1
|
Curzel F, Tillmann B, Ferreri L. Lights on music cognition: A systematic and critical review of fNIRS applications and future perspectives. Brain Cogn 2024; 180:106200. [PMID: 38908228 DOI: 10.1016/j.bandc.2024.106200] [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: 04/06/2024] [Revised: 06/10/2024] [Accepted: 06/16/2024] [Indexed: 06/24/2024]
Abstract
Research investigating the neural processes related to music perception and production constitutes a well-established field within the cognitive neurosciences. While most neuroimaging tools have limitations in studying the complexity of musical experiences, functional Near-Infrared Spectroscopy (fNIRS) represents a promising, relatively new tool for studying music processes in both laboratory and ecological settings, which is also suitable for both typical and pathological populations across development. Here we systematically review fNIRS studies on music cognition, highlighting prospects and potentialities. We also include an overview of fNIRS basic theory, together with a brief comparison to characteristics of other neuroimaging tools. Fifty-nine studies meeting inclusion criteria (i.e., using fNIRS with music as the primary stimulus) are presented across five thematic sections. Critical discussion of methodology leads us to propose guidelines of good practices aiming for robust signal analyses and reproducibility. A continuously updated world map is proposed, including basic information from studies meeting the inclusion criteria. It provides an organized, accessible, and updatable reference database, which could serve as a catalyst for future collaborations within the community. In conclusion, fNIRS shows potential for investigating cognitive processes in music, particularly in ecological contexts and with special populations, aligning with current research priorities in music cognition.
Collapse
Affiliation(s)
- Federico Curzel
- Laboratoire d'Étude des Mécanismes Cognitifs (EMC), Université Lumière Lyon 2, Bron, Auvergne-Rhône-Alpes, 69500, France; Lyon Neuroscience Research Center (CRNL), INSERM, U1028, CNRS, UMR 5292, Université Claude Bernard Lyon1, Université de Lyon, Bron, Auvergne-Rhône-Alpes, 69500, France.
| | - Barbara Tillmann
- Lyon Neuroscience Research Center (CRNL), INSERM, U1028, CNRS, UMR 5292, Université Claude Bernard Lyon1, Université de Lyon, Bron, Auvergne-Rhône-Alpes, 69500, France; LEAD CNRS UMR5022, Université de Bourgogne-Franche Comté, Dijon, Bourgogne-Franche Comté 21000, France.
| | - Laura Ferreri
- Laboratoire d'Étude des Mécanismes Cognitifs (EMC), Université Lumière Lyon 2, Bron, Auvergne-Rhône-Alpes, 69500, France; Department of Brain and Behavioural Sciences, Università di Pavia, Pavia, Lombardia 27100, Italy.
| |
Collapse
|
2
|
Thunberg P, Wastensson G, Lidén G, Adjeiwaah M, Tellman J, Bergström B, Fornander L, Lundberg P. Welding techniques and manganese concentrations in blood and brain: Results from the WELDFUMES study. Neurotoxicology 2024; 105:121-130. [PMID: 39326638 DOI: 10.1016/j.neuro.2024.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 09/19/2024] [Accepted: 09/23/2024] [Indexed: 09/28/2024]
Abstract
This study used whole-brain mapping to investigate the effect of different welding processes on manganese (Mn) accumulation in the brain. Exposure measurements were performed at the welders' workplaces about 3 weeks before a magnetic resonance imaging (MRI) examination. The welders were categorized into three main groups based on welding method, and the T1-relaxation rate (R1) was measured using quantitative MRI (qMRI). Welders using shielded metal arc welding (SMAW) were found to have lower accumulations of total Mn in clusters encompassing white matter, thalamus, putamen, pallidum, and substantia nigra compared with welders using inert gas tungsten arc welding (GTAW) or continuous consumable electrode arc welding (CCEAW). A positive correlation was found between Mn in red blood cells (Mn-RBC) and R1 in a region encompassing pre-and post-central gyri. The results of this study show that the accumulation of free, bound, or compartmentalized Mn ions in the brain differed depending on the welding method used. These differences were predominately located in the basal ganglia but were also found in regions encompassing white matter. The level of Mn-RBC was correlated to the deposition of Mn in the left primary somatosensory and motor cortex and may therefore be linked to neurological and neurobehavioral symptoms.
Collapse
Affiliation(s)
- Per Thunberg
- Center for Experimental and Biomedical Imaging in Örebro (CEBIO), Örebro University, Örebro, Sweden; Department of Radiology and Medical Physics, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
| | - Gunilla Wastensson
- Department of Occupational and Environmental Medicine, School of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Göran Lidén
- Department of Environment Science, Stockholm University, Stockholm, Sweden
| | - Mary Adjeiwaah
- Center for Medical Imaging and Visualization Science (CMIV), Linköping University, Linköping, Sweden; Department of Radiation Physics and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Jens Tellman
- Center for Medical Imaging and Visualization Science (CMIV), Linköping University, Linköping, Sweden; Department of Radiation Physics and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Bernt Bergström
- Department of Occupational and Environmental Medicine, Örebro University Hospital, Region Örebro County, Sweden
| | - Louise Fornander
- Department of Occupational and Environmental Medicine, Faculty of Medicine and Health, Örebro University, Sweden
| | - Peter Lundberg
- Center for Medical Imaging and Visualization Science (CMIV), Linköping University, Linköping, Sweden; Department of Radiation Physics and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| |
Collapse
|
3
|
Liu J, Han L, Ji J. MCAN: Multimodal Causal Adversarial Networks for Dynamic Effective Connectivity Learning From fMRI and EEG Data. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:2913-2923. [PMID: 38526887 DOI: 10.1109/tmi.2024.3381670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Dynamic effective connectivity (DEC) is the accumulation of effective connectivity in the time dimension, which can describe the continuous neural activities in the brain. Recently, learning DEC from functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data has attracted the attention of neuroinformatics researchers. However, the current methods fail to consider the gap between the fMRI and EEG modality, which can not precisely learn the DEC network from multimodal data. In this paper, we propose a multimodal causal adversarial network for DEC learning, named MCAN. The MCAN contains two modules: multimodal causal generator and multimodal causal discriminator. First, MCAN employs a multimodal causal generator with an attention-guided layer to produce a posterior signal and output a set of DEC networks. Then, the proposed method uses a multimodal causal discriminator to unsupervised calculate the joint gradient, which directs the update of the whole network. The experimental results on simulated data sets show that MCAN is superior to other state-of-the-art methods in learning the network structure of DEC and can effectively estimate the brain states. The experimental results on real data sets show that MCAN can better reveal abnormal patterns of brain activity and has good application potential in brain network analysis.
Collapse
|
4
|
Klein F. Optimizing spatial specificity and signal quality in fNIRS: an overview of potential challenges and possible options for improving the reliability of real-time applications. FRONTIERS IN NEUROERGONOMICS 2024; 5:1286586. [PMID: 38903906 PMCID: PMC11188482 DOI: 10.3389/fnrgo.2024.1286586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 04/29/2024] [Indexed: 06/22/2024]
Abstract
The optical brain imaging method functional near-infrared spectroscopy (fNIRS) is a promising tool for real-time applications such as neurofeedback and brain-computer interfaces. Its combination of spatial specificity and mobility makes it particularly attractive for clinical use, both at the bedside and in patients' homes. Despite these advantages, optimizing fNIRS for real-time use requires careful attention to two key aspects: ensuring good spatial specificity and maintaining high signal quality. While fNIRS detects superficial cortical brain regions, consistently and reliably targeting specific regions of interest can be challenging, particularly in studies that require repeated measurements. Variations in cap placement coupled with limited anatomical information may further reduce this accuracy. Furthermore, it is important to maintain good signal quality in real-time contexts to ensure that they reflect the true underlying brain activity. However, fNIRS signals are susceptible to contamination by cerebral and extracerebral systemic noise as well as motion artifacts. Insufficient real-time preprocessing can therefore cause the system to run on noise instead of brain activity. The aim of this review article is to help advance the progress of fNIRS-based real-time applications. It highlights the potential challenges in improving spatial specificity and signal quality, discusses possible options to overcome these challenges, and addresses further considerations relevant to real-time applications. By addressing these topics, the article aims to help improve the planning and execution of future real-time studies, thereby increasing their reliability and repeatability.
Collapse
Affiliation(s)
- Franziska Klein
- Biomedical Devices and Systems Group, R&D Division Health, OFFIS - Institute for Information Technology, Oldenburg, Germany
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical School, RWTH Aachen University, Aachen, Germany
- Neurocognition and Functional Neurorehabilitation Group, Department of Psychology, University of Oldenburg, Oldenburg, Germany
| |
Collapse
|
5
|
Zinos A, Wagner JC, Beardsley SA, Chen WL, Conant L, Malloy M, Heffernan J, Quirk B, Prost R, Maheshwari M, Sugar J, Whelan HT. Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: Toward clinical use within subject. Neuroimage 2024; 290:120569. [PMID: 38461959 DOI: 10.1016/j.neuroimage.2024.120569] [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: 08/29/2023] [Revised: 12/15/2023] [Accepted: 03/07/2024] [Indexed: 03/12/2024] Open
Abstract
Functional near infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) both measure the hemodynamic response, and so both imaging modalities are expected to have a strong correspondence in regions of cortex adjacent to the scalp. To assess whether fNIRS can be used clinically in a manner similar to fMRI, 22 healthy adult participants underwent same-day fMRI and whole-head fNIRS testing while they performed separate motor (finger tapping) and visual (flashing checkerboard) tasks. Analyses were conducted within and across subjects for each imaging approach, and regions of significant task-related activity were compared on the cortical surface. The spatial correspondence between fNIRS and fMRI detection of task-related activity was good in terms of true positive rate, with fNIRS overlap of up to 68 % of the fMRI for analyses across subjects (group analysis) and an average overlap of up to 47.25 % for individual analyses within subject. At the group level, the positive predictive value of fNIRS was 51 % relative to fMRI. The positive predictive value for within subject analyses was lower (41.5 %), reflecting the presence of significant fNIRS activity in regions without significant fMRI activity. This could reflect task-correlated sources of physiologic noise and/or differences in the sensitivity of fNIRS and fMRI measures to changes in separate (vs. combined) measures of oxy and de-oxyhemoglobin. The results suggest whole-head fNIRS as a noninvasive imaging modality with promising clinical utility for the functional assessment of brain activity in superficial regions of cortex physically adjacent to the skull.
Collapse
Affiliation(s)
- Anthony Zinos
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
| | - Julie C Wagner
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
| | - Scott A Beardsley
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA; Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA.
| | - Wei-Liang Chen
- Center for Neuroscience Research, Children's National Medical Center, George Washington University, Washington DC, USA
| | - Lisa Conant
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Marsha Malloy
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA; Department of Neurology, Children's Wisconsin, Milwaukee, WI, USA
| | - Joseph Heffernan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Brendan Quirk
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Robert Prost
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Mohit Maheshwari
- Department of Radiology, Children's Wisconsin, Milwaukee, WI, USA
| | - Jeffrey Sugar
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Harry T Whelan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA; Department of Neurology, Children's Wisconsin, Milwaukee, WI, USA
| |
Collapse
|
6
|
Tang L, Kebaya LMN, Altamimi T, Kowalczyk A, Musabi M, Roychaudhuri S, Vahidi H, Meyerink P, de Ribaupierre S, Bhattacharya S, de Moraes LTAR, St Lawrence K, Duerden EG. Altered resting-state functional connectivity in newborns with hypoxic ischemic encephalopathy assessed using high-density functional near-infrared spectroscopy. Sci Rep 2024; 14:3176. [PMID: 38326455 PMCID: PMC10850364 DOI: 10.1038/s41598-024-53256-0] [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: 11/06/2023] [Accepted: 01/30/2024] [Indexed: 02/09/2024] Open
Abstract
Hypoxic-ischemic encephalopathy (HIE) results from a lack of oxygen to the brain during the perinatal period. HIE can lead to mortality and various acute and long-term morbidities. Improved bedside monitoring methods are needed to identify biomarkers of brain health. Functional near-infrared spectroscopy (fNIRS) can assess resting-state functional connectivity (RSFC) at the bedside. We acquired resting-state fNIRS data from 21 neonates with HIE (postmenstrual age [PMA] = 39.96), in 19 neonates the scans were acquired post-therapeutic hypothermia (TH), and from 20 term-born healthy newborns (PMA = 39.93). Twelve HIE neonates also underwent resting-state functional magnetic resonance imaging (fMRI) post-TH. RSFC was calculated as correlation coefficients amongst the time courses for fNIRS and fMRI data, respectively. The fNIRS and fMRI RSFC maps were comparable. RSFC patterns were then measured with graph theory metrics and compared between HIE infants and healthy controls. HIE newborns showed significantly increased clustering coefficients, network efficiency and modularity compared to controls. Using a support vector machine algorithm, RSFC features demonstrated good performance in classifying the HIE and healthy newborns in separate groups. Our results indicate the utility of fNIRS-connectivity patterns as potential biomarkers for HIE and fNIRS as a new bedside tool for newborns with HIE.
