ReviewNeuroscience and biobehavioral reviews2017
Deep temporal models and active inference.
Review in Neuroscience and biobehavioral reviews, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 90 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
90 citing papers in PubMed.
- A neurocognitive account of complex PTSD: self-modelling, affective dysregulation, and implications for MDMA-assisted and targeted psychotherapies.European journal of psychotraumatology · 2026Review
- Active inference with reusable state-dependent value profiles.Biological cybernetics · 2026Article
- Active inference and artificial reasoning.Nature communications · 2026Article
- Prediction, pain, and the power of context: toward a contemporary identity for the chiropractic profession.Chiropractic & manual therapies · 2026Review
- Limb apraxia and active inference in the visuomotor pathways.Psychonomic bulletin & review · 2026Review
- The active construction of past episodes.Translational neuroscience · 2026Article
- Music-induced emotion as controlled hallucination: an active interoceptive inference account.Frontiers in psychology · 2026Article
- From self-organizing systems to subjective temporal extension.Neuroscience of consciousness · 2026Article
- When prediction fails: a computational complexity view of stress.Frontiers in veterinary science · 2026Article
- Towards an active inference account of deep meditative deconstruction.Neuroscience of consciousness · 2026Article
- The neurobiology of human sequential signal prediction: Insights from language, music, and mathematics.Neuroscience research · 2026Review
- Decision-Making in Repeated Games: Insights from Active Inference.Behavioral sciences (Basel, Switzerland) · 2025Review
- Five Fristonian Formulae.Entropy (Basel, Switzerland) · 2025Article
- SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025Review
- Embodied decisions as active inference.PLoS computational biology · 2025Article
- Deep Hybrid Models: Infer and Plan in a Dynamic World.Entropy (Basel, Switzerland) · 2025Article
- As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference.Entropy (Basel, Switzerland) · 2025Article
- Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models.Entropy (Basel, Switzerland) · 2025Article
- From pixels to planning: scale-free active inference.Frontiers in network physiology · 2025Article
- Mechanisms of brain self-regulation: psychological factors, mechanistic models and neural substrates.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
30 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
How do we navigate a deeply structured world? Why are you reading this sentence first - and did you actually look at the fifth word? This review offers some answers by appealing to active inference based on deep temporal models. It builds on previous formulations of active inference to simulate behavioural and electrophysiological responses under hierarchical generative models of state transitions. Inverting these models corresponds to sequential inference, such that the state at any hierarchical level entails a sequence of transitions in the level below. The deep temporal aspect of these models means that evidence is accumulated over nested time scales, enabling inferences about narratives (i.e., temporal scenes). We illustrate this behaviour with Bayesian belief updating - and neuronal process theories - to simulate the epistemic foraging seen in reading. These simulations reproduce perisaccadic delay period activity and local field potentials seen empirically. Finally, we exploit the deep structure of these models to simulate responses to local (e.g., font type) and global (e.g., semantic) violations; reproducing mismatch negativity and P300 responses respectively.
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Registered trials
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.