Emerson Harkin

@efharkin.bsky.social

Computational neuroscience post doc interested in serotonin | Dayan lab @mpicybernetics.bsky.social | 🇨🇦 in 🇩🇪

Dopamine neurons are heterogeneous, but their diffuse axons are homogenizing. What does this mean for RL models? Stop by poster 362 at #FENS2026 this morning to find out! "Multi-timescale reward prediction learning dynamics with entangled connectivity between the striatum and the dopamine system."

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Great opportunity to work with a group that's very productive yet somehow also easygoing! To get an idea of Roxana's interests check out her recent review, just out in Nature Neuroscience: doi.org/10.1038/s415...

Roxana Zeraati@roxana-zeraati.bsky.social · last mo.

We (@neuroprinciplist.bsky.social & I) will soon open joint PhD & postdoc positions on cross-species mechanisms of different adaptive behaviors. If you’re interested and would like to chat during #FENS2026, drop me a message :)

This is one of the most outstanding examples of circuit understanding I've seen in a long time. The unification of theory and experiment is beautiful. When Malcolm presented this in my lab, the audience was cheering at the end, and one person shouted (non-ironically) "You did it!"

Malcolm Campbell@malcolmgcampbell.bsky.social · 11mo ago

🚨Our preprint is online!🚨 www.biorxiv.org/content/10.1... How do #dopamine neurons perform the key calculations in reinforcement #learning? Read on to find out more! 🧵

Looking forward to attending #CCN2025 for the first time and presenting the first steps of my postdoc project! If you’re interested in how learning the temporal structure of the environment affects foraging decisions and how we’re testing this in a naturalistic experiment come by poster B90, Wed.

🚨Pre-print alert🚨 We stimulated serotonin with optogenetics while doing large-scale Neuropixel recordings across the mouse brain. We found strong widespread modulation of neural activity, but no effect on the choices of the mouse 🐭 How is this possible? Strap in! (1/9) 👇🧵 doi.org/10.1101/2025...

Serotonin drives choice-independent reconfiguration of distributed neural activity

Serotonin (5-HT) is a central neuromodulator which is implicated in, amongst other functions, cognitive flexibility. 5-HT is released from the dorsal raphe nucleus (DRN) throughout nearly the entire f...

doi.org

I've been watching the debate over "representations" in neuroscience 🍿 and I wanted to suggest a thought experiment: Suppose a driver sees a 🛑 and this causes vision neurons to spike in a characteristic way, but the driver blows through the intersection. Is the stop sign *represented* in the brain?

⏰ Check out this inspiring pair of articles from @paulmasset.bsky.social and Margarida Sousa! Some dopamine neurons care about rewards far in the future more than others, allowing the brain to learn the timing of future rewards. Congrats to the authors! 🍾 🔓 links: rdcu.be/epxkE rdcu.be/epxkG

A multidimensional distributional map of future reward in dopamine neurons

Nature - An algorithm called time–magnitude reinforcement learning (TMRL) extends distributional reinforcement learning to take account of reward time and magnitude, and behavioural and...

rdcu.be

Ugh… there’s also what I call messianic AI, the fantasy that AI will “solve” science. Treating science like a vending machine for solitons/profit & scientists as human cogs replaceable by machinery. But Science is a living culture of critical discussion, mentorship, shared community values &methods.

TIL that at certain journals the date your paper is published online might be very different from the date it appears in print. Unrelated, is there anyone whose work was published in the March 27 print edition of Nature who'd like several copies to share with supportive family members?

Most simulators for time-series data (e.g., numerical solvers for differential equations) are Markovian-- this can be exploited for efficient simulation-based inference on time-series data! Talk to Manuel and Shoji at #ICLR2025, or read the paper ⬇️!

Machine Learning in Science@mackelab.bsky.social · last yr.

Excited to present our work on compositional SBI for time series at #ICLR2025 tomorrow! If you're interested in simulation-based inference for time series, come chat with Manuel Gloeckler or Shoji Toyota at Poster #420, Saturday 10:00–12:00 in Hall 3. 📰: arxiv.org/abs/2411.02728

Attention climate scholars seeking to leave the US: Next year the University of Ottawa will be seeking int'l candidates for a Canada Excellence Research Chair in "Climate and Societal Solutions" (broadly defined) They'll seek established scholars with global reach in this area (see below)...

 uOttawa is seeking applications from world-class
researchers in this thematic area of Sustainability in Action: Climate and Societal
Solutions, including:
• Arctic and Northern Studies: Advancing solutions-oriented research that benefits
Arctic communities and strengthens Canada’s leadership in Arctic research.
• Environmental Health and Toxicology: Studying the impact of environmental toxins on
human, animal and ecosystem health, including toxicology, environmental
genomics, and the development of tools to inform policy and promote sustainable
health outcomes.
• Disaster Communication: Conducting critical studies on disaster communication
and strategies for countering disinformation.
• Law, Democracy and Climate Action: Strengthening governance and legal
frameworks to address climate-related societal challenges in northern communities,
environmental protection and climate change resilience.

Many people (myself included), note the lack of top-down feedback in deep NN models of the brain. Mashbayar has come to the rescue! She built a code-base for making models with top-down feedback. Check out her paper at @elife.bsky.social showing the impact of FB on audio-visual integration. 🧠📈 🧪

Mashbayar Tugsbayar@tmshbr.bsky.social · last yr.

Top-down feedback is ubiquitous in the brain and computationally distinct, but rarely modeled in deep neural networks. What happens when a DNN has biologically-inspired top-down feedback? 🧠📈 Our new paper explores this: elifesciences.org/reviewed-pre...

When a scientific idea is ambiguous, is it good to err on the side of agreeing with it? Sometimes I read discussions like "Our data are broadly consistent with X and Y," where X and Y are plausibly contradictory but vague enough that there's wiggle room.