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Miura H, Ono Y, Suzuki T, Ogihara Y, Imai Y, Watanabe A, Tokikuni Y, Sakuraba S, Sawamura D. Regional brain activity and neural network changes in cognitive-motor dual-task interference: A functional near-infrared spectroscopy study. Neuroimage 2024; 297:120714. [PMID: 38950665 DOI: 10.1016/j.neuroimage.2024.120714] [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: 01/05/2024] [Revised: 06/25/2024] [Accepted: 06/28/2024] [Indexed: 07/03/2024] Open
Abstract
Previous neuroimaging studies have reported dual-task interference (DTi) and deterioration of task performance in a cognitive-motor dual task (DT) compared to that in a single task (ST). Greater frontoparietal activity is a neural signature of DTi; nonetheless, the underlying mechanism of cortical network in DTi still remains unclear. This study aimed to investigate the regional brain activity and neural network changes during DTi induced by highly demanding cognitive-motor DT. Thirty-four right-handed healthy young adults performed the spiral-drawing task. They underwent a paced auditory serial addition test (PASAT) simultaneously or independently while their cortical activity was measured using functional near-infrared spectroscopy. Motor performance was determined using the balanced integration score (BIS), a balanced index of drawing speed and precision. The cognitive task of the PASAT was administered with two difficulty levels defined by 1 s (PASAT-1 s) and 2 s (PASAT-2 s) intervals, allowing for the serial addition of numbers. Cognitive performance was determined using the percentage of correct responses. These motor and cognitive performances were significantly reduced during DT, which combined a drawing and a cognitive task at either difficulty level, compared to those in the corresponding ST conditions. The DT conditions were also characterized by significantly increased activity in the right dorsolateral prefrontal cortex (DLPFC) compared to that in the ST conditions. Multivariate Granger causality (GC) analysis of cortical activity in the selected frontoparietal regions of interest further revealed selective top-down causal connectivity from the right DLPFC to the right inferior parietal cortex during DTs. Furthermore, changes in the frontoparietal GC connectivity strength between the PASAT-2 s DT and ST conditions significantly correlated negatively with changes in the percentage of correct responses. Therefore, DTi can occur even in cognitively proficient young adults, and the right DLPFC and frontoparietal network being crucial neural mechanisms underlying DTi. These findings provide new insights into DTi and its underlying neural mechanisms and have implications for the clinical utility of cognitive-motor DTs applied to clinical populations with cognitive decline, such as those with psychiatric and brain disorders.
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Affiliation(s)
- Hiroshi Miura
- Graduate School of Health Sciences, Hokkaido University, Sapporo, Japan; Department of Rehabilitation, Higashinaebo Hospital, Sapporo, Japan
| | - Yumie Ono
- Department of Electronics and Bioinformatics, School of Science and Technology, Meiji University, Kawasaki, Japan
| | - Tatsuya Suzuki
- Department of Electronics and Bioinformatics, School of Science and Technology, Meiji University, Kawasaki, Japan; Electrical Engineering Program, Graduate School of Science and Technology, Meiji University, Kawasaki, Japan
| | - Yuji Ogihara
- Department of Rehabilitation, Higashinaebo Hospital, Sapporo, Japan
| | - Yuna Imai
- Department of Rehabilitation, Higashinaebo Hospital, Sapporo, Japan
| | - Akihiro Watanabe
- Department of Rehabilitation Science, Faculty of Health Sciences, Hokkaido University, Sapporo, Hokkaido, 060-0812, Japan
| | - Yukina Tokikuni
- Department of Rehabilitation Science, Faculty of Health Sciences, Hokkaido University, Sapporo, Hokkaido, 060-0812, Japan
| | - Satoshi Sakuraba
- Department of Rehabilitation Sciences, Health Sciences University of Hokkaido, Tobetsu, Ishikari, Japan
| | - Daisuke Sawamura
- Department of Rehabilitation Science, Faculty of Health Sciences, Hokkaido University, Sapporo, Hokkaido, 060-0812, Japan.
