Listeners:
Top listeners:
play_arrow
Paul Verschure on consciousness and distributed adaptive control CSN Podcasts
play_arrow
Edvard Moser on grid cells and entorhinal cortex CSN Podcasts
play_arrow
Giacomo Rizzolatti on mirror neurons and action understanding CSN Podcasts
play_arrow
Robert Axelrod on game theory and prisoner's dilemma CSN Podcasts
play_arrow
Adrian Owen on disorders of consciousness and vegetative state CSN Podcasts
play_arrow
Jonathan Whitlock on markerless motion capture and posterior parietal cortex CSN Podcasts
play_arrow
Luis Puelles on neuroanatomy and prosomeric model CSN Podcasts
play_arrow
Zoltan Molnar on subplate neurons and cortical development CSN Podcasts
Episode 10 15.03.2018
play_arrow
PLAY EPISODE
What if the mathematics behind neural networks could unlock the secrets of the immune system? Physicist Ton Coolen reveals how techniques from statistical mechanics, originally developed for obscure magnetic materials, now expose deep structural parallels between how brains store memories and how immune systems learn to fight disease. Subscribe for more from the Convergent Science Network podcast series. Ton Coolen joins Paul Verschure and Tony Prescott to explain how a collaboration with Italian researchers led him to apply finite connectivity analysis, a mathematical framework only available since around 2000, to models of immune network function. The resulting models map directly onto Hopfield-type attractor networks from neural network theory, with cytokine signaling playing the role of synaptic connections and B-cell receptor evolution functioning as a rewiring mechanism. The conversation traces how applied problems in biology have driven fundamental advances in theoretical physics, inverting the usual relationship between basic and applied science. The discussion explores what the immune system can teach neuroscience about memory and learning. Unlike neural networks where few patterns with many bits are stored, immune networks store many patterns with few bits each , a regime that demands entirely different mathematical treatment. Coolen argues that biological heterogeneity, shaped by evolution rather than randomness, represents a fundamental challenge that standard physical methods cannot handle, pointing toward a new class of problems at the boundary of physics and biology. Key topics include the mathematical parallels between Hopfield networks and immune models, why equilibrium statistical mechanics fails for living systems, how hypermutation and selection function as a learning algorithm, the unsolved problem of immune memory, and the tantalizing possibility that the nervous system anticipates and regulates immune responses through brain-immune coupling. Part of the Convergent Science Network podcast series from the BCBT Summer School.
Tagged as:
immune networks Mathematical neural networks Patterns Bits Statistical Mechanics
About the author call_made
Both the triumphs of humanity and its most evil deeds have resulted from collaboration. In a time where humanity is required to aspire to the former and minimize the latter, the question arises of how collaboration arises and why it fails. Surprisingly, this phenomenon, so central to who we are, is not well understood. Hence, a collaborative effort is required to understand collaboration in its full biological, psychological, sociological, cultural, and economic complexity and to translate this understanding into operational impact. This series of podcasts is one step toward achieving these complementary goals. The Collaboration Podcast presents interviews with people who are central orchestrators of collaboration in various domains including business, government, science, art, health, sustainability, and the military. The discussions were conducted by Prof. Dr. Paul F.M.J. Verschure and members of the Program Advisory Committee of the Ernst Strungmann Forum on Collaboration (https://www.esforum.de/forums/ESF32_Collaboration.html) during 2021 and had the goal to sketch a map of opportunities, challenges, and obstacles in human collaboration. The forum took place in May 2022, and now we would like to share this series of interviews with a broader audience. The full report of the Forum will be published in 2023 by MIT Press. The podcast was produced by the Convergent Science Network (https://www.convergentsciencenetwork.org/). Context: The stability of social systems depends critically on realizing sustainable methods of “collaboration,” yet how and by which means collaboration is achieved is not clearly understood; neither are the conditions or processes that lead to its breakdown or failure. Collaboration can be understood as cooperation between agents toward mutually constructed goals. Part of the reason for our lack of understanding is that the phenomenon of collaboration is, by nature, a highly multidisciplinary problem, and effective research into its complexities has been difficult to achieve across the broad range of scientific and technical disciplines involved. The need for a fundamental understanding of collaboration, however, has become increasingly important. Not only does humankind demand answers as it attempts to address critical challenges at multiple scales (e.g., climate change, migration, enhanced automation, social and economic inequality), but ever-increasing technological and economic means of interconnecting people and societies are disrupting long-established, familiar patterns of how we interact. Radical technological changes that are ongoing have the potential to reshape collaboration in ways that are currently hard to predict or influence (e.g., by altering configurations in interaction, information creation, and modes of communication). On one hand, such changes could disrupt hitherto stable forms of collaboration by affecting critical communication channels and traditional roles, as can be observed in the rapidly changing patterns in governance, commerce, and social interaction. Conversely, technology could lead to the emergence of novel, successful forms of collaboration that deviate from traditional “hierarchical” architectures. Evidence of this can be seen in areas as diverse as highly automated manufacturing plants, the open science movement, collaborative software repositories, user-centered services, and the sharing of economy-based modes of organization. Without a fundamental understanding of the mechanisms, processes, and boundary conditions of collaboration, it is not possible to evaluate or predict which of these possible scenarios are sustainable or even plausible. The Forum “How Collaboration Arises and Why it Fails” (May 8–13, 2022, Location: Frankfurt am Main, Germany) Chairs: Andreas Roepstorff and Paul Verschure Program Advisory Committee: Jenna Bednar, Julia R. Lupp, Bhavani R. Rao , Andreas Roepstorff, Ferdinand von Siemens, and Paul Verschure
Exploring the convergence of neuroscience, robotics, and AI through conversations with leading researchers since 2010.
A project of the Convergent Science Network Foundation.
© CSN Podcasts. Developed by IMCreative & WEBC
✖
✖
Are you sure you want to cancel your subscription? You will lose your Premium access and stored playlists.
✖
Be the first to leave a comment