Uri Hasson
neurobiologist
Facts
11 properties- Instance of
- human
- Date of birth
- 1972
- Occupation
- neurobiologist, psychologist
- Employer
- Princeton University[5]
- Field of work
- cognitive neuroscience[4]
- Educated at
- Weizmann Institute of Science
- Doctoral advisor
- Rafael Malach[6]
- Different from
- Uri Hasson[10]
🏷️ Also known as
en Uri Hasson
he אורי חסון
🔖 Identifiers · 15
- ISNI
- 0000000044784485
- ORCID iD
- 0000-0002-3599-7168
- VIAF cluster ID
- 71101174
- Library of Congress authority ID
- no2004045693
- GND ID
- 138601933
- OpenAlex ID
- A5067264638, A5141241181as of 2026-09-23
where from?
- Source
- OpenAlex
- Edition
- 20260923 · as of 2026-09-23
- Licence
- CC0 1.0 Universal
- Bronze
- not in the catalog
- Transform
- 4ort-mint · openalex:20260923 · version not recorded
- Academic Tree ID
- 2967
- Canadiana Name Authority ID
- ncf13675506
- DBLP author ID
- 66/8267
- DDB person (GND) ID
- 138601933
- Google Scholar author ID
- VRw8v4kAAAAJ, QTWWp4MAAAAJ
- National Library of Israel J9U ID
- 987007455073205171
Show all 15 identifiers +3
- Nationale Thesaurus voor Auteursnamen ID
- 225908239
- TED speaker ID
- uri_hasson
- WorldCat Entities ID
- E39PCjG86Cf87YyKVGgBX8kpbm
📚 Sources · 1
📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 23
Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns,
Amplification of local changes along the timescale processing hierarchy,
A neural network model of when to retrieve and encode episodic memories,
A reduced-dimension fMRI shared response model,
A unified acoustic-to-speech-to-language embedding space captures the neural basis of natural language processing in everyday conversations,
Bayesian Surprise Predicts Human Event Segmentation in Story Listening,
BrainIAK: The Brain Imaging Analysis Kit,
Consensus-building conversation leads to neural alignment
+15 more
← Authored by 23
Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns,
Amplification of local changes along the timescale processing hierarchy,
A neural network model of when to retrieve and encode episodic memories,
A reduced-dimension fMRI shared response model,
A unified acoustic-to-speech-to-language embedding space captures the neural basis of natural language processing in everyday conversations,
Bayesian Surprise Predicts Human Event Segmentation in Story Listening,
BrainIAK: The Brain Imaging Analysis Kit,
Consensus-building conversation leads to neural alignment
+15 more
Affiliated with 4
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