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Hu F, Yao P, He K, Yang X, Gouda MA, Zhang L. Effects of Emotional Olfactory Stimuli on Modulating Angry Driving Based on an EEG Connectivity Study. Int J Neural Syst 2024; 34:2450058. [PMID: 39155690 DOI: 10.1142/s0129065724500588] [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] [Indexed: 08/20/2024]
Abstract
Effectively regulating anger driving has become critical in ensuring road safety. The existing research lacks a feasible exploration of anger-driving regulation. This paper delves into the effect and neural mechanisms of emotional olfactory stimuli (EOS) on regulating anger driving based on EEG. First, this study designed an angry driving regulation experiment based on EOS to record EEG signals. Second, brain activation patterns under various EOS conditions are explored by analyzing functional brain networks (FBNs). Additionally, the paper analyzes dynamic alterations in anger-related characteristics to explore the intensity and persistence of regulating anger driving under different EOS. Finally, the paper studies the frequency energy of EEG changes under EOS through time-frequency analysis. The results indicate that EOS can effectively regulate a driver's anger emotions, especially with the banana odor showing superior effects. Under banana odor stimulus, synchronization between the parietal and temporal lobes significantly decreased. Notably, the regulatory effect of banana odor is optimal and exhibits sustained efficacy. The regulatory effect of banana odor on anger emotions is persistent. Furthermore, the impact of banana odor significantly reduces the distribution of high-energy activation states in the parietal lobe region. Our findings provide new insights into the dynamic characterization of functional connectivity during anger-driving regulation and demonstrate the potential of using EOS as a reliable tool for regulating angry driving.
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Affiliation(s)
- Fo Hu
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, P. R. China
| | - Peipei Yao
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, P. R. China
| | - Kailun He
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, P. R. China
| | - Xusheng Yang
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, P. R. China
| | - Mohamed Amin Gouda
- Department of Mechanical Engineering and Automation, Northeastern University, Shenyang, Liaoning 110819, P. R. China
| | - Lekai Zhang
- School of Design and Architecture, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, P. R. China
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Gutiérrez-de Pablo V, Poza J, Maturana-Candelas A, Rodríguez-González V, Tola-Arribas MÁ, Cano M, Hoshi H, Shigihara Y, Hornero R, Gómez C. Exploring the disruptions of the neurophysiological organization in Alzheimer's disease: An integrative approach. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 250:108197. [PMID: 38688139 DOI: 10.1016/j.cmpb.2024.108197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 12/20/2023] [Accepted: 04/21/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND AND OBJECTIVE Alzheimer's disease (AD) is a neurological disorder that impairs brain functions associated with cognition, memory, and behavior. Noninvasive neurophysiological techniques like magnetoencephalography (MEG) and electroencephalography (EEG) have shown promise in reflecting brain changes related to AD. These techniques are usually assessed at two levels: local activation (spectral, nonlinear, and dynamic properties) and global synchronization (functional connectivity, frequency-dependent network, and multiplex network organization characteristics). Nonetheless, the understanding of the organization formed by the existing relationships between these levels, henceforth named neurophysiological organization, remains unexplored. This work aims to assess the alterations AD causes in the resting-state neurophysiological organization. METHODS To that end, three datasets from healthy controls (HC) and patients with dementia due to AD were considered: MEG database (55 HC and 87 patients with AD), EEG1 database (51 HC and 100 patients with AD), and EEG2 database (45 HC and 82 patients with AD). To explore the alterations induced by AD in the relationships between several features extracted from M/EEG data, association networks (ANs) were computed. ANs are graphs, useful to quantify and visualize the intricate relationships between multiple features. RESULTS Our results suggested a disruption in the neurophysiological organization of patients with AD, exhibiting a greater inclination towards the local activation level; and a significant decrease in the complexity and diversity of the ANs (p-value ¡ 0.05, Mann-Whitney U-test, Bonferroni correction). This effect might be due to a shift of the neurophysiological organization towards more regular configurations, which may increase its vulnerability. Moreover, our findings support the crucial role played by the local activation level in maintaining the stability of the neurophysiological organization. Classification performance exhibited accuracy values of 83.91%, 73.68%, and 72.65% for MEG, EEG1, and EEG2 databases, respectively. CONCLUSION This study introduces a novel, valuable methodology able to integrate parameters characterize different properties of the brain activity and to explore the intricate organization of the neurophysiological organization at different levels. It was noted that AD increases susceptibility to changes in functional neural organization, suggesting a greater ease in the development of severe impairments. Therefore, ANs could facilitate a deeper comprehension of the complex interactions in brain function from a global standpoint.
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Affiliation(s)
- Víctor Gutiérrez-de Pablo
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER-BBN, Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Spain.
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER-BBN, Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Spain
| | - Aarón Maturana-Candelas
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER-BBN, Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Spain
| | - Víctor Rodríguez-González
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER-BBN, Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Spain
| | - Miguel Ángel Tola-Arribas
- CIBER-BBN, Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Spain; Department of Neurology, Río Hortega University Hospital, Valladolid, Spain
| | - Mónica Cano
- Department of Clinical Neurophysiology, Río Hortega University Hospital, Valladolid, Spain
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
| | | | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER-BBN, Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Spain
| | - Carlos Gómez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; CIBER-BBN, Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Spain
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Hoshi H, Hirata Y, Fukasawa K, Kobayashi M, Shigihara Y. Oscillatory characteristics of resting-state magnetoencephalography reflect pathological and symptomatic conditions of cognitive impairment. Front Aging Neurosci 2024; 16:1273738. [PMID: 38352236 PMCID: PMC10861731 DOI: 10.3389/fnagi.2024.1273738] [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: 08/07/2023] [Accepted: 01/12/2024] [Indexed: 02/16/2024] Open
Abstract
Background Dementia and mild cognitive impairment are characterised by symptoms of cognitive decline, which are typically assessed using neuropsychological assessments (NPAs), such as the Mini-Mental State Examination (MMSE) and Frontal Assessment Battery (FAB). Magnetoencephalography (MEG) is a novel clinical assessment technique that measures brain activities (summarised as oscillatory parameters), which are associated with symptoms of cognitive impairment. However, the relevance of MEG and regional cerebral blood flow (rCBF) data obtained using single-photon emission computed tomography (SPECT) has not been examined using clinical datasets. Therefore, this study aimed to investigate the relationships among MEG oscillatory parameters, clinically validated biomarkers computed from rCBF, and NPAs using outpatient data retrieved from hospital records. Methods Clinical data from 64 individuals with mixed pathological backgrounds were retrieved and analysed. MEG oscillatory parameters, including relative power (RP) from delta to high gamma bands, mean frequency, individual alpha frequency, and Shannon's spectral entropy, were computed for each cortical region. For SPECT data, three pathological parameters-'severity', 'extent', and 'ratio'-were computed using an easy z-score imaging system (eZIS). As for NPAs, the MMSE and FAB scores were retrieved. Results MEG oscillatory parameters were correlated with eZIS parameters. The eZIS parameters associated with Alzheimer's disease pathology were reflected in theta power augmentation and slower shift of the alpha peak. Moreover, MEG oscillatory parameters were found to reflect NPAs. Global slowing and loss of diversity in neural oscillatory components correlated with MMSE and FAB scores, whereas the associations between eZIS parameters and NPAs were sparse. Conclusion MEG oscillatory parameters correlated with both SPECT (i.e. eZIS) parameters and NPAs, supporting the clinical validity of MEG oscillatory parameters as pathological and symptomatic indicators. The findings indicate that various components of MEG oscillatory characteristics can provide valuable pathological and symptomatic information, making MEG data a rich resource for clinical examinations of patients with cognitive impairments. SPECT (i.e. eZIS) parameters showed no correlations with NPAs. The results contributed to a better understanding of the characteristics of electrophysiological and pathological examinations for patients with cognitive impairments, which will help to facilitate their co-use in clinical application, thereby improving patient care.
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Affiliation(s)
- Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
| | - Yoko Hirata
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya, Japan
| | | | - Momoko Kobayashi
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, Japan
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, Japan
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Tsallis C, Pasechnik R. Medical Applications of Nonadditive Entropies. ENTROPY (BASEL, SWITZERLAND) 2023; 25:e25040578. [PMID: 37190366 PMCID: PMC10137456 DOI: 10.3390/e25040578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 03/22/2023] [Indexed: 05/17/2023]
Abstract
The Boltzmann-Gibbs additive entropy SBG=-k∑ipilnpi and associated statistical mechanics were generalized in 1988 into nonadditive entropy Sq=k1-∑ipiqq-1 and nonextensive statistical mechanics, respectively. Since then, a plethora of medical applications have emerged. In the present review, we illustrate them by briefly presenting image and signal processings, tissue radiation responses, and modeling of disease kinetics, such as for the COVID-19 pandemic.