Collapse
Affiliation(s)
- Lingkai Tang
- Biomedical Engineering, Faculty of Engineering, Western University, London, ON, Canada
| | - Lilian M N Kebaya
- Neuroscience, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
- Neonatal-Perinatal Medicine, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Paediatrics, Division of Neonatal-Perinatal Medicine, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Talal Altamimi
- Neonatal-Perinatal Medicine, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Alexandra Kowalczyk
- Neonatal-Perinatal Medicine, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Melab Musabi
- Neonatal-Perinatal Medicine, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Sriya Roychaudhuri
- Neonatal-Perinatal Medicine, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Homa Vahidi
- Neuroscience, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Paige Meyerink
- Neonatal-Perinatal Medicine, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Sandrine de Ribaupierre
- Neuroscience, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
- Clinical Neurological Sciences, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Soume Bhattacharya
- Neonatal-Perinatal Medicine, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Keith St Lawrence
- Biomedical Engineering, Faculty of Engineering, Western University, London, ON, Canada
- Medical Biophysics, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada
| | - Emma G Duerden
- Biomedical Engineering, Faculty of Engineering, Western University, London, ON, Canada.
- Neuroscience, Schulich Faculty of Medicine and Dentistry, Western University, London, ON, Canada.
- Applied Psychology, Faculty of Education, Western University, 1137 Western Rd, London, ON, N6G 1G7, Canada.
| |
Collapse
|
7
|
Dimova V, Welte-Jzyk C, Kronfeld A, Korczynski O, Baier B, Koirala N, Steenken L, Kollmann B, Tüscher O, Brockmann MA, Birklein F, Muthuraman M. Brain connectivity networks underlying resting heart rate variability in acute ischemic stroke. Neuroimage Clin 2023; 41:103558. [PMID: 38142520 PMCID: PMC10788522 DOI: 10.1016/j.nicl.2023.103558] [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: 09/14/2023] [Revised: 12/18/2023] [Accepted: 12/18/2023] [Indexed: 12/26/2023]
Abstract
Acute strokes can affect heart rate variability (HRV), the mechanisms how are not well understood. We included 42 acute stroke patients (2-7 days after ischemic stroke, mean age 66 years, 16 women). For analysis of HRV, 20 matched controls (mean age 60.7, 10 women) were recruited. HRV was assessed at rest, in a supine position and individual breathing rhythmus for 5 min. The coefficient of variation (VC), the root mean square of successive differences (RMSSD), the powers of low (LF, 0.04-0.14 Hz) and high (HF, 0.15-0.50 Hz) frequency bands were extracted. HRV parameters were z-transformed related to age- and sex-matched normal subjects. Z-values < -1 indicate reduced HRV. Acute stroke lesions were marked on diffusion-weighted images employing MRIcroN and co-registered to a T1-weighted structural volume-dataset. Using independent component analysis (ICA), stroke lesions were related to HRV. Subsequently, we used the ICA-derived lesion pattern as a seed and estimated the connectivity between these brain regions and seven common functional networks, which were obtained from 50 age-matched healthy subjects (mean age 68.9, 27 women). Especially, LF and VC were frequently reduced in patients. ICA revealed one covarying lesion pattern for LF and one similar for VC, predominantly affecting the right hemisphere. Activity in brain areas corresponding to these lesions mainly impact on limbic (r = 0.55 ± 0.08) and salience ventral attention networks (0.61 ± 0.10) in the group with reduced LF power (z-score < -1), but on control and default mode networks in the group with physiological LF power (z-score > -1). No different connectivity could be found for the respective VC groups. Our results suggest that HRV alteration after acute stroke might be due to affecting resting-state brain networks.
Collapse
Affiliation(s)
- Violeta Dimova
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Claudia Welte-Jzyk
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Andrea Kronfeld
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Oliver Korczynski
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Bernhard Baier
- Edith-Stein Fachklinik for Neurorehabilitation, Bad Bergzabern, Germany
| | - Nabin Koirala
- Haskins Laboratories, Yale University, New Haven, CT 06511, USA
| | - Livia Steenken
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Bianca Kollmann
- Leibniz Institute for Resilience Research (LIR) gGmbH, Mainz, Germany; Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Oliver Tüscher
- Leibniz Institute for Resilience Research (LIR) gGmbH, Mainz, Germany; Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany; Institute for Molecular Biology (IMB), Mainz, Germany
| | - Marc A Brockmann
- Department of Neuroradiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Frank Birklein
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany; Neural Engineering with Signal Analytics and Artificial Intelligence, Department of Neurology, University of Würzburg, Würzburg, Germany.
| |
Collapse
|
8
|
Jordan N, Emanuelle R. Hands off, brain off? A meta-analysis of neuroimaging data during active and passive driving. Brain Behav 2023; 13:e3272. [PMID: 37828722 PMCID: PMC10726911 DOI: 10.1002/brb3.3272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 09/21/2023] [Accepted: 09/23/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND Car driving is more and more automated, to such an extent that driving without active steering control is becoming a reality. Although active driving requires the use of visual information to guide actions (i.e., steering the vehicle), passive driving only requires looking at the driving scene without any need to act (i.e., the human is passively driven). MATERIALS & METHODS After a careful search of the scientific literature, 11 different studies, providing 17 contrasts, were used to run a comprehensive meta-analysis contrasting active driving with passive driving. RESULTS Two brain regions were recruited more consistently for active driving compared to passive driving, the left precentral gyrus (BA3 and BA4) and the left postcentral gyrus (BA4 and BA3/40), whereas a set of brain regions was recruited more consistently in passive driving compared to active driving: the left middle frontal gyrus (BA6), the right anterior lobe and the left posterior lobe of the cerebellum, the right sub-lobar thalamus, the right anterior prefrontal cortex (BA10), the right inferior occipital gyrus (BA17/18/19), the right inferior temporal gyrus (BA37), and the left cuneus (BA17). DISCUSSION From a theoretical perspective, these findings support the idea that the output requirement of the visual scanning process engaged for the same activity can trigger different cerebral pathways, associated with different cognitive processes. A dorsal stream dominance was found during active driving, whereas a ventral stream dominance was obtained during passive driving. From a practical perspective, and contrary to the dominant position in the Human Factors community, our findings support the idea that a transition from passive to active driving would remain challenging as passive and active driving engage distinct neural networks.
Collapse
Affiliation(s)
- Navarro Jordan
- Laboratoire d'Etude des Mécanismes Cognitifs (EA 3082)Université de LyonBron Cedex, LyonFrance
- Institut Universitaire de FranceParisFrance
| | - Reynaud Emanuelle
- Laboratoire d'Etude des Mécanismes Cognitifs (EA 3082)Université de LyonBron Cedex, LyonFrance
| |
Collapse
|
9
|
Rosanne O, Alves de Oliveira A, Falk TH. EEG Amplitude Modulation Analysis across Mental Tasks: Towards Improved Active BCIs. SENSORS (BASEL, SWITZERLAND) 2023; 23:9352. [PMID: 38067725 PMCID: PMC10708818 DOI: 10.3390/s23239352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 11/15/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023]
Abstract
Brain-computer interface (BCI) technology has emerged as an influential communication tool with extensive applications across numerous fields, including entertainment, marketing, mental state monitoring, and particularly medical neurorehabilitation. Despite its immense potential, the reliability of BCI systems is challenged by the intricacies of data collection, environmental factors, and noisy interferences, making the interpretation of high-dimensional electroencephalogram (EEG) data a pressing issue. While the current trends in research have leant towards improving classification using deep learning-based models, our study proposes the use of new features based on EEG amplitude modulation (AM) dynamics. Experiments on an active BCI dataset comprised seven mental tasks to show the importance of the proposed features, as well as their complementarity to conventional power spectral features. Through combining the seven mental tasks, 21 binary classification tests were explored. In 17 of these 21 tests, the addition of the proposed features significantly improved classifier performance relative to using power spectral density (PSD) features only. Specifically, the average kappa score for these classifications increased from 0.57 to 0.62 using the combined feature set. An examination of the top-selected features showed the predominance of the AM-based measures, comprising over 77% of the top-ranked features. We conclude this paper with an in-depth analysis of these top-ranked features and discuss their potential for use in neurophysiology.
Collapse
Affiliation(s)
- Olivier Rosanne
- Institut National de la Recherche Scientifique, University of Quebec, Montreal, QC H5A 1K6, Canada;
| | - Alcyr Alves de Oliveira
- Graduate Program in Psychology and Health, Federal University of Health Sciences of Porto Alegre, Porto Alegre 90050-170, Brazil;
| | - Tiago H. Falk
- Institut National de la Recherche Scientifique, University of Quebec, Montreal, QC H5A 1K6, Canada;
| |
Collapse
|
10
|
Chen YF, Mao MC, Zhu GY, Sun CC, Zhao JW, He HX, Chen YH, Xu DS. The changes of neuroactivity of Tui Na (Chinese massage) at Hegu acupoint on sensorimotor cortex in stroke patients with upper limb motor dysfunction: a fNIRS study. BMC Complement Med Ther 2023; 23:334. [PMID: 37735652 PMCID: PMC10512523 DOI: 10.1186/s12906-023-04143-0] [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: 09/07/2022] [Accepted: 08/27/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND Tui Na (Chinese massage) is a relatively simple, inexpensive, and non-invasive intervention, and has been used to treat stroke patients for many years in China. Tui Na acts on specific parts of the body which are called meridians and acupoints to achieve the role of treating diseases. Yet the underlying neural mechanism associated with Tui Na is not clear due to the lack of detection methods. OBJECTIVE Functional near-infrared spectroscopy (fNIRS) was used to explore the changes of sensorimotor cortical neural activity in patients with upper limb motor dysfunction of stroke and healthy control groups during Tui Na Hegu Point. METHODS Ten patients with unilateral upper limb motor dysfunction after stroke and eight healthy subjects received Tui Na. fNIRS was used to record the hemodynamic data in the sensorimotor cortex and the changes in blood flow were calculated based on oxygenated hemoglobin (Oxy-Hb), the task session involved repetitive Tui Na on Hegu acupoint, using a block design [six cycles: rest (20 seconds); Tui Na (20 seconds); rest (30 seconds)]. The changes in neural activity in sensorimotor cortex could be inferred according to the principle of neurovascular coupling, and the number of activated channels in the bilateral hemisphere was used to calculate the lateralization index. RESULT 1. For hemodynamic response induced by Hegu acupoint Tui Na, a dominant increase in the contralesional primary sensorimotor cortex during Hegu point Tui Na of the less affected arm in stroke patients was observed, as well as that in healthy controls, while this contralateral pattern was absent during Hegu point Tui Na of the affected arm in stroke patients. 2. Concerning the lateralization index in stroke patients, a significant difference was observed between lateralization index values for the affected arm and the less affected arm (P < 0.05). Wilcoxon tests showed a significant difference between lateralization index values for the affected arm in stroke patients and lateralization index values for the dominant upper limb in healthy controls (P < 0.05), and no significant difference between lateralization index values for the less affected arm in stroke patients and that in healthy controls (P = 0.36). CONCLUSION The combination of Tui Na and fNIRS has the potential to reflect the functional status of sensorimotor neural circuits. The changes of neuroactivity in the sensorimotor cortex when Tui Na Hegu acupoint indicate that there is a certain correlation between acupoints in traditional Chinese medicine and neural circuits.
Collapse
Affiliation(s)
- Yu-Feng Chen
- Department of Massage, Hangzhou Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Meng-Chai Mao
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
- The Second Rehabilitation Hospital of Shanghai, Shanghai, China
| | - Guang-Yue Zhu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Cheng-Cheng Sun
- Rehabilitation Medical Center, Tongji Hospital Affiliated to Tongji University School of Medicine, Shanghai, China
| | - Jing-Wang Zhao
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Hao-Xiang He
- Department of Intensive Rehabilitation, Shanghai Third Rehabilitation Hospital, Shanghai, China
| | - Yu-Hui Chen
- Department of Internal Neurology, Tongji Hospital, Tongji University, Shanghai, China.
| | - Dong-Sheng Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China.
