1
|
Wu S, Peng H, Deng H, Guo Z, Jiang Z, Mu Q. Insomnia disorder characterized by probabilistic metastable substates using blood-oxygenation-level-dependent (BOLD) phase signals. Sleep Breath 2024; 28:1409-1414. [PMID: 38451462 DOI: 10.1007/s11325-024-03018-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/12/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE From a clinical point of view, how to force a transition from insomnia brain state to healthy brain state by external driven stimulation is of great interest. This needs to define brain state of insomnia disorder as metastable substates. The current study was to identify recurrent substates of insomnia disorder in terms of probability of occurrence, lifetime, and alternation profiles by using leading eigenvector dynamics analysis (LEiDA) method. METHODS We enrolled 32 patients with insomnia disorder and 30 healthy subjects. We firstly obtained the BOLD phase coherence matrix from Hilbert transform of BOLD signals and then extracted all the leading eigenvectors from the BOLD phase coherence matrix for all subjects across all time points. Lastly, we clustered the leading eigenvectors using a k-means clustering algorithm to find the probabilistic metastable substates (PMS) and calculate the probability of occurrence and associated lifetime for substates. RESULTS The resulting 3 clusters were optimal for brain state of insomnia disorder and healthy brain state, respectively. The occurred probabilities of the PMS were significantly different between the patients with insomnia disorder and healthy subjects, with 0.51 versus 0.44 for PMS-1 (p < 0.001), 0.25 versus 0.27 for PMS-2 (p = 0.051), and 0.24 versus 0.29 for PMS-3 (p < 0.001), as well as the lifetime (in TR) of 36.65 versus 33.15 for PMS-1 (p = 0.068), 14.36 versus 15.43 for PMS-2 (p = 0.117), and 14.80 versus 16.34 for PMS-3 (p = 0.042). The values of the diagonal of the transition matrix were much higher than the probabilities of switching states, indicating the metastable nature of substates. CONCLUSION The resulted probabilistic metastable substates hint the characteristic brain dynamics of insomnia disorder. The results may lay a foundation to help determine how to force a transition from insomnia brain state to healthy brain state by external driven stimulation.
Collapse
Affiliation(s)
- Suzhou Wu
- Department of Radiology, Yilong Country Hospital of Traditional Chinese Medicine, Nanchong, 637000, Sichuan, China
| | - Huaiping Peng
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Haobing Deng
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Zhiwei Guo
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Zhijun Jiang
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Qiwen Mu
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China.
| |
Collapse
|
2
|
Capouskova K, Zamora‐López G, Kringelbach ML, Deco G. Integration and segregation manifolds in the brain ensure cognitive flexibility during tasks and rest. Hum Brain Mapp 2023; 44:6349-6363. [PMID: 37846551 PMCID: PMC10681658 DOI: 10.1002/hbm.26511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 09/14/2023] [Accepted: 09/25/2023] [Indexed: 10/18/2023] Open
Abstract
Adapting to a constantly changing environment requires the human brain to flexibly switch among many demanding cognitive tasks, processing both specialized and integrated information associated with the activity in functional networks over time. In this study, we investigated the nature of the temporal alternation between segregated and integrated states in the brain during rest and six cognitive tasks using functional MRI. We employed a deep autoencoder to explore the 2D latent space associated with the segregated and integrated states. Our results show that the integrated state occupies less space in the latent space manifold compared to the segregated states. Moreover, the integrated state is characterized by lower entropy of occupancy than the segregated state, suggesting that integration plays a consolidating role, while segregation may serve as cognitive expertness. Comparing rest and the tasks, we found that rest exhibits higher entropy of occupancy, indicating a more random wandering of the mind compared to the expected focus during task performance. Our study demonstrates that both transient, short-lived integrated and segregated states are present during rest and task performance, flexibly switching between them, with integration serving as information compression and segregation related to information specialization.