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Affiliation(s)
- Constantino Tsallis
- Centro Brasileiro de Pesquisas Fisicas and National Institute of Science and Technology of Complex Systems, Rua Xavier Sigaud 150, Rio de Janeiro 22290-180, RJ, Brazil
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
- Complexity Science Hub Vienna, Josefstädter Strasse 39, 1080 Vienna, Austria
| | - Roman Pasechnik
- Department of Physics, Lund University, Sölvegatan 14A, SE-22362 Lund, Sweden
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Hoshi H, Hirata Y, Kobayashi M, Sakamoto Y, Fukasawa K, Ichikawa S, Poza J, Rodríguez-González V, Gómez C, Shigihara Y. Distinctive effects of executive dysfunction and loss of learning/memory abilities on resting-state brain activity. Sci Rep 2022; 12:3459. [PMID: 35236888 PMCID: PMC8891272 DOI: 10.1038/s41598-022-07202-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 02/11/2022] [Indexed: 01/08/2023] Open
Abstract
Dementia is a syndrome characterised by cognitive impairments, with a loss of learning/memory abilities at the earlier stages and executive dysfunction at the later stages. However, recent studies have suggested that impairments in both learning/memory abilities and executive functioning might co-exist. Cognitive impairments have been primarily evaluated using neuropsychological assessments, such as the Mini-Mental State Examination (MMSE). Recently, neuroimaging techniques such as magnetoencephalography (MEG), which assess changes in resting-state brain activity, have also been used as biomarkers for cognitive impairment. However, it is unclear whether these changes reflect dysfunction in executive function as well as learning and memory. In this study, parameters from the MEG for brain activity, MMSE for learning/memory, and Frontal Assessment Battery (FAB) for executive function were compared within 207 individuals. Three MEG parameters were used as representatives of resting-state brain activity: median frequency, individual alpha frequency, and Shannon’s spectral entropy. Regression analysis showed that median frequency was predicted by both the MMSE and FAB scores, while individual alpha frequency and Shannon’s spectral entropy were predicted by MMSE and FAB scores, respectively. Our results indicate that MEG spectral parameters reflect both learning/memory and executive functions, supporting the utility of MEG as a biomarker of cognitive impairment.
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Affiliation(s)
- Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan
| | - Yoko Hirata
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Momoko Kobayashi
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Yuki Sakamoto
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Keisuke Fukasawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Sayuri Ichikawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Jesús Poza
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, 47011, Valladolid, Castilla y León, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina, (CIBER-BBN), 47011, Valladolid, Castilla y León, Spain.,Instituto de Investigación en Matemáticas (IMUVA), University of Valladolid, 47011, Valladolid, Castilla y León, Spain
| | - Víctor Rodríguez-González
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, 47011, Valladolid, Castilla y León, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina, (CIBER-BBN), 47011, Valladolid, Castilla y León, Spain
| | - Carlos Gómez
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, 47011, Valladolid, Castilla y León, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina, (CIBER-BBN), 47011, Valladolid, Castilla y León, Spain
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan. .,Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan.
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6
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Rodríguez-González V, Gómez C, Hoshi H, Shigihara Y, Hornero R, Poza J. Exploring the Interactions Between Neurophysiology and Cognitive and Behavioral Changes Induced by a Non-pharmacological Treatment: A Network Approach. Front Aging Neurosci 2021; 13:696174. [PMID: 34393759 PMCID: PMC8358307 DOI: 10.3389/fnagi.2021.696174] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 07/13/2021] [Indexed: 11/24/2022] Open
Abstract
Dementia due to Alzheimer's disease (AD) is a neurological syndrome which has an increasing impact on society, provoking behavioral, cognitive, and functional impairments. AD lacks an effective pharmacological intervention; thereby, non-pharmacological treatments (NPTs) play an important role, as they have been proven to ameliorate AD symptoms. Nevertheless, results associated with NPTs are patient-dependent, and new tools are needed to predict their outcome and to improve their effectiveness. In the present study, 19 patients with AD underwent an NPT for 83.1 ± 38.9 days (mean ± standard deviation). The NPT was a personalized intervention with physical, cognitive, and memory stimulation. The magnetoencephalographic activity was recorded at the beginning and at the end of the NPT to evaluate the neurophysiological state of each patient. Additionally, the cognitive (assessed by means of the Mini-Mental State Examination, MMSE) and behavioral (assessed in terms of the Dementia Behavior Disturbance Scale, DBD-13) status were collected before and after the NPT. We analyzed the interactions between cognitive, behavioral, and neurophysiological data by generating diverse association networks, able to intuitively characterize the relationships between variables of a different nature. Our results suggest that the NPT remarkably changed the structure of the association network, reinforcing the interactions between the DBD-13 and the neurophysiological parameters. We also found that the changes in cognition and behavior are related to the changes in spectral-based neurophysiological parameters. Furthermore, our results support the idea that MEG-derived parameters can predict NPT outcome; specifically, a lesser degree of AD neurophysiological alterations (i.e., neural oscillatory slowing, decreased variety of spectral components, and increased neural signal regularity) predicts a better NPT prognosis. This study provides deeper insights into the relationships between neurophysiology and both, cognitive and behavioral status, proving the potential of network-based methodology as a tool to further understand the complex interactions elicited by NPTs.
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Affiliation(s)
| | - Carlos Gómez
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
| | | | - Roberto Hornero
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
- IMUVA, Instituto de Investigación en Matemáticas, Universidad de Valladolid, Valladolid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
- IMUVA, Instituto de Investigación en Matemáticas, Universidad de Valladolid, Valladolid, Spain
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Matsumoto T, Hoshi H, Hirata Y, Ichikawa S, Fukasawa K, Gonda T, Poza J, Rodríguez-González V, Gómez C, Shigihara Y. The association between carotid blood flow and resting-state brain activity in patients with cerebrovascular diseases. Sci Rep 2021; 11:15225. [PMID: 34315975 PMCID: PMC8316461 DOI: 10.1038/s41598-021-94717-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 07/15/2021] [Indexed: 11/09/2022] Open
Abstract
Cerebral hypoperfusion impairs brain activity and leads to cognitive impairment. Left and right common carotid arteries (CCA) are the major source of cerebral blood supply. It remains unclear whether blood flow in both CCA contributes equally to brain activity. Here, CCA blood flow was evaluated using ultrasonography in 23 patients with cerebrovascular diseases. Resting-state brain activity and cognitive status were also assessed using magnetoencephalography and a cognitive subscale of the Functional Independence Measure, respectively, to explore the relationships between blood flow, functional brain activity, and cognitive status. Our findings indicated that there was an association between blood flow and resting-state brain activity, and between resting-state brain activity and cognitive status. However, blood flow was not significantly associated with cognitive status directly. Furthermore, blood velocity in the right CCA correlated with resting-state brain activity, but not with the resistance index. In contrast, the resistance index in the left CCA correlated with resting-state brain activity, but not with blood velocity. Our findings suggest that hypoperfusion is important in the right CCA, whereas cerebral microcirculation is important in the left CCA for brain activity. Hence, this asymmetry should be considered when designing appropriate therapeutic strategies.
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Affiliation(s)
- Takahiro Matsumoto
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya, 360-8567, Japan
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan
| | - Yoko Hirata
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya, 360-8567, Japan
| | - Sayuri Ichikawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya, 360-8567, Japan
| | - Keisuke Fukasawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya, 360-8567, Japan
| | - Tomoyuki Gonda
- Department of Rehabilitation, Kumagaya General Hospital, Kumagaya, 360-8567, Japan
| | - Jesús Poza
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Castilla y León, 47011, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, (CIBER-BBN), Biomateriales y Nanomedicina, Castilla y León, 47011, Valladolid, Spain.,Instituto de Investigación en Matemáticas (IMUVA), University of Valladolid, Castilla y León, 47011, Valladolid, Spain
| | - Víctor Rodríguez-González
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Castilla y León, 47011, Valladolid, Spain
| | - Carlos Gómez
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Castilla y León, 47011, Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, (CIBER-BBN), Biomateriales y Nanomedicina, Castilla y León, 47011, Valladolid, Spain
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan. .,Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, 360-8567, Japan.