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Hu Z, Di X, Yang Z. Editorial: Shared responses and individual differences in the human brain during naturalistic stimulations. Front Hum Neurosci 2023; 17:1201728. [PMID: 37213928 PMCID: PMC10198652 DOI: 10.3389/fnhum.2023.1201728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 04/20/2023] [Indexed: 05/23/2023] Open
Affiliation(s)
- Zhishan Hu
- Neuroimaging Core, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xin Di
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, United States
| | - Zhi Yang
- Neuroimaging Core, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders and National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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Wang D, Huang Y, Liang S, Meng Q, Yu H. The identification of interacting brain networks during robot-assisted training with multimodal stimulation. J Neural Eng 2023; 20. [PMID: 36548992 DOI: 10.1088/1741-2552/acae05] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022]
Abstract
Objective.Robot-assisted rehabilitation training is an effective way to assist rehabilitation therapy. So far, various robotic devices have been developed for automatic training of central nervous system following injury. Multimodal stimulation such as visual and auditory stimulus and even virtual reality technology were usually introduced in these robotic devices to improve the effect of rehabilitation training. This may need to be explained from a neurological perspective, but there are few relevant studies.Approach.In this study, ten participants performed right arm rehabilitation training tasks using an upper limb rehabilitation robotic device. The tasks were completed under four different feedback conditions including multiple combinations of visual and auditory components: auditory feedback; visual feedback; visual and auditory feedback (VAF); non-feedback. The functional near-infrared spectroscopy devices record blood oxygen signals in bilateral motor, visual and auditory areas. Using hemoglobin concentration as an indicator of cortical activation, the effective connectivity of these regions was then calculated through Granger causality.Main results.We found that overall stronger activation and effective connectivity between related brain regions were associated with VAF. When participants completed the training task without VAF, the trends in activation and connectivity were diminished.Significance.This study revealed cerebral cortex activation and interacting networks of brain regions in robot-assisted rehabilitation training with multimodal stimulation, which is expected to provide indicators for further evaluation of the effect of rehabilitation training, and promote further exploration of the interaction network in the brain during a variety of external stimuli, and to explore the best sensory combination.
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Affiliation(s)
- Duojin Wang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China.,Shanghai Engineering Research Center of Assistive Devices, 516 Jungong Road, Shanghai 200093, People's Republic of China
| | - Yanping Huang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China
| | - Sailan Liang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China
| | - Qingyun Meng
- College of Rehabilitation Sciences, Shanghai University of Medicine & Health Sciences, 279 Zhouzhu Road, Shanghai 201318, People's Republic of China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, People's Republic of China.,Shanghai Engineering Research Center of Assistive Devices, 516 Jungong Road, Shanghai 200093, People's Republic of China
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Hu Z, Liu G, Dong Q, Niu H. Applications of Resting-State fNIRS in the Developing Brain: A Review From the Connectome Perspective. Front Neurosci 2020; 14:476. [PMID: 32581671 PMCID: PMC7284109 DOI: 10.3389/fnins.2020.00476] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 04/16/2020] [Indexed: 12/21/2022] Open
Abstract
Early brain development from infancy through childhood is closely related to the development of cognition and behavior in later life. Human brain connectome is a novel framework for describing topological organization of the developing brain. Resting-state functional near-infrared spectroscopy (fNIRS), with a natural scanning environment, low cost, and high portability, is considered as an emerging imaging technique and has shown valuable potential in exploring brain network architecture and its changes during the development. Here, we review the recent advances involving typical and atypical development of the brain connectome from neonates to children using resting-state fNIRS imaging. This review highlights that the combination of brain connectome and resting-state fNIRS imaging offers a promising framework for understanding human brain development.
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Affiliation(s)
- Zhishan Hu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Guangfang Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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Hu Z, Lam KF, Yuan Z. Effective Connectivity of the Fronto-Parietal Network during the Tangram Task in a Natural Environment. Neuroscience 2019; 422:202-211. [DOI: 10.1016/j.neuroscience.2019.09.021] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2019] [Revised: 09/12/2019] [Accepted: 09/13/2019] [Indexed: 12/14/2022]
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