ArticlePLoS computational biology2022
A normative model of peripersonal space encoding as performing impact prediction.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- From peripersonal space to cognitive maps: An evolutionary perspective.Progress in neurobiology · 2026Review
- Embodied Neuropsychodynamics of the Relational Self Across Space and Time: An Integrative Narrative Review.Brain sciences · 2026Review
- Global remapping of the sensory homunculus emerges early in childhood development.Nature communications · 2026Article
- No effect of the short-term learning of object trajectories on multisensory perception within the peripersonal space.Attention, perception & psychophysics · 2026Article
- Modulation of auditory peripersonal space by approaching and receding sources moving in discrete trajectories.Attention, perception & psychophysics · 2025Article
- Computational models of peripersonal space representation.Physics of life reviews · 2025Review
- Egocentric value maps of the near-body environment.Nature neuroscience · 2025Article
- Peripersonal space: why so last-second?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurately predicting contact between our bodies and environmental objects is paramount to our evolutionary survival. It has been hypothesized that multisensory neurons responding both to touch on the body, and to auditory or visual stimuli occurring near them-thus delineating our peripersonal space (PPS)-may be a critical player in this computation. However, we lack a normative account (i.e., a model specifying how we ought to compute) linking impact prediction and PPS encoding. Here, we leverage Bayesian Decision Theory to develop such a model and show that it recapitulates many of the characteristics of PPS. Namely, a normative model of impact prediction (i) delineates a graded boundary between near and far space, (ii) demonstrates an enlargement of PPS as the speed of incoming stimuli increases, (iii) shows stronger contact prediction for looming than receding stimuli-but critically is still present for receding stimuli when observation uncertainty is non-zero-, (iv) scales with the value we attribute to environmental objects, and finally (v) can account for the differing sizes of PPS for different body parts. Together, these modeling results support the conjecture that PPS reflects the computation of impact prediction, and make a number of testable predictions for future empirical studies.
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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.