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Verma RK, Pandey M, Chawla P, Choudhury H, Mayuren J, Bhattamisra SK, Gorain B, Raja MAG, Amjad MW, Obaidur Rahman S. An insight into the role of Artificial Intelligence in the early diagnosis of Alzheimer's disease. CNS & NEUROLOGICAL DISORDERS-DRUG TARGETS 2021; 21:901-912. [PMID: 33982657 DOI: 10.2174/1871527320666210512014505] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 01/12/2021] [Accepted: 02/17/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The complication of Alzheimer's disease (AD) has made the development of its therapeutic a challenging task. Even after decades of research, we have achieved no more than a few years of symptomatic relief. The inability to diagnose the disease early is the foremost hurdle behind its treatment. Several studies have aimed to identify potential biomarkers that can be detected in body fluids (CSF, blood, urine, etc) or assessed by neuroimaging (i.e., PET and MRI). However, the clinical implementation of these biomarkers is incomplete as they cannot be validated. METHOD To overcome the limitation, the use of artificial intelligence along with technical tools has been extensively investigated for AD diagnosis. For developing a promising artificial intelligence strategy that can diagnose AD early, it is critical to supervise neuropsychological outcomes and imaging-based readouts with a proper clinical review. CONCLUSION Profound knowledge, a large data pool, and detailed investigations are required for the successful implementation of this tool. This review will enlighten various aspects of early diagnosis of AD using artificial intelligence.
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Affiliation(s)
- Rohit Kumar Verma
- International Medical University Department of Pharmacy Practice, School of Pharmacy, Malaysia
| | - Manisha Pandey
- Department of Pharmaceutical Technology, School of Pharmacy, International Medical University-Bukit Jalil 57000, Kuala Lumpur, Malaysia School of Pharmacy,, Malaysia
| | - Pooja Chawla
- ISF College of Pharmacy, Moga Pharmaceutical Chemistry, India
| | - Hira Choudhury
- International Medical University Pharmaceutical Technology, Malaysia
| | - Jayashree Mayuren
- School of Pharmacy, International Medical University Department of Pharmaceutical Technology,, Malaysia
| | | | - Bapi Gorain
- Lincoln University College Faculty of Pharmacy, Malaysia
| | | | | | - Syed Obaidur Rahman
- Department of Pharmaceutical Medicine, School of Pharmaceutical Education and Research, Jamia Humdard, New Delhi India Pharmacology, India
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Shigihara Y, Hoshi H, Poza J, Rodríguez-González V, Gómez C, Kanzawa T. Predicting the outcome of non-pharmacological treatment for patients with dementia-related mild cognitive impairment. Aging (Albany NY) 2020; 12:24101-24116. [PMID: 33289701 PMCID: PMC7762505 DOI: 10.18632/aging.202270] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 11/08/2020] [Indexed: 06/12/2023]
Abstract
Dementia is a progressive cognitive syndrome, with few effective pharmacological treatments that can slow its progress. Hence, non-pharmacological treatments (NPTs) play an important role in improving patient symptoms and quality of life. Designing the optimal personalised NPT strategy relies on objectively and quantitatively predicting the treatment outcome. Magnetoencephalography (MEG) findings can reflect the cognitive status of patients with dementia, and thus potentially predict NPT outcome. In the present study, 16 participants with cognitive impairment underwent NPT for several months. Their cognitive performance was evaluated based on the Mini-Mental State Examination and the Alzheimer's Disease Assessment Scale - Cognitive at the beginning and end of the NPT period, while resting-state brain activity was evaluated using MEG during the NPT period. Our results showed that the spectral properties of MEG signals predicted the changes in cognitive performance scores. High frequency oscillatory intensity at the right superior frontal gyrus medial segment, opercular part of the inferior frontal gyrus, triangular part of the inferior frontal gyrus, post central gyrus, and angular gyrus predicted the changes in cognitive performance scores. Thus, resting-state brain activity may be a powerful tool in designing personalised NPT.
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Affiliation(s)
- Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Obihiro 080-0833, Hokkaido, Japan
- MEG Centre, Kumagaya General Hospital, Kumagaya 360-8567, Saitama, Japan
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro 080-0833, Hokkaido, Japan
| | - Jesús Poza
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Valladolid 47011, Castilla y León, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid 47011, Castilla y León, Spain
- Instituto de Investigación en Matemáticas (IMUVA), University of Valladolid, Valladolid 47011, Castilla y León, Spain
| | - Víctor Rodríguez-González
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Valladolid 47011, Castilla y León, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid 47011, Castilla y León, Spain
| | - Carlos Gómez
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, Valladolid 47011, Castilla y León, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid 47011, Castilla y León, Spain
| | - Takao Kanzawa
- The Dementia Center, Institute of Brain and Vessels Mihara Memorial Hospital, Isehara 372-0006, Gunma, Japan
- Isesaki Clinic, Gunma, Isehara 372-0056, Gunma, Japan
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de Frutos-Lucas J, Cuesta P, Ramírez-Toraño F, Nebreda A, Cuadrado-Soto E, Peral-Suárez Á, Lopez-Sanz D, Bruña R, Marcos-de Pedro S, Delgado-Losada ML, López-Sobaler AM, Concepción Rodríguez-Rojo I, Barabash A, Serrano Rodriguez JM, Laws SM, Dolado AM, López-Higes R, Brown BM, Maestú F. Age and APOE genotype affect the relationship between objectively measured physical activity and power in the alpha band, a marker of brain disease. Alzheimers Res Ther 2020; 12:113. [PMID: 32962736 PMCID: PMC7507658 DOI: 10.1186/s13195-020-00681-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 09/10/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Electrophysiological studies show that reductions in power within the alpha band are associated with the Alzheimer's disease (AD) continuum. Physical activity (PA) is a protective factor that has proved to reduce AD risk and pathological brain burden. Previous research has confirmed that exercise increases power in the alpha range. However, little is known regarding whether other non-modifiable risk factors for AD, such as increased age or APOE ε4 carriage, alter the association between PA and power in the alpha band. METHODS The relationship between PA and alpha band power was examined in a sample of 113 healthy adults using magnetoencephalography. Additionally, we explored whether ε4 carriage and age modulate this association. The correlations between alpha power and gray matter volumes and cognition were also investigated. RESULTS We detected a parieto-occipital cluster in which PA positively correlated with alpha power. The association between PA and alpha power remained following stratification of the cohort by genotype. Younger and older adults were investigated separately, and only younger adults exhibited a positive relationship between PA and alpha power. Interestingly, when four groups were created based on age (younger-older adult) and APOE (E3/E3-E3/E4), only younger E3/E3 (least predicted risk) and older E3/E4 (greatest predicted risk) had associations between greater alpha power and higher PA. Among older E3/E4, greater alpha power in these regions was associated with improved memory and preserved brain structure. CONCLUSION PA could protect against the slowing of brain activity that characterizes the AD continuum, where it is of benefit for all individuals, especially E3/E4 older adults.
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Affiliation(s)
- Jaisalmer de Frutos-Lucas
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
- Biological and Health Psychology Department, School of Psychology, Universidad Autonoma de Madrid, 28049, Madrid, Spain.
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain.
