Ila discusses her theoretical neuroscience work suggesting how our memories are formed within the cognitive maps we use to navigate the world and navigate our thoughts. The main idea is that grid cell networks in the entorhinal cortex internally generate a structured scaffold, which gets sent to the hippocampus. Neurons in the hippocampus, like the well-known place cells, receive that scaffolding and also receive external signals from the neocortex- signals about what’s happening in the world and in our thoughts. Thus, the place cells act to “pin” what’s happening in our neocortex to the scaffold, forming a memory. We also discuss her background as a physicist and her approach as a “neurophysicist”, and a review she’s publishing all about the many brain areas and cognitive functions being explained as attractor landscapes within a dynamical systems framework.
Sri and Mei join me to discuss how including principles of neuromodulation in deep learning networks may improve network performance. It’s an ever-present question how much detail to include in models, and we are in the early stages of learning how neuromodulators and their interactions shape biological brain function. But as we continue to learn more, Sri and Mei are interested in building “neuromodulation-aware DNNs”.
Eve discusses many of the lessons she has learned studying a small nervous system, the crustacean stomatogastric nervous system (STG). The STG has only about 30 neurons and its connections and neurophysiology are well-understood. Yet Eve’s work has shown it functions under a remarkable diversity of conditions, and does so is a remarkable variety of ways. We discuss her work on the STG specifically, and what her work implies about trying to study much larger nervous systems, like our human brains.
Patryk and I discuss his wide-ranging background working in both the neuroscience and AI worlds, and his resultant perspective on what’s needed to move forward in AI, including some principles of brain processes that are more and less important. We also discuss his own work using some of those principles to help deep learning generalize to better capture how humans behave in and perceive the world.
Hakwan and I discuss many of the topics in his new book, In Consciousness we Trust: The Cognitive Neuroscience of Subjective Experience. Hakwan describes his perceptual reality monitoring theory of consciousness, which suggests consciousness may act as a systems check between our sensory perceptions and higher cognitive functions. We also discuss his latest thoughts on mental quality space and how it relates to perceptual reality monitoring. Among many other topics, we chat about the many confounds and challenges to empirically studying consciousness, a topic featured heavily in the first half of his book. Hakwan was on a previous episode with Steve Fleming, BI 099 Hakwan Lau and Steve Fleming: Neuro-AI Consciousness.
