Marcus Ghosh
Computational neuroscientist.
Research Fellow @imperialcollegeldn.bsky.social and @imperial-ix.bsky.social
Funded by @schmidtsciences.bsky.social
- Toy models, just in time for Christmas! Excited to share my first article for @thetransmitter.bsky.social #neuroskyence
- Amid the rise of billion-parameter models, I argue that toy models, with just a few neurons, remain essential—and may be all neuroscience needs, writes @marcusghosh.bsky.social. #neuroskyence www.thetransmitter.org/theoretical-...
- I'm excited to be teaching with @trendcamina.bsky.social again this summer. Come along!
- Applications Are Open! 🥳 #TReNDCaMinA Summer School 2026 | 29 Jun–15 Jul Dedan Kimathi University of Technology, Kenya For applicants in African countries with backgrounds in neuroscience, medicine, Computer Science, engineering, & related fields. Apply 👉 trendinafrica.org/trend-camina/
- Adam was a truly inspiring scientist. He made neuroscience fun and exciting, and made everything seem possible. The Behaviour and Neural Systems course was formative for many of us. The photo below is from my time @champalimaudr.bsky.social in 2016.
- Interested in #neuroscience + #AI and looking for a PhD position? I can support your application @imperialcollegeldn.bsky.social ✅ Check your eligibility (below) ✅ Contact me (DM or email) UK nationals: www.imperial.ac.uk/life-science... Otherwise: www.imperial.ac.uk/study/fees-a...
- Are #NeuroAI and #AINeuro equivalent? @rdgao.bsky.social draws a nice distinction between the two. And introduces Gao's second law: “Any state-of-the-art algorithm for analyzing brain signals is, for some time, how the brain works.” Part 1: www.rdgao.com/blog/2024/01...
- The misleading manifold? The current debate (decoding vs causal relevance) and a toy example I gave in the thread below got me thinking about a related issue: how decoding may reflect structure more than function. 🧵 1/5
- If we start from this circuit: Input -> neuron_1 -> output ↓ ⋮ ↓ neuron_n And record neurons 1 to n simultaneously (where n could be very large). We can obtain a matrix of neural activity (neurons x time). 🧵2/5
- A common approach to analysing this data would be to apply PCA (or another technique). Yielding a matrix of population activity (d x time). Where d < the number of neurons. A common interpretation of this would be that "the brain uses a low dimensional manifold to link this input-output". 🧵3/5
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View full threadCausal experiments could help to untangle this. But, it seems like this remains underexplored? Keen to hear your thoughts @mattperich.bsky.social, @juangallego.bsky.social and others! www.nature.com/articles/s41... 🧵5/5
- Being part of this grassroots 🌱 neuroscience collaboration was a great experience! Keep an eye out for our next collaborative effort
- I'll be presenting this work at #CCN2025 tomorrow (A173). Come and say hi or message me if you'd like to meet up!
- How does the structure of a neural circuit shape its function? @neuralreckoning.bsky.social & I explore this in our new preprint: doi.org/10.1101/2025... 🤖🧠🧪 🧵1/9
