Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysis
Abstract Human sensory, cognitive, and motor processes often result in asymmetric cerebral hemisphere activation, observable through neurovascular coupling (NVC). Brain lateralization enables simultaneous performance of distinct functions, enhancing cognitive capacity. This study examined cognitive...
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| Format: | Article |
| Language: | English |
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Wiley
2025-08-01
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| Series: | Physiological Reports |
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| Online Access: | https://doi.org/10.14814/phy2.70492 |
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| author | Héctor Rojas‐Pescio Lucy Beishon Ronney B. Panerai Max Chacón |
| author_facet | Héctor Rojas‐Pescio Lucy Beishon Ronney B. Panerai Max Chacón |
| author_sort | Héctor Rojas‐Pescio |
| collection | DOAJ |
| description | Abstract Human sensory, cognitive, and motor processes often result in asymmetric cerebral hemisphere activation, observable through neurovascular coupling (NVC). Brain lateralization enables simultaneous performance of distinct functions, enhancing cognitive capacity. This study examined cognitive lateralization through NVC responses to the Addenbrooke's Cognitive Examination‐III (ACE‐III) assessment, using entropy‐based methods and statistical complexity measures (SCM). We tested whether applying dispersion entropy (DE) to cerebral blood velocity (CBv), critical closing pressure (CrCP), and resistance area‐product (RAP) signals could identify significant hemispheric differences during cognitive tasks. Statistical analysis revealed SCM effectively detected lateralization (best p‐value = 0.001), whereas entropy alone did not differentiate hemisphere activity. Furthermore, cognitive stimulation (attention, fluency, language, memory, and visuospatial tasks) generally produced lower SCM values compared to baseline, predominantly in the dominant hemisphere. These findings indicate that NVC exhibits distinct complexity patterns based on hemisphere dominance and cognitive domain stimulated. Additionally, comparison with prior ACE‐III analyses, using population‐normalized mean peak change, reinforces that advanced biomedical‐oriented information theory methods, such as DE and SCM, offer valuable insights into cerebral lateralization mechanisms and NVC responses during cognitive stimulation. |
| format | Article |
| id | doaj-art-7f3a704a41a749369dea1e329bc4cfb7 |
| institution | DOAJ |
| issn | 2051-817X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | Physiological Reports |
| spelling | doaj-art-7f3a704a41a749369dea1e329bc4cfb72025-08-20T03:07:32ZengWileyPhysiological Reports2051-817X2025-08-011315n/an/a10.14814/phy2.70492Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysisHéctor Rojas‐Pescio0Lucy Beishon1Ronney B. Panerai2Max Chacón3Departamento de Ingeniería Informática Universidad de Santiago de Chile Santiago ChileDepartment of Cardiovascular Sciences University of Leicester Leicester UKDepartment of Cardiovascular Sciences University of Leicester Leicester UKDepartamento de Ingeniería Informática Universidad de Santiago de Chile Santiago ChileAbstract Human sensory, cognitive, and motor processes often result in asymmetric cerebral hemisphere activation, observable through neurovascular coupling (NVC). Brain lateralization enables simultaneous performance of distinct functions, enhancing cognitive capacity. This study examined cognitive lateralization through NVC responses to the Addenbrooke's Cognitive Examination‐III (ACE‐III) assessment, using entropy‐based methods and statistical complexity measures (SCM). We tested whether applying dispersion entropy (DE) to cerebral blood velocity (CBv), critical closing pressure (CrCP), and resistance area‐product (RAP) signals could identify significant hemispheric differences during cognitive tasks. Statistical analysis revealed SCM effectively detected lateralization (best p‐value = 0.001), whereas entropy alone did not differentiate hemisphere activity. Furthermore, cognitive stimulation (attention, fluency, language, memory, and visuospatial tasks) generally produced lower SCM values compared to baseline, predominantly in the dominant hemisphere. These findings indicate that NVC exhibits distinct complexity patterns based on hemisphere dominance and cognitive domain stimulated. Additionally, comparison with prior ACE‐III analyses, using population‐normalized mean peak change, reinforces that advanced biomedical‐oriented information theory methods, such as DE and SCM, offer valuable insights into cerebral lateralization mechanisms and NVC responses during cognitive stimulation.https://doi.org/10.14814/phy2.70492brain lateralizationcognitive examinationdispersion entropyneurovascular couplingstatistical complexity |
| spellingShingle | Héctor Rojas‐Pescio Lucy Beishon Ronney B. Panerai Max Chacón Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysis Physiological Reports brain lateralization cognitive examination dispersion entropy neurovascular coupling statistical complexity |
| title | Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysis |
| title_full | Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysis |
| title_fullStr | Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysis |
| title_full_unstemmed | Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysis |
| title_short | Cognitive brain lateralization through neurovascular coupling in healthy subjects: A statistical complexity analysis |
| title_sort | cognitive brain lateralization through neurovascular coupling in healthy subjects a statistical complexity analysis |
| topic | brain lateralization cognitive examination dispersion entropy neurovascular coupling statistical complexity |
| url | https://doi.org/10.14814/phy2.70492 |
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