The DIME Architecture: A Unified Operational Algorithm for Neural Representation, Dynamics, Control and Integration

Quantitative Biology > Neurons and Cognition [Submitted on 7 Mar 2026] The DIME Architecture: A Unified Operational Algorithm for Neural Representation, Dynamics, Control and Integration Ionel Cristian Vladu, Nicu Bizdoaca, Ionica Pirici, Tudor-Adrian Balseanu, Eduard Nicusor Bondoc Modern neuroscience has accumulated extensive evidence on perception, memory, prediction, valuation, and consciousness, yet still lacks an explicit operational architecture capable of integrating these phenomena within a unified computational framework. Existing theories address specific aspects of neural function: predictive coding and active inference emphasize hierarchical inference and prediction error minimization; engram theories explain memory through distributed cell assemblies; neuromodulatory accounts focus on value-dependent regulation of plasticity and behaviour; and global workspace or large-scale network models investigate mechanisms underlying conscious access. Despite their explanatory power, these approaches remain only partially integrated at the architectural level. This work introduces DIME (Detect-Integrate-Mark-Execute), a neural architecture organizing perception, memory, valuation, and conscious access within a common operational cycle. The framework includes four interacting components: engrams, distributed recurrent neural structures supporting multiple activation trajectories; execution threads, spatiotemporal trajectories implementing neural processes; marker systems, neuromodulatory and limbic mechanisms regulating gain, plasticity, and trajectory selection; and hyperengrams, large-scale integrative states associated with operational conscious access. The framework is consistent with empirical evidence from hippocampal indexing, recurrent cortical processing, replay phenomena, large-scale network integration, and neuromodulatory regulation. Formulated at an abstract computational level, DIME may also inform artificial intelligence and robotics by providing an architectural template in which representation, valuation, and temporal sequencing emerge from a unified mechanism. An extended theoretical exposition is available in a companion monograph on Zenodo. Comments: 45 pages, 8 figures. Architectural overview of the DIME framework. Extended theoretical treatment available in companion monograph (Zenodo) Subjects: Neurons and Cognition (q-bio.NC); Artificial Intelligence (cs.AI) Cite as: arXiv:2603.12286 [q-bio.NC]   (or arXiv:2603.12286v1 [q-bio.NC] for this version)   https://doi.org/10.48550/arXiv.2603.12286 Focus to learn more Submission history From: Ionel Cristian Vladu [view email] [v1] Sat, 7 Mar 2026 11:05:15 UTC (760 KB) Access Paper: view license Current browse context: q-bio.NC < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.AI q-bio References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)