Thomas Frank

@frankfishlab.bsky.social

1/8 New preprint alert! How are signals from the heart encoded in the brain? What could be the functional implications of cardioception? We found that neurons in the posterior insular cortex are precisely tuned to heartbeats, and that this cardio-insular coupling supports emotion coding in mice.

biorxiv.org

Exciting new results from our neighbors in the @mace-lab.bsky.social! Using functional ultrasound imaging, they look at brain-wide activity patterns in response to arousing events, showing propagation from subcortical regions to the cortex, and find a surprisingly weak modulation by noradrenaline!

Emilie Macé@mace-lab.bsky.social · 5mo ago

1/8. New preprint! Using fUSi in head-fixed mice🐭, we found that arousal events trigger a brain-wide wave of activity 🌊🧠. Surprisingly, this pattern was preserved during opto manipulations of the locus coeruleus, pointing to a minor role for noradrenergic tone. www.biorxiv.org/content/10.6...

Massive FOMo seeing the posts of people heading to #SfN2025, all that beach...ehm.. science I’m missing 😭 If you’re there, go say hi to the brilliant Bruno Pilcher and the INSS crew, who just built my lab a custom multiphoton microscope with a spatial light modulator that is pure chef’s kiss 👨‍🍳💋✨

Bruno Pichler@brunopichler.bsky.social · 9mo ago

Independent NeuroScience Services INSS was registered as a company on 14th November 2016, which means it's our 9th birthday today! As a birthday present we've treated ourselves to an SfN exhibitor booth for the first time ever. Come and say hello at Booth #3327

The most universally agreed upon property that sets emotion/affect apart from everything else is valence: approach/avoid; pleasant/unpleasant. Here they target its computation in flies, where you can really figure out the biology. We know so little about how valence is computed by brains. Exciting!

Katrin Vogt@katrinvogt.bsky.social · 10mo ago

How is valence computed in the brain? Check out our new preprint about a single cell that integrates excitatory and inhibitory input across modalities according to valence and impacts behavioral decisions. An exciting collaboration across many labs. Enjoy reading! www.biorxiv.org/content/10.1...

How is valence computed in the brain? Check out our new preprint about a single cell that integrates excitatory and inhibitory input across modalities according to valence and impacts behavioral decisions. An exciting collaboration across many labs. Enjoy reading! www.biorxiv.org/content/10.1...

A multisensory, bidirectional, valence encoder guides behavioral decisions

A key function of the brain is to categorize sensory cues as repulsive or attractive and respond accordingly. While we have some understanding of how sensory information is processed in the sensory pe...

biorxiv.org

Ever wonder if there are spatial maps in the brain outside the hippocampal-entorhinal regions? In this preprint, we describe a novel spatial map in the orbitofrontal cortex (OFC) that preserves the topological arrangements and distance between locations. However, ... www.biorxiv.org/cgi/content/...

The orbitofrontal cortex forms a context-generalized spatial schema that preserves topology and distance

Flexible and efficient navigation requires the brain to construct maps that are both topological, preserving the relationships between locations, and schematic, enabling generalization across environm...

biorxiv.org

New preprint on common algorithms and evolutionary inventions that may account for apparent idiosyncratic encoding of odor concentration across species millions of years apart by taking advantage of divisive normalization: steered by Yang Shen, @arkarupbanerjee.bsky.social and Saket Navlakha. 1/3

An evolutionarily conserved scheme for reformatting odor concentration in early olfactory circuits

Understanding how stimuli from the sensory periphery are progressively reformatted to yield useful representations is a fundamental challenge in neuroscience. In olfaction, assessing odor concentration is key for many behaviors, such as tracking and navigation. Initially, as odor concentration increases, the average response of first-order sensory neurons also increases. However, the average response of second-order neurons remains flat with increasing concentration – a transformation that is believed to help with concentration-invariant odor identification, but that seemingly discards concentration information before it could be sent to higher brain regions. By combining neural data analyses from diverse species with computational modeling, we propose strategies by which second-order neurons preserve concentration information, despite flat mean responses at the population level. We find that individual second-order neurons have diverse concentration response curves that are unique to each odorant — some neurons respond more with higher concentration and others respond less — and together this diversity generates distinct combinatorial representations for different concentrations. We show that this encoding scheme can be recapitulated using a circuit computation, called divisive normalization, and we derive sufficient conditions for this diversity to emerge. We then discuss two mechanisms (spike rate vs. timing based) by which higher order brain regions may decode odor concentration from the reformatted representations. Since vertebrate and invertebrate olfactory systems likely evolved independently, our findings suggest that evolution converged on similar algorithmic solutions despite stark differences in neural circuit architectures. Finally, in land vertebrates a parallel olfactory pathway has evolved whose second-order neurons do not exhibit such diverse response curves; rather neurons in this pathway represent concentration information in a more monotonic fashion on average, potentially allowing for easier odor localization and identification at the expense of increased energy use. ### Competing Interest Statement The authors have declared no competing interest.

doi.org

⚡️ Excited to introduce ZAPBench, our #ICLR2025 spotlight: The Zebrafish Activity Prediction Benchmark measures progress in predicting neural activity within an entire vertebrate brain (70k+ neurons!) Explore interactive visualizations, datasets, code + paper: google-research.github.io/zapbench 🧠🧪

ZAPBench

ZAPBench evaluates how well different models can predict the activity of over 70,000 neurons in a novel larval zebrafish dataset.

google-research.github.io