| | - Pablo Cuesta
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Federico Ramírez-Toraño
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Alberto Nebreda
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Esther Cuadrado-Soto
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
- IMDEA-Food, CEI UAM + CSIC, Madrid, 28049, Spain
| | - África Peral-Suárez
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - David Lopez-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Department of Psychobiology and Methodology in Behavioral Sciences, Universidad Complutense de Madrid (UCM), Pozuelo de Alarcón, 28223, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029, Madrid, Spain
| | - Silvia Marcos-de Pedro
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Departamento de Especialidades Medicas y Salud Pública, Universidad Rey Juan Carlos, 28922, Alcorcon, Spain
| | - María Luisa Delgado-Losada
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Ana María López-Sobaler
- Departamento de Nutricion y Ciencia de los Alimentos, Facultad de Farmacia, Universidad Complutense de Madrid, 28040, Madrid, Spain
| | - Inmaculada Concepción Rodríguez-Rojo
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, 28040, Madrid, Spain
- Physiotherapy and Nursing Faculty, University of Castilla-La Mancha, Toledo, 45004, Spain
| | - Ana Barabash
- Endocrinology and Nutrition Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, 28040, Madrid, Spain
- Facultad de Psicología, Centro Universitario Villanueva, 28034, Madrid, Spain
| | - Juan Manuel Serrano Rodriguez
- Biological and Health Psychology Department, School of Psychology, Universidad Autonoma de Madrid, 28049, Madrid, Spain
| | - Simon M Laws
- Collaborative Genomics Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia
| | - Alberto Marcos Dolado
- Neurology Department, Hospital Clinico San Carlos and Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, 28040, Madrid, Spain
| | - Ramón López-Higes
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
| | - Belinda M Brown
- Discipline of Exercise Science, College of Science, Health, Engineering and Education, Murdoch University, Murdoch, Western Australia, 6150, Australia
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology, Parque Científico y Tecnológico de la UPM, Crta. M40, Km. 38, 28223, Pozuelo de Alarcón, Madrid, Spain
- Experimental Psychology Department, School of Psychology, Universidad Complutense de Madrid, 28223, Pozuelo de Alarcon, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029, Madrid, Spain
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11
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Ren P, Ma M, Xie G, Wu Z, Wu D. Altered complexity of resting-state BOLD activity in Alzheimer's disease-related neurodegeneration: a multiscale entropy analysis. Aging (Albany NY) 2020; 12:13571-13582. [PMID: 32649309 PMCID: PMC7377896 DOI: 10.18632/aging.103463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 05/27/2020] [Indexed: 11/25/2022]
Abstract
Brain complexity, which reflects the ability of the brain to adapt to a changing environment, has been found to be significantly changed with age. However, there is less evidence on the alterations of brain complexity in neurodegenerative disorders such as Alzheimer's disease (AD). Here we investigated the altered complexity of resting-state blood oxygen level-dependent signals in AD-related neurodegeneration using multiscale entropy (MSE) analysis. All participants were recruited from the Alzheimer's Disease Neuroimaging Initiative, including healthy controls (HC, n=62), amnestic mild cognitive impairment (aMCI, n =81) patients, and Alzheimer's disease (AD, n=25) patients. Our results showed time scale-dependent MSE differences across the three groups. In scale=1, significantly changed MSE patterns (HC>aMCI>AD) were found in four brain regions, including the hippocampus, middle frontal gyrus, intraparietal lobe, and superior frontal gyrus. In scale=4, reversed MSE patterns (HC<aMCI<AD) were found in the middle frontal gyrus and middle occipital gyrus. Furthermore, the values of regional entropy were significantly associated with cognitive functions positively on the short time scale, while negatively on the longer time scale. Our findings suggest that MSE could be a reliable measure for characterizing brain deterioration in AD, and may provide insights into the neural mechanism of AD-related neurodegeneration.
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Affiliation(s)
- Ping Ren
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Manxiu Ma
- Center for Neurobiology Research, Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA 24016, USA
| | - Guohua Xie
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Zhiwei Wu
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Donghui Wu
- Shenzhen Mental Health Center, Shenzhen, Guangdong, China.,Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
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12
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Sun J, Wang B, Niu Y, Tan Y, Fan C, Zhang N, Xue J, Wei J, Xiang J. Complexity Analysis of EEG, MEG, and fMRI in Mild Cognitive Impairment and Alzheimer's Disease: A Review. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E239. [PMID: 33286013 PMCID: PMC7516672 DOI: 10.3390/e22020239] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 02/15/2020] [Accepted: 02/17/2020] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) is a degenerative brain disease with a high and irreversible incidence. In recent years, because brain signals have complex nonlinear dynamics, there has been growing interest in studying complex changes in the time series of brain signals in patients with AD. We reviewed studies of complexity analyses of single-channel time series from electroencephalogram (EEG), magnetoencephalogram (MEG), and functional magnetic resonance imaging (fMRI) in AD and determined future research directions. A systematic literature search for 2000-2019 was performed in the Web of Science and PubMed databases, resulting in 126 identified studies. Compared to healthy individuals, the signals from AD patients have less complexity and more predictable oscillations, which are found mainly in the left parietal, occipital, right frontal, and temporal regions. This complexity is considered a potential biomarker for accurately responding to the functional lesion in AD. The current review helps to reveal the patterns of dysfunction in the brains of patients with AD and to investigate whether signal complexity can be used as a biomarker to accurately respond to the functional lesion in AD. We proposed further studies in the signal complexities of AD patients, including investigating the reliability of complexity algorithms and the spatial patterns of signal complexity. In conclusion, the current review helps to better understand the complexity of abnormalities in the AD brain and provide useful information for AD diagnosis.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.S.); (B.W.); (Y.N.); (Y.T.); (C.F.); (N.Z.); (J.X.); (J.W.)
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13
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Echegoyen I, López-Sanz D, Martínez JH, Maestú F, Buldú JM. Permutation Entropy and Statistical Complexity in Mild Cognitive Impairment and Alzheimer's Disease: An Analysis Based on Frequency Bands. ENTROPY 2020; 22:e22010116. [PMID: 33285891 PMCID: PMC7516422 DOI: 10.3390/e22010116] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 01/15/2020] [Accepted: 01/16/2020] [Indexed: 12/14/2022]
Abstract
We present one of the first applications of Permutation Entropy (PE) and Statistical Complexity (SC) (measured as the product of PE and Jensen-Shanon Divergence) on Magnetoencephalography (MEG) recordings of 46 subjects suffering from Mild Cognitive Impairment (MCI), 17 individuals diagnosed with Alzheimer's Disease (AD) and 48 healthy controls. We studied the differences in PE and SC in broadband signals and their decomposition into frequency bands ( δ , θ , α and β ), considering two modalities: (i) raw time series obtained from the magnetometers and (ii) a reconstruction into cortical sources or regions of interest (ROIs). We conducted our analyses at three levels: (i) at the group level we compared SC in each frequency band and modality between groups; (ii) at the individual level we compared how the [PE, SC] plane differs in each modality; and (iii) at the local level we explored differences in scalp and cortical space. We recovered classical results that considered only broadband signals and found a nontrivial pattern of alterations in each frequency band, showing that SC does not necessarily decrease in AD or MCI.
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Affiliation(s)
- Ignacio Echegoyen
- Laboratory of Biological Networks, Centre for Biomedical Technology, Universidad Politécnica de Madrid (UPM), 28223 Madrid, Spain;
- Complex Systems Group, Rey Juan Carlos University, 28933 Madrid, Spain
- Grupo Interdisciplinar de Sistemas Complejos (GISC), 28911 Madrid, Spain;
- Correspondence:
| | - David López-Sanz
- Laboratory of Cognitive and Computational Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid (UPM), 28223 Madrid, Spain; (D.L.-S.); (F.M.)
- Department of Experimental Psychology, Complutense University of Madrid, 28223 Madrid, Spain
| | - Johann H. Martínez
- Grupo Interdisciplinar de Sistemas Complejos (GISC), 28911 Madrid, Spain;
- Biomedical Engineering Department, Universidad de los Andes, Bogotá 111711, Colombia
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid (UPM), 28223 Madrid, Spain; (D.L.-S.); (F.M.)
- Department of Experimental Psychology, Complutense University of Madrid, 28223 Madrid, Spain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine, 28029 Zaragoza, Spain
| | - Javier M. Buldú
- Laboratory of Biological Networks, Centre for Biomedical Technology, Universidad Politécnica de Madrid (UPM), 28223 Madrid, Spain;
- Complex Systems Group, Rey Juan Carlos University, 28933 Madrid, Spain
- Grupo Interdisciplinar de Sistemas Complejos (GISC), 28911 Madrid, Spain;
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14
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Maturana-Candelas A, Gómez C, Poza J, Pinto N, Hornero R. EEG Characterization of the Alzheimer's Disease Continuum by Means of Multiscale Entropies. ENTROPY 2019; 21:e21060544. [PMID: 33267258 PMCID: PMC7515033 DOI: 10.3390/e21060544] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 05/24/2019] [Accepted: 05/24/2019] [Indexed: 01/31/2023]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder with high prevalence, known for its highly disabling symptoms. The aim of this study was to characterize the alterations in the irregularity and the complexity of the brain activity along the AD continuum. Both irregularity and complexity can be studied applying entropy-based measures throughout multiple temporal scales. In this regard, multiscale sample entropy (MSE) and refined multiscale spectral entropy (rMSSE) were calculated from electroencephalographic (EEG) data. Five minutes of resting-state EEG activity were recorded from 51 healthy controls, 51 mild cognitive impaired (MCI) subjects, 51 mild AD patients (ADMIL), 50 moderate AD patients (ADMOD), and 50 severe AD patients (ADSEV). Our results show statistically significant differences (p-values < 0.05, FDR-corrected Kruskal-Wallis test) between the five groups at each temporal scale. Additionally, average slope values and areas under MSE and rMSSE curves revealed significant changes in complexity mainly for controls vs. MCI, MCI vs. ADMIL and ADMOD vs. ADSEV comparisons (p-values < 0.05, FDR-corrected Mann-Whitney U-test). These findings indicate that MSE and rMSSE reflect the neuronal disturbances associated with the development of dementia, and may contribute to the development of new tools to track the AD progression.
