:Draft:Gabriel Kreiman

Kreiman was born in Buenos Aires in December 1971. He received a Licenciado (B.S.) in physical chemistry from the University of Buenos Aires in 1996, followed by an M.S. in computation and neural systems and a Ph.D. in biology (2002) from the California Institute of Technology, supervised by Christof Koch. His dissertation examined neuron‑level correlates of visual awareness in humans.{{cite thesis |type=Ph.D. |title=On the neuronal activity in the human brain during visual recognition, imagery and binocular rivalry |author=Gabriel Kreiman |publisher=California Institute of Technology |year=2002}} After post‑doctoral work with Tomaso Poggio at MIT, he joined Harvard Medical School in 2006.

Using intracranial recordings from epilepsy patients, Kreiman and colleagues showed that individual neurons in the human medial temporal lobe respond selectively and invariantly to complex stimuli such as faces or landmarks.{{cite journal |last1=Kreiman |first1=G. |last2=Koch |first2=C. |last3=Fried |first3=I. |title=Category‑specific visual responses of single neurons in the human medial temporal lobe |journal=Nature Neuroscience |volume=3 |issue=9 |pages=946–953 |year=2000 |doi=10.1038/78868 |pmid=10966627}} Subsequent work with macaques and humans examined how neuronal populations encode visual information during natural viewing and memory retrieval.{{cite journal |last1=Quiroga |first1=R.Q. |last2=Reddy |first2=L. |last3=Kreiman |first3=G. |last4=Koch |first4=C. |last5=Fried |first5=I. |title=Invariant visual representation by single neurons in the human brain |journal=Nature |volume=435 |issue=7045 |pages=1102–1107 |year=2005 |doi=10.1038/nature03687 |pmid=15973409|bibcode=2005Natur.435.1102Q |url=https://resolver.caltech.edu/CaltechAUTHORS:20130816-103222719 }}

With William Lotter and David Cox, Kreiman introduced PredNet, a recurrent deep‑learning architecture trained to predict future video frames.{{cite arXiv |title=Deep predictive coding networks for video prediction and unsupervised learning |eprint=1605.08104 |year=2016 |author1=Lotter, W. |author2=Kreiman, G. |author3=Cox, D.|class=cs.LG }}{{cite magazine |last=Ananthaswamy |first=Anil |title=To Be Energy‑Efficient, Brains Predict Their Perceptions |url=https://www.quantamagazine.org/to-be-energy-efficient-brains-predict-their-perceptions-20211115/ |magazine=Quanta Magazine |date=November 15, 2021 |access-date=17 April 2025}}{{cite magazine |last=Ananthaswamy |first=Anil |title=Your Brain Is an Energy‑Efficient "Prediction Machine" |url=https://www.wired.com/story/your-brain-is-an-energy-efficient-prediction-machine/ |magazine=Wired |date=November 28, 2021 |access-date=17 April 2025}} His group has also proposed hippocampally inspired continual‑learning algorithms intended to mitigate catastrophic forgetting in artificial networks.{{cite arXiv |title=Sparse Distributed Memory for Continual Learning |eprint=1912.04783 |year=2023 |author1=Tadros, T. |author2=Krishnan, G.P. |author3=Ramyaa, R. |author4=Kreiman, G.|class=cs.LG }}

The Kreiman laboratory has reported "boundary" cells in the hippocampus that fire at transitions between remembered events, a finding proposed as a mechanism for segmenting experience.{{cite journal |last1=Zheng |first1=J. |last2=Kreiman |first2=G. |last3=Rutishauser |first3=U. |title=Neurons detect cognitive boundaries to structure episodic memories in humans |journal=Nature Neuroscience |volume=25 |issue=3 |pages=358–368 |year=2022 |doi=10.1038/s41593-022-01020-w |pmid=35260859|pmc=8966433 }}

