Neural correlates of consciousness: progress and problems
Nature reviews. Neuroscience April 20, 2016 Christof Koch, Marcello Massimini, Mélanie Boly et al. 1,654 citations
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Christof Koch
Allen Institute, Seattle, WA 98109, USA; Tiny Blue Dot Foundation, Santa Monica, CA 90401, USA. Electronic address: christofk@alleninstitute.org.
10 papers in the library · 3,222 citations · publishing 2002-2026
Papers
Neural correlates of consciousness in humans
Nature reviews. Neuroscience April 1, 2002 Geraint Rees, Gabriel Kreiman, Christof Koch 742 citations
No Summary
The Neural Correlates of Consciousness
Annals of the New York Academy of Sciences March 1, 2008 Giulio Tononi, Christof Koch 615 citations
This review synthesizes recent findings on the neural correlates of consciousness, distinguishing consciousness from other brain functions. It examines global changes in consciousness during sleep, anesthesia, and seizures, then explores paradigms for studying neural correlates of specific conscious percepts, highlighting the roles of different brain regions. Dynamic aspects of neural activity—sustained versus phasic, feedforward versus reentrant, and neural synchronization—are discussed. The review also considers how theoretical analysis of consciousness's fundamental properties can complement neurobiological research.
Neural correlates of consciousness
Scholarpedia January 1, 2007 Florian Mormann, Christof Koch 154 citations
Consciousness is a puzzling property of complex biological systems that depends on their state. The central question is how immaterial conscious mental states relate to physical brain states. Scientists are using various empirical approaches to investigate the neural basis of consciousness. This article reviews those approaches and summarizes what has been learned so far.
Are the neural correlates of consciousness in the front or in the back of the cerebral cortex? Clinical and neuroimaging evidence
bioRxiv Preprint Server March 19, 2017 Melanie Boly, Marcello Massimini, Naotsugu Tsychiya et al. 56 citations preprint
The role of the frontal cortex in consciousness is debated. This perspective critically reviews clinical and neuroimaging evidence on whether the front or back of the cortex specifies conscious contents, and discusses promising research avenues. The authors argue that current evidence does not clearly support a primary role for the frontal cortex in generating conscious experience, pointing instead to posterior regions as more directly involved. They suggest that future research should focus on distinguishing neural correlates of consciousness from prerequisites and consequences.
The void and the brain.
Cell reports July 22, 2025 Christof Koch 1 citation
Inhaling a high dose of the psychedelic 5-methoxy-N,N-dimethyltryptamine profoundly slows down brain activity, but unlike other psychedelics, it does not significantly reduce alpha band power in the electroencephalogram.
Pupil-DLC: An open-source deep learning pipeline for scalable, marker-less tracking of pupil dynamics across conscious and unconscious states.
Journal of neuroscience methods July 4, 2026 Parsa Seyfourian, Lydia C Marks, Leslie D Claar et al.
Pupil diameter is a non-invasive biomarker of brain state, correlating with arousal, attention, cognitive processing, and consciousness. Existing pupillometry software often lacks scalability and robustness across diverse experimental conditions and species. Pupil-DLC is an open-source, offline, DeepLabCut-based pipeline for scalable, marker-less pupil tracking, primarily designed for mice. Trained on 21,909 manually annotated frames from over 140 videos of head-fixed mice spanning wakefulness and drug-induced states, including psychedelics and anesthesia, the dataset was deliberately selected to maximize pupil size variability and model generalization.
Transition to chaos separates learning regimes and relates to measure of consciousness in recurrent neural networks
bioRxiv Preprint Server May 15, 2024 Dana Mastrovito, Yuhan Helena Liu, Lukasz Kusmierz et al. preprint
The critical coupling strength that separates chaotic from ordered dynamics in recurrent neural networks also differentiates two learning strategies: networks initialized with low coupling learn rich representations, while those with larger variance learn lazier solutions. Training moves both stable and chaotic networks closer to the edge of chaos. Biologically realistic connectivity fosters stability across a wide range of variances. The transition to chaos is reflected in the perturbational complexity index (PCIst), a measure that clinically discriminates levels of consciousness. Networks with high PCIst exhibit stable dynamics and rich learning, suggesting a consciousness prior may promote rich learning. The results indicate a relationship between critical dynamics, learning regimes, and complexity-based measures of consciousness.
An adversarial collaboration to critically evaluate theories of consciousness
bioRxiv Preprint Server June 23, 2023 Oscar Ferrante, Urszula Gorska-Klimowska, Simon Henin et al. preprint
An open science adversarial collaboration directly juxtaposed Integrated Information Theory (IIT) and Global Neuronal Workspace Theory (GNWT) by investigating neural correlates of visual experience. 256 human subjects viewed suprathreshold stimuli for variable durations while neural activity was measured with fMRI, MEG, and ECoG. Information about conscious content was found in visual, ventro-temporal, and inferior frontal cortex, with sustained responses in occipital and lateral temporal cortex reflecting stimulus duration, and content-specific synchronization between frontal and early visual areas.
Consciousness: Here, There but Not Everywhere
arXiv Preprint Archive May 27, 2014 Giulio Tononi, Christof Koch
Integrated Information Theory (IIT) starts from five axioms about conscious experience—existence, composition, information, integration, and exclusion—to derive physical postulates that specify which systems can be conscious and what their experience is like. IIT provides a calculus to measure both the quantity and quality of experience, explains clinical and laboratory findings, and makes testable predictions. It holds that consciousness is graded, common among biological organisms, and present even in some simple systems, but not in everything: groups of individuals or feedforward networks lack it. Crucially, IIT implies that digital computers, even those that perfectly simulate human behavior or brain function, would experience next to nothing, contradicting functionalist views.