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Affiliation(s)
- Aarón Maturana-Candelas
- Biomedical Engineering Group, E.T.S.I. de Telecomunicación, Universidad de Valladolid, 47011 Valladolid, Spain
| | - Carlos Gómez
- Biomedical Engineering Group, E.T.S.I. de Telecomunicación, Universidad de Valladolid, 47011 Valladolid, Spain
- Correspondence: ; Tel.: +34-983-423-981
| | - Jesús Poza
- Biomedical Engineering Group, E.T.S.I. de Telecomunicación, Universidad de Valladolid, 47011 Valladolid, Spain
- Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, 47011 Valladolid, Spain
- Instituto de Neurociencias de Castilla y León (INCYL), Universidad de Salamanca, 37007 Salamanca, Spain
| | - Nadia Pinto
- Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal
- Instituto de Investigação e Inovação em Saúde (i3S), 4200-135 Porto, Portugal
- Center of Mathematics of the University of Porto (CMUP), 4169-007 Porto, Portugal
| | - Roberto Hornero
- Biomedical Engineering Group, E.T.S.I. de Telecomunicación, Universidad de Valladolid, 47011 Valladolid, Spain
- Instituto de Investigación en Matemáticas (IMUVA), Universidad de Valladolid, 47011 Valladolid, Spain
- Instituto de Neurociencias de Castilla y León (INCYL), Universidad de Salamanca, 37007 Salamanca, Spain
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López-Sanz D, Bruña R, de Frutos-Lucas J, Maestú F. Magnetoencephalography applied to the study of Alzheimer's disease. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:25-61. [PMID: 31481165 DOI: 10.1016/bs.pmbts.2019.04.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Magnetoencephalography (MEG) is a relatively modern neuroimaging technique able to study normal and pathological brain functioning with temporal resolution in the order of milliseconds and adequate spatial resolution. Although its clinical applications are still relatively limited, great advances have been made in recent years in the field of dementia and Alzheimer's disease (AD) in particular. In this chapter, we briefly describe the physiological phenomena underlying MEG brain signals and the different metrics that can be computed from these data in order to study the alterations disrupting brain activity not only in demented patients, but also in the preclinical and prodromal stages of the disease. Changes in non-linear brain dynamics, power spectral properties, functional connectivity and network topological changes observed in AD are narratively summarized in the context of the pathophysiology of the disease. Furthermore, the potential of MEG as a potential biomarker to identify AD pathology before dementia onset is discussed in the light of current knowledge and the relationship between potential MEG biomarkers and current established hallmarks of the disease is also reviewed. To this aim, findings from different approaches such as resting state or during the performance of different cognitive paradigms are discussed.Lastly, there is an increasing interest in current scientific literature in promoting interventions aimed at modifying certain lifestyles, such as nutrition or physical activity among others, thought to reduce or delay AD risk. We discuss the utility of MEG as a potential marker of the success of such interventions from the available literature.
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Affiliation(s)
- David López-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Biological and Health Psychology Department, Universidad Autonoma de Madrid, Madrid, Spain; School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain.
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16
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Monge-Alvarez J, Hoyos-Barcelo C, San-Jose-Revuelta LM, Casaseca-de-la-Higuera P. A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features. IEEE Trans Biomed Eng 2018; 66:2319-2330. [PMID: 30575527 DOI: 10.1109/tbme.2018.2888998] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Cough is a protective reflex conveying information on the state of the respiratory system. Cough assessment has been limited so far to subjective measurement tools or uncomfortable (i.e., non-wearable) cough monitors. This limits the potential of real-time cough monitoring to improve respiratory care. OBJECTIVE This paper presents a machine hearing system for audio-based robust cough segmentation that can be easily deployed in mobile scenarios. METHODS Cough detection is performed in two steps. First, a short-term spectral feature set is separately computed in five predefined frequency bands: [0, 0.5), [0.5, 1), [1, 1.5), [1.5, 2), and [2, 5.5125] kHz. Feature selection and combination are then applied to make the short-term feature set robust enough in different noisy scenarios. Second, high-level data representation is achieved by computing the mean and standard deviation of short-term descriptors in 300 ms long-term frames. Finally, cough detection is carried out using a support vector machine trained with data from different noisy scenarios. The system is evaluated using a patient signal database which emulates three real-life scenarios in terms of noise content. RESULTS The system achieves 92.71% sensitivity, 88.58% specificity, and 90.69% Area Under Receiver Operating Charcteristic (ROC) curve (AUC), outperforming state-of-the-art methods. CONCLUSION Our research outcome paves the way to create a device for cough monitoring in real-life situations. SIGNIFICANCE Our proposal is aligned with a more comfortable and less disruptive patient monitoring, with benefits for patients (allows self-monitoring of cough symptoms), practitioners (e.g., assessment of treatments or better clinical understanding of cough patterns), and national health systems (by reducing hospitalizations).
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Mandal PK, Banerjee A, Tripathi M, Sharma A. A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD). Front Comput Neurosci 2018; 12:60. [PMID: 30190674 PMCID: PMC6115612 DOI: 10.3389/fncom.2018.00060] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Accepted: 07/09/2018] [Indexed: 12/16/2022] Open
Abstract
Neural oscillations were established with their association with neurophysiological activities and the altered rhythmic patterns are believed to be linked directly to the progression of cognitive decline. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution. Single channel, connectivity as well as brain network analysis using MEG data in resting state and task-based experiments were analyzed from existing literature. Single channel analysis studies reported a less complex, more regular and predictable oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal and occipital regions. Investigations on both functional connectivity (FC) and effective (EC) connectivity analysis demonstrated a loss of connectivity in AD compared to healthy control (HC) subjects found in higher frequency bands. It has been reported from multiplex network of MEG study in AD in the affected regions of hippocampus, posterior default mode network (DMN) and occipital areas, however, conclusions cannot be drawn due to limited availability of clinical literature. Potential utilization of high spatial resolution in MEG likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in AD. This review is a comprehensive report to investigate diagnostic biomarkers for AD may be identified by from MEG data. It is also important to note that MEG data can also be utilized for the same pursuit in combination with other imaging modalities.
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Affiliation(s)
- Pravat K. Mandal
- Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, India
- Department of Neurodegeneration, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia
| | - Anwesha Banerjee
- Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, India
| | - Manjari Tripathi
- Department of Neurology, All Indian Institute of Medical Sciences, New Delhi, India
| | - Ankita Sharma
- Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, India
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Monge-Alvarez J, Hoyos-Barcelo C, Lesso P, Casaseca-de-la-Higuera P. Robust Detection of Audio-Cough Events Using Local Hu Moments. IEEE J Biomed Health Inform 2018; 23:184-196. [PMID: 29994432 DOI: 10.1109/jbhi.2018.2800741] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Telehealth has shown potential to improve access to healthcare cost-effectively in respiratory illness. However, it has failed to live up to expectation, in part because of poor objective measures of symptoms such as cough events, which could lead to early diagnosis or prevention. Considering the burden that these conditions constitute for national health systems, an effort is needed to foster telehealth potential by developing low-cost technology for efficient monitoring and analysis of cough events. This paper proposes the use of local Hu moments as a robust feature set for automatic cough detection in smartphone-acquired audio signals. The final system feeds a k-nearest-neighbor classifier with the extracted features. To properly evaluate the system in a diversity of noisy backgrounds, we contaminated real cough audio data with a variety of sounds including noise from both indoor and outdoor environments and noncough events (sneeze, laugh, speech, etc.). The created database allows flexible settings of signal-to-noise ratio levels between background sounds and events (cough and noncough). This evaluation was complemented using real patient data from an outpatient clinic. The system is able to detect cough events with high sensitivity (up to 88.51%) and specificity (up to 99.77%) in a variety of noisy environments, overcoming other state-of-the-art audio features. Our proposal paves the way for ubiquitous cough monitoring with minimal disruption in daily activities.
