ReviewPatterns (New York, N.Y.)2021
The overfitted brain: Dreams evolved to assist generalization.
Review in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- The exploration of consciousness in insects.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2025Review
- Investigating dreams by strategically presenting sounds during REM sleep to reactivate waking experiences.Neuropsychologia · 2025Article
- Article
- On the varieties of conscious experiences: Altered Beliefs Under Psychedelics (ALBUS).Neuroscience of consciousness · 2025Article
- REM refines and rescues memory representations: a new theory.Sleep advances : a journal of the Sleep Research Society · 2025Review
- Unlocking Dreams and Dreamless Sleep: Machine Learning Classification With Optimal EEG Channels.BioMed research international · 2025Article
- From high- to low-density EEG for automatic classification of dream experiences during stage 2 of NREM.Sleep advances : a journal of the Sleep Research Society · 2025Article
- Abrupt and spontaneous strategy switches emerge in simple regularised neural networks.PLoS computational biology · 2024Article
- Dreams: The Mind's Minecraft.Cureus · 2024Article
- Neurosurgery for mental conditions and pain: An historical perspective on the limits of biological determinism.Surgical neurology international · 2024Review
- A role for cortical interneurons as adversarial discriminators.PLoS computational biology · 2023Article
- The developmental trajectory of object recognition robustness: Children are like small adults but unlike big deep neural networks.Journal of vision · 2023Article
- Adult neurogenesis acts as a neural regularizer.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Article
- Artificial intelligence insights into hippocampal processing.Frontiers in computational neuroscience · 2022Article
- Grounding deep neural network predictions of human categorization behavior in understandable functional features: The case of face identity.Patterns (New York, N.Y.) · 2021Article
- The overfitted brain hypothesis.Patterns (New York, N.Y.) · 2021Article
- Relationship Between Epilepsy and Dreaming: Current Knowledge, Hypotheses, and Perspectives.Frontiers in neuroscience · 2021Review
- Balancing Prediction and Surprise: A Role for Active Sleep at the Dawn of Consciousness?Frontiers in systems neuroscience · 2021Article
- Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K'iche'.Open research Europe · 2021Article
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Authors and funding
1 author.
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No grant is acknowledged in the PubMed record.
Abstract
Understanding of the evolved biological function of sleep has advanced considerably in the past decade. However, no equivalent understanding of dreams has emerged. Contemporary neuroscientific theories often view dreams as epiphenomena, and many of the proposals for their biological function are contradicted by the phenomenology of dreams themselves. Now, the recent advent of deep neural networks (DNNs) has finally provided the novel conceptual framework within which to understand the evolved function of dreams. Notably, all DNNs face the issue of overfitting as they learn, which is when performance on one dataset increases but the network's performance fails to generalize (often measured by the divergence of performance on training versus testing datasets). This ubiquitous problem in DNNs is often solved by modelers via "noise injections" in the form of noisy or corrupted inputs. The goal of this paper is to argue that the brain faces a similar challenge of overfitting and that nightly dreams evolved to combat the brain's overfitting during its daily learning. That is, dreams are a biological mechanism for increasing generalizability via the creation of corrupted sensory inputs from stochastic activity across the hierarchy of neural structures. Sleep loss, specifically dream loss, leads to an overfitted brain that can still memorize and learn but fails to generalize appropriately. Herein this "overfitted brain hypothesis" is explicitly developed and then compared and contrasted with existing contemporary neuroscientific theories of dreams. Existing evidence for the hypothesis is surveyed within both neuroscience and deep learning, and a set of testable predictions is put forward that can be pursued both
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.