Understanding how the brain supports flexible, goal-directed behavior is a central aim of neuroscience. Yet such behavior is highly variable and unfolds over long timescales, making it challenging to understand its organization. Advances in behavioral tracking quantify movements but do not reveal the objectives that gu...
Aditi Jha, Keyue Sky Shi, Kara A. Fulton et al.· bioRxiv· 0 citations
Distillation has become a core primitive of large language model training, but its properties are not yet well understood. We take an entropic perspective, studying how the entropy of the student depends on the data and the divergence that define the distillation objective. We prove that forward KL inflates the entropy...
The serotonin system innervates nearly the entire brain to support diverse functions, and its dysfunction is implicated in multiple psychiatric disorders. Although recent studies suggested that this anatomically diffuse system supports differentiated rather than uniform modulation, its overall organization is unclear....
Jun H. Song, Drew Friedmann, Yun-Ming Wu et al.· Cell· 1 citation
Designing expressive sequence layers with efficient inference remains a central challenge in modern machine learning. Standard softmax attention achieves excellent sequence modeling performance through rich nonlinear token interactions, but it requires a key-value cache that grows linearly with sequence length, limitin...
Hyun Dong Lee, X. Gonzalez, Nicolas Zucchet et al.· 0 citations
It is shown that the serotonin projectome is organized by functional relatedness rather than physical proximity of its targets, and projectomic identity emerges as a central axis linking axon collateralization, molecular diversity, and behavioral function.
Jun H. Song, Drew Friedmann, Yun-Ming Wu et al.· bioRxiv· 0 citations
Excitatory (E) and inhibitory (I) neural populations interact within and across distributed regions to support brain function, yet local and distributed E and I dynamics during naturalistic behavior remain unknown. To address this gap, we developed a dual-color multisite spectrally- resolved fiber photometry platform t...
Nicholas K. Branigan, T. Nghiem, T. Chao et al.· bioRxiv· 0 citations
Multi-compartment Hodgkin-Huxley (HH) models provide a principled framework for predicting neural dynamics and responses to electrical stimulation. However, fitting HH biophysical parameters typically requires intracellular recordings, which are invasive and low-throughput, limiting the ability to capture the geometry...
A. Lotlikar, Ian-Christopher Tanoh, Praful K. Vasireddy et al.· 0 citations
This work identifies a curse of ambiguity: in large language models, and more broadly in all neural networks that produce discrete probability distributions, the more ambiguous a next-token distribution is, the harder it is to learn accurately.
Nicolas Zucchet, Hyun Dong Lee, Scott W. Linderman· 2 citations
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