Learning cortical representations through perturbed and adversarial dreaming
- University of Bern, Switzerland
Abstract
Humans and other animals learn to extract general concepts from sensory experience without extensive teaching. This ability is thought to be facilitated by offline states like sleep where previous experiences are systemically replayed. However, the characteristic creative nature of dreams suggests that learning semantic representations may go beyond merely replaying previous experiences. We support this hypothesis by implementing a cortical architecture inspired by generative adversarial networks (GANs). Learning in our model is organized across three different global brain states mimicking wakefulness, NREM and REM sleep, optimizing different, but complementary objective functions. We train the model on standard datasets of natural images and evaluate the quality of the learned representations. Our results suggest that generating new, virtual sensory inputs via adversarial dreaming during REM sleep is essential for extracting semantic concepts, while replaying episodic memories via perturbed dreaming during NREM sleep improves the robustness of latent representations. The model provides a new computational perspective on sleep states, memory replay and dreams and suggests a cortical implementation of GANs.
Data availability
The current manuscript is a computational study, so no data have been generated for this manuscript. Deep learning benchmark datasets (CIFAR-10 and SVHN) were used for the simulations.We published all code necessary to repeat our experiments in the following repository: https://github.com/NicoZenith/PAD
Article and author information
Author details
Funding
European Commission (604102)
- Mihai A Petrovici
- Walter Senn
- Jakob Jordan
European Commission (720270)
- Mihai A Petrovici
- Walter Senn
- Jakob Jordan
European Commission (785907)
- Mihai A Petrovici
- Walter Senn
- Jakob Jordan
European Commission (945539)
- Mihai A Petrovici
- Walter Senn
- Jakob Jordan
Universität Bern (Interfaculty Research Cooperation 'Decoding Sleep')
- Nicolas Deperrois
- Walter Senn
Universität Heidelberg (Manfred Stärk Foundation)
- Mihai A Petrovici
Swiss National Science Foundation (Sinergia Grant CRSII5-180316)
- Walter Senn
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Deperrois et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Learning cortical representations through perturbed and adversarial dreaming
eLife 11:e76384.
https://doi.org/10.7554/eLife.76384
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