Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications
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 foundation...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1456587/full |
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| author | Francesco Benso Carlo Chiorri Eleonora Ardu Paola Venuti Angela Pasqualotto Angela Pasqualotto |
| author_facet | Francesco Benso Carlo Chiorri Eleonora Ardu Paola Venuti Angela Pasqualotto Angela Pasqualotto |
| author_sort | Francesco Benso |
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| description | 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. |
| format | Article |
| id | doaj-art-3668c3bd93d74aeba7a10179f0820d87 |
| institution | Kabale University |
| issn | 1664-1078 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Psychology |
| spelling | doaj-art-3668c3bd93d74aeba7a10179f0820d872025-01-23T06:56:30ZengFrontiers Media S.A.Frontiers in Psychology1664-10782025-01-011610.3389/fpsyg.2025.14565871456587Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implicationsFrancesco Benso0Carlo Chiorri1Eleonora Ardu2Paola Venuti3Angela Pasqualotto4Angela Pasqualotto5Department of Psychology and Cognitive Science, University of Trento, Trento, ItalyDepartment of Education Sciences, University of Genoa, Genoa, ItalyAssociazione Neuroscienze Cognitive Clinica Ricerca Intervento (ANCCRI), Genova, ItalyDepartment of Psychology and Cognitive Science, University of Trento, Trento, ItalyFaculty of Psychology and Education Sciences (FPSE), University of Geneva, Geneva, SwitzerlandDepartment of Education and Learning, University of Applied Sciences and Arts of Southern Switzerland, Manno, SwitzerlandThe 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.https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1456587/fullmassive modularityexecutive controlworking memorycentral executive networkneural networks |
| spellingShingle | Francesco Benso Carlo Chiorri Eleonora Ardu Paola Venuti Angela Pasqualotto Angela Pasqualotto Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications Frontiers in Psychology massive modularity executive control working memory central executive network neural networks |
| title | Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications |
| title_full | Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications |
| title_fullStr | Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications |
| title_full_unstemmed | Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications |
| title_short | Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications |
| title_sort | beyond modular and non modular states theoretical considerations exemplifications and practical implications |
| topic | massive modularity executive control working memory central executive network neural networks |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2025.1456587/full |
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