- Department of Rehabilitation, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
| |
Collapse
|
11
|
Bonnal J, Ozsancak C, Monnet F, Valery A, Prieur F, Auzou P. Neural Substrates for Hand and Shoulder Movement in Healthy Adults: A Functional near Infrared Spectroscopy Study. Brain Topogr 2023:10.1007/s10548-023-00972-x. [PMID: 37202647 DOI: 10.1007/s10548-023-00972-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 05/11/2023] [Indexed: 05/20/2023]
Abstract
Characterization of cortical activation patterns during movements in healthy adults may help our understanding of how the injured brain works. Upper limb motor tasks are commonly used to assess impaired motor function and to predict recovery in individuals with neurological disorders such as stroke. This study aimed to explore cortical activation patterns associated with movements of the hand and shoulder using functional near-infrared spectroscopy (fNIRS) and to demonstrate the potential of this technology to distinguish cerebral activation between distal and proximal movements. Twenty healthy, right-handed participants were recruited. Two 10-s motor tasks (right-hand opening-closing and right shoulder abduction-adduction) were performed in a sitting position at a rate of 0.5 Hz in a block paradigm. We measured the variations in oxyhemoglobin (HbO2) and deoxyhemoglobin (HbR) concentrations. fNIRS was performed with a 24-channel system (Brite 24®; Artinis) that covered most motor control brain regions bilaterally. Activation was mostly contralateral for both hand and shoulder movements. Activation was more lateral for hand movements and more medial for shoulder movements, as predicted by the classical homunculus representation. Both HbO2 and HbR concentrations varied with the activity. Our results showed that fNIRS can distinguish patterns of cortical activity in upper limb movements under ecological conditions. These results suggest that fNIRS can be used to measure spontaneous motor recovery and rehabilitation-induced recovery after brain injury. The trial was restropectively registered on January 20, 2023: NCT05691777 (clinicaltrial.gov).
Collapse
Affiliation(s)
- Julien Bonnal
- Service de Neurologie, Centre Hospitalier Universitaire d'Orléans, 14 Avenue de l'Hôpital, 45100, Orleans, France.
- CIAMS, Université Paris-Saclay, 91405, Orsay Cedex, France.
- CIAMS, Université d'Orléans, 45067, Orléans, France.
- SAPRéM, Université d'Orléans, Orléans, France.
| | - Canan Ozsancak
- Service de Neurologie, Centre Hospitalier Universitaire d'Orléans, 14 Avenue de l'Hôpital, 45100, Orleans, France
| | - Fanny Monnet
- Institut Denis Poisson, Bâtiment de mathématiques, Université d'Orléans, CNRS, Université de Tours, Institut Universitaire de France, Rue de Chartres, 45067, Orléans cedex 2, B.P. 6759, France
| | - Antoine Valery
- Département d'Informations Médicales, Centre Hospitalier Universitaire d'Orléans, 14 Avenue de l'Hôpital, 45100, Orleans, France
| | - Fabrice Prieur
- CIAMS, Université Paris-Saclay, 91405, Orsay Cedex, France
- CIAMS, Université d'Orléans, 45067, Orléans, France
- SAPRéM, Université d'Orléans, Orléans, France
| | - Pascal Auzou
- Service de Neurologie, Centre Hospitalier Universitaire d'Orléans, 14 Avenue de l'Hôpital, 45100, Orleans, France
| |
Collapse
|
12
|
Nandi B, Ostrand A, Johnson V, Ford TJ, Gazzaley A, Zanto TP. Musical Training Facilitates Exogenous Temporal Attention via Delta Phase Entrainment within a Sensorimotor Network. J Neurosci 2023; 43:3365-3378. [PMID: 36977585 PMCID: PMC10162458 DOI: 10.1523/jneurosci.0220-22.2023] [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: 01/27/2022] [Revised: 01/24/2023] [Accepted: 01/28/2023] [Indexed: 03/30/2023] Open
Abstract
Temporal orienting of attention plays an important role in our day-to-day lives and can use timing information from exogenous or endogenous sources. Yet, it is unclear what neural mechanisms give rise to temporal attention, and it is debated whether both exogenous and endogenous forms of temporal attention share a common neural source. Here, older adult nonmusicians (N = 47, 24 female) were randomized to undergo 8 weeks of either rhythm training, which places demands on exogenous temporal attention, or word search training as a control. The goal was to assess (1) the neural basis of exogenous temporal attention and (2) whether training-induced improvements in exogenous temporal attention can transfer to enhanced endogenous temporal attention abilities, thereby providing support for a common neural mechanism of temporal attention. Before and after training, exogenous temporal attention was assessed using a rhythmic synchronization paradigm, whereas endogenous temporal attention was evaluated via a temporally cued visual discrimination task. Results showed that rhythm training improved performance on the exogenous temporal attention task, which was associated with increased intertrial coherence within the δ (1-4 Hz) band as assessed by EEG recordings. Source localization revealed increased δ-band intertrial coherence arose from a sensorimotor network, including premotor cortex, anterior cingulate cortex, postcentral gyrus, and the inferior parietal lobule. Despite these improvements in exogenous temporal attention, such benefits were not transferred to endogenous attentional ability. These results support the notion that exogenous and endogenous temporal attention uses independent neural sources, with exogenous temporal attention relying on the precise timing of δ band oscillations within a sensorimotor network.SIGNIFICANCE STATEMENT Allocating attention to specific points in time is known as temporal attention, and may arise from external (exogenous) or internal (endogenous) sources. Despite its importance to our daily lives, it is unclear how the brain gives rise to temporal attention and whether exogenous- or endogenous-based sources for temporal attention rely on shared brain regions. Here, we demonstrate that musical rhythm training improves exogenous temporal attention, which was associated with more consistent timing of neural activity in sensory and motor processing brain regions. However, these benefits did not extend to endogenous temporal attention, indicating that temporal attention relies on different brain regions depending on the source of timing information.
Collapse
Affiliation(s)
- Bijurika Nandi
- Department of Neurology, University of California-San Francisco, San Francisco, California 94158
- Neuroscape, University of California-San Francisco, San Francisco, California 94158
| | - Avery Ostrand
- Department of Neurology, University of California-San Francisco, San Francisco, California 94158
- Neuroscape, University of California-San Francisco, San Francisco, California 94158
| | - Vinith Johnson
- Department of Neurology, University of California-San Francisco, San Francisco, California 94158
- Neuroscape, University of California-San Francisco, San Francisco, California 94158
| | - Tiffany J Ford
- Department of Neurology, University of California-San Francisco, San Francisco, California 94158
- Neuroscape, University of California-San Francisco, San Francisco, California 94158
| | - Adam Gazzaley
- Department of Neurology, University of California-San Francisco, San Francisco, California 94158
- Neuroscape, University of California-San Francisco, San Francisco, California 94158
- Departments of Physiology and Psychiatry, University of California-San Francisco, San Francisco, California 94158
| | - Theodore P Zanto
- Department of Neurology, University of California-San Francisco, San Francisco, California 94158
- Neuroscape, University of California-San Francisco, San Francisco, California 94158
| |
Collapse
|
13
|
Muller CO, Perrey S, Bakhti K, Muthalib M, Dray G, Xu B, Mottet D, Laffont I. Aging effects on electrical and hemodynamic responses in the sensorimotor network during unilateral proximal upper limb functional tasks. Behav Brain Res 2023; 443:114322. [PMID: 36731658 DOI: 10.1016/j.bbr.2023.114322] [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: 10/10/2022] [Revised: 01/04/2023] [Accepted: 01/29/2023] [Indexed: 02/01/2023]
Abstract
Healthy aging leads to poorer performance in upper limb (UL) daily living movements. Understanding the neural correlates linked with UL functional movements may help to better understand how healthy aging affects motor control. Two non-invasive neuroimaging methods allow for monitoring the movement-related brain activity: functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), respectively based on the hemodynamic response and electrical activity of brain regions. Coupled, they provide a better spatiotemporal mapping. The aim of this study was to evaluate the effect of healthy aging on the bilateral sensorimotor (SM1) activation patterns of functional proximal UL movements. Twenty-one young and 21 old healthy participants realized two unilateral proximal UL movements during: i) a paced reaching target task and ii) a circular steering task to capture the speed-accuracy trade-off. Combined fNIRS-EEG system was synchronised with movement capture system to record SM1 activation while moving. The circular steering task performance was significantly lower for the older group. The rate of increase in hemodynamic response was longer in the older group with no difference on the amplitude of fNIRS signal for the two tasks. The EEG results showed aging related reduction of the alpha-beta rhythms synchronisation but no desynchronisation modification. In conclusion, this study uncovers the age-related changes in brain electrical and hemodynamic response patterns in the bilateral sensorimotor network during two functional proximal UL movements using two complementary neuroimaging methods. This opens up the possibility to utilise combined fNIRS-EEG for monitoring the movement-related neuroplasticity in clinical practice.
Collapse
Affiliation(s)
- C O Muller
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France; Physical Rehabilitation and Medicine, CHU Montpellier, Montpellier, France.
| | - S Perrey
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - K Bakhti
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France; Physical Rehabilitation and Medicine, CHU Montpellier, Montpellier, France; Clinical Research and Epidemiology unit, CHU Montpellier, Univ Montpellier, Montpellier, France
| | - M Muthalib
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France; Physical Rehabilitation and Medicine, CHU Montpellier, Montpellier, France; Silverline Research, Brisbane, Australia
| | - G Dray
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - B Xu
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - D Mottet
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France
| | - I Laffont
- EuroMov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Montpellier, France; Physical Rehabilitation and Medicine, CHU Montpellier, Montpellier, France
| |
Collapse
|
14
|
Ji J, Zou A, Liu J, Yang C, Zhang X, Song Y. A Survey on Brain Effective Connectivity Network Learning. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023; 34:1879-1899. [PMID: 34469315 DOI: 10.1109/tnnls.2021.3106299] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Human brain effective connectivity characterizes the causal effects of neural activities among different brain regions. Studies of brain effective connectivity networks (ECNs) for different populations contribute significantly to the understanding of the pathological mechanism associated with neuropsychiatric diseases and facilitate finding new brain network imaging markers for the early diagnosis and evaluation for the treatment of cerebral diseases. A deeper understanding of brain ECNs also greatly promotes brain-inspired artificial intelligence (AI) research in the context of brain-like neural networks and machine learning. Thus, how to picture and grasp deeper features of brain ECNs from functional magnetic resonance imaging (fMRI) data is currently an important and active research area of the human brain connectome. In this survey, we first show some typical applications and analyze existing challenging problems in learning brain ECNs from fMRI data. Second, we give a taxonomy of ECN learning methods from the perspective of computational science and describe some representative methods in each category. Third, we summarize commonly used evaluation metrics and conduct a performance comparison of several typical algorithms both on simulated and real datasets. Finally, we present the prospects and references for researchers engaged in learning ECNs.
Collapse
|
15
|
Hashitomi T, Hoshi D, Fukuie M, Tarumi T, Sugawara J, Watanabe K. Differences in the prefrontal cortex responses of healthy young men performing either water-based or land-based exercise at light to moderate intensity. Exp Brain Res 2023; 241:991-1000. [PMID: 36943454 PMCID: PMC10082107 DOI: 10.1007/s00221-023-06583-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 02/24/2023] [Indexed: 03/23/2023]
Abstract
Cerebral blood flow increases more during water-based exercise than land-based exercise owing to the effects of end-tidal CO2 (PETCO2) and mean arterial pressure (MAP) changes due to water immersion. However, it is unclear whether oxygenated hemoglobin (oxy-Hb) concentrations in the prefrontal cortex (PFC) are increased more by water-based or land-based exercise. We hypothesized that oxy-Hb concentrations in the PFC are higher during water-based exercise than land-based exercise when the exercise intensity is matched. To test this hypothesis, 10 healthy participants (age: 24.2 ± 1.7 years; height: 1.75 ± 0.04 m; weight: 69.5 ± 5.2 kg) performed light- to moderate-intensity cycling exercise in water (water-based cycling (WC); chest-high water at 30 °C) and on land (LC). Stroke volume, cardio output, heart rate, MAP, respiratory rate, PETCO2, and oxy-Hb in the PFC were assessed during 15 min of exercise, with exercise intensity increased every 5 min. Both WC and LC significantly increased oxy-Hb concentrations in the PFC as exercise intensity was increased (intensity effect: p < 0.001). There was no significant difference in oxy-Hb concentrations during WC and LC in most prefrontal areas, although significant differences were found in areas corresponding to the left dorsolateral PFC (exercise effect: p < 0.001). Thus, WC and LC increase oxy-Hb concentrations in the PFC in a similar manner with increasing exercise intensity, but part of the PFC exhibits enhanced oxy-Hb levels during WC. The neural response of the PFC may differ during water-based and land-based exercise owing to differences in external information associated with water immersion.
