BI 026 Kendrick Kay: A Model By Any Other Name

BI 026 Kendrick Kay: A Model By Any Other Name

Brain Inspired
Brain Inspired
BI 026 Kendrick Kay: A Model By Any Other Name
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Kendrick and I discuss his models that predict how the human brain responds to pictures of faces and words, how we make decisions about those pictures, and how our brain gears up for such tasks. We also discuss models in general- what they are, how we should judge them, and so on, plus a few of his other projects and…. wait for it… lots more.

BI 116 Michael W. Cole: Empirical Neural Networks

BI 116 Michael W. Cole: Empirical Neural Networks

Brain Inspired
Brain Inspired
BI 116 Michael W. Cole: Empirical Neural Networks
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Mike and I discuss his modeling approach to study cognition. Many people I have on the podcast use deep neural networks to study brains, where the idea is to train or optimize the model to perform a task, then compare the model properties with brain properties. Mike’s approach is different in at least two ways. For one, he builds the architecture of his models using structural connectivity data from fMRI recordings. Two, he doesn’t train his models; instead, he uses functional connectivity data from the fMRI recordings to assign weights between nodes of the network (in deep learning, the weights are learned through lots of training). Mike calls his networks empirically-estimated neural networks (ENNs), and/or network coding models. We walk through his approach, what we can learn from models like ENNs, discuss some of his earlier work on cognitive control and our ability to flexibly adapt to new task rules through instruction, and he fields questions from Kanaka Rajan, Kendrick Kay, and Patryk Laurent.

BI 100.4 Special: What Ideas Are Holding Us Back?

BI 100.4 Special: What Ideas Are Holding Us Back?

Brain Inspired
Brain Inspired
BI 100.4 Special: What Ideas Are Holding Us Back?
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In the 4th installment of our 100th episode celebration, previous guests responded to the question:
What ideas, assumptions, or terms do you think is holding back neuroscience/AI, and why?
As per usual, the responses are varied and wonderful!

BI 092 Russ Poldrack: Cognitive Ontologies

BI 092 Russ Poldrack: Cognitive Ontologies

Brain Inspired
Brain Inspired
BI 092 Russ Poldrack: Cognitive Ontologies
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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.

Bibliography

Bibliography: This is a simple and abbreviated list of the main scientific papers and/or books discussed in each episode. For more links, papers, and information, click on the episode title.     BI 001 & 002 Steven Potter: Brains in Dishes What Can AI...