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Theoretical Neuroscience Podcast
On reverse engineering of the roundworm C.elegans - with Konrad Kording - #8
Mar 2, 2024
Challenges in traditional neuroscience methods, focus on reverse engineering C.elegans, parallels between transistors and neurons, pitfalls of statistical analysis in biology, mechanistic understanding in neuroscience, neural complexity of C.elegans, error recalibration in neural modeling, activation functions in machine learning, optimization challenges in bio-physical models, variability in neural networks
01:34:14
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Quick takeaways
- Shift focus to C.elegans for reverse engineering due to simplicity and potential for understanding neural networks.
- Challenges in understanding causality in neural systems require precise neural stimulation and scalable modeling techniques.
Deep dives
Challenging the Neuroscience Research Approach
Current neuroscience research involves recording activities from hundreds or thousands of neurons, followed by statistical analysis to understand neural network actions. A study on applying this approach to a microprocessor questioned the efficacy of this method for understanding complex mammalian brains with millions of neurons. Despite some similarities found between microprocessor recordings and neural activity, the conclusion was that true understanding eluded researchers.
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