- Title: Neural prediction of risky choice: From rats to risk markets
- Affiliation: Stanford University
- Abstract:Due in part to advances in neuroimaging techniques, investigators can now predict risky choices in individual humans on a trial-to-trial basis. I’ll discuss two new directions of this work, both “down” to apply neuroscience tools to causally manipulate relevant circuits in animal models, and “up” to explore whether neural activity in groups of individuals can forecast the movement of option prices at the market level. Together, relevant findings may help link levels of analysis to inform a coalescing “deep science” of risky choice.
- Title: Minds Without Brains
- Affiliation: University of Iowa
- Abstract: Sci-fi speculation about brainless creatures with minds is so yesterday. New biological research appears to show that actual brainless species – such as plants and bacteria – can make decisions, communicate linguistically, or anticipate or expect rewards (among other examples). Such cases should be taken seriously as challenges to traditional views of the mind-brain relation. I’ll review some of the evidence for these research claims and argue that they reveal a fundamental transition away from anthropocentrism in our theorizing about the mind.
- Title: Computational Approaches to Mapping and Modeling Brain Networks
- Affiliation: Indiana University Bloomington
- Abstract: Modern neuroscience is in the middle of a transformation, driven by the development of novel high-resolution brain mapping and recording technologies that deliver increasingly large and detailed “big neuroscience data”. Network science has emerged as one of the principal approaches to model and analyze neural systems, from individual neurons to circuits and systems spanning the whole brain. A core theme of network neuroscience is the comprehensive mapping of anatomical and functional brain connectivity, also called connectomics. In this presentation I will review current themes and future directions of network neuroscience, including comparative studies of brain networks across different animal species, investigation of prominent network attributes in human brains, and use of computational models to map information flow and communication dynamics. I will argue that network neuroscience represents a promising theoretical framework for understanding the complex structure, operations and functioning of nervous systems.
- Title: The Computing Power of Wetware
- Affiliation: University of Washington
- Abstract: Our world is becoming increasingly influenced by machine intelligence, as artificial neural networks, trained to carry out sophisticated tasks, become part of our daily lives. Powerful as they are, our brains and the nervous systems of even simple organisms perform at levels that are— for now-- beyond the reach of these networks, in terms of specific capabilities, rapid learning, the ability to adapt and the energy efficiency with which they run. What is it about “wetware” that endows it with its special properties? Evolution has equipped nervous systems with an exquisite array of complex interacting parts; Adrienne Fairhall will discuss some of the physics and biology that may underlie the remarkable performance of living computers.
4:15 Reception (EV3 Atrium)
Past brain day lecturers include: William Seager, Marisa Carrasco, Konrad Kording, James DiCarlo, Daniel Dennett, Daniel Schacter, Paul Glimcher, David van Essen, Patricia Churchland, William Bechtel, Geoff Hinton, Jack Gallant, Ned Block, Carl Craver, Terry Sejnowski, Keith Holyoak, Peter Strick, Jay McLelland, Tony Movshon, Jonathan Cohen, Larry Barsalou, Sebastien Seung, Mel Goodale, John Hopfield, Jesse Prinz, David Sheinberg, Gyorgy Buzsaki, Ian Gold, Michael Tarr, and Michael Hasselmo.