@gershbrain

Professor, Department of Psychology and Center for Brain Science, Harvard University

 Cambridge, MA
gershmanlab.com/index.html
Joined July 2016
  • Tweets2.7K
  • Following58
  • Followers16.5K
156Media
I love this project, which feels like it opens many doors.
Tomer Ullman@TomerUllman5 Nov 2024
Looking for a distraction (for some reason)? May I interest you in this cool new paper on "Blending simulation and abstraction for physical reasoning"? (by Sosa, Gershman, and me) paper link: sciencedirect.com/science/ar… OSF: osf.io/preprints/psyarxiv/f9…
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Great opportunity here!!
Jay Hennig@jehosafet28 Oct 2024
I'm hiring a postdoc to work with me on problems related to meta-learning and probabilistic representation learning in the brain. Perks: i) the amazing research community at @bcm_neurosci and @RiceNeuro. ii) Houston food is DELICIOUS (and cheap) jobs.bcm.edu/job/Postdoctora…
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I think my point here has been misunderstood by most commentators. Obviously I agree that ephys is a more direct measure of spiking activity. Let me try to clarify...
Sam Gershman@gershbrain17 Oct 2024
Papers that report neuronal recordings sometimes say that they provide "direct" evidence for neural encoding of something, in contrast to "indirect" methods such as non-invasive brain imaging. I don't really understand this. What makes one "direct" and the other "indirect"?
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My point is that it's too simplistic to think that measuring spiking activity is always a more "direct" way of testing hypotheses about the relationship between neural activity and information processing.
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My impression is that there is a cultural barrier where systems neuroscientists overlook the relevance of non-invasive brain imaging to test certain hypotheses, simply because it's not directly measuring spikes.
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Papers that report neuronal recordings sometimes say that they provide "direct" evidence for neural encoding of something, in contrast to "indirect" methods such as non-invasive brain imaging. I don't really understand this. What makes one "direct" and the other "indirect"?
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Is the alternative hypothesis that something other than neural activity is generating the non-invasive brain signals? Or is the qualifier "direct" simply a rhetorical flourish?
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I'd like to teach a paper which shows how a fact about the brain materially improved an AI system in a way that is unlikely to have been figured out by engineering alone. I haven't been able to find a single example of this. Suggestions welcome.
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I'm mainly interested in examples where neuroscientists make a correct ex ante prediction that some brain fact will improve performance when incorporated into an AI system (without changing other things). Ex post explanations in terms of neuroscience are less convincing.
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Please don't tell me about perceptrons, neocognitrons, or TD learning. These aren't good examples, for reasons I go into here: gershmanlab.com/pubs/NeuroAI…
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What are the most compelling real-world applications of cognitive science? I'm looking for empirical papers (not opinions/reviews).
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Sam Gershman retweeted
Lucy Lai, PhD@drlucylai10 Oct 2024
we've finally updated our 2⃣ year old preprint on action chunking as (conditional) policy compression! this was a lesson in perseverance and not giving up on your ideas...work with @gershbrain & @AnnHuang42 ✨ (1/3) osf.io/preprints/psyarxiv/z8… – at Onna-son, Okinawa

Action chunking as conditional policy compression

Many skills in our everyday lives are learned by sequencing actions towards a desired goal. The action sequence can become a ``chunk'' when individual actions are grouped together and executed as one...

osf.io
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I advised a physics student and I kept worrying that the physics police would burst in to take her away because she wasn’t doing “real” physics. But I realized that if it’s interesting to physicists, it’s physics.
Michael Baym@baym8 Oct 2024
I feel like the critique that the physics Nobel is going to computer science misunderstands the culture of physics. They aren’t ceding the prize to cs, they’re claiming it as a branch of physics
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[Please retweet!] My paper, 'Cognitive Representations of Social Relationships and their Developmental Origins" has been accepted at Behavioral and Brain Sciences! I'm thrilled to be able to engage with people's commentary! Please consider writing one! osf.io/preprints/psyarxiv/xh…
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If you're interested in the future of scholarly publishing, check out this panel discussion (open to the public): libcal.library.harvard.edu/e…

In Conversation with Open Mind, a No-fee Open Access Journal in Cognitive Science

In celebration of International Open Access Week 2024, please join us for a conversation with Open Mind, MIT Press, MIT Libraries, and Harvard Library. Although a young journal in...

libcal.library.harvard.edu
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This has been happening for a while. I have a few ideas for fixes: (1) Editorial boards should be larger so that load is small for each editor. We've done this at Open Mind and I think it works well.
Tomer Ullman@TomerUllman1 Oct 2024
- revised paper still under review, 90+ days, no word from late reviewer - diff revised paper, 90+ days in, reviewers have not even been assigned - another paper is 1+ month, waiting for editor to make initial decision is everything broken right now or is it just locally me?
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(5) Many editorial workflows wait for a reviewer to decline an invitation before the next reviewer is invited. The time limit for this waiting period is typically a week or more. I think it should be more like 2-3 days. Many people just never respond.
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(5') If you are invited to review and you don't have time, please just decline! Don't leave the invitation hanging, because this just slows down the whole process.
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