arXiv subjects

Wiesław L. Galus

Publications and source records attributed to Wiesław L. Galus.

4 recordsLinked to original sources

arXiv2026

MEM as an Extension of Recurrent Processing Theory: Toward a Motivational Account of Consciousness

Victor Lamme's Recurrent Processing Theory (RPT) proposes that the feedforward sweep (FFS) can extract and categorize visual features unconsciously, while conscious vision emerges through recurrent processing and feedback interactions across representational levels. The Motivated Emotional Mind (MEM) model, developed by Wiesław L. Galus and Janusz A. Starzyk, retains this core principle but embeds it in an embodied architecture integrating multilayer networks, semi-hierarchical semblions, receptors, effectors, allostasis, emotional valuation, and memory-based sensory reconstruction. This article examines the substantive but limited relationship between RPT and MEM. While RPT explains the role of recurrence in perceptual organization and the transition to conscious vision, MEM addresses the content of recurrent processing, its grounding in receptor activity and bodily states, its interaction with memory and action, and the possible role of reconstructed sensory representations in phenomenal experience. Particular emphasis is placed on secondary perception: the top-down reconstruction of sensory and interoceptive maps through which memories, mental imagery, dreams, hallucinations, feelings, and observed scenarios acquire experiential form. MEM thus associates phenomenality not merely with recurrent activity or reportability, but with the reconstruction of modality-specific, receptor-grounded sensory and bodily content. The article also presents the mathematical model of MEM, formalizing re-entrant processing, representational competition, allostasis, affect, curiosity, procedural gaps, and action selection. We conclude that MEM can be viewed as an embodied and motivational extension of RPT. However, its distinctive claims, particularly the sufficiency of secondary perception for phenomenality and the proposed microstructure of semblions, remain hypotheses requiring causal testing.

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arXiv2026

Does Global Neuronal Workspace Theory Explain Phenomenal Consciousness? The Motivated Emotional Mind Challenge

Global Neuronal Workspace Theory (GNWT) is one of the most extensively developed empirical research programmes on access consciousness. By contrast, the Motivated Emotional Mind (MEM) model proposes an embodied, semi-hierarchical associative memory in which representational selection, action, recurrent reconstruction of modality-specific fields, interoception, and valence form a single functional cycle. This article assesses whether MEM mechanisms can reproduce the functions explained by GNWT and whether they yield additional hypotheses concerning phenomenal quality. We first reconstruct the origins, mechanistic core, strengths, and limitations of GNWT, and then present the origins of MEM, the architecture of semblions, and the FFS-RP cycle. In the comparative analysis, we distinguish functional similarity from mechanistic identity and empirical equivalence. We examine 25 publications: twelve canonical studies of GNWT or critiques thereof, and thirteen studies of perception, interoception, and affect. For each study, we juxtapose the GNWT interpretation with a possible MEM reinterpretation. The findings indicate that most classical effects - including threshold dynamics, maintenance, recurrence, long-range connectivity, and flexible use of information - are compatible with both theories. This compatibility weakens the claim that the GNWT interpretation is exclusive, but does not yet provide theory-specific support for MEM. MEM advances a broader hypothesis integrating access, modality-specific reconstruction, bodily state, affect, and action; its potential explanatory advantage nevertheless remains a hypothesis requiring preregistered quantitative tests. We propose a series of interventions designed to dissociate sensory re-entry, global availability, report, and interoceptive valuation.

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arXiv2026

From Biological Precursors to Artificial Cognition: Consciousness, Embodiment, and the MEM Architecture

This article asks under what conditions artificial intelligence could warrant a rational attribution of consciousness. Linguistic ability, multimodality, memory, planning, action control, and humanoid embodiment are not sufficient evidence of phenomenal experience. Biological precursors such as excitability, homeostasis, neural networks, and hierarchical representation instead identify functions whose counterparts may be engineered. The paper compares conventional LLMs, hybrid h-LLMs, vision-language-action systems, and embodied agents with the Motivated Emotional Mind (MEM) architecture. MEM adds receptor-grounded representations, regulatory self-monitoring and interoception, affect, semblion-based associative memory, and re-entry into lower sensory and interoceptive maps. A related formulation defines a phenomenal state as a dynamic, integrated state of the whole embodied system in which sensor-grounded modal content is recurrently stabilized and coupled to a suprathreshold interoceptive representation of the system's regulatory state. The mathematical model of MEM published on arXiv specifies implementable relations among these components and makes the proposal more precise and testable. Comparative and causal tests in humans, invertebrates, and artificial systems could strengthen or weaken the MEM capabilities. MEM is therefore presented as a falsifiable research program requiring empirical validation and ethical caution.

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arXiv2026

A Mathematical Model of Motivated Emotional Mind - Cognitive Embodied System

This article presents a mathematical model of the Motivated Emotional Mind cognitive architecture developed for embodied intelligent systems. Such a system learns to maintain its homeostasis through a generalized form of reinforcement learning based on its internal motivations, termed motivated learning (ML). The principal contribution of this article is a rigorous formalization of the re-entrant loop integrating feedforward processing, lateral interactions, and feedback pathways, together with the representational selection mechanisms that govern adaptive system responses. The model specifies how ongoing exteroceptive and interoceptive signals, bodily-motivational context, and memory traces are bound into associative memory structures termed semblions, which compete for access to further processing and top-down reconstruction. The formalization encompasses secondary perception, representational competition, curiosity, procedural gaps, and action selection directed toward limiting allostatic violations. Within this framework, motivated learning is tailored to embodied systems whose dynamics are shaped by needs, affect, and the current regulatory state. Unlike standard reinforcement-learning models, the proposed approach incorporates need thresholds, goal generation and shifting goals, bodily state, resource constraints, and action uncertainty, thereby providing a more adequate account of response selection under regulatory pressure. Global affect functions as a central control signal, modulating the learning rate, representational valence, and the balance between exploration and exploitation. The model presented here is a step toward a more rigorous formalization of cognitive phenomena and may provide a basis for further theoretical analysis, computer simulation, and implementation in artificial-intelligence systems inspired by biological processes.

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