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HYPOTHESIS AND THEORY article

Front. Psychol.
Sec. Neuropsychology
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1456587
This article is part of the Research Topic Changing Perspectives in Speech and Language Neuropsychology, 1863-2023 View all 7 articles

Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications

Provisionally accepted
Francesco Benso Francesco Benso 1Carlo Chiorri Carlo Chiorri 2Eleonora Ardu Eleonora Ardu 3Paola Venuti Paola Venuti 1Angela Pasqualotto Angela Pasqualotto 4,5*
  • 1 University of Trento, Trento, Trentino-Alto Adige/Südtirol, Italy
  • 2 University of Genoa, Genoa, Liguria, Italy
  • 3 Associazione Neuroscienze Cognitive Clinica Ricerca Intervento (ANCCRI), Genova, Italy
  • 4 University of Geneva, Geneva, Switzerland
  • 5 University of Applied Sciences and Arts of Southern Switzerland, Manno, Ticino, Switzerland

The final, formatted version of the article will be published soon.

    The concept of modularity in neuropsychology remains a topic of significant debate, especially when considering complex, non-innate, hyper-learned, and adaptable modular systems. This paper critically examines the evolution of cognitive modularity, addressing the challenges of integrating foundational theories with recent empirical and theoretical developments. We begin by analyzing the contributions of Sternberg and Fodor, whose foundational work established the concept of specialized, encapsulated modules within cognitive processes, particularly in the domains of perception and language. Building on this, we explore Carruthers' theory of massive modularity, which extends the modular framework to broader cognitive functions, though we reject its application to central amodal systems, which are overarching and resistant to modularization. We also evaluate recent discoveries, such as mirror neurons and the neural reuse hypothesis, and their implications for traditional modularity models. Furthermore, we investigate the dynamic interactions between the Default Mode Network (DMN), Central Executive Network (CEN), and Salience Network (SN), highlighting their roles in shifting between automatic and controlled states. This exploration refines existing theoretical models, distinguishing innate systems, genetically predisposed ones, and those hyper-learned through working memory, as exemplified by the three-level model of Moscovitch and Umiltà. We address the blurred boundary between domain-specific and domain-general systems, proposing modular versus non-modular states-indexed by automaticity and mandatoriness-as key discriminators. This systematization, supported by empirical literature and our own research, provides a more stable framework for understanding modular systems, avoiding interpretive confusion across varying levels of complexity. These insights advance both theoretical understanding and practical applications in cognitive science.

    Keywords: massive modularity, executive control, working memory, Central executive network (CEN), neural networks

    Received: 28 Jun 2024; Accepted: 03 Jan 2025.

    Copyright: © 2025 Benso, Chiorri, Ardu, Venuti and Pasqualotto. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Angela Pasqualotto, University of Geneva, Geneva, Switzerland

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.