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Kreiman Lab News

Towards understanding real-world episodic memory formation

Memory, Cognition and In Between

In memoriam: Fani Adelmann

Tel Aviv, March 24, 2022

See also:

Zheng J, Schjetnan AGP, Yebra M, Mosher C, Kalia S, Valiante TA, Mamelak A, Kreiman G, Rutishauser U (2021). Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation. Nature Neuroscience 25:358-368 PDF

Misra P, Marconi A, Petterson M, Kreiman G. (2018) Minimal memory for details in real-life events. Scientific Reports, 8, 16701. PDF

Tang H, Singer J, Ison M, Pivazyan G, Romaine M, Frias R, Meller E, Boulin A, Carroll JD, Perron V, Dowcett S, Arlellano M, Kreiman G. (2016). Predicting episodic memory formation for movie events. Scientific Reports, 6:30175. PDF

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Kreiman Lab News

PredNet: A deep neural network architecture for predictive coding

Bill Lotter explains the PredNet neural network architecture

See publication:
Lotter W, Kreiman G, Cox D. (2020) A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception. Nature Machine Intelligence, 2:210-219 PDF

See also:

Tang H, Schrimpf M, Lotter W, Moerman C, Paredes A, Ortega Caro J, Hardesty W, Cox D, Kreiman G. (2018) Recurrent computations for visual pattern completion. PNAS, 115:8835-8840. PDF

Lotter W, Kreiman, G, Cox, D. (2017) Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning. International Conference on Learning Representations (ICLR), Toulon, France. PDF

Lotter, W, Kreiman, G, Cox, D. (2016.) Unsupervised representation learning using predictive generative works. International Conference on Learning Representations (ICLR), Puerto Rico. PDF

GitHub Page

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Kreiman Lab News

Congratulations to Jay Chandra on this thesis!

Jay Chandra

Classification of Continuous Natural Human Behavior Using Intracranial Field Potential. Jay Chandra. Harvard University (2022). 

Read his thesis here.

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Kreiman Lab News

Congratulations to Ahmed Zergham on this thesis!

Biologically-inspired deep predictive learning for episodic memory event segmentation. Zergham Ahmed. Harvard University (2022).

Read his thesis here.

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Kreiman Lab News

Congratulations to Camille Gollety on her thesis!

Camille Gollety
Camille Gollety

Neuronal correlates of rapid learning in a human visual memory task. Camille Gollety. Ecole Polytechnique Federale de Lausanne (EPFL) (2022). 

Read her thesis here.