• NIH Director's New Innovator Award (2009–2014){{cite press release |title=NIH announces 115 awards to encourage high‑risk research and innovation |publisher=National Institutes of Health |date=September 24, 2009 |url=https://www.nih.gov/news-events/news-releases/nih-announces-115-awards-encourage-high-risk-research-innovation |access-date=17 April 2025}}
• NSF CAREER Award (2010–2014){{cite web |title=Faculty Early Career Development (CAREER) Program – Award list |url=https://www.nsf.gov |website=National Science Foundation |access-date=17 April 2025}}
• Pisart Award for Vision Research (2015){{cite web |title=Past Pisart Award Recipients |url=https://lighthouseguild.org/research/vision-science-awards/pisart-award-in-vision-science/past-pisart-award-recipients/ |website=Lighthouse Guild |access-date=17 April 2025}}
• McKnight Scholar Award (2017){{cite web |title=McKnight Memory and Cognitive Disorders Awardees |url=https://www.mcknight.org/programs/the-mcknight-endowment-fund-for-neuroscience/memory-cognitive-disorders-awards/awardees/ |website=McKnight Foundation |access-date=17 April 2025}}
• Society for Neuroscience Career Development Award (2010){{cite web |title=Society for Neuroscience announces CDA recipients |url=https://www.sfn.org |website=Society for Neuroscience |access-date=17 April 2025}}
• Klingenstein Fund Award (2007){{cite web |title= Klingenstein Philanthrophies Fellowship Awards |url=https://klingenstein.org/esther-a-joseph-klingenstein-fund/neuroscience/fellowship-programs-2/ |access-date=19 April 2025}}
• Milton and Francis Clauser Doctoral Prize (2002) {{cite web |title= Milton and Francis Clauser Doctoral Prize Recipients|url=https://gradoffice.caltech.edu/documents/6410/clauser_winners_2018.pdf |access-date=19 April 2025}}
• Lawrence L. and Audrey W. Ferguson Prize (2002) {{cite thesis |title= Caltech Theses|date=2002 |doi=10.7907/E0XZ-QP78 |url=https://thesis.library.caltech.edu/2075/ |access-date=19 April 2025 |last1=Kreiman |first1=Gabriel Alejandro |publisher=California Institute of Technology }}

• Kreiman, G.; Koch, C.; Fried, I. (2000). "Category‑specific visual responses of single neurons in the human medial temporal lobe." Nature Neuroscience, 3(9), 946–953.
• Hung, C.P.; Kreiman, G.; Poggio, T.; DiCarlo, J.J. (2005). "Fast readout of object identity from macaque inferior temporal cortex." Science, 310(5749), 863–866.
• Lotter, W.; Kreiman, G.; Cox, D. (2016). "Deep predictive coding networks for video prediction and unsupervised learning." arXiv:1605.08104.
• Zheng, J.; Kreiman, G.; Rutishauser, U.; et al. (2022). "Neurons detect cognitive boundaries to structure episodic memories in humans." Nature Neuroscience, 25(3), 358–368.

A complete list of Gabriel Kreiman's publications can be found on his research group's website [http://klab.tch.harvard.edu/ Gabriel Kreiman's Lab at Harvard University]

A 2019 collaboration between Kreiman, Carlos Ponce, and Margaret Livingstone on AI‑generated images that strongly activate monkey face‑processing neurons was reported by Science{{cite news |last=Underwood |first=Emily |title=Artificial intelligence created these bizarre faces—and monkey neurons love them |url=https://www.science.org/content/article/artificial-intelligence-created-these-bizarre-faces-and-monkey-neurons-love-them |work=Science |date=May 2, 2019 |access-date=17 April 2025}} and The Atlantic{{cite news |last=Yong |first=Ed |title=AI evolved creepy images to please a monkey's brain |url=https://www.theatlantic.com/science/archive/2019/05/ai-evolved-these-trippy-images-to-please-a-monkeys-neurons/588517/ |work=The Atlantic |date=May 2, 2019 |access-date=17 April 2025}}. The work was also discussed in Wired and Quanta Magazine, and covered on Science Friday{{cite news |last=Science Friday Staff |title=Neuroscientists Peer Into the Mind's Eye |url=https://www.sciencefriday.com/segments/neuroscientists-peer-into-the-minds-eye/ |work=Science Friday |date=May 3, 2019 |access-date=17 April 2025}}.

• {{Official website|https://klab.tch.harvard.edu|Kreiman Laboratory}}
• {{Google Scholar id|WxZ_6nsAAAAJ}}

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