ReviewFrontiers in neuroscience2014
Bayesian action&perception: representing the world in the brain.
Review in Frontiers in neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- OCD Compulsions as Aberrant Integration of Uncertainty from Local Goals to Global Goals.Computational psychiatry (Cambridge, Mass.) · 2026Article
- High-dimensional cortical signals reveal rich bimodal and working memory-like representations among S1 neuron populations.Communications biology · 2024Article
- Remembrance of things perceived: Adding thalamocortical function to artificial neural networks.Frontiers in integrative neuroscience · 2023Review
- Remote cortical perturbation dynamically changes the network solutions to given tactile inputs in neocortical neurons.iScience · 2022Article
- Developing Intelligent Robots that Grasp Affordance.Frontiers in robotics and AI · 2022Review
- It's in your hands: How variable perception affects grasping estimates in virtual reality.Psychonomic bulletin & review · 2021Article
- Learning to use Muscles.Journal of human kinetics · 2021Article
- Multi-structure Cortical States Deduced From Intracellular Representations of Fixed Tactile Input Patterns.Frontiers in cellular neuroscience · 2021Article
- Motor modules account for active perception of force.Scientific reports · 2019Article
- Article
- Intracellular Dynamics in Cuneate Nucleus Neurons Support Self-Stabilizing Learning of Generalizable Tactile Representations.Frontiers in cellular neuroscience · 2018Article
- Sensory Flow as a Basis for a Novel Distance Cue in Freely Behaving Electric Fish.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017Article
- The Representation of Objects in Apraxia: From Action Execution to Error Awareness.Frontiers in human neuroscience · 2016Review
- Lower neuronal variability in the monkey dorsolateral prefrontal than posterior parietal cortex.Journal of neurophysiology · 2015Article
- Emergence of Cognition from Action.Cold Spring Harbor symposia on quantitative biology · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Theories of perception seek to explain how sensory data are processed to identify previously experienced objects, but they usually do not consider the decisions and effort that goes into acquiring the sensory data. Identification of objects according to their tactile properties requires active exploratory movements. The sensory data thereby obtained depend on the details of those movements, which human subjects change rapidly and seemingly capriciously. Bayesian Exploration is an algorithm that uses prior experience to decide which next exploratory movement should provide the most useful data to disambiguate the most likely possibilities. In previous studies, a simple robot equipped with a biomimetic tactile sensor and operated according to Bayesian Exploration performed in a manner similar to and actually better than humans on a texture identification task. Expanding on this, "Bayesian Action&Perception" refers to the construction and querying of an associative memory of previously experienced entities containing both sensory data and the motor programs that elicited them. We hypothesize that this memory can be queried (i) to identify useful next exploratory movements during identification of an unknown entity ("action for perception") or (ii) to characterize whether an unknown entity is fit for purpose ("perception for action") or (iii) to recall what actions might be feasible for a known entity (Gibsonian affordance). The biomimetic design of this mechatronic system may provide insights into the neuronal basis of biological action and perception.
Indexed as
Identifiers
What OpenQuestion holds
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.