Collapse
Affiliation(s)
- Tatsuya Hashitomi
- Doctoral Program in Sports Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Daisuke Hoshi
- Doctoral Program in Sports Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan
| | - Marina Fukuie
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan
| | - Takashi Tarumi
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan
- Faculty of Health and Sports Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Jun Sugawara
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan
- Faculty of Health and Sports Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8577, Japan
| | - Koichi Watanabe
- Faculty of Health and Sports Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki, 305-8577, Japan.
| |
Collapse
|
16
|
Chiarion G, Sparacino L, Antonacci Y, Faes L, Mesin L. Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends. Bioengineering (Basel) 2023; 10:bioengineering10030372. [PMID: 36978763 PMCID: PMC10044923 DOI: 10.3390/bioengineering10030372] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 03/10/2023] [Accepted: 03/14/2023] [Indexed: 03/30/2023] Open
Abstract
Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural activation and connectivity. In this work, we provide a technical account and a categorization of the most-used data-driven approaches to assess brain-functional connectivity, intended as the study of the statistical dependencies between the recorded EEG signals. Different pairwise and multivariate, as well as directed and non-directed connectivity metrics are discussed with a pros-cons approach, in the time, frequency, and information-theoretic domains. The establishment of conceptual and mathematical relationships between metrics from these three frameworks, and the discussion of novel methodological approaches, will allow the reader to go deep into the problem of inferring functional connectivity in complex networks. Furthermore, emerging trends for the description of extended forms of connectivity (e.g., high-order interactions) are also discussed, along with graph-theory tools exploring the topological properties of the network of connections provided by the proposed metrics. Applications to EEG data are reviewed. In addition, the importance of source localization, and the impacts of signal acquisition and pre-processing techniques (e.g., filtering, source localization, and artifact rejection) on the connectivity estimates are recognized and discussed. By going through this review, the reader could delve deeply into the entire process of EEG pre-processing and analysis for the study of brain functional connectivity and learning, thereby exploiting novel methodologies and approaches to the problem of inferring connectivity within complex networks.
Collapse
Affiliation(s)
- Giovanni Chiarion
- Mathematical Biology and Physiology, Department Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy
| | - Laura Sparacino
- Department of Engineering, University of Palermo, 90128 Palermo, Italy
| | - Yuri Antonacci
- Department of Engineering, University of Palermo, 90128 Palermo, Italy
| | - Luca Faes
- Department of Engineering, University of Palermo, 90128 Palermo, Italy
| | - Luca Mesin
- Mathematical Biology and Physiology, Department Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy
| |
Collapse
|
17
|
Multimodal assessment of the spatial correspondence between fNIRS and fMRI hemodynamic responses in motor tasks. Sci Rep 2023; 13:2244. [PMID: 36755139 PMCID: PMC9908920 DOI: 10.1038/s41598-023-29123-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 01/31/2023] [Indexed: 02/10/2023] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) provides a cost-efficient and portable alternative to functional magnetic resonance imaging (fMRI) for assessing cortical activity changes based on hemodynamic signals. The spatial and temporal underpinnings of the fMRI blood-oxygen-level-dependent (BOLD) signal and corresponding fNIRS concentration of oxygenated (HbO), deoxygenated (HbR), and total hemoglobin (HbT) measurements are still not completely clear. We aim to analyze the spatial correspondence between these hemodynamic signals, in motor-network regions. To this end, we acquired asynchronous fMRI and fNIRS recordings from 9 healthy participants while performing motor imagery and execution. Using this multimodal approach, we investigated the ability to identify motor-related activation clusters in fMRI data using subject-specific fNIRS-based cortical signals as predictors of interest. Group-level activation was found in fMRI data modeled from corresponding fNIRS measurements, with significant peak activation found overlapping the individually-defined primary and premotor motor cortices, for all chromophores. No statistically significant differences were observed in multimodal spatial correspondence between HbO, HbR, and HbT, for both tasks. This suggests the possibility of translating neuronal information from fMRI into an fNIRS motor-coverage setup with high spatial correspondence using both oxy and deoxyhemoglobin data, with the inherent benefits of translating fMRI paradigms to fNIRS in cognitive and clinical neuroscience.
Collapse
|
18
|
Ding H, Droby A, Anwar AR, Bange M, Hausdorff JM, Nasseroleslami B, Mirelman A, Maidan I, Groppa S, Muthuraman M. Treadmill training in Parkinson's disease is underpinned by the interregional connectivity in cortical-subcortical network. NPJ Parkinsons Dis 2022; 8:153. [PMID: 36369264 PMCID: PMC9652466 DOI: 10.1038/s41531-022-00427-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 10/31/2022] [Indexed: 11/13/2022] Open
Abstract
Treadmill training (TT) has been extensively used as an intervention to improve gait and mobility in patients with Parkinson's disease (PD). Regional and global effects on brain activity could be induced through TT. Training effects can lead to a beneficial shift of interregional connectivity towards a physiological range. The current work investigates the effects of TT on brain activity and connectivity during walking and at rest by using both functional near-infrared spectroscopy and functional magnetic resonance imaging. Nineteen PD patients (74.0 ± 6.59 years, 13 males, disease duration 10.45 ± 6.83 years) before and after 6 weeks of TT, along with 19 age-matched healthy controls were assessed. Interregional effective connectivity (EC) between cortical and subcortical regions were assessed and its interrelation to prefrontal cortex (PFC) activity. Support vector regression (SVR) on the resting-state ECs was used to predict prefrontal connectivity. In response to TT, EC analysis indicated modifications in the patients with PD towards the level of healthy controls during walking and at rest. SVR revealed cerebellum related connectivity patterns that were associated with the training effect on PFC. These findings suggest that the potential therapeutic effect of training on brain activity may be facilitated via changes in compensatory modulation of the cerebellar interregional connectivity.
Collapse
Affiliation(s)
- Hao Ding
- Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
- Academic Unit of Neurology, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | - Amgad Droby
- Department of Neurology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Laboratory for Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility (CMCM), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Abdul Rauf Anwar
- Biomedical Engineering Centre, UET Lahore (KSK Campus), Lahore, Pakistan
| | - Manuel Bange
- Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Jeffrey M Hausdorff
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Laboratory for Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility (CMCM), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Department of Physical Therapy, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Rush Alzheimer's Disease Center and Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | - Anat Mirelman
- Department of Neurology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Laboratory for Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility (CMCM), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Inbal Maidan
- Department of Neurology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
- Laboratory for Early Markers of Neurodegeneration (LEMON), Center for the Study of Movement, Cognition, and Mobility (CMCM), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
| |
Collapse
|
19
|
Hooyman A, Garbin A, Fisher BE, Kutch JJ, Winstein CJ. Paired associative stimulation applied to the cortex can increase resting-state functional connectivity: A proof of principle study. Neurosci Lett 2022; 784:136753. [PMID: 35753613 PMCID: PMC10035603 DOI: 10.1016/j.neulet.2022.136753] [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: 01/27/2022] [Revised: 06/15/2022] [Accepted: 06/21/2022] [Indexed: 10/17/2022]
Abstract
INTRODUCTION There is emerging evidence that high Beta coherence (hBc) between prefrontal and motor corticies, measured with resting-state electroencephalography (rs-EEG), can be an accurate predictor of motor skill learning and stroke recovery. However, it remains unknown whether and how intracortical connectivity may be influenced using neuromodulation. Therefore, a cortico-cortico PAS (ccPAS) paradigm may be used to increase resting-state intracortical connectivity (rs-IC) within a targeted neural circuit. PURPOSE Our purpose is to demonstrate proof of principle that ccPAS can be used to increase rs-IC between a prefrontal and motor cortical region. METHODS Eleven non-disabled adults were recruited (mean age 26.4, sd 5.6, 5 female). Each participant underwent a double baseline measurement, followed by a real and control ccPAS condition, counter-balanced for order. Control and ccPAS conditions were performed over electrodes of the right prefrontal and motor cortex. Both ccPAS conditions were identical apart from the inter-stimulus interval (i.e ISI 5 ms: real ccPAS and 500 ms: control ccPAS). Whole brain rs-EEG of high Beta coherence (hBc) was acquired before and after each ccPAS condition and then analyzed for changes in rs-IC along the targeted circuit. RESULTS Compared to ccPAS500 and baseline, ccPAS5 induced a significant increase in rs-IC, measured as coherence between electrodes over right prefrontal and motor cortex, (p <.05). CONCLUSION These findings demonstrate proof of principle that ccPAS with an STDP derived ISI, can effectively increase hBc along a targeted circuit.
Collapse
Affiliation(s)
- Andrew Hooyman
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
| | - Alexander Garbin
- Department of Physical Medicine and Rehabilitation, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Geriatric Research Education and Clinical Center, VA Eastern Colorado Health Care System, Aurora, CO, USA
| | - Beth E Fisher
- Division of Biokinesiology and Physical Therapy, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, CA, USA; Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jason J Kutch
- Division of Biokinesiology and Physical Therapy, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, CA, USA
| | - Carolee J Winstein
- Division of Biokinesiology and Physical Therapy, Herman Ostrow School of Dentistry, University of Southern California, Los Angeles, CA, USA; Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| |
Collapse
|
20
|
Yang Z, Zhang W, Liu D, Zhang SS, Tang Y, Song J, Long J, Yang J, Jiang H, Li Y, Liu X, Lü Y, Ding F. Effects of Sport Stacking on Neuropsychological, Neurobiological, and Brain Function Performances in Patients With Mild Alzheimer's Disease and Mild Cognitive Impairment: A Randomized Controlled Trial. Front Aging Neurosci 2022; 14:910261. [PMID: 35645781 PMCID: PMC9133718 DOI: 10.3389/fnagi.2022.910261] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 04/20/2022] [Indexed: 11/30/2022] Open
Abstract
Objective To investigate the effects of sport stacking on the overall cognition and brain function in patients with mild Alzheimer's disease (AD) and mild cognitive impairment (MCI). Methods A single-blind randomized controlled design was performed using sport stacking for 30 min, 5 days/week for 12 weeks. Forty-eight subjects with mild AD or MCI were randomly divided into the sport stacking group (T-mAD = 12, T-MCI = 12) and the active control group (C-mAD = 11, C-MCI = 13). Auditory Verbal Learning Test (AVLT), Alzheimer's Disease Cooperative Study–Activities of Daily Living scale (ADCS-ADL), Geriatric Depression Scale (GDS-30), and Pittsburgh Sleep Quality Index (PSQI) were performed, the level of amyloid β-protein-40 (Aβ-40), Aβ-42, brain-derived neurotrophic factor (BDNF), insulin-like growth factor-1(IGF-1), tumor necrosis factor-alpha (TNF-α), Interleukin-6 (IL-6), and soluble trigger receptor expressed on myeloid cells 2 (sTREM2) in plasma were tested, and brain functional connectivity in resting state and activation under finger movement task were analyzed by functional near-infrared spectroscopy (fNIRS). Results Thirty-nine patients completed the trial. After 4 weeks, we found a significant increase in AVLT score in T-MCI (6.36 ± 5.08 vs. −1.11 ± 4.23, p = 0.004), and T-mAD group (4.60 ± 4.77 vs. −0.11 ± 2.89, p = 0.039). After 12 weeks, there was a significantly improved in AVLT (9.64 ± 4.90 vs. −0.33 ± 6.10, p = 0.002) and ADCS-ADL (3.36 ± 3.59 vs. −1.89 ± 2.71, p = 0.003) in T-MCI. There was a significant improvement in AVLT (5.30 ± 5.42 vs. 0.44 ± 2.40) in T-mAD (p < 0.05). Plasma levels of BDNF were upregulated in both T-MCI and T-mAD, and IGF-1 increased in T-MCI (P < 0.05) compared to the control groups. The functional connectivity in MCI patients between DLPFC.R and SCA.R, SMA.L, and SCA.R was decreased. In contrast, in mAD patients, the brain regional function connection was increased between DLPFC.R and Broca's.L. The activation of channel 36 located in the left primary somatosensory cortex was significantly increased after 12-week training, which was correlated with the improved AVLT and the increase of BDNF. Conclusion Our findings suggested that sport stacking is effective for patients with MCI and mild AD, possibly through increasing the expression of neuroprotective growth factors and enhancing neural plasticity to improve neurocognitive performance. Clinical Trial Registration https://www.ClinicalTrials.gov, ChiCTR.org.cn, identifier: ChiCTR-2100045980.