Collapse
Affiliation(s)
- Katerina Capouskova
- Center for Brain and Cognition, Computational Neuroscience Group, DTICUniversitat Pompeu FabraBarcelonaSpain
| | - Gorka Zamora‐López
- Center for Brain and Cognition, Computational Neuroscience Group, DTICUniversitat Pompeu FabraBarcelonaSpain
| | - Morten L. Kringelbach
- Department of PsychiatryUniversity of OxfordOxfordUnited Kingdom
- Center for Music in the Brain, Department of Clinical MedicineAarhus UniversityAarhusDenmark
- Centre for Eudaimonia and Human Flourishing, Linacre CollegeUniversity of OxfordOxfordUnited Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, DTICUniversitat Pompeu FabraBarcelonaSpain
- Institució Catalana de Recerca i Estudis Avançats (ICREA)BarcelonaSpain
| |
Collapse
|
3
|
Tang X, Zhang J, Liu L, Yang M, Li S, Chen J, Ma Y, Zhang J, Liu H, Lu C, Ding G. Distinct brain state dynamics of native and second language processing during narrative listening in late bilinguals. Neuroimage 2023; 280:120359. [PMID: 37661079 DOI: 10.1016/j.neuroimage.2023.120359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 07/01/2023] [Accepted: 08/31/2023] [Indexed: 09/05/2023] Open
Abstract
The process of complex cognition, which includes language processing, is dynamic in nature and involves various network modes or cognitive modes. This dynamic process can be manifested by a set of brain states and transitions between them. Previous neuroimaging studies have shed light on how bilingual brains support native language (L1) and second language (L2) through a shared network. However, the mechanism through which this shared brain network enables L1 and L2 processing remains unknown. This study examined this issue by testing the hypothesis that L1 and L2 processing is associated with distinct brain state dynamics in terms of brain state integration and transition flexibility. A group of late Chinese-English bilinguals was scanned using functional magnetic resonance imaging (fMRI) while listening to eight short narratives in Chinese (L1) and English (L2). Brain state dynamics were modeled using the leading eigenvector dynamic analysis framework. The results show that L1 processing involves more integrated states and frequent transitions between integrated and segregated states, while L2 processing involves more segregated states and fewer transitions. Our work provides insight into the dynamic process of narrative listening comprehension in late bilinguals and sheds new light on the neural representation of language processing and related disorders.
Collapse
Affiliation(s)
- Xiangrong Tang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Juan Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Institute of Graphic Communication, Beijing 102600, China
| | - Lanfang Liu
- Department of Psychology, Faculty of Arts and Sciences, Beijing Normal University at Zhuhai, Zhuhai 519087, China; Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University at Zhuhai, Zhuhai 519087, China.
| | - Menghan Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Department of Psychological and Brain Sciences, Dartmouth College, Hanover NH 03755, USA
| | - Shijie Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Jie Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Faculty of Psychology, Beijing Normal University, Beijing 100875, China
| | - Yumeng Ma
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, UK; Department of Psychology, Emory University, Atlanta GA 30322, USA
| | - Jia Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; School of Psychology, Beijing Language and Culture University, Beijing 100083, China
| | - Haiyi Liu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Chunming Lu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Guosheng Ding
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
| |
Collapse
|
4
|
Idesis S, Allegra M, Vohryzek J, Sanz Perl Y, Faskowitz J, Sporns O, Corbetta M, Deco G. A low dimensional embedding of brain dynamics enhances diagnostic accuracy and behavioral prediction in stroke. Sci Rep 2023; 13:15698. [PMID: 37735201 PMCID: PMC10514061 DOI: 10.1038/s41598-023-42533-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 09/11/2023] [Indexed: 09/23/2023] Open
Abstract
Large-scale brain networks reveal structural connections as well as functional synchronization between distinct regions of the brain. The latter, referred to as functional connectivity (FC), can be derived from neuroimaging techniques such as functional magnetic resonance imaging (fMRI). FC studies have shown that brain networks are severely disrupted by stroke. However, since FC data are usually large and high-dimensional, extracting clinically useful information from this vast amount of data is still a great challenge, and our understanding of the functional consequences of stroke remains limited. Here, we propose a dimensionality reduction approach to simplify the analysis of this complex neural data. By using autoencoders, we find a low-dimensional representation encoding the fMRI data which preserves the typical FC anomalies known to be present in stroke patients. By employing the latent representations emerging from the autoencoders, we enhanced patients' diagnostics and severity classification. Furthermore, we showed how low-dimensional representation increased the accuracy of recovery prediction.
