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Episode 10 15.03.2019
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How does the brain build its own maps, and what constrains the patterns that evolution can produce? Computational neuroscientist Stuart Wilson argues that cortical arealization emerges from self-organizing processes operating within the design space defined by reaction-diffusion dynamics , not from a genetic blueprint that specifies each area independently. Subscribe for more from the Convergent Science Network podcast series. Stuart Wilson joins Paul Verschure and Tony Prescott to discuss how self-organization and natural selection interact to produce the diverse cortical maps observed across mammalian species. Drawing on Stuart Kauffman’s framework and Alan Turing’s reaction-diffusion mathematics, Wilson proposes that gene expression gradients across the developing cortex are themselves generated by self-organizing processes constrained by boundary shape and diffusion constants. Only certain patterns are possible for a given cortical geometry, and natural selection works within this limited design space rather than engineering maps from scratch. The conversation probes the methodology of building models that bridge abstract mathematical principles and messy biological reality. Wilson describes a collaboration with biologists Leah Krubitzer and Kelly Huffman, where software tools simulate self-organizing processes on arbitrary boundary shapes derived from actual cortical drawings across species. His strategy for validation is explicit: fit the model to reproduce observed variability in cortical boundaries across all catalogued species, then systematically remove components until the model breaks , identifying the minimal set of mechanisms required. Prescott and Verschure push on whether adult boundary shape is sufficient as a constraint, given that the cortex changes shape during development, and whether the model can generate predictions that biologists can test. Key topics include why the Jonas and Kording microprocessor paper matters for modelers, how knockout experiments reveal a minimal gene interaction network of approximately five genes driving cortical patterning, the relationship between tissue growth and successive self-organizing modes during development, and why the simplest model that accounts for biological complexity is more valuable than one that matches it. Part of the Convergent Science Network podcast series from the BCBT Summer School.
Tagged as:
Cortical cortical maps Design Space Natural Selection self-organization Self-organizing Processes
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
15.03.2019
15.03.2019
15.03.2019
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