Collapse
Affiliation(s)
- Ziying Yang
- Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Wenbo Zhang
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Dunxiu Liu
- Department of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Shan-shan Zhang
- Department of Histology and Embryology, Faculty of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cell and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Yong Tang
- Department of Histology and Embryology, Faculty of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
- Laboratory of Stem Cell and Tissue Engineering, Chongqing Medical University, Chongqing, China
| | - Jiaqi Song
- Institute of Neuroscience, Chongqing Medical University, Chongqing, China
| | - Jinfeng Long
- Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jun Yang
- Department of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Hong Jiang
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yaling Li
- Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xintong Liu
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yang Lü
- Department of Geriatrics, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Yang Lü
| | - Fu Ding
- Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Fu Ding
| |
Collapse
|
21
|
Tyagi O, Mehta RK. Mind over body: A neuroergonomic approach to assessing motor performance under stress in older adults. APPLIED ERGONOMICS 2022; 101:103691. [PMID: 35086006 DOI: 10.1016/j.apergo.2022.103691] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/20/2021] [Accepted: 01/14/2022] [Indexed: 06/14/2023]
Abstract
Stress impairs motor performance, which is exacerbated with age. Stress also impairs brain activity in the prefrontal cortex, which communicates with the motor areas of the brain to regulate exercise and motor performance. To develop ergogenic strategies for the aging workforce, mind (brain)-body mechanisms behind the effect of stress on neuromuscular performance need to be well understood. This study investigated the influence of social stress on motor performance and information flow between the frontal and motor regions of the brain during intermittent handgrip contractions among older adults. Thirty older adults, balanced by gender, performed intermittent handgrip contractions at 30% of maximum strength before and after being subjected to a social stressor. Force steadiness, strength loss, root mean square electromyogram (EMG) activity, activation of the brain regions, and functional and effective connectivity between the frontal and motor brain regions were computed for pre- and post-stressor handgrip contractions. Older men exhibited improved motor performance after the stressor and concomitant reduction in functional connectivity between the frontal-motor brain regions ipsilateral to the contracting hand. Additionally, while both sexes exhibited significant causal information flow, i.e., effective connectivity, from the frontal to the motor regions of the brain, irrespective of the stressor, older women exhibited a bidirectional effective connectivity between the frontal-motor brain regions after the stressor. Stress had a facilitative effect on the motor performance of older men through compensatory brain network reorganization. Older women exhibited comparable motor performance pre/post stress, despite showing an increase in bidirectional information flow between the frontal-motor areas. Employing brain hemodynamics can facilitate better understanding of the impact of stress on neuromuscular performance and its differential impacts on brain network reorganization between the sexes.
Collapse
Affiliation(s)
- Oshin Tyagi
- Wm. Michael Barnes '64 Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843, USA
| | - Ranjana K Mehta
- Wm. Michael Barnes '64 Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843, USA; J. Mike Walker '66 Department of Mechanical Engineering, Texas A&M University, College Station, TX, 77843, USA.
| |
Collapse
|
22
|
Vila‐Villar A, Naya‐Fernández M, Madrid A, Madinabeitia‐Mancebo E, Robles‐García V, Cudeiro J, Arias P. Exploring the role of the left
DLPFC
in fatigue during unresisted rhythmic movements. Psychophysiology 2022; 59:e14078. [PMID: 35428988 PMCID: PMC9539568 DOI: 10.1111/psyp.14078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 10/20/2021] [Accepted: 03/30/2022] [Indexed: 01/17/2023]
Abstract
Understanding central fatigue during motor activities is important in neuroscience and different medical fields. The central mechanisms of motor fatigue are known in depth for isometric muscle contractions; however, current knowledge about rhythmic movements and central fatigue is rather scarce. In this study, we explored the role of an executive area (left dorsolateral prefrontal cortex [DLPFC]) in fatigue development during rhythmic movement execution, finger tapping (FT) at the maximal rate, and fatigue after effects on the stability of rhythmic patterns. Participants (n = 19) performed six sets of unresisted FT (with a 3 min rest in‐between). Each set included four interleaved 30 s repetitions of self‐selected (two repetitions) and maximal rate FT (two repetitions) without rest in‐between. Left DLPFC involvement in the task was perturbed by transcranial static magnetic stimulation (tSMS) in two sessions (one real and one sham). Moreover, half of the self‐selected FT repetitions were performed concurrently with a demanding cognitive task, the Stroop test. Compared with sham stimulation, real tSMS stimulation prevented waning in tapping frequency at the maximal rate without affecting perceived levels of fatigue. Participants' engagement in the Stroop test just prior to maximal FT reduced the movement amplitude during this mode of execution. Movement variability at self‐selected rates increased during Stroop execution, especially under fatigue previously induced by maximal FT. Our results indicate cognitive‐motor interactions and a prominent role of the prefrontal cortex in fatigue and the motor control of simple repetitive movement patterns. We suggest the need to approach motor fatigue including cognitive perspectives. We show the fundamental role of executive areas in fatigue caused by very simple repetitive movements. Fatigue developed less during the maximal frequency of movement production, while the left DLPFC received magnetic stimulation (in right‐handers). The role of cognitive‐motor interaction in fine motor control was also clear when participants engaged in cognitive tasks. At the clinical level, our work reinforces the need to treat fatigue from a comprehensive perspective.
Collapse
Affiliation(s)
- Aranza Vila‐Villar
- Department of Physiotherapy, Medicine and Biomedical Sciences and INEF Galicia Universidade da Coruña, NEUROcom (Neuroscience and Motor Control Group) and Biomedical Institute of A Coruña (INIBIC) A Coruña Spain
| | - Mariña Naya‐Fernández
- Department of Physiotherapy, Medicine and Biomedical Sciences and INEF Galicia Universidade da Coruña, NEUROcom (Neuroscience and Motor Control Group) and Biomedical Institute of A Coruña (INIBIC) A Coruña Spain
| | - Antonio Madrid
- Department of Physiotherapy, Medicine and Biomedical Sciences and INEF Galicia Universidade da Coruña, NEUROcom (Neuroscience and Motor Control Group) and Biomedical Institute of A Coruña (INIBIC) A Coruña Spain
| | - Elena Madinabeitia‐Mancebo
- Department of Physiotherapy, Medicine and Biomedical Sciences and INEF Galicia Universidade da Coruña, NEUROcom (Neuroscience and Motor Control Group) and Biomedical Institute of A Coruña (INIBIC) A Coruña Spain
| | - Verónica Robles‐García
- Department of Physiotherapy, Medicine and Biomedical Sciences and INEF Galicia Universidade da Coruña, NEUROcom (Neuroscience and Motor Control Group) and Biomedical Institute of A Coruña (INIBIC) A Coruña Spain
| | - Javier Cudeiro
- Department of Physiotherapy, Medicine and Biomedical Sciences and INEF Galicia Universidade da Coruña, NEUROcom (Neuroscience and Motor Control Group) and Biomedical Institute of A Coruña (INIBIC) A Coruña Spain
- Centro de Estimulación Cerebral de Galicia A Coruña Spain
| | - Pablo Arias
- Department of Physiotherapy, Medicine and Biomedical Sciences and INEF Galicia Universidade da Coruña, NEUROcom (Neuroscience and Motor Control Group) and Biomedical Institute of A Coruña (INIBIC) A Coruña Spain
| |
Collapse
|
23
|
Yeung MK, Chu VW. Viewing neurovascular coupling through the lens of combined EEG-fNIRS: A systematic review of current methods. Psychophysiology 2022; 59:e14054. [PMID: 35357703 DOI: 10.1111/psyp.14054] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/01/2022] [Accepted: 03/08/2022] [Indexed: 12/25/2022]
Abstract
Neurovascular coupling is a key physiological mechanism that occurs in the healthy human brain, and understanding this process has implications for understanding the aging and neuropsychiatric populations. Combined electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has emerged as a promising, noninvasive tool for probing neurovascular interactions in humans. However, the utility of this approach critically depends on the methodological quality used for multimodal integration. Despite a growing number of combined EEG-fNIRS applications reported in recent years, the methodological rigor of past studies remains unclear, limiting the accurate interpretation of reported findings and hindering the translational application of this multimodal approach. To fill this knowledge gap, we critically evaluated various methodological aspects of previous combined EEG-fNIRS studies performed in healthy individuals. A literature search was conducted using PubMed and PsycINFO on June 28, 2021. Studies involving concurrent EEG and fNIRS measurements in awake and healthy individuals were selected. After screening and eligibility assessment, 96 studies were included in the methodological evaluation. Specifically, we critically reviewed various aspects of participant sampling, experimental design, signal acquisition, data preprocessing, outcome selection, data analysis, and results presentation reported in these studies. Altogether, we identified several notable strengths and limitations of the existing EEG-fNIRS literature. In light of these limitations and the features of combined EEG-fNIRS, recommendations are made to improve and standardize research practices to facilitate the use of combined EEG-fNIRS when studying healthy neurovascular coupling processes and alterations in neurovascular coupling among various populations.
Collapse
Affiliation(s)
- Michael K Yeung
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Vivian W Chu
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| |
Collapse
|
24
|
Zafeiridis A, Kounoupis A, Papadopoulos S, Koutlas A, Boutou AK, Smilios I, Dipla K. Brain oxygenation during multiple sets of isometric and dynamic resistance exercise of equivalent workloads: Association with systemic haemodynamics. J Sports Sci 2022; 40:1020-1030. [PMID: 35271420 DOI: 10.1080/02640414.2022.2045061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Brain function relies on sufficient blood flow and oxygen supply. Changes in cerebral oxygenation during exercise have been linked to brain activity and central command. Isometric- and dynamic-resistance exercise-(RE) may elicit differential responses in systemic circulation, neural function and metabolism; all important regulators of cerebral circulation. We examined whether (i) cerebral oxygenation differs between isometric- and dynamic-RE of similar exercise characteristics and (ii) cerebral oxygenation changes relate to cardiovascular adjustments occurring during RE. Fourteen men performed, randomly, an isometric-RE and a dynamic-RE of similar characteristics (bilateral-leg-press, 2-min×4-sets, 30% of maximal-voluntary-contraction, equivalent tension-time-index/workload). Cerebral-oxygenation (oxyhaemoglobin-O2Hb; total haemoglobin-tHb/blood-volume-index; deoxyhemoglobin-HHb) was assessed by NIRS and beat-by-beat haemodynamics via photoplethysmography. Cerebral-O2Hb and tHb progressively increased from the 1st to 4th set in both RE-protocols (p < 0.05); HHb slightly decreased (p < 0.05). Changes in NIRS-parameters were similar between RE-protocols within each exercise-set (p = 0.91-1.00) and during the entire protocol (including resting-phases) (p = 0.48-0.63). O2Hb and tHb changes were not correlated with changes in systemic haemodynamics. In conclusion, cerebral oxygenation/blood-volume steadily increased during multiple-set RE-protocols. Isometric- and dynamic-RE of matched exercise characteristics resulted in similar prefrontal oxygenation/blood volume changes, suggesting similar cerebral haemodynamic and possibly neuronal responses to maintain a predetermined force.
Collapse
Affiliation(s)
- Andreas Zafeiridis
- Laboratory of Exercise Physiology and Biochemistry, Department of Physical Education and Sports Science at Serres, Aristotle University of Thessaloniki, Serres, Greece
| | - Anastasios Kounoupis
- Laboratory of Exercise Physiology and Biochemistry, Department of Physical Education and Sports Science at Serres, Aristotle University of Thessaloniki, Serres, Greece
| | - Stavros Papadopoulos
- Laboratory of Exercise Physiology and Biochemistry, Department of Physical Education and Sports Science at Serres, Aristotle University of Thessaloniki, Serres, Greece
| | - Aggelos Koutlas
- Laboratory of Exercise Physiology and Biochemistry, Department of Physical Education and Sports Science at Serres, Aristotle University of Thessaloniki, Serres, Greece
| | - Afroditi K Boutou
- Department of Respiratory Medicine, General Papanikolaou Hospital, Thessaloniki, Greece
| | - Ilias Smilios
- Department of Physical Education and Sport Science, Democritus University of Thrace, Komotini, Greece
| | - Konstantina Dipla
- Laboratory of Exercise Physiology and Biochemistry, Department of Physical Education and Sports Science at Serres, Aristotle University of Thessaloniki, Serres, Greece
| |
Collapse
|
25
|
Klein F, Debener S, Witt K, Kranczioch C. fMRI-based validation of continuous-wave fNIRS of supplementary motor area activation during motor execution and motor imagery. Sci Rep 2022; 12:3570. [PMID: 35246563 PMCID: PMC8897516 DOI: 10.1038/s41598-022-06519-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/28/2022] [Indexed: 11/09/2022] Open
Abstract
Compared to functional magnetic resonance imaging (fMRI), functional near infrared spectroscopy (fNIRS) has several advantages that make it particularly interesting for neurofeedback (NFB). A pre-requisite for NFB applications is that with fNIRS, signals from the brain region of interest can be measured. This study focused on the supplementary motor area (SMA). Healthy older participants (N = 16) completed separate continuous-wave (CW-) fNIRS and (f)MRI sessions. Data were collected for executed and imagined hand movements (motor imagery, MI), and for MI of whole body movements. Individual anatomical data were used to (i) define the regions of interest for fMRI analysis, to (ii) extract the fMRI BOLD response from the cortical regions corresponding to the fNIRS channels, and (iii) to select fNIRS channels. Concentration changes in oxygenated ([Formula: see text]) and deoxygenated ([Formula: see text]) hemoglobin were considered in the analyses. Results revealed subtle differences between the different MI tasks, indicating that for whole body MI movements as well as for MI of hand movements [Formula: see text] is the more specific signal. Selection of the fNIRS channel set based on individual anatomy did not improve the results. Overall, the study indicates that in terms of spatial specificity and task sensitivity SMA activation can be reliably measured with CW-fNIRS.
Collapse
Affiliation(s)
- Franziska Klein
- Neurocognition and Neurorehabilitation Group, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany.