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19
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Engels MMA, van der Flier WM, Stam CJ, Hillebrand A, Scheltens P, van Straaten ECW. Alzheimer's disease: The state of the art in resting-state magnetoencephalography. Clin Neurophysiol 2017. [PMID: 28622527 DOI: 10.1016/j.clinph.2017.05.012] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Alzheimer's disease (AD) is accompanied by functional brain changes that can be detected in imaging studies, including electromagnetic activity recorded with magnetoencephalography (MEG). Here, we systematically review the studies that have examined resting-state MEG changes in AD and identify areas that lack scientific or clinical progress. Three levels of MEG analysis will be covered: (i) single-channel signal analysis, (ii) pairwise analyses over time series, which includes the study of interdependencies between two time series and (iii) global network analyses. We discuss the findings in the light of other functional modalities, such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Overall, single-channel MEG results show consistent changes in AD that are in line with EEG studies, but the full potential of the high spatial resolution of MEG and advanced functional connectivity and network analysis has yet to be fully exploited. Adding these features to the current knowledge will potentially aid in uncovering organizational patterns of brain function in AD and thereby aid the understanding of neuronal mechanisms leading to cognitive deficits.
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Affiliation(s)
- M M A Engels
- Alzheimer Centrum and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.
| | - W M van der Flier
- Alzheimer Centrum and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands; Department of Epidemiology and Biostatistics, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - C J Stam
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - A Hillebrand
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Ph Scheltens
- Alzheimer Centrum and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - E C W van Straaten
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center, Amsterdam, The Netherlands
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Hyper-resting brain entropy within chronic smokers and its moderation by Sex. Sci Rep 2016; 6:29435. [PMID: 27377552 PMCID: PMC4932513 DOI: 10.1038/srep29435] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Accepted: 06/17/2016] [Indexed: 01/29/2023] Open
Abstract
Cigarette smoking is a chronic relapsing brain disorder, and remains a premier cause of morbidity and mortality. Functional neuroimaging has been used to assess differences in the mean strength of brain activity in smokers’ brains, however less is known about the temporal dynamics within smokers’ brains. Temporal dynamics is a key feature of a dynamic system such as the brain, and may carry information critical to understanding the brain mechanisms underlying cigarette smoking. We measured the temporal dynamics of brain activity using brain entropy (BEN) mapping and compared BEN between chronic non-deprived smokers and non-smoking controls. Because of the known sex differences in neural and behavioral smoking characteristics, comparisons were also made between males and females. Associations between BEN and smoking related clinical measures were assessed in smokers. Our data showed globally higher BEN in chronic smokers compared to controls. The escalated BEN was associated with more years of smoking in the right limbic area and frontal region. Female nonsmokers showed higher BEN than male nonsmokers in prefrontal cortex, insula, and precuneus, but the BEN sex difference in smokers was less pronounced. These findings suggest that BEN mapping may provide a useful tool for probing brain mechanisms related to smoking.
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Poza J, Gómez C, García M, Bachiller A, Fernández A, Hornero R. Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using Jensen's divergence. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2014:1501-4. [PMID: 25570254 DOI: 10.1109/embc.2014.6943886] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The aim of this study was to analyze the changes that mild cognitive impairment (MCI) and Alzheimer's disease (AD) elicit in brain dynamics. For this task, the spontaneous magnetoencephalographic (MEG) activity from 36 AD patients, 18 MCI subjects and 24 healthy controls was analyzed. A disequilibrium measure, Jensen's divergence, was used to estimate the irregularity of neural dynamics. Results revealed that AD patients displayed significant changes (p<;0.05) in the patterns of irregularity in comparison with MCI subjects and healthy controls. Slight differences between MCI subjects and elderly controls were also found. Our results suggest that AD progression is accompanied by region-specific patterns of abnormalities in the neural activity.
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Zhou F, Zhuang Y, Gong H, Zhan J, Grossman M, Wang Z. Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis. PLoS One 2016; 11:e0146080. [PMID: 26727514 PMCID: PMC4699711 DOI: 10.1371/journal.pone.0146080] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Accepted: 12/11/2015] [Indexed: 01/01/2023] Open
Abstract
Brain entropy (BEN) mapping provides a novel approach to characterize brain temporal dynamics, a key feature of human brain. Using resting state functional magnetic resonance imaging (rsfMRI), reliable and spatially distributed BEN patterns have been identified in normal brain, suggesting a potential use in clinical populations since temporal brain dynamics and entropy may be altered in disease conditions. The purpose of this study was to characterize BEN in multiple sclerosis (MS), a neurodegenerative disease that affects millions of people. Since currently there is no cure for MS, developing treatment or medication that can slow down its progression represents a high research priority, for which validating a brain marker sensitive to disease and the related functional impairments is essential. Because MS can start long time before any measurable symptoms and structural deficits, assessing the dynamic brain activity and correspondingly BEN may provide a critical way to study MS and its progression. Because BEN is new to MS, we aimed to assess BEN alterations in the relapsing-remitting MS (RRMS) patients using a patient versus control design, to examine the correlation of BEN to clinical measurements, and to check the correlation of BEN to structural brain measures which have been more often used in MS studies. As compared to controls, RRMS patients showed increased BEN in motor areas, executive control area, spatial coordinating area, and memory system. Increased BEN was related to greater disease severity as measured by the expanded disability status scale (EDSS) and greater tissue damage as indicated by the mean diffusivity. Patients also showed decreased BEN in other places, which was associated with less disability or fatigue, indicating a disease-related BEN re-distribution. Our results suggest BEN as a novel and useful tool for characterizing RRMS.
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Affiliation(s)
- Fuqing Zhou
- Department of Radiology, the First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi Province, China
- Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi Province, China
- * E-mail: (FZ); (ZW)
| | - Ying Zhuang
- Department of Oncology, the Second Hospital of Nanchang, Nanchang, Jiangxi Province, China
| | - Honghan Gong
- Department of Radiology, the First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi Province, China
- Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi Province, China
| | - Jie Zhan
- Department of Radiology, the First Affiliated Hospital, Nanchang University, Nanchang, Jiangxi Province, China
- Jiangxi Province Medical Imaging Research Institute, Nanchang, Jiangxi Province, China
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Ze Wang
- Department of Psychology, Hangzhou Normal University, Hangzhou, Zhejiang Province, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, China
- * E-mail: (FZ); (ZW)
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Decreased entropy modulation of EEG response to novelty and relevance in schizophrenia during a P300 task. Eur Arch Psychiatry Clin Neurosci 2015; 265:525-35. [PMID: 25164969 DOI: 10.1007/s00406-014-0525-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2014] [Accepted: 08/08/2014] [Indexed: 10/24/2022]
Abstract
The analysis of the interaction between novelty and relevance may be of interest to test the aberrant salience hypothesis of schizophrenia (SCH). In comparison with other neuroimaging techniques, such as functional magnetic resonance imaging, electroencephalography (EEG) provides high temporal resolution. Therefore, EEG is useful to analyze transient dynamics in neural activity, even in the range of milliseconds. In this study, EEG activity from 31 patients with SCH and 38 controls was analyzed using Shannon spectral entropy (SE) and median frequency (MF). The aim of the study was to quantify differences between distractor (i.e., novelty) and target (i.e., novelty and relevance) tones in an auditory oddball paradigm. Healthy controls displayed a larger SE decrease in response to target stimulus than in response to distractor tones. SE decrease was accompanied by a significant and widespread reduction of MF (i.e., a significant slowing of EEG activity). In comparison with controls, patients showed a significant reduction of changes in SE in response to both target and distractor tones. These differences were also observed in patients that only received a minimal treatment prior to EEG recording. Furthermore, significant changes in SE were inversely correlated to positive and total symptoms severity for SCH patients. Our findings support the notion that SCH is associated with a reduced response to both novelty and relevance during an auditory P300 task.
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Azami H, Smith K, Fernandez A, Escudero J. Evaluation of resting-state magnetoencephalogram complexity in Alzheimer's disease with multivariate multiscale permutation and sample entropies. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2015:7422-7425. [PMID: 26738007 DOI: 10.1109/embc.2015.7320107] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Alzheimer's disease (AD) is one of the fastest growing neurological diseases in the world. We evaluate multivariate multiscale sample entropy (mvMSE) and multivariate multiscale permutation entropy (mvMPE) approaches to distinguish resting-state magnetoencephalogram (MEG) signals of 36 AD patients from those of 26 normal controls. We also discuss about choosing the appropriate embedding dimension value as an effective parameter for mvMPE and MPE for the first time. The results illustrate that both the mvMPE and mvMSE can be useful in the diagnosis of AD, although with different running times and abilities. In addition, our findings show that the MEG complexity analysis performed on deeper time scales by mvMPE and mvMSE may be a useful tool to characterize AD. In most scale factors, the average of the mvMPE and mvMSE values of AD patients are lower than those of controls.
