--- title: "Neuroscience — papers" description: "Neuroscience: 76 papers of the Elamur Research library · page 1 of 2 · 1–25, the most cited first — our summary of each, its ideas, references and who…" canonical: "https://research.elamur.ai/free/en/shelves/neuroscience/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/neuroscience/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / Neuroscience # 🧠 Neuroscience 76 papers · page 1 of 2 · 1–25 · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) The brain and the nervous system, from molecules to cognition. ## Subfields The sub-shelves of Neuroscience, the most papers first, with the two OpenAlex topics most of their papers here are on. 1. [**Cognitive Neuroscience**Neurobiology of Language and Bilingualism · EEG and Brain-Computer Interfaces*76 papers*](https://md.research.elamur.ai/free/en/shelves/neuroscience/cognitive-neuroscience/) ## Papers **1** [2](https://md.research.elamur.ai/free/en/shelves/neuroscience/page/2/) [next →](https://md.research.elamur.ai/free/en/shelves/neuroscience/page/2/) 1. [**FaceNet: A Unified Embedding for Face Recognition and Clustering**Florian Schroff, Dmitry Kalenichenko, James Philbin*2015 · 11,939 citations*](https://md.research.elamur.ai/free/en/papers/schroff-2015-facenet-unified-embedding-face-recognition/) 2. [**An Argument for Basic Emotions**Paul Ekman*1992 · 9,900 citations*](https://md.research.elamur.ai/free/en/papers/ekman-1992-argument-basic-emotions/) 3. [**A Probabilistic Earley Parser as a Psycholinguistic Model**John Hale*2001 · 1,448 citations*](https://md.research.elamur.ai/free/en/papers/hale-2001-probabilistic-earley-parser-as-psycholinguistic/) 4. [**Aligning AI With Shared Human Values**Dan Hendrycks, Collin Burns, Steven Basart, et al.*2020 · 382 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-aligning-ai-shared-human-values/) 5. [**Predictive power of word surprisal for reading times is a linear function of language model quality**Adam Goodkind, Klinton Bicknell*2018 · 294 citations*](https://md.research.elamur.ai/free/en/papers/goodkind-2018-predictive-power-word-surprisal-reading/) 6. [**Neural language models as psycholinguistic subjects: Representations of syntactic state**Richard Futrell, Ethan Wilcox, Takashi Morita, et al.*2019 · 291 citations*](https://md.research.elamur.ai/free/en/papers/futrell-2019-neural-language-models-as-psycholinguistic/) 7. [**What do RNN Language Models Learn about Filler-Gap Dependencies?**Ethan Wilcox, Roger Levy, Takashi Morita, et al.*2018 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wilcox-2018-rnn-language-models-learn-about/) 8. [**A Maximum Entropy Model for Prepositional Phrase Attachment**Adwait Ratnaparkhi, Jeff Reynar, Salim Roukos*1994 · 276 citations*](https://md.research.elamur.ai/free/en/papers/ratnaparkhi-1994-maximum-entropy-model-prepositional-phrase/) 9. [**HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 264 citations*](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/) 10. [**Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?**Byung-Doh Oh, William Schuler*2023 · 211 citations*](https://md.research.elamur.ai/free/en/papers/oh-2023-why-does-surprisal-larger-transformer/) 11. [**Testing the Predictions of Surprisal Theory in 11 Languages**Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/) 12. [**Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models**Tianyi Tang, Wenyang Luo, Haoyang Huang, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-language-specific-neurons-key-multilingual/) 13. [**SyntaxGym: An Online Platform for Targeted Evaluation of Language Models**Jon Gauthier, Jennifer Hu, Ethan Wilcox, et al.*2020 · 145 citations*](https://md.research.elamur.ai/free/en/papers/gauthier-2020-syntaxgym-online-platform-targeted-evaluation/) 14. [**MorphoLex: A derivational morphological database for 70,000 English words**Claudia H. Sánchez-Gutiérrez, Hugo Mailhot, S. Hélène Deacon, et al.*2018 · 115 citations*](https://md.research.elamur.ai/free/en/papers/gutierrez-2018-sanchezgutierrez-morpholex/) 15. [**Missing objects in Hebrew: Argument ellipsis, not VP ellipsis**Idan Landau*2018 · 89 citations*](https://md.research.elamur.ai/free/en/papers/landau-2018-missing-objects-hebrew-argument-ellipsis/) 16. [**RNNs as psycholinguistic subjects: Syntactic state and grammatical dependency**Richard Futrell, Ethan Wilcox, Takashi Morita, et al.*2018 · 75 citations*](https://md.research.elamur.ai/free/en/papers/futrell-2018-rnns-psycholinguistic-subjects-syntactic-state/) 17. [**Anticausatives are semantically reflexive in Norwegian, but not in English**Björn Lundquist, Martin Corley, Mai Tungseth, et al.*2016 · 41 citations*](https://md.research.elamur.ai/free/en/papers/lundquist-2016-anticausatives-are-semantically-reflexive-norwegian/) 18. [**No case for Case in locality: Case does not help interpretation when intervention blocks A-bar chains**Naama Friedmann, Luigi Rizzi, Adriana Belletti*2017 · 37 citations*](https://md.research.elamur.ai/free/en/papers/friedmann-2017-no-case-case-locality-case/) 19. [**A Quantitative Model of Word Order and Movement in English, Dutch and German Complement Constructions**Karin Harbusch, Gerard Kempen*2002 · 30 citations*](https://md.research.elamur.ai/free/en/papers/harbusch-2002-quantitative-model-word-order-movement/) 20. [**A closer look at the performance of neural language models on reflexive anaphor licensing**Jennifer Hu, Sherry Yong Chen, Roger Levy*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/hu-2020-closer-look-performance-neural-language/) 21. [**On the Proper Treatment of Tokenization in Psycholinguistics**Mario Giulianelli, Luca Malagutti, Juan Luis Gastaldi, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/giulianelli-2024-proper-treatment-tokenization-psycholinguistics/) 22. [**UniCoRN: Unified Cognitive Signal ReconstructioN bridging cognitive signals and human language**Nuwa Xi, Sendong Zhao, Haochun Wang, et al.*2023 · 23 citations*](https://md.research.elamur.ai/free/en/papers/xi-2023-unicorn-unified-cognitive-signal-reconstruction/) 23. [**Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection**Maria Corkery, Yevgen Matusevych, Sharon Goldwater*2019 · 22 citations*](https://md.research.elamur.ai/free/en/papers/corkery-2019-are-we-there-yet-encoder/) 24. [**Adjectival polarity and the processing of scalar inferences**Bob van Tiel, Elizabeth Pankratz*2021 · 21 citations*](https://md.research.elamur.ai/free/en/papers/tiel-2021-adjectival-polarity-processing-scalar-inferences/) 25. [**Stages rather than ages in the acquisition of movement structures: Data from sentence repetition and 27,696 spontaneous clauses**Naama Friedmann, Julia Reznick*2021 · 18 citations*](https://md.research.elamur.ai/free/en/papers/friedmann-2021-stages-rather-than-ages-acquisition/) **1** [2](https://md.research.elamur.ai/free/en/shelves/neuroscience/page/2/) [next →](https://md.research.elamur.ai/free/en/shelves/neuroscience/page/2/) Updated 23 October 2026 - [← previous shelf Medicine](https://md.research.elamur.ai/free/en/shelves/medicine/) - [next shelf → Nursing](https://md.research.elamur.ai/free/en/shelves/nursing/) - [↑ back to shelves](https://md.research.elamur.ai/free/en/shelves/)