Robert Rosenbaum
@RobertRosenba14
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Associate prof in Applied Mathematics at U Notre Dame. Theoretically a neuroscientist. @robertrosenbaum.bsky.social
Joined February 2019
Happy to announce that my book is now published. It's an undergrad level computational neuroscience textbook with a focus on modeling. It's great for the classroom, but also for readers from other fields (such as ML/AI) who want to learn about biological neural networks (1/n)
@danielumera @MatthewHancocks @htsoukas @Karminker @GiovanniTusa @chriscfrench 📘 Modeling Neural Circuits Made Simple with Python ✍ @RobertRosenba14 An accessible undergraduate textbook in computational neuroscience that provides an introduction to the mathematical and computational modeling of neurons and networks of neurons.
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The question "Actually, what does area even mean?" ignited some of the deepest, most counterintuitive, and ultimately useful mathematics of the 20th century. And answering this question occupied some of the brightest mathematicians of the 20th century for years.
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@jehosafet No prob. I should add that I was lucky to get a grant first year, but it should in no way be expected. In some ways it's not ideal because that grant will be old news by the time you go for tenure. Also get NSF specific advice for writing NSF grants, which are very diff from NIH
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@klarakaleb @ClopathLab @victorpedrosabc @BarbaFeu @JAlGallego Congratulations! And great job on your thesis and defense.
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... cellular neurobiology, molecular neurobiology, or computational neurobiology. Candidates can be hired into one of three departments: Biology, Chemistry, or AppliedMath/Stats See the linked ads for more info.
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RT @eli_j_muller: How is a brain able to support stable neural dynamics and yet remain flexible in order to adapt to changing contexts. He…
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@arjunrajlab Then the length wouldn't have changed very much on average, unless I'm missing something
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An open access version of my book is now available on the publisher's website.
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@Samuel_Eckmann @cian_neuro @ostojic_srdjan @UliGraupner Yep, I just wasn't sure if that's what you meant. That's probably mostly true in cortex But synapses in some non-cortical synapses might be more sensitive to faster timescales not easily captured by rate models. An obvious example is auditory neurons for sound localization
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@cian_neuro @Samuel_Eckmann @ostojic_srdjan @UliGraupner But STDP doesn't care about noise versus signal correlations. Noise correlations are usually weakish in ctx (like <10%) Signal correlations are larger and will look like rate modulations, so as @Samuel_Eckmann mentioned, fluctuating rates will affect syn weights under STDP
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