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Innovative diagnostic tools for early detection of Alzheimer's disease. Alzheimers Dement 2014; 11:561-78. [PMID: 25443858 DOI: 10.1016/j.jalz.2014.06.004] [Citation(s) in RCA: 157] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2014] [Revised: 04/21/2014] [Accepted: 06/16/2014] [Indexed: 02/06/2023]
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Decreased spectral entropy modulation in patients with schizophrenia during a P300 task. Eur Arch Psychiatry Clin Neurosci 2014; 264:533-43. [PMID: 24496581 DOI: 10.1007/s00406-014-0488-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2013] [Accepted: 01/24/2014] [Indexed: 12/18/2022]
Abstract
Spectral entropy (SE), also known as Shannon entropy, is a useful parameter for quantifying the global regularity of the electroencephalographic (EEG) signal. Hence, it is of interest in the assessment of the electrophysiological correlates of cognitive processing in schizophrenia. However, to date, SE has been barely used in studies comparing resting EEG recordings between patients and controls. In this work, we compared SE between resting baseline [-250 0] ms and active task [150 550] ms windows of a P300 task in 31 patients with schizophrenia and 38 controls. Moreover, we also calculated the median frequency (MF) and relative power in each frequency band for these windows to assess the correlates of the possible SE differences. Controls showed a significant (p < 0.0029) SE decrease (i.e., meaning higher signal regularity) from baseline to the active task window at parietal and central electrode sites. This SE decrease from baseline to active conditions was significantly lower in patients. In controls, this SE decrease was accompanied by a statistically significant decrease in MF (i.e., a significant slowing of the EEG activity), not observed in patients. In this latter group, the difference in SE between resting baseline and active task windows was inversely correlated to positive and total symptoms scores, as measured with the positive and negative symptoms scale. Our data support the relevance of SE in the study of cerebral processing in schizophrenia.
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Abstract
Entropy is an important trait for life as well as the human brain. Characterizing brain entropy (BEN) may provide an informative tool to assess brain states and brain functions. Yet little is known about the distribution and regional organization of BEN in normal brain. The purpose of this study was to examine the whole brain entropy patterns using a large cohort of normal subjects. A series of experiments were first performed to validate an approximate entropy measure regarding its sensitivity, specificity, and reliability using synthetic data and fMRI data. Resting state fMRI data from a large cohort of normal subjects (n = 1049) from multi-sites were then used to derive a 3-dimensional BEN map, showing a sharp low-high entropy contrast between the neocortex and the rest of brain. The spatial heterogeneity of resting BEN was further studied using a data-driven clustering method, and the entire brain was found to be organized into 7 hierarchical regional BEN networks that are consistent with known structural and functional brain parcellations. These findings suggest BEN mapping as a physiologically and functionally meaningful measure for studying brain functions.
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Poza J, Gómez C, García M, Corralejo R, Fernández A, Hornero R. Analysis of neural dynamics in mild cognitive impairment and Alzheimer's disease using wavelet turbulence. J Neural Eng 2014; 11:026010. [PMID: 24608272 DOI: 10.1088/1741-2560/11/2/026010] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Current diagnostic guidelines encourage further research for the development of novel Alzheimer's disease (AD) biomarkers, especially in its prodromal form (i.e. mild cognitive impairment, MCI). Magnetoencephalography (MEG) can provide essential information about AD brain dynamics; however, only a few studies have addressed the characterization of MEG in incipient AD. APPROACH We analyzed MEG rhythms from 36 AD patients, 18 MCI subjects and 27 controls, introducing a new wavelet-based parameter to quantify their dynamical properties: the wavelet turbulence. MAIN RESULTS Our results suggest that AD progression elicits statistically significant regional-dependent patterns of abnormalities in the neural activity (p < 0.05), including a progressive loss of irregularity, variability, symmetry and Gaussianity. Furthermore, the highest accuracies to discriminate AD and MCI subjects from controls were 79.4% and 68.9%, whereas, in the three-class setting, the accuracy reached 67.9%. SIGNIFICANCE Our findings provide an original description of several dynamical properties of neural activity in early AD and offer preliminary evidence that the proposed methodology is a promising tool for assessing brain changes at different stages of dementia.
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Affiliation(s)
- Jesús Poza
- Biomedical Engineering Group, Department TSCIT, ETS. Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain. IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain. INCYL, Instituto de Neurociencias de Castilla y León, Salamanca, Spain
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García M, Poza J, Santamarta D, Abásolo D, Barrio P, Hornero R. Spectral analysis of intracranial pressure signals recorded during infusion studies in patients with hydrocephalus. Med Eng Phys 2013; 35:1490-8. [PMID: 23664413 DOI: 10.1016/j.medengphy.2013.04.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Revised: 02/26/2013] [Accepted: 04/11/2013] [Indexed: 10/26/2022]
Abstract
Hydrocephalus includes a number of disorders characterised by clinical symptoms, enlarged ventricles (observable using neuroimaging techniques) and altered cerebrospinal fluid (CSF) dynamics. Infusion tests are one of the available procedures to study CSF circulation in patients with clinical and radiological features of hydrocephalus. In them, intracranial pressure (ICP) is deliberately raised and CSF circulation disorders evaluated through measurements of the resulting ICP. In this study, we analysed seventy-seven ICP signals recorded during infusion tests using four spectral-based parameters: median frequency (MF) and relative power (RP) in three frequency bands. These measures provide a novel perspective for the analysis of ICP signals in the frequency domain. Each signal was divided into four artefact-free epochs (corresponding to the basal, early infusion, plateau and recovery phases of the infusion study). The four spectral parameters were calculated for each epoch. We analysed differences between epochs of the infusion test and correlations between these epochs and patient data. Statistically significant differences (p < 1.7 × 10(-3), Bonferroni-corrected Wilcoxon signed-rank tests) were found between epochs of the infusion test using MF and RP. Furthermore, some spectral parameters (MF in the basal phase, RP for the first frequency band and in the early infusion phase, RP for the second frequency band and in all phases of the infusion study and RP in the third frequency band and in the basal phase) revealed significant correlations (p < 0.01) between epochs of the infusion test and signal amplitude in the basal and plateau phases. Our results suggest that spectral analysis of ICP signals could be useful for understanding CSF dynamics in hydrocephalus.
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Affiliation(s)
- María García
- Biomedical Engineering Group, Department T.S.C.I.T., E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain.
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Gómez C, Martínez-Zarzuela M, Poza J, Díaz-Pernas FJ, Fernández A, Hornero R. Synchrony analysis of spontaneous MEG activity in Alzheimer's disease patients. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2013; 2012:6188-91. [PMID: 23367342 DOI: 10.1109/embc.2012.6347407] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The aim of this study was to analyze the magnetoencephalography (MEG) background activity in Alzheimer's disease (AD) patients using cross-approximate entropy (Cross-ApEn). Cross-ApEn is a nonlinear measure of asynchrony between time series. Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 12 AD patients and 12 age-matched control subjects. We found significantly higher synchrony between MEG signals from AD patients compared with control subjects. Additionally, we evaluated the ability of Cross-ApEn to discriminate these two groups using receiver operating characteristic (ROC) curves with a leave-one-out cross-validation procedure. We obtained an accuracy of 70.83% (66.67% sensitivity, 75% specificity) and a value of area under the ROC curve of 0.83. These results provide evidence of disconnection problems in AD. Our findings show the usefulness of Cross-ApEn to detect the brain dysfunction in AD.
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Affiliation(s)
- Carlos Gómez
- Department of Signal Theory and Communications, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Campus Miguel Delibes, 47011 – Valladolid, Spain.
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Poza J, Gómez C, Bachiller A, Hornero R. Spectral and Non-Linear Analyses of Spontaneous Magnetoencephalographic Activity in Alzheimer's Disease. JOURNAL OF HEALTHCARE ENGINEERING 2012. [DOI: 10.1260/2040-2295.3.2.299] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Bruña R, Poza J, Gómez C, García M, Fernández A, Hornero R. Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures. J Neural Eng 2012; 9:036007. [PMID: 22571870 DOI: 10.1088/1741-2560/9/3/036007] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz-Mancini-Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.