Collapse
Affiliation(s)
- Sebastian Idesis
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain.
| | - Michele Allegra
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padua, Italy
- Department of Physics and Astronomy "G. Galilei", University of Padova, via Marzolo 8, 35131, Padua, Italy
| | - Jakub Vohryzek
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
| | - Yonatan Sanz Perl
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain
- Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Institut du Cerveau et de la Moelle Épinière, ICM, Paris, France
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405, USA
| | - Maurizio Corbetta
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, 35129, Padua, Italy
- Department of Neuroscience, University of Padova, via Giustiniani 5, 35128, Padua, Italy
- Veneto Institute of Molecular Medicine (VIMM), via Orus 2/B, 35129, Padua, Italy
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, 08005, Barcelona, Catalonia, Spain
| |
Collapse
|
5
|
Fan L, Li Y, Huang ZG, Zhang W, Wu X, Liu T, Wang J. Low-frequency repetitive transcranial magnetic stimulation alters the individual functional dynamical landscape. Cereb Cortex 2023; 33:9583-9598. [PMID: 37376783 DOI: 10.1093/cercor/bhad228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/29/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive approach to modulate brain activity and behavior in humans. Still, how individual resting-state brain dynamics after rTMS evolves across different functional configurations is rarely studied. Here, using resting state fMRI data from healthy subjects, we aimed to examine the effects of rTMS to individual large-scale brain dynamics. Using Topological Data Analysis based Mapper approach, we construct the precise dynamic mapping (PDM) for each participant. To reveal the relationship between PDM and canonical functional representation of the resting brain, we annotated the graph using relative activation proportion of a set of large-scale resting-state networks (RSNs) and assigned the single brain volume to corresponding RSN-dominant or a hub state (not any RSN was dominant). Our results show that (i) low-frequency rTMS could induce changed temporal evolution of brain states; (ii) rTMS didn't alter the hub-periphery configurations underlined resting-state brain dynamics; and (iii) the rTMS effects on brain dynamics differ across the left frontal and occipital lobe. In conclusion, low-frequency rTMS significantly alters the individual temporo-spatial dynamics, and our finding further suggested a potential target-dependent alteration of brain dynamics. This work provides a new perspective to comprehend the heterogeneous effect of rTMS.
Collapse
Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Zi-Gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Wenlong Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Xiaofeng Wu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
- The Key Laboratory of Neuro-Informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China
| |
Collapse
|
6
|
Kurtin DL, Scott G, Hebron H, Skeldon AC, Violante IR. Task-based differences in brain state dynamics and their relation to cognitive ability. Neuroimage 2023; 271:119945. [PMID: 36870433 DOI: 10.1016/j.neuroimage.2023.119945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 02/06/2023] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Transient patterns of interregional connectivity form and dissipate in response to varying cognitive demands. Yet, it is not clear how different cognitive demands influence brain state dynamics, and whether these dynamics relate to general cognitive ability. Here, using functional magnetic resonance imaging (fMRI) data, we characterised shared, recurrent, global brain states in 187 participants across the working memory, emotion, language, and relation tasks from the Human Connectome Project. Brain states were determined using Leading Eigenvector Dynamics Analysis (LEiDA). In addition to the LEiDA-based metrics of brain state lifetimes and probabilities, we also computed information-theoretic measures of Block Decomposition Method of complexity, Lempel-Ziv complexity and transition entropy. Information theoretic metrics are notable in their ability to compute relationships amongst sequences of states over time, compared to lifetime and probability, which capture the behaviour of each state in isolation. We then related task-based brain state metrics to fluid intelligence. We observed that brain states exhibited stable topology across a range of numbers of clusters (K = 2:15). Most metrics of brain state dynamics, including state lifetime, probability, and all information theoretic metrics, reliably differed between tasks. However, relationships between state dynamic metrics and cognitive abilities varied according to the task, the metric, and the value of K, indicating that there are contextual relationships between task-dependant state dynamics and trait cognitive ability. This study provides evidence that the brain reconfigures across time in response to cognitive demands, and that there are contextual, rather than generalisable, relationships amongst task, state dynamics, and cognitive ability.
