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From Connectome to Computation Through the Genomic Bottleneck

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  • UserProf. Tony Zador, Cold Spring Harbor Laboratory.
  • ClockThursday 20 April 2023, 15:00-16:00
  • HouseOnline.

If you have a question about this talk, please contact Sofia Orellana .

Artificial neural networks (ANNs) have undergone a revolution. However, the success of ANNs is based on massive amounts of training data. By contrast, most animal behavior is not the result of clever learning algorithms—supervised or unsupervised— but is encoded in the genome. Specifically, animals are born with highly structured brain connectivity, which enables them to learn very rapidly. Because the wiring diagram is far too complex to be specified explicitly in the genome, it must be compressed through a “genomic bottleneck”. The genomic bottleneck suggests a path toward ANNs capable of rapid learning

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