down and data-driven approaches to analyze and refine current ontologies, and how all this has affected his own thinking about minds. We also discuss some of the current meta-science issues and challenges in neuroscience and AI, and Russ answers guest questions from Kendrick Kay and David Poeppel.
- Russ’s website.
- Poldrack Lab.
- Stanford Center For Reproducible Neuroscience.
- Twitter: @russpoldrack.
- The papers we discuss or mention:
- Atlases of cognition with large-scale human brain mapping.
- Mapping Mental Function to Brain Structure: How Can Cognitive Neuroimaging Succeed?
- From Brain Maps to Cognitive Ontologies: Informatics and the Search for Mental Structure.
- Uncovering the structure of self-regulation through data-driven ontology discovery
- Reproducibility: NeuroHackademy: Russell Poldrack – Reproducibility in fMRI: What is the problem?
- Cognitive Ontology: Cognitive Ontologies, from Top to Bottom
- A good series of talks about cognitive ontologies: Online Seminar Series: Problem of Cognitive Ontology.
Some take-home points:
- Our folk psychological cognitive ontology hasn’t changed much since early Greek Philosophy, and especially since William James wrote about attention, consciousness, and so on.
- Using encoding models, we can predict brain responses pretty well based on what task a subject is performing or what “cognitive function” a subject is engaging, at least to a course approximation.
- Using a data-driven approach has potential to help determine mental structure, but important human decisions must still be made regarding how exactly to divide up the various “parts” of the mind.
0:00 – Introduction
5:59 – Meta-science issues
19:00 – Kendrick Kay question
23:00 – State of the field
30:06 – fMRI for understanding minds
35:13 – Computational mind
42:10 – Cognitive ontology
45:17 – Cognitive Atlas
52:05 – David Poeppel question
57:00 – Does ontology matter?
59:18 – Data-driven ontology
1:12:29 – Dynamical systems approach
1:16:25 – György Buzsáki’s inside-out approach
1:22:26 – Ontology for AI
1:27:39 – Deep learning hype