Tool Embodiment Is Reflected in Movement Multifractal Nonlinearity
Recent advances in neuroscience have linked dynamical systems theory to cognition. The main contention is that extended cognition relies on a unitary brain-body-tool system showing the expected signatures of interaction-dominance reflected in a multifractal behavior. This might be particularly relev...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Fractal and Fractional |
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| Online Access: | https://www.mdpi.com/2504-3110/6/5/240 |
| _version_ | 1827668930402975744 |
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| author | Yvan Pratviel Veronique Deschodt-Arsac Florian Larrue Laurent M. Arsac |
| author_facet | Yvan Pratviel Veronique Deschodt-Arsac Florian Larrue Laurent M. Arsac |
| author_sort | Yvan Pratviel |
| collection | DOAJ |
| description | Recent advances in neuroscience have linked dynamical systems theory to cognition. The main contention is that extended cognition relies on a unitary brain-body-tool system showing the expected signatures of interaction-dominance reflected in a multifractal behavior. This might be particularly relevant when it comes to understanding how the brain is able to embody a tool to perform a task. Here we applied the multifractal formalism to the dynamics of hand movement while one was performing a computer task (the herding task) using a mouse or its own hand as a tool to move an object on the screen. We applied a focus-based multifractal detrended fluctuation analysis to acceleration time series. Then, multifractal nonlinearity was assessed by comparing original series to a finite set of surrogates obtained after Iterated Amplitude Adjusted Fourier transformation, a method that removes nonlinear multiscale dependencies while preserving the linear structure of the time series. Both hand and mouse task execution demonstrated multifractal nonlinearity, a typical form of across-scales interactivity in cognitive control. In addition, a wider multifractal spectrum was observed in mouse condition, which might highlight a richer set of interactions when the cognitive system is extended to the embodied mouse. We conclude that the emergence of multifractal nonlinearity from a brain-body-tool system pleads for recent theories of radical tool embodiment. Multifractal nonlinearity may be a promising metric to appreciate how physical objects—but also virtual tools and potentially prosthetics—are efficiently embodied by the brain. |
| first_indexed | 2024-03-10T03:52:26Z |
| format | Article |
| id | doaj.art-aad7dfe24e2849bea60d375cd1b53a9a |
| institution | Directory Open Access Journal |
| issn | 2504-3110 |
| language | English |
| last_indexed | 2024-03-10T03:52:26Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fractal and Fractional |
| spelling | doaj.art-aad7dfe24e2849bea60d375cd1b53a9a2023-11-23T11:03:22ZengMDPI AGFractal and Fractional2504-31102022-04-016524010.3390/fractalfract6050240Tool Embodiment Is Reflected in Movement Multifractal NonlinearityYvan Pratviel0Veronique Deschodt-Arsac1Florian Larrue2Laurent M. Arsac3Univ. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, 33400 Talence, FranceUniv. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, 33400 Talence, FranceCentre Aquitain Technologies Information et Électroniques (CATIE), 33400 Talence, FranceUniv. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, 33400 Talence, FranceRecent advances in neuroscience have linked dynamical systems theory to cognition. The main contention is that extended cognition relies on a unitary brain-body-tool system showing the expected signatures of interaction-dominance reflected in a multifractal behavior. This might be particularly relevant when it comes to understanding how the brain is able to embody a tool to perform a task. Here we applied the multifractal formalism to the dynamics of hand movement while one was performing a computer task (the herding task) using a mouse or its own hand as a tool to move an object on the screen. We applied a focus-based multifractal detrended fluctuation analysis to acceleration time series. Then, multifractal nonlinearity was assessed by comparing original series to a finite set of surrogates obtained after Iterated Amplitude Adjusted Fourier transformation, a method that removes nonlinear multiscale dependencies while preserving the linear structure of the time series. Both hand and mouse task execution demonstrated multifractal nonlinearity, a typical form of across-scales interactivity in cognitive control. In addition, a wider multifractal spectrum was observed in mouse condition, which might highlight a richer set of interactions when the cognitive system is extended to the embodied mouse. We conclude that the emergence of multifractal nonlinearity from a brain-body-tool system pleads for recent theories of radical tool embodiment. Multifractal nonlinearity may be a promising metric to appreciate how physical objects—but also virtual tools and potentially prosthetics—are efficiently embodied by the brain.https://www.mdpi.com/2504-3110/6/5/240cognitive systemnonlinear dynamicsembodimenthuman-machine interface |
| spellingShingle | Yvan Pratviel Veronique Deschodt-Arsac Florian Larrue Laurent M. Arsac Tool Embodiment Is Reflected in Movement Multifractal Nonlinearity Fractal and Fractional cognitive system nonlinear dynamics embodiment human-machine interface |
| title | Tool Embodiment Is Reflected in Movement Multifractal Nonlinearity |
| title_full | Tool Embodiment Is Reflected in Movement Multifractal Nonlinearity |
| title_fullStr | Tool Embodiment Is Reflected in Movement Multifractal Nonlinearity |
| title_full_unstemmed | Tool Embodiment Is Reflected in Movement Multifractal Nonlinearity |
| title_short | Tool Embodiment Is Reflected in Movement Multifractal Nonlinearity |
| title_sort | tool embodiment is reflected in movement multifractal nonlinearity |
| topic | cognitive system nonlinear dynamics embodiment human-machine interface |
| url | https://www.mdpi.com/2504-3110/6/5/240 |
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