{"title":"A never-ending prediction: meta-prediction, counter-oscillatory system and traumatic affordance","authors":"Clémence Ortega Douville","doi":"10.1016/j.biosystems.2025.105508","DOIUrl":null,"url":null,"abstract":"<div><div>This article comes back on the hypothesis developed by the evolutionary theory of the sensorimotor paradox that our capacity to produce mental representation could be derived from a dissociation of sensory prediction systems from motor action. As they should be then coordinated together, we are drawing further possible leads regarding the intermediary space between linear mental projections that are not bound and stopped by sensory feedback, and ongoing sensory perception whether large or discrete. Dissociated prediction would be eventually interrupted by sensory input, getting lost, reinitiated and derived onto another prediction. In that sense, we connect this inspection with studies on attentional capture and the interference caused by sensory perception of cyclical and discrete body events such as breathing, blinking and swallowing. A global state of balance and expectation to dissociative activity, called meta-prediction, could compensate on the other hand for the lack of sensory feedback. As a representational infrastructure, its model is to be detailled, as would be the role of a system's avoidance of memories of pain, defined here by the concept of traumatic affordance, or the stabilising role of gravity. If the stochastic approach of this hypothesis is yet mostly speculative, interrogating mental imagery and language's structure, this article suggests several ways of testing the theory based on upcoming EEG recordings.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"254 ","pages":"Article 105508"},"PeriodicalIF":1.9000,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0303264725001182","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
This article comes back on the hypothesis developed by the evolutionary theory of the sensorimotor paradox that our capacity to produce mental representation could be derived from a dissociation of sensory prediction systems from motor action. As they should be then coordinated together, we are drawing further possible leads regarding the intermediary space between linear mental projections that are not bound and stopped by sensory feedback, and ongoing sensory perception whether large or discrete. Dissociated prediction would be eventually interrupted by sensory input, getting lost, reinitiated and derived onto another prediction. In that sense, we connect this inspection with studies on attentional capture and the interference caused by sensory perception of cyclical and discrete body events such as breathing, blinking and swallowing. A global state of balance and expectation to dissociative activity, called meta-prediction, could compensate on the other hand for the lack of sensory feedback. As a representational infrastructure, its model is to be detailled, as would be the role of a system's avoidance of memories of pain, defined here by the concept of traumatic affordance, or the stabilising role of gravity. If the stochastic approach of this hypothesis is yet mostly speculative, interrogating mental imagery and language's structure, this article suggests several ways of testing the theory based on upcoming EEG recordings.
期刊介绍:
BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.