We discuss phenomenology as an alternative perspective on our scientific endeavors. Although we like to believe our science is objective and explains the reality of the world we inhabit, we can’t escape the fact that all of our scientific knowledge comes through our perceptions and interpretations as conscious living beings. Michel has used phenomenology to resolve many of the paradoxes that quantum mechanics generates when it is understood as a description of reality, and more recently he has applied phenomenology to the philosophy of mind and consciousness. Alex is currently trying to apply the phenomenological approach to his research on brains and behavior. Much of our conversation revolves around how phenomenology and our “normal” scientific explorations can co-exist, including the study of minds, brains, and intelligence- our own and that of other organisms. We also discuss the “blind spot” of science, the history and practice of phenomenology, various kinds of explanation, the language we use to describe things, and more.
Brains are often conceived as consisting of neurons and “everything else.” As Elena discusses, the “everything else,” including glial cells and in particular astrocytes, have largely been ignored in neuroscience. That’s partly because the fast action potentials of neurons have been assumed to underlie computations in the brain, and because technology only recently afforded closer scrutiny of astrocyte activity. Now that we can record calcium signaling in astrocytes, it’s possible to relate how astrocyte signaling with each other and with neurons may complement the cognitive roles once thought the sole domain of neurons. Although the computational role of astrocytes remains unclear, it is clear that astrocytes interact with neurons and neural circuits in dynamic and interesting ways. We talk about the historical story of astrocytes, the emerging modern story, and Elena shares her views on the path forward to understand astrocyte function in cognition, disease, homeostasis, and – Elena’s favorite current hypothesis – their integrative role in negative feedback control.
Srini is Emeritus Professor at Queensland Brain Institute in Australia. In this episode, he shares his wide range of behavioral experiments elucidating the principles of flight and navigation in insects. We discuss how bees use optic flow signals to determine their speed, distance, proximity to objects, and to gracefully land. These abilities are largely governed via control systems, balancing incoming perceptual signals with internal reference signals. We also talk about a few of the aerial robotics projects his research has inspired, many of the other cognitive skills bees can learn, the possibility of their feeling pain , and the nature of their possible subjective conscious experience.
communication with subjects while they experience lucid dreams. This new paradigm opens many avenues to study the neuroscience and psychology of sleep, dreams, memory, and learning, and to the improvement and optimization of sleep for cognition. Ken and his team are developing a Lucid Dreaming App which is freely available via his lab. We also discuss much of his work on memory and learning in general and specifically related to sleep, like reactivating specific memories during sleep to improve learning.
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.
