Cognition without neurons: modelling anticipation in a basal reservoir computer
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866912360717877248 |
|---|---|
| author | Bruna, Polyphony Gyllingberg, Linnéa |
| author_facet | Bruna, Polyphony Gyllingberg, Linnéa |
| contents | How do non-neural organisms, such as the slime mould \textit{Physarum polycephalum}, anticipate periodic events in their environment? We present a minimal, biologically inspired reservoir model that demonstrates simple temporal anticipation without neurons, spikes, or trained readouts. The model consists of a spatially embedded hexagonal network in which nodes regulate their energy through local, allostatic adaptation. Input perturbations shape energy dynamics over time, allowing the system to internalize temporal regularities into its structure. After being exposed to a periodic input signal, the model spontaneously re-enacts those dynamics even in the absence of further input -- a form of unsupervised temporal pattern completion. This behaviour emerges from internal homeodynamic regulation, without supervised learning or symbolic processing. Our results show that simple homeodynamic regulation can support unsupervised prediction, suggesting a pathway to memory and anticipation in basal organisms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_02114 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cognition without neurons: modelling anticipation in a basal reservoir computer Bruna, Polyphony Gyllingberg, Linnéa Neurons and Cognition Neural and Evolutionary Computing Adaptation and Self-Organizing Systems How do non-neural organisms, such as the slime mould \textit{Physarum polycephalum}, anticipate periodic events in their environment? We present a minimal, biologically inspired reservoir model that demonstrates simple temporal anticipation without neurons, spikes, or trained readouts. The model consists of a spatially embedded hexagonal network in which nodes regulate their energy through local, allostatic adaptation. Input perturbations shape energy dynamics over time, allowing the system to internalize temporal regularities into its structure. After being exposed to a periodic input signal, the model spontaneously re-enacts those dynamics even in the absence of further input -- a form of unsupervised temporal pattern completion. This behaviour emerges from internal homeodynamic regulation, without supervised learning or symbolic processing. Our results show that simple homeodynamic regulation can support unsupervised prediction, suggesting a pathway to memory and anticipation in basal organisms. |
| title | Cognition without neurons: modelling anticipation in a basal reservoir computer |
| topic | Neurons and Cognition Neural and Evolutionary Computing Adaptation and Self-Organizing Systems |
| url | https://arxiv.org/abs/2505.02114 |