I'm a big believer that #ANNs are a great tool to improve our knowledge of the brain, but often think the "ANN as abstraction of the brain" analogy does more harm than benefit /end
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Replying to @r_chavarriaga @KordingLab and
You need to separate your concern about hype in the popular press from the use of ANNs in neuroscience. ANNs are a very useful model in neuroscience, and we shouldn't shy away from that because Deep Mind's PR ppl go a bit far sometimes.
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Replying to @tyrell_turing @r_chavarriaga and
what have ANNs done for neuroscience, aside from serving as classifiers?
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Replying to @GaryMarcus @r_chavarriaga and
You don't actually keep up with the neuroscience literature, do you? That has been evident in these conversations... Here, lemme give you a few examples:
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Replying to @tyrell_turing @GaryMarcus and
1) ANNs optimised on relevant tasks match the representations in human (and primate) cortical areas better than other models developed to date: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003963 … https://www.sciencedirect.com/science/article/pii/S0896627318302502 …https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003915 …
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Replying to @tyrell_turing @GaryMarcus and
2) ANNs trained on motor tasks successfully predict both motor behaviour and the distribution of representations in motor cortex: https://www.sciencedirect.com/science/article/pii/S0896627312009920 … https://www.biorxiv.org/content/biorxiv/early/2019/08/24/742189.full.pdf …
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Replying to @tyrell_turing @GaryMarcus and
3) Recurrent ANNs can model prefrontal cortical activity well, and explain both behaviour and representations related to multi-task learning: https://www.nature.com/articles/s41593-018-0310-2 …https://www.nature.com/articles/s41593-018-0147-8 …
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Replying to @tyrell_turing @GaryMarcus and
4) In my own work, I found that the original predictions of complimentary learning theory from ANNs (https://psycnet.apa.org/record/1995-42327-001 …) predicts the impact of memory consolidation on mouse navigation behaviour:https://www.nature.com/articles/nn.3736 …
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Replying to @tyrell_turing @GaryMarcus and
And there's more! But, I have to go to lab meeting... Nonetheless, I would encourage you to actually approach the role of ANNs in neuroscience with an open mind. A lot has been accomplished, and there's more to come.
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Replying to @tyrell_turing @GaryMarcus and
Here's a couple of reviews for you if you're actually interested and not so ideological that you are incapable of approaching it neutrally (you have not convinced me of this to date): https://www.nature.com/articles/s41593-019-0520-2 …https://www.biorxiv.org/content/10.1101/133504v2.abstract …
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= yet another a promissory note. "DNNs represent a powerful framework for building task-performing models and will drive substantial insights in computational neuroscience." NOT: "have driven" Maybe it will pan out, maybe not. It's your certainty that I keep objecting to.
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Replying to @GaryMarcus @tyrell_turing and
For me, ANNs have provided an intuition for how at least some aspects of object recognition might be solved. It's far from complete but it's also more than the promissory note that early workmon perceptrons provided
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