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany.
| | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Karsten Witt
- Neurology, Department of Human Medicine, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Cornelia Kranczioch
- Neurocognition and Neurorehabilitation Group, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| |
Collapse
|
26
|
Lee M, Kim YH, Lee SW. Motor Impairment in Stroke Patients is Associated with Network Properties During Consecutive Motor Imagery. IEEE Trans Biomed Eng 2022; 69:2604-2615. [PMID: 35171761 DOI: 10.1109/tbme.2022.3151742] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Our study aimed to predict the Fugl-Meyer assessment (FMA) upper limb using network properties during motor imagery using electroencephalography (EEG) signals. METHODS The subjects performed a finger tapping imagery task according to consecutive cues. We measured the weighted phase lag index (wPLI) as functional connectivity and directed transfer function (DTF) as causal connectivity in healthy controls and stroke patients. The network properties based on the wPLI and DTF were calculated. We predicted the FMA upper limb using partial least squares regression. RESULTS A higher DTF in the mu band was observed in stroke patients than in healthy controls. Notably, the difference in local properties at node F3 was negatively correlated with motor impairment in stroke patients. Finally, using significant network properties based on the wPLI and DTF, we predicted motor impairments using the FMA upper limb with a root-mean-square error of 1.68 (R2 = 0.97). This outperformed the state-of-the-art predictors. CONCLUSION These findings demonstrate that network properties based on functional and causal connectivity were highly associated with motor function in stroke patients. SIGNIFICANCE Our network properties can help calculate the predictor of motor impairments in stroke rehabilitation and provide insight into the neural correlates related to motor function based on EEG after reorganization induced by stroke.
Collapse
|
27
|
The brain state of motor imagery is reflected in the causal information of functional near-infrared spectroscopy. Neuroreport 2022; 33:137-144. [PMID: 35139061 DOI: 10.1097/wnr.0000000000001765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Brain-computer interface (BCI) is a promising neurorehabilitation strategy for ameliorating post-stroke function disorders. Physiological changes in the brain, such as functional near-infrared spectroscopy (fNIRS) dedicated to exploring cerebral circulatory responses during neurological rehabilitation tasks, are essential for gaining insights into neurorehabilitation mechanisms. However, the relationship between the neurovascular responses in different brain regions under rehabilitation tasks remains unknown. OBJECTIVE The present study explores the fNIRS interactions between brain regions under different motor imagery (MI) tasks, emphasizing functional characteristics of brain network patterns and BCI motor task classification. METHODS Granger causality analysis (GCA) is carried out for oxyhemoglobin data from 29 study participants in left- and right-hand MI tasks. RESULTS According to research findings, homozygous and heterozygous states in the two brain connectivity modes reveal one and nine channel pairs, respectively, with significantly different (P < 0.05) GC values under the left- and right-hand MI tasks in the population. With reference to the total 10 channel pairs of causality differences between the two brain working states, a support vector machine is used to classify the two tasks with an overall accuracy of 83% for five-fold cross-validation. CONCLUSION As demonstrated in the present study, fNIRS offers causality patterns in different brain states of MIBCI motor tasks. The research findings show that fNIRS causality can be used to assess different states of the brain, providing theoretical support for its application to neurorehabilitation assessment protocols to ultimately improve patients' quality of life.Video Abstract: http://links.lww.com/WNR/A653.
Collapse
|
28
|
Guo Z, Chen F. Idle-state detection in motor imagery of articulation using early information: A functional Near-infrared spectroscopy study. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103369] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
|
29
|
Yongyue Z, Yang S, Li Z, Rongjin Z, Shumin W. Functional Brain Imaging Based on the Neurovascular Unit for Evaluating Neural Networks after Strok. ADVANCED ULTRASOUND IN DIAGNOSIS AND THERAPY 2022. [DOI: 10.37015/audt.2022.210033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
|
30
|
Khan H, Noori FM, Yazidi A, Uddin MZ, Khan MNA, Mirtaheri P. Classification of Individual Finger Movements from Right Hand Using fNIRS Signals. SENSORS (BASEL, SWITZERLAND) 2021; 21:7943. [PMID: 34883949 PMCID: PMC8659988 DOI: 10.3390/s21237943] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 11/17/2022]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a comparatively new noninvasive, portable, and easy-to-use brain imaging modality. However, complicated dexterous tasks such as individual finger-tapping, particularly using one hand, have been not investigated using fNIRS technology. Twenty-four healthy volunteers participated in the individual finger-tapping experiment. Data were acquired from the motor cortex using sixteen sources and sixteen detectors. In this preliminary study, we applied standard fNIRS data processing pipeline, i.e., optical densities conversation, signal processing, feature extraction, and classification algorithm implementation. Physiological and non-physiological noise is removed using 4th order band-pass Butter-worth and 3rd order Savitzky-Golay filters. Eight spatial statistical features were selected: signal-mean, peak, minimum, Skewness, Kurtosis, variance, median, and peak-to-peak form data of oxygenated haemoglobin changes. Sophisticated machine learning algorithms were applied, such as support vector machine (SVM), random forests (RF), decision trees (DT), AdaBoost, quadratic discriminant analysis (QDA), Artificial neural networks (ANN), k-nearest neighbors (kNN), and extreme gradient boosting (XGBoost). The average classification accuracies achieved were 0.75±0.04, 0.75±0.05, and 0.77±0.06 using k-nearest neighbors (kNN), Random forest (RF) and XGBoost, respectively. KNN, RF and XGBoost classifiers performed exceptionally well on such a high-class problem. The results need to be further investigated. In the future, a more in-depth analysis of the signal in both temporal and spatial domains will be conducted to investigate the underlying facts. The accuracies achieved are promising results and could open up a new research direction leading to enrichment of control commands generation for fNIRS-based brain-computer interface applications.
Collapse
Affiliation(s)
- Haroon Khan
- Department of Mechanical, Electronics and Chemical Engineering, OsloMet-Oslo Metropolitan University, 0167 Oslo, Norway;
| | - Farzan M. Noori
- Department of Informatics, University of Oslo, 0315 Oslo, Norway;
| | - Anis Yazidi
- Department of Computer Science, OsloMet-Oslo Metropolitan University, 0167 Oslo, Norway;
- Department of Neurosurgery, Oslo University Hospital, 0450 Oslo, Norway
- Department of Computer Science, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Md Zia Uddin
- Software and Service Innovation, SINTEF Digital, 0373 Oslo, Norway;
| | - M. N. Afzal Khan
- School of Mechanical Engineering, Pusan National University, Busan 46241, Korea;
| | - Peyman Mirtaheri
- Department of Mechanical, Electronics and Chemical Engineering, OsloMet-Oslo Metropolitan University, 0167 Oslo, Norway;
- Department of Biomedical Engineering, Michigan Technological University, Houghton, MI 49931, USA
| |
Collapse
|
31
|
Kreis SL, Luhmann HJ, Ciolac D, Groppa S, Muthuraman M. Translational Model of Cortical Premotor-Motor Networks. Cereb Cortex 2021; 32:2621-2634. [PMID: 34689188 PMCID: PMC9201593 DOI: 10.1093/cercor/bhab369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 09/07/2021] [Accepted: 09/08/2021] [Indexed: 11/17/2022] Open
Abstract
Deciphering the physiological patterns of motor network connectivity is a prerequisite to elucidate aberrant oscillatory transformations and elaborate robust translational models of movement disorders. In the proposed translational approach, we studied the connectivity between premotor (PMC) and primary motor cortex (M1) by recording high-density electroencephalography in humans and between caudal (CFA) and rostral forelimb (RFA) areas by recording multi-site extracellular activity in mice to obtain spectral power, functional and effective connectivity. We identified a significantly higher spectral power in β- and γ-bands in M1compared to PMC and similarly in mice CFA layers (L) 2/3 and 5 compared to RFA. We found a strong functional β-band connectivity between PMC and M1 in humans and between CFA L6 and RFA L5 in mice. We observed that in both humans and mice the direction of information flow mediated by β- and γ-band oscillations was predominantly from PMC toward M1 and from RFA to CFA, respectively. Combining spectral power, functional and effective connectivity, we revealed clear similarities between human PMC-M1 connections and mice RFA-CFA network. We propose that reciprocal connectivity of mice RFA-CFA circuitry presents a suitable model for analysis of motor control and physiological PMC-M1 functioning or pathological transformations within this network.
Collapse
Affiliation(s)
- Svenja L Kreis
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz D-55128, Germany
| | - Heiko J Luhmann
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz D-55128, Germany
| | - Dumitru Ciolac
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz D-55131, Germany.,Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau MD-2001, Republic of Moldova
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz D-55131, Germany
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz D-55131, Germany
| |
Collapse
|
32
|
Muthuraman M, Palotai M, Jávor-Duray B, Kelemen A, Koirala N, Halász L, Erőss L, Fekete G, Bognár L, Deuschl G, Tamás G. Frequency-specific network activity predicts bradykinesia severity in Parkinson's disease. Neuroimage Clin 2021; 32:102857. [PMID: 34662779 PMCID: PMC8526781 DOI: 10.1016/j.nicl.2021.102857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 09/15/2021] [Accepted: 10/12/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVE Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson's disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia. METHODS Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1-3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13-20 Hz) and high (21-30 Hz) beta frequency bands and low (31-60 Hz) and high (61-100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures. RESULTS Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side. DISCUSSION Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes.
Collapse
Affiliation(s)
- Muthuraman Muthuraman
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Marcell Palotai
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | | | - Andrea Kelemen
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Nabin Koirala
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany; Haskins Laboratories, New Haven, USA
| | - László Halász
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Loránd Erőss
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Gábor Fekete
- Department of Neurosurgery, University of Debrecen, Debrecen, Hungary
| | - László Bognár
- Department of Neurosurgery, University of Debrecen, Debrecen, Hungary
| | - Günther Deuschl
- Department of Neurology, Christian-Albrechts University, Kiel, Germany
| | - Gertrúd Tamás
- Department of Neurology, Semmelweis University, Budapest, Hungary.
| |
Collapse
|
33
|
Huo C, Xu G, Li W, Xie H, Zhang T, Liu Y, Li Z. A review on functional near-infrared spectroscopy and application in stroke rehabilitation. MEDICINE IN NOVEL TECHNOLOGY AND DEVICES 2021. [DOI: 10.1016/j.medntd.2021.100064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
|
34
|
Jian C, Liu H, Deng L, Wang X, Yan T, Song R. Stroke-induced alteration in multi-layer information transmission of cortico-motor system during elbow isometric contraction modulated by myoelectric-controlled interfaces. J Neural Eng 2021; 18. [PMID: 34320485 DOI: 10.1088/1741-2552/ac18ae] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 07/28/2021] [Indexed: 11/12/2022]
Abstract
Objective. Human movement is a complex process requiring information transmission in inter-cortical, cortico-muscular and inter-muscular networks. Though motor deficits after stroke are associated with impaired networks in the cortico-motor system, the mechanisms underlying these networks are to date not fully understood. The purpose of this study is to investigate the changes in information transmission of the inter-cortical, cortico-muscular and inter-muscular networks after stroke and the effect of myoelectric-controlled interface (MCI) dimensionality on such information transmission in each network.Approach. Fifteen healthy control subjects and 11 post-stroke patients were recruited to perform elbow tracking tasks within different dimensional MCIs in this study. Their electromyography (EMG) and functional near-infrared spectroscopy (fNIRS) signals were recorded simultaneously. Transfer entropy was used to analyse the functional connection that represented the information transmission in each network based on the fNIRS and EMG signals.Main results.The results found that post-stroke patients showed the increased inter-cortical connection versus healthy control subjects, which might be attributed to cortical reorganisation to compensate for motor deficits. Compared to healthy control subjects, a lower strength cortico-muscular connection was found in post-stroke patients due to the reduction of information transmission following a stroke. Moreover, the increased MCI dimensionality strengthened inter-cortical, cortico-muscular and inter-muscular connections because of higher visual information processing demands.Significance. These findings not only provide a comprehensive overview to evaluate changes in the cortico-motor system due to stroke, but also suggest that increased MCI dimensionality may serve as a useful rehabilitation tool for boosting information transmission in the cortico-motor system of post-stroke patients.