Collapse
Affiliation(s)
- Danielle L Kurtin
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
| | - Gregory Scott
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Henry Hebron
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK; UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK
| | - Anne C Skeldon
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK; Department of Mathematics, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK
| | - Ines R Violante
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
| |
Collapse
|
7
|
Marschall TM, Koops S, Brederoo SG, Cabral J, Ćurčić-Blake B, Sommer IEC. Time varying dynamics of hallucinations in clinical and non-clinical voice-hearers. Neuroimage Clin 2023; 37:103351. [PMID: 36805417 PMCID: PMC9969260 DOI: 10.1016/j.nicl.2023.103351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/24/2023] [Accepted: 02/12/2023] [Indexed: 02/16/2023]
Abstract
Auditory verbal hallucinations (AVH) are frequently associated with psychotic disorders, yet also occur in non-clinical voice-hearers. AVH in this group are similar to those within clinical voice-hearers in terms of several phenomenological aspects, but non-clinical voice-hearers report to have more control over their AVH and attribute less emotional valence to them. These dissimilarities may stem from differences on the neurobiological level, as it is still under debate whether the mechanisms involved in AVH are the same in clinical and non-clinical voice-hearers. In this study, 21 clinical and 21 non-clinical voice-hearers indicated the onset and offsets of AVH during an fMRI scan. Using a method called leading eigenvector dynamics analysis (LEiDA), we examined time-varying dynamics of functional connectivity involved in AVH with a sub-second temporal resolution. We assessed differences between groups, and between hallucination and rest periods in dwell time, switching frequency, probability of occurrence, and transition probabilities of nine recurrent states of functional connectivity with a permutation ANOVA. Deviations in dwell times, switching frequencies, and switch probabilities in the hallucination period indicated more erratic dynamics during this condition regardless of their clinical status. Post-hoc analyses of the dwell times exhibited the most distinct differences between the rest and hallucination condition for the non-clinical sample, suggesting stronger differences between the two conditions in this group. Overall, these findings suggest that the neurobiological mechanisms involved in AVH are similar in clinical and non-clinical individuals.
Collapse
Affiliation(s)
- Theresa M Marschall
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands.
| | - Sanne Koops
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
| | - Sanne G Brederoo
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
| | - Joana Cabral
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
| | - Branislava Ćurčić-Blake
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
| | - Iris E C Sommer
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
| |
Collapse
|
8
|
Liu Y, Zhu L, Cai K, Dong X, Xiong X, Liu Z, Chen A. Relationship between Cardiorespiratory Fitness and Executive Function in Young Adults: Mediating Effects of Gray Matter Volume. Brain Sci 2022; 12:1441. [PMID: 36358366 PMCID: PMC9688695 DOI: 10.3390/brainsci12111441] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 10/17/2022] [Accepted: 10/22/2022] [Indexed: 08/01/2023] Open
Abstract
We evaluated the association between cardiorespiratory fitness (CRF) and executive function (EF) in young adults and the mediating effects of GMV on this relationship. This study involved 217 college students. An incremental load exercise program was used to evaluate VO2max. EF was estimated by the Flanker task, the 2-back task, and the more-odd shifting task, while structural magnetic resonance and region-based morphometry (RBM) were used to analyze GMV. The high CRF group had a shorter updating reaction time (RT) (p ≤ 0.05). CRF was positively correlated with the right orbital part of the middle frontal gyrus (ORBmid.R) GMV (p ≤ 0.05). ORBmid.R GMV was negatively correlated with updating RT (p ≤ 0.05). Model 4 in SPSS was used to assess the mediating effects of ORBmid.R GMV between CRF and updating RT. ORBmid.R GMV was established to have a partially mediating role between CRF and updating RT, which accounted for 19.6% of the total effect value. These findings indicate that the negative correlation between CRF and EF was significant, and ORBmid.R GMV played a mediating role in the relationship between CRF and EF, providing new evidence toward comprehensively revealing that CRF promotes EF performance.
Collapse
Affiliation(s)
- Yuexin Liu
- College of Physical Education, Yangzhou University, Yangzhou 225127, China
- Institute of Sports, Exercise and Brain, Yangzhou University, Yangzhou 225127, China
| | - Lina Zhu
- College of Physical Education, Yangzhou University, Yangzhou 225127, China
- Institute of Sports, Exercise and Brain, Yangzhou University, Yangzhou 225127, China
| | - Kelong Cai
- College of Physical Education, Yangzhou University, Yangzhou 225127, China
- Institute of Sports, Exercise and Brain, Yangzhou University, Yangzhou 225127, China
| | - Xiaoxiao Dong
- College of Physical Education, Yangzhou University, Yangzhou 225127, China
- Institute of Sports, Exercise and Brain, Yangzhou University, Yangzhou 225127, China
| | - Xuan Xiong
- College of Physical Education, Yangzhou University, Yangzhou 225127, China
- Institute of Sports, Exercise and Brain, Yangzhou University, Yangzhou 225127, China
| | - Zhimei Liu
- College of Physical Education, Yangzhou University, Yangzhou 225127, China
- Institute of Sports, Exercise and Brain, Yangzhou University, Yangzhou 225127, China
| | - Aiguo Chen
- College of Physical Education, Yangzhou University, Yangzhou 225127, China
- Institute of Sports, Exercise and Brain, Yangzhou University, Yangzhou 225127, China
| |
Collapse
|