BI 199 Hessam Akhlaghpour: Natural Universal Computation
Nov 26, 2024
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Hessam Akhlaghpour, a postdoctoral researcher at Rockefeller University, delves into the theoretical realm of molecular computation and its intersections with neuroscience. He unveils fascinating insights on RNA's potential as a universal computational medium. The discussion spans the evolutionary significance of this capability and how combinatory logic plays a role in biological systems. Hessam reflects on how his journey through neuroscience reshaped his understanding of memory and computation, challenging traditional views and igniting new ideas in computational theories.
Hessam Akhlaghpour discusses how RNA's capabilities as both a genetic template and catalyst suggest its role in universal computation.
The transition to molecular computation challenges traditional neuroscience views and integrates concepts from computer science and molecular biology.
Combinatory logic in RNA highlights its potential for performing computational functions, reflecting longstanding ideas in cognitive science and biology.
Deep dives
Universal Computation and its Importance
Universal computation is a concept that suggests a system can solve any computable function given an appropriate set of rules or algorithms. While it is commonly believed that biological models of computation achieve universality, this notion is challenged by the idea that they may actually fall short. The discussion highlights the relevance of biochemical molecules in cellular processes, particularly RNA, which may possess capabilities that allow for universal computation in nature. Understanding these concepts points to a significant intersection between computational theories and biological systems.
Molecular Computation Foundations
Molecular computation explores the ways in which biological molecules, particularly RNA, can function as computational systems. RNA, with its ability to fold into complex structures and act as a string of symbols, presents a compelling case for implementing computational logic. The work draws inspiration from Randy Gallistel and Adam King's arguments for genetic material storage beyond synaptic transmission, proposing that RNA could serve as a substrate for memory and processing information. This paradigm encourages an exploration of how the brain and molecular biology could achieve and utilize computational capacities.
Overcoming Disillusionment in Neuroscience
The transition from a traditional view of neuroscience, which often relies heavily on classical models of computation, to a perspective that embraces molecular computation indicates a significant shift in understanding. Early disillusionment with the limitations of conventional neuroscience reframed personal inquiries into how computational principles might be relevant at the molecular level. This academic journey emphasizes the importance of integrating insights from various disciplines, such as computer science and molecular biology, in forging a more dynamic understanding of cognitive processes. By shedding previous misconceptions, new avenues for investigation emerge, reopening discussions on the computational nature of biological systems.
RNA's Role in Computation
RNA's unique ability to exist as both a template for genetic information and a catalyst in biochemical reactions posits it as a crucial player in molecular computation. This dual functionality allows RNA to perform operations analogous to those in computer systems, suggesting that it might not only store memory but actively compute using combinatorial logic principles. The hypothesis that RNA could serve as a foundational component of a computational system aligns with historical notions from the 1960s that may have been dismissed too quickly. Revisiting these ideas with contemporary insights provides fertile ground for understanding the computational capabilities intrinsic to life's molecular structures.
Integration of Combinatory Logic
The concept of combinatory logic, which involves constructing new functions from existing ones through the application of combinators, parallels RNA's functional capabilities in biological systems. RNA molecules can form secondary structures that allow for local interactions, akin to applying operations in combinatory logic, enabling various computational applications. By realizing that RNA operations can embody combinatory logic without necessitating intricate or separate mechanisms, the framework presents a tangible model for exploring how molecular computation can occur in biological contexts. The goal is to establish whether similar operational models operate within cells, leveraging RNA’s inherent properties for computational purposes.
Challenges and Opportunities in Molecular Biology
The study of molecular computation, particularly centered around RNA, faces challenges due to the traditional focus of molecular biology on more established mediators like proteins and DNA. Skepticism towards the potential computational functions of RNA may hinder the exploration of its capabilities and importance in biological processes. In shifting perspectives to consider RNA as potentially central to understanding molecular computation, researchers can uncover insights about memory, learning, and cognitive functions. Encouraging interdisciplinary collaboration and dialogue between fields could foster innovative research and prevent potentially ground-breaking ideas from fading into obscurity, as they did in prior decades.
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Hessam Akhlaghpour is a postdoctoral researcher at Rockefeller University in the Maimon lab. His experimental work is in fly neuroscience mostly studying spatial memories in fruit flies. However, we are going to be talking about a different (although somewhat related) side of his postdoctoral research. This aspect of his work involves theoretical explorations of molecular computation, which are deeply inspired by Randy Gallistel and Adam King's book Memory and the Computational Brain. Randy has been on the podcast before to discuss his ideas that memory needs to be stored in something more stable than the synapses between neurons, and how that something could be genetic material like RNA. When Hessam read this book, he was re-inspired to think of the brain the way he used to think of it before experimental neuroscience challenged his views. It re-inspired him to think of the brain as a computational system. But it also led to what we discuss today, the idea that RNA has the capacity for universal computation, and Hessam's development of how that might happen. So we discuss that background and story, why universal computation has been discovered in organisms yet since surely evolution has stumbled upon it, and how RNA might and combinatory logic could implement universal computation in nature.
0:00 - Intro
4:44 - Hessam's background
11:50 - Randy Gallistel's book
14:43 - Information in the brain
17:51 - Hessam's turn to universal computation
35:30 - AI and universal computation
40:09 - Universal computation to solve intelligence
44:22 - Connecting sub and super molecular
50:10 - Junk DNA
56:42 - Genetic material for coding
1:06:37 - RNA and combinatory logic
1:35:14 - Outlook
1:42:11 - Reflecting on the molecular world
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