

BI 180 Panel Discussion: Long-term Memory Encoding and Connectome Decoding
Dec 11, 2023
Panel discussion on using neuroscience technologies to decode memory from connectomes, featuring a group of experts including Kenneth Hayworth. Topics include advancements in connectomics, decoding memory and connectomes, analyzing connectome complexity, the role of molecules, deep learning parallelism, studying connectome data with cultured neurons, understanding neuronal interactions, and the rules of connectome interpretation.
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Decoding Memories and Connectomes
- Decoding a non-trivial memory from a static connectome is the central topic.
- Multiple connectomes are needed to compare and understand individual differences, like experiences.
Genomics Analogy and Memory Engrams
- Tomás Ryan suggests that sequencing whole genomes wasn't how the genetic code was deciphered.
- He believes a similar approach may not be the most effective way to understand memory engrams.
Perturbation Studies and Causal Insight
- Konrad Kording emphasizes the power of perturbation studies in C. elegans for understanding neural function.
- He suggests that the fly connectome, while valuable, doesn't offer the same level of causal insight.