Collapse
Affiliation(s)
- Chuyao Jian
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, People's Republic of China.,Shenzhen Research Institute of Sun Yat-sen University, Shenzhen 518057, People's Republic of China
| | - Huihua Liu
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, People's Republic of China
| | - Linchuan Deng
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, People's Republic of China.,Shenzhen Research Institute of Sun Yat-sen University, Shenzhen 518057, People's Republic of China
| | - Xiaoyun Wang
- Guangdong Work Injury Rehabilitation Center, Guangzhou 510440, People's Republic of China
| | - Tiebin Yan
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, People's Republic of China
| | - Rong Song
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, People's Republic of China.,Shenzhen Research Institute of Sun Yat-sen University, Shenzhen 518057, People's Republic of China
| |
Collapse
|
35
|
|
36
|
Abbas AK, Azemi G, Amiri S, Ravanshadi S, Omidvarnia A. Effective connectivity in brain networks estimated using EEG signals is altered in children with ADHD. Comput Biol Med 2021; 134:104515. [PMID: 34126282 DOI: 10.1016/j.compbiomed.2021.104515] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 05/16/2021] [Accepted: 05/21/2021] [Indexed: 11/18/2022]
Abstract
This study presents a methodology developed for estimating effective connectivity in brain networks (BNs) using multichannel scalp EEG recordings. The methodology uses transfer entropy as an information transfer measure to detect pair-wise directed information transfer between EEG signals within δ, θ, α, β and γ-bands. The developed methodology is then used to study the properties of directed BNs in children with attention-deficit hyperactivity disorder (ADHD) and compare them with that of the healthy controls using both statistical and receiver operating characteristic (ROC) analyses. The results indicate that directed information transfer between scalp EEG electrodes in the ADHD subjects differs significantly compared to the healthy ones. The results of the statistical and ROC analyses of frequency-specific graph measures demonstrate their highly discriminative ability between the two groups. Specifically, the graph measures extracted from the estimated directed BNs in the β-band show the highest discrimination between the ADHD and control groups. These findings are in line with the fact that β-band reflects active concentration, motor activity, and anxious mental states. The reported results show that the developed methodology has the capacity to be used for investigating patterns of directed BNs in neuropsychiatric disorders.
Collapse
Affiliation(s)
- Ali Kareem Abbas
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran
| | - Ghasem Azemi
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran; Department of Cognitive Science, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia.
| | - Sajad Amiri
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran
| | - Samin Ravanshadi
- Faculty of Electrical and Computer Engineering, Razi University, Kermanshah, Iran
| | - Amir Omidvarnia
- Institute of Bioengineering, Center for Neuroprosthetics, Center for Biomedical Imaging, EPFL, Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| |
Collapse
|
37
|
Devezas MÂM. Shedding light on neuroscience: Two decades of functional near-infrared spectroscopy applications and advances from a bibliometric perspective. J Neuroimaging 2021; 31:641-655. [PMID: 34002425 DOI: 10.1111/jon.12877] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 04/23/2021] [Accepted: 04/30/2021] [Indexed: 12/14/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical brain-imaging technique that detects changes in hemoglobin concentration in the cerebral cortex. fNIRS devices are safe, silent, portable, robust against motion artifacts, and have good temporal resolution. fNIRS is reliable and trustworthy, as well as an alternative and a complement to other brain-imaging modalities, such as electroencephalography or functional magnetic resonance imaging. Given these advantages, fNIRS has become a well-established tool for neuroscience research, used not only for healthy cortical activity but also as a biomarker during clinical assessment in individuals with schizophrenia, major depressive disorder, bipolar disease, epilepsy, Alzheimer's disease, vascular dementia, and cancer screening. Owing to its wide applicability, studies on fNIRS have increased exponentially over the last two decades. In this study, scientific publications indexed in the Web of Science databases were collected and a bibliometric-type methodology was developed. For this purpose, a comprehensive science mapping analysis, including top-ranked authors, journals, institutions, countries, and co-occurring keywords network, was conducted. From a total of 2310 eligible documents, 6028 authors and 531 journals published fNIRS-related papers, Fallgatter published the highest number of articles and was the most cited author. University of Tübingen in Germany has produced the most trending papers since 2000. USA was the most prolific country with the most active institutions, followed by China, Japan, Germany, and South Korea. The results also revealed global trends in emerging areas of research, such as neurodevelopment, aging, and cognitive and emotional assessment.
Collapse
|
38
|
Dans PW, Foglia SD, Nelson AJ. Data Processing in Functional Near-Infrared Spectroscopy (fNIRS) Motor Control Research. Brain Sci 2021; 11:606. [PMID: 34065136 PMCID: PMC8151801 DOI: 10.3390/brainsci11050606] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/05/2021] [Accepted: 05/07/2021] [Indexed: 12/26/2022] Open
Abstract
FNIRS pre-processing and processing methodologies are very important-how a researcher chooses to process their data can change the outcome of an experiment. The purpose of this review is to provide a guide on fNIRS pre-processing and processing techniques pertinent to the field of human motor control research. One hundred and twenty-three articles were selected from the motor control field and were examined on the basis of their fNIRS pre-processing and processing methodologies. Information was gathered about the most frequently used techniques in the field, which included frequency cutoff filters, wavelet filters, smoothing filters, and the general linear model (GLM). We discuss the methodologies of and considerations for these frequently used techniques, as well as those for some alternative techniques. Additionally, general considerations for processing are discussed.
Collapse
Affiliation(s)
- Patrick W. Dans
- Department of Kinesiology, McMaster University, Hamilton, ON L8S 4K1, Canada;
| | - Stevie D. Foglia
- School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada;
| | - Aimee J. Nelson
- Department of Kinesiology, McMaster University, Hamilton, ON L8S 4K1, Canada;
- School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada;
| |
Collapse
|
39
|
Zheng Y, Tian B, Zhang Y, Wang D. Effect of force accuracy on hemodynamic response: an fNIRS study using fine visuomotor task. J Neural Eng 2021; 18. [PMID: 33784650 DOI: 10.1088/1741-2552/abf399] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 03/30/2021] [Indexed: 11/12/2022]
Abstract
Objective. Despite converging neuroimaging studies investigating how neural activity is modulated by various motor related factors, such as movement velocity and force magnitude, little has been devoted to identifying the effect of force accuracy. This study thus aimed to investigate the effect of task difficulty on cortical neural responses when participants performed a visuomotor task with varying demands on force accuracy.Approach. Fourteen healthy adults performed a set of force generation operations with six levels of force accuracy. The participants held a pen-shaped tool and moved the tool along a planar ring path, meanwhile producing a constant force against the plane under visual guidance. The required force accuracy was modulated by allowable tolerance of the force during the task execution. We employed functional near-infrared spectroscopy to record signals from bilateral prefrontal, sensorimotor and occipital areas, used the hemoglobin concentration as indicators of cortical activation, then calculated the effective connectivity across these regions by Granger causality.Main results.We observed overall stronger activation (oxy-hemoglobin concentration,p= 0.015) and connectivity (p< 0.05) associated with the initial increase in force accuracy, and the diminished trend in activation and connectivity when participants were exposed to excessive demands on accurate force generation. These findings suggested that the increasing task difficulty would be only beneficial for the mental investment up to a certain point, and above that point neural responses would show patterns of lower activation and connections, revealing mental overload at excessive task demands.Significance.Our results provide the first evidence for the inverted U-shaped effect of force accuracy on hemodynamic responses during fine visuomotor tasks. The insights obtained through this study also highlight the essential role of inter-region connectivity alterations for coping with task difficulty, enhance our understanding of the underlying motor neural processes, and provide the groundwork for developing adaptive neurorehabilitation strategies.
Collapse
Affiliation(s)
- Yilei Zheng
- State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, People's Republic of China.,Peng Cheng Laboratory, Shenzhen, People's Republic of China
| | - Bohao Tian
- State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, People's Republic of China
| | - Yuru Zhang
- State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, People's Republic of China.,Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, People's Republic of China
| | - Dangxiao Wang
- State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing, People's Republic of China.,Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, People's Republic of China.,Peng Cheng Laboratory, Shenzhen, People's Republic of China
| |
Collapse
|
40
|
Aliakbaryhosseinabadi S, Lontis R, Farina D, Mrachacz-Kersting N. Effect of motor learning with different complexities on EEG spectral distribution and performance improvement. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102447] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
41
|
Khastkhodaei Z, Muthuraman M, Yang JW, Groppa S, Luhmann HJ. Functional and directed connectivity of the cortico-limbic network in mice in vivo. Brain Struct Funct 2021; 226:685-700. [PMID: 33442810 PMCID: PMC7981333 DOI: 10.1007/s00429-020-02202-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 12/16/2020] [Indexed: 11/22/2022]
Abstract
Higher cognitive processes and emotional regulation depend on densely interconnected telencephalic and limbic areas. Central structures of this cortico-limbic network are ventral hippocampus (vHC), medial prefrontal cortex (PFC), basolateral amygdala (BLA) and nucleus accumbens (NAC). Human and animal studies have revealed both anatomical and functional alterations in specific connections of this network in several psychiatric disorders. However, it is often not clear whether functional alterations within these densely interconnected brain areas are caused by modifications in the direct pathways, or alternatively through indirect interactions. We performed multi-site extracellular recordings of spontaneous activity in three different brain regions to study the functional connectivity in the BLA-NAC-PFC-vHC network of the lightly anesthetized mouse in vivo. We show that BLA, NAC, PFC and vHC are functionally connected in distinct frequency bands and determined the influence of a third brain region on this connectivity. In addition to describing mutual synchronicity, we determined the strength of functional connectivity for each region in the BLA-NAC-PFC-vHC network. We find a region-specificity in the strength of feedforward and feedback connections for each region in its interaction with other areas in the network. Our results provide insights into functional and directed connectivity in the cortico-limbic network of adult wild-type mice, which may be helpful to further elucidate the pathophysiological changes of this network in psychiatric disorders and to develop target-specific therapeutic interventions.
Collapse
Affiliation(s)
- Zeinab Khastkhodaei
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128, Mainz, Germany
| | - Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and MULTIMODAL Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128, Mainz, Germany
| | - Jenq-Wei Yang
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128, Mainz, Germany
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and MULTIMODAL Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128, Mainz, Germany
| | - Heiko J Luhmann
- Institute of Physiology, University Medical Center of the Johannes Gutenberg University Mainz, Duesbergweg 6, 55128, Mainz, Germany.
| |
Collapse
|
42
|
Condy EE, Miguel HO, Millerhagen J, Harrison D, Khaksari K, Fox N, Gandjbakhche A. Characterizing the Action-Observation Network Through Functional Near-Infrared Spectroscopy: A Review. Front Hum Neurosci 2021; 15:627983. [PMID: 33679349 PMCID: PMC7930074 DOI: 10.3389/fnhum.2021.627983] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 01/18/2021] [Indexed: 12/19/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that has undergone tremendous growth over the last decade due to methodological advantages over other measures of brain activation. The action-observation network (AON), a system of brain structures proposed to have “mirroring” abilities (e.g., active when an individual completes an action or when they observe another complete that action), has been studied in humans through neural measures such as fMRI and electroencephalogram (EEG); however, limitations of these methods are problematic for AON paradigms. For this reason, fNIRS is proposed as a solution to investigating the AON in humans. The present review article briefly summarizes previous neural findings in the AON and examines the state of AON research using fNIRS in adults. A total of 14 fNIRS articles are discussed, paying particular attention to methodological choices and considerations while summarizing the general findings to aid in developing better protocols to study the AON through fNIRS. Additionally, future directions of this work are discussed, specifically in relation to researching AON development and potential multimodal imaging applications.
Collapse
Affiliation(s)
- Emma E Condy
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Helga O Miguel
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - John Millerhagen
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Doug Harrison
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Kosar Khaksari
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Nathan Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, United States
| | - Amir Gandjbakhche
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| |
Collapse
|
43
|
EEG based dementia diagnosis using multi-class support vector machine with motor speed cognitive test. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2020.102102] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
|
44
|
Zheng X, Luo J, Deng L, Li B, Li L, Huang DF, Song R. Detection of functional connectivity in the brain during visuo-guided grip force tracking tasks: A functional near-infrared spectroscopy study. J Neurosci Res 2020; 99:1108-1119. [PMID: 33368535 DOI: 10.1002/jnr.24769] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 11/23/2020] [Indexed: 11/10/2022]
Abstract
The functional connectivity (FC) between multiple brain regions during tasks is currently gradually being explored with functional near-infrared spectroscopy (fNIRS). However, the FC present during grip force tracking tasks performed under visual feedback remains unclear. In the present study, we used fNIRS to measure brain activity during resting states and grip force tracking tasks at 25%, 50%, and 75% of maximum voluntary contraction (MVC) in 11 healthy subjects, and the activity was measured from four target brain regions: the left prefrontal cortex (lPFC), right prefrontal cortex (rPFC), left sensorimotor cortex (lSMC), and right sensorimotor cortex (rSMC). We determined the FC between these regions utilizing three different methods: Pearson's correlation method, partial correlation method, and a pairwise maximum entropy model (MEM). The results showed that the FC of lSMC-rSMC and lPFC-rPFC (interhemispheric homologous pairs) were significantly stronger than those of other brain region pairs. Moreover, FC of lPFC-rPFC was strengthened during the 75% MVC task compared to the other task states and the resting states. The FC of lSMC-lPFC and rSMC-rPFC (intrahemispheric region pairs) strengthened with a higher task load. The results provided new insights into the FC between brain regions during visuo-guided grip force tracking tasks.
