ArticleNature communications2023
Experimental validation of the free-energy principle with in vitro neural networks.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- A Perovskite Memdiode-Based Neuromorphic in Silico Surrogate Model for Emulating Predictive Coding Failure in Diabetic Neuropathy.Neuroinformatics · 2026Article
- Predictive processing as a scalable computational principle for embodied multitask intelligence.Science advances · 2026Article
- An energy-gradient theory of embedded predictions in the brain.AIMS neuroscience · 2026Article
- A Rosetta Stone hypothesis for neurophenomenology: mathematical predictions from predictive processing.Neuroscience of consciousness · 2026Article
- The Geometric Signatures of Brain State Transitions: Recursive Informational Curvature Reveals Hidden Dynamics in Primate Cortex.Neuroscience insights · 2026Article
- A cybernetic framework for synthetic biological intelligence in the era of neural tissue engineering.Npj unconventional computing · 2026Review
- Biomimetic Visual Information Spatiotemporal Encoding Method for In Vitro Biological Neural Networks.Biomimetics (Basel, Switzerland) · 2025Article
- Starting a synthetic biological intelligence lab from scratch.Patterns (New York, N.Y.) · 2025Review
- A Computational Account of the Development and Evolution of Psychotic Symptoms.Biological psychiatry · 2025Review
- Neuronal Electrical Activity in Neuronal Networks Induced by a Focused Femtosecond Laser.ACS omega · 2025Article
- Deviance detection and regularity sensitivity in dissociated neuronal cultures.Frontiers in neural circuits · 2025Article
- Formalizing Lacanian psychoanalysis through the free energy principle.Frontiers in psychology · 2025Article
- A hierarchical active inference model of spatial alternation tasks and the hippocampal-prefrontal circuit.Nature communications · 2024Article
- On Predictive Planning and Counterfactual Learning in Active Inference.Entropy (Basel, Switzerland) · 2024Article
- Article
- Experimental validation of the free-energy principle with in vitro neural networks.Nature communications · 2023Article
- Closing the box.Cognitive neuroscienceArticle
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4 authors.
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Abstract
Empirical applications of the free-energy principle are not straightforward because they entail a commitment to a particular process theory, especially at the cellular and synaptic levels. Using a recently established reverse engineering technique, we confirm the quantitative predictions of the free-energy principle using in vitro networks of rat cortical neurons that perform causal inference. Upon receiving electrical stimuli-generated by mixing two hidden sources-neurons self-organised to selectively encode the two sources. Pharmacological up- and downregulation of network excitability disrupted the ensuing inference, consistent with changes in prior beliefs about hidden sources. As predicted, changes in effective synaptic connectivity reduced variational free energy, where the connection strengths encoded parameters of the generative model. In short, we show that variational free energy minimisation can quantitatively predict the self-organisation of neuronal networks, in terms of their responses and plasticity. These results demonstrate the applicability of the free-energy principle to in vitro neural networks and establish its predictive validity in this setting.
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