Collapse
Affiliation(s)
- Xinyi Zheng
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Jie Luo
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Lingyun Deng
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Bing Li
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Le Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Dong Feng Huang
- Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Xinhua College, Sun Yat-sen University, Guangzhou, China
| | - Rong Song
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| |
Collapse
|
45
|
Muthuraman M, Bange M, Koirala N, Ciolac D, Pintea B, Glaser M, Tinkhauser G, Brown P, Deuschl G, Groppa S. Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in Parkinson's disease. Brain 2020; 143:3393-3407. [PMID: 33150359 PMCID: PMC7116448 DOI: 10.1093/brain/awaa297] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 07/16/2020] [Accepted: 07/20/2020] [Indexed: 12/30/2022] Open
Abstract
The disruption of pathologically enhanced beta oscillations is considered one of the key mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's disease. However, a specific modulation of other distinct physiological or pathological oscillatory activities could also play an important role in symptom control and motor function recovery during deep brain stimulation. Finely tuned gamma oscillations have been suggested to be prokinetic in nature, facilitating the preferential processing of physiological neural activity. In this study, we postulate that clinically effective high-frequency stimulation of the subthalamic nucleus imposes cross-frequency interactions with gamma oscillations in a cortico-subcortical network of interconnected regions and normalizes the balance between beta and gamma oscillations. To this end we acquired resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underwent deep brain stimulation to compare spectral power and power-to-power cross-frequency coupling using a beamformer algorithm for coherent sources. To show that modulations exclusively relate to stimulation frequencies that alleviate motor symptoms, two clinically ineffective frequencies were tested as control conditions. We observed a robust reduction of beta and increase of gamma power, attested in the regions of a cortical (motor cortex, supplementary motor area, premotor cortex) and subcortical network (subthalamic nucleus and cerebellum). Additionally, we found a clear cross-frequency coupling of narrowband gamma frequencies to the stimulation frequency in all of these nodes, which negatively correlated with motor impairment. No such dynamics were revealed within the control posterior parietal cortex region. Furthermore, deep brain stimulation at clinically ineffective frequencies did not alter the source power spectra or cross-frequency coupling in any region. These findings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differentially modifies different oscillatory activities in a widespread network of cortical and subcortical regions. Particularly the cross-frequency interactions between finely tuned gamma oscillations and the stimulation frequency may suggest an entrainment mechanism that could promote dynamic neural processing underlying motor symptom alleviation.
Collapse
Affiliation(s)
- Muthuraman Muthuraman
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Manuel Bange
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Nabin Koirala
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Dumitru Ciolac
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Bogdan Pintea
- Department of Neurosurgery, Bergmannsheil Clinic, Ruhr University Bochum, Bochum, Germany
| | - Martin Glaser
- Department of Neurosurgery, University Medical Center of the Johannes Gutenberg University, Mainz, Mainz, Germany
| | - Gerd Tinkhauser
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
- Department of Neurology, Bern University Hospital and University of Bern, Switzerland
| | - Peter Brown
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Günther Deuschl
- Department of Neurology, Christian Albrecht’s University, Kiel, Germany
| | - Sergiu Groppa
- Section of Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| |
Collapse
|
46
|
Karunakaran KD, Peng K, Berry D, Green S, Labadie R, Kussman B, Borsook D. NIRS measures in pain and analgesia: Fundamentals, features, and function. Neurosci Biobehav Rev 2020; 120:335-353. [PMID: 33159918 DOI: 10.1016/j.neubiorev.2020.10.023] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 09/28/2020] [Accepted: 10/19/2020] [Indexed: 02/06/2023]
Abstract
Current pain assessment techniques based only on clinical evaluation and self-reports are not objective and may lead to inadequate treatment. Having a functional biomarker will add to the clinical fidelity, diagnosis, and perhaps improve treatment efficacy in patients. While many approaches have been deployed in pain biomarker discovery, functional near-infrared spectroscopy (fNIRS) is a technology that allows for non-invasive measurement of cortical hemodynamics. The utility of fNIRS is especially attractive given its ability to detect specific changes in the somatosensory and high-order cortices as well as its ability to measure (1) brain function similar to functional magnetic resonance imaging, (2) graded responses to noxious and innocuous stimuli, (3) analgesia, and (4) nociception under anesthesia. In this review, we evaluate the utility of fNIRS in nociception/pain with particular focus on its sensitivity and specificity, methodological advantages and limitations, and the current and potential applications in various pain conditions. Everything considered, fNIRS technology could enhance our ability to evaluate evoked and persistent pain across different age groups and clinical populations.
Collapse
Affiliation(s)
- Keerthana Deepti Karunakaran
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States.
| | - Ke Peng
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States; Département en Neuroscience, Centre de Recherche du CHUM, l'Université de Montréal Montreal, QC, Canada
| | - Delany Berry
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - Stephen Green
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - Robert Labadie
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - Barry Kussman
- Division of Cardiac Anesthesia, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - David Borsook
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States.
| |
Collapse
|
47
|
Wang Y, Chen W. Effective brain connectivity for fNIRS data analysis based on multi-delays symbolic phase transfer entropy. J Neural Eng 2020; 17:056024. [PMID: 33055365 DOI: 10.1088/1741-2552/abb4a4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Recently, effective connectivity (EC) calculation methods for functional near-infrared spectroscopy (fNIRS) data mainly face two problems: the first problem is that noise can seriously affect the EC calculation and even lead to false connectivity; the second problem is that it ignores the various real neurotransmission delays between the brain region, and instead uses a fixed delay coefficient for calculation. APPROACH To overcome these two issues, a delay symbolic phase transfer entropy (dSPTE) is proposed by developing traditional transfer entropy (TE) to estimate EC for fNIRS. Firstly, the phase time sequence was obtained from the original sequence by the Hilbert transform and state-space reconstruction was realized using a uniform embedding scheme. Then, a symbolization technique was applied based on a neural-gas algorithm to improve its noise robustness. Finally, the EC was calculated on multiple time delay scales to match different inter-region neurotransmission delays. MAIN RESULTS A linear AR model, a nonlinear model and a multivariate hybrid model were introduced to simulate the performance of dSPTE, and the results showed that the accuracy of dSPTE was the highest, up to 74.27%, and specificity was 100% which means no false connectivity. The results confirmed that the dSPTE method realized better noise robustness, higher accuracy, and correct identification even if there was a long delay between series. Finally, we applied dSPTE to fNIRS dataset to analyse the EC during the finger-tapping task, the results showed that EC strength of task state significantly increased compared with the resting state. SIGNIFICANCE The proposed dSPTE method is a promising way to measure the EC for fNIRS. It incorporates the phase information TE with a symbolic process for fNIRS analysis for the first time. It has been confirmed to be noise robust and suitable for the complex network with different coupling delays.
Collapse
Affiliation(s)
- Yalin Wang
- Department of Electronic Engineering, Center for Intelligent Medical Electronics, School of Information Science and Technology, Fudan University, Shanghai, People's Republic of China. Human Phenome Institute, Fudan University, Shanghai, People's Republic of China
| | | |
Collapse
|
48
|
Soto-Leon V, Alonso-Bonilla C, Peinado-Palomino D, Torres-Pareja M, Mendoza-Laiz N, Mordillo-Mateos L, Onate-Figuerez A, Arias P, Aguilar J, Oliviero A. Effects of fatigue induced by repetitive movements and isometric tasks on reaction time. Hum Mov Sci 2020; 73:102679. [PMID: 32980590 DOI: 10.1016/j.humov.2020.102679] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2019] [Revised: 01/12/2020] [Accepted: 09/02/2020] [Indexed: 10/23/2022]
Abstract
PURPOSE The understanding of fatigue of the human motor system is important in the fields of ergonomics, sport, rehabilitation and neurology. In order to understand the interactions between fatigue and reaction time, we evaluated the effects of two different fatiguing tasks on reaction time. METHODS 83 healthy subjects were included in a case-control study with three arms where single and double choice reaction time tasks were performed before and after 2 min fatiguing task (an isometric task, a finger tapping task and at rest). RESULTS After an isometric task, the right-fatigued hand was slower in the choice component of a double choice reaction time task (calculated as the individual difference between single and double choice reaction times); also, the subjects that felt more fatigued had slower choice reaction time respect to the baseline assessment. Moreover, in relationship to the performance decay after two minutes, finger tapping task produces more intense fatigability perception. CONCLUSIONS We confirmed that two minutes of isometric or repetitive tasks are enough to produce fatigue. The fatigue perception is more intense for finger tapping tasks in relation to the performance decay. We therefore confirmed that the two fatiguing tasks produced two different kind of fatigue demonstrating that with a very simple protocol it is possible to test subjects or patients to quantify different form of fatigue.
Collapse
Affiliation(s)
- Vanesa Soto-Leon
- FENNSI Group, National Hospital for Paraplegics, SESCAM, Toledo, Spain
| | | | - Diego Peinado-Palomino
- FENNSI Group, National Hospital for Paraplegics, SESCAM, Toledo, Spain; Faculty of Sport Sciences, University of Castilla- La Mancha, UCLM, Toledo, Spain
| | - Marta Torres-Pareja
- FENNSI Group, National Hospital for Paraplegics, SESCAM, Toledo, Spain; Faculty of Sport Sciences, University of Castilla- La Mancha, UCLM, Toledo, Spain
| | | | | | | | - Pablo Arias
- Neuroscience and Motor Control Group, NEUROcom, Department of Medicine, University of Coruna and Biomedical Research Institute of A Coruna (INIBIC), A Coruña, Galicia, Spain
| | - Juan Aguilar
- Experimental Neurophysiology, National Hospital for Paraplegics, SESCAM, Toledo, Spain
| | - Antonio Oliviero
- FENNSI Group, National Hospital for Paraplegics, SESCAM, Toledo, Spain.
| |
Collapse
|
49
|
Kim H. Cerebral hemodynamics predicts the cortical area and coding scheme in the human brain for force generation by wrist muscles. Behav Brain Res 2020; 396:112865. [PMID: 32827565 DOI: 10.1016/j.bbr.2020.112865] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 07/14/2020] [Accepted: 08/12/2020] [Indexed: 10/23/2022]
Abstract
The goal of this study is to identify the cortical area maximally active over the primary sensorimotor cortex (SM1) and characterize the cortical encoding for force production by wrist muscles in the human brain. The technique of functional near-infrared spectroscopy (fNIRS) was used to continuously monitor the changes in hemoglobin concentrations from the left hemisphere during isometric contractions of wrist flexion muscles over a broad range of load forces (0 ∼ 8 kgf) on the right hand. As previously shown in primate studies, this action produced hemodynamic activity predominantly in the wrist area localized dorsally to the finger region over SM1 and the hemodynamic response was systematically related to the level of load intensity. The coding scheme for force production in terms of hemodynamic signals was characterized defining eight trajectory parameters (four for amplitude coding and four for temporal coding) and analyzed for the area maximally activated over SM1. The trajectory parameter representing the oxygenated hemoglobin concentration change at the end of motor task (amplitude coding) and the timing of maximum change in oxygenated hemoglobin concentration (temporal coding) was most strongly correlated with the load variation in a superliner manner. All these results indicate the applicability of fNIRS to monitor and decode cortical activity that is correlated with low-level motor control such as isometric muscle contractions. This study may provide not only insights into cortical neural control of muscle force but also predictors of muscle force in clinical diagnostics and neural interfaces for the human brain.
Collapse
Affiliation(s)
- Hojeong Kim
- Division of Biotechnology, Convergence Research Institute, DGIST, Republic of Korea.
| |
Collapse
|
50
|
Dietz V. Neural coordination of bilateral power and precision finger movements. Eur J Neurosci 2020; 54:8249-8255. [PMID: 32682343 DOI: 10.1111/ejn.14911] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 07/02/2020] [Accepted: 07/03/2020] [Indexed: 11/29/2022]
Abstract
The dexterity of hands and fingers is related to the strength of control by cortico-motoneuronal connections which exclusively exist in primates. The cortical command is associated with a task-specific, rapid proprioceptive adaptation of forces applied by hands and fingers to an object. This neural control differs between "power grip" movements (e.g., reach and grasp of a cup) where hand and fingers act as a unity and "precision grip" movements (e.g., picking up a raspberry) where fingers move independently from the hand. In motor tasks requiring hands and fingers of both sides a "neural coupling" (reflected in bilateral reflex responses to unilateral stimulations) coordinates power grip movements (e.g., opening a bottle). In contrast, during bilateral precision movements, such as playing piano, the fingers of both hands move independently, due to a direct cortico-motoneuronal control, while the hands are coupled (e.g., to maintain the rhythm between the two sides). While most studies on prehension concern unilateral hand movements, many activities of daily life are tackled by bilateral power grips where a neural coupling serves for an automatic movement performance. In primates this mode of motor control is supplemented by a system that enables the uni- or bilateral performance of skilled individual finger movements.
Collapse
Affiliation(s)
- Volker Dietz
- Spinal Injury Center, University Hospital Balgrist, Zürich, Switzerland
| |
Collapse
|