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Affiliation(s)
- Ricardo Bruña
- Biomedical Engineering Group, Departmento T.S.C.I.T., E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain
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Escudero J, Sanei S, Jarchi D, Abásolo D, Hornero R. Regional coherence evaluation in mild cognitive impairment and Alzheimer's disease based on adaptively extracted magnetoencephalogram rhythms. Physiol Meas 2011; 32:1163-80. [PMID: 21709337 DOI: 10.1088/0967-3334/32/8/011] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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34
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Gomez C, Abasolo D, Poza J, Fernandez A, Hornero R. MEG analysis in Alzheimer's disease computing approximate entropy for different frequency bands. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2011; 2010:2379-82. [PMID: 21096583 DOI: 10.1109/iembs.2010.5627236] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The goal of this study was to analyze the magnetoencephalogram (MEG) background activity in patients with Alzheimer's disease (AD) using a regularity measure: approximate entropy (ApEn). This measure was computed for a broad band (0.5-40 Hz) as well as typical frequency bands (delta, theta, alpha, beta and gamma). Five minutes of recording were acquired with a 148-channel whole-head magnetometer in 15 patients with probable AD and 15 elderly control subjects. Our results showed that AD patients' MEGs were more regular than controls' recordings at all frequency bands, with the exception of beta. Additionally, there were statistically significant differences (p 〈 0.01, Student's t-test) at the broad and delta bands. Using receiver operating characteristic curves, the highest accuracy (83.33%) was reached at delta band. These results suggest the usefulness of ApEn to gain a better understanding of dynamical processes underlying the MEG recording.
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Affiliation(s)
- Carlos Gomez
- Biomedical Engineering Group at Department of Signal Theory and Communications, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Campus Miguel Delibes, 47011, Spain.
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Bruña R, Poza J, Gómez C, Fernández A, Hornero R. Analysis of spontaneous MEG activity in mild cognitive impairment using spectral entropies and disequilibrium measures. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2010:6296-9. [PMID: 21097360 DOI: 10.1109/iembs.2010.5628085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The aim of this study was to explore the ability of several spectral entropies and disequilibrium measures to discriminate between spontaneous magnetoencephalographic (MEG) oscillations from 18 mild cognitive impairment (MCI) patients and 24 controls. The Shannon spectral entropy (SSE), Tsallis spectral entropy (TSE), and Rényi spectral entropy (RSE) were calculated from the normalized power spectral density to evaluate the irregularity patterns. In addition, the Euclidean (ED) and Wootters (WD) distances were computed as disequilibrium measures. Results revealed statistically significant lower SSE and TSE(2) values for MCI patients than for controls (p < 0.05) in the right lateral region of the brain. ED also obtained statistically significant lower values for MCI patients than for controls using the (p < 0.05) in the right lateral region of the brain. These findings suggest that MCI is associated with a significant decrease in irregularity of MEG activity. In addition, the highest accuracy of 64.3% was achieved by the SSE. We conclude that measures from information theory can be useful to both characterize abnormal brain dynamics and help in MCI detection.
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Affiliation(s)
- Ricardo Bruña
- Biomedical Engineering Group (GIB), Dpt. TSCIT, University of Valladolid, Camino del Cementerio s/n, 47011, Spain
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Gómez C, Hornero R. Entropy and Complexity Analyses in Alzheimer's Disease: An MEG Study. Open Biomed Eng J 2010; 4:223-35. [PMID: 21625647 PMCID: PMC3044892 DOI: 10.2174/1874120701004010223] [Citation(s) in RCA: 54] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2010] [Revised: 07/27/2010] [Accepted: 07/29/2010] [Indexed: 11/22/2022] Open
Abstract
Alzheimer’s disease (AD) is one of the most frequent disorders among elderly population and it is considered the main cause of dementia in western countries. This irreversible brain disorder is characterized by neural loss and the appearance of neurofibrillary tangles and senile plaques. The aim of the present study was the analysis of the magnetoencephalogram (MEG) background activity from AD patients and elderly control subjects. MEG recordings from 36 AD patients and 26 controls were analyzed by means of six entropy and complexity measures: Shannon spectral entropy (SSE), approximate entropy (ApEn), sample entropy (SampEn), Higuchi’s fractal dimension (HFD), Maragos and Sun’s fractal dimension (MSFD), and Lempel-Ziv complexity (LZC). SSE is an irregularity estimator in terms of the flatness of the spectrum, whereas ApEn and SampEn are embbeding entropies that quantify the signal regularity. The complexity measures HFD and MSFD were applied to MEG signals to estimate their fractal dimension. Finally, LZC measures the number of different substrings and the rate of their recurrence along the original time series. Our results show that MEG recordings are less complex and more regular in AD patients than in control subjects. Significant differences between both groups were found in several brain regions using all these methods, with the exception of MSFD (p-value < 0.05, Welch’s t-test with Bonferroni’s correction). Using receiver operating characteristic curves with a leave-one-out cross-validation procedure, the highest accuracy was achieved with SSE: 77.42%. We conclude that entropy and complexity analyses from MEG background activity could be useful to help in AD diagnosis.
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Affiliation(s)
- Carlos Gómez
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, University of Valladolid, Spain
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Alonso JF, Poza J, Mañanas MA, Romero S, Fernández A, Hornero R. MEG connectivity analysis in patients with Alzheimer's disease using cross mutual information and spectral coherence. Ann Biomed Eng 2010; 39:524-36. [PMID: 20824340 DOI: 10.1007/s10439-010-0155-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2010] [Accepted: 08/24/2010] [Indexed: 11/24/2022]
Abstract
Alzheimer's disease (AD) is an irreversible brain disorder which represents the most common form of dementia in western countries. An early and accurate diagnosis of AD would enable to develop new strategies for managing the disease; however, nowadays there is no single test that can accurately predict the development of AD. In this sense, only a few studies have focused on the magnetoencephalographic (MEG) AD connectivity patterns. This study compares brain connectivity in terms of linear and nonlinear couplings by means of spectral coherence and cross mutual information function (CMIF), respectively. The variables defined from these functions provide statistically significant differences (p < 0.05) between AD patients and control subjects, especially the variables obtained from CMIF. The results suggest that AD is characterized by both decreases and increases of functional couplings in different frequency bands as well as by an increase in regularity, that is, more evident statistical deterministic relationships in AD patients' MEG connectivity. The significant differences obtained indicate that AD could disturb brain interactions causing abnormal brain connectivity and operation. Furthermore, the combination of coherence and CMIF features to perform a diagnostic test based on logistic regression improved the tests based on individual variables for its robustness.
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Affiliation(s)
- Joan Francesc Alonso
- Department of Automatic Control (ESAII), Biomedical Engineering Research Centre (CREB), Universitat Politècnica de Catalunya (UPC), Carrer Pau Gargallo 5, 08028, Barcelona, Spain.
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Stam CJ. Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders. J Neurol Sci 2009; 289:128-34. [PMID: 19729174 DOI: 10.1016/j.jns.2009.08.028] [Citation(s) in RCA: 170] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The pathophysiological mechanisms underlying clinical symptoms in neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD) are incompletely understood. Magnetoencephalography (MEG) is a relatively new functional neuroimaging technique, which allows the simultaneous recording of the brain's magnetic activity from large arrays of sensors covering the whole head. MEG studies in PD and AD have identified characteristic patterns of abnormal oscillatory activity in different frequency bands. Furthermore, MEG studies aimed at the characterization of distributed functional networks have demonstrated distinct patterns of abnormal connectivity in demented and non-demented PD, as well as in AD. In PD abnormal oscillatory activity and disturbed connectivity may respond differently to dopaminergic treatment. Further studies in this field could benefit from new technological developments such as ultra low field MRI and from the application of a well-defined theoretical framework such as graph theory to the study of disturbed brain networks.
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Affiliation(s)
- C J Stam
- Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, The Netherlands.
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Poza J, Hornero R, Escudero J, Fernandez A, Gomez C. Analysis of spontaneous MEG activity in Alzheimer's disease using time-frequency parameters. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2008; 2008:5712-5715. [PMID: 19164014 DOI: 10.1109/iembs.2008.4650511] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
The aim of this study was to explore the ability of several time-frequency parameters to discriminate between spontaneous magnetoencephalographic (MEG) oscillations from 20 Alzheimer's disease (AD) patients and 21 controls. The spectral crest factor (SCF) and the spectral turbulence (ST) were calculated from the time-frequency distribution of the normalized power spectral density averaged over all MEG sensors. Results revealed statistically significant higher SCF and ST mean values for AD patients than controls (p 0.05). This fact suggests a significant decrease in irregularity of AD patients' MEG activity. The standard deviation of SCF also provided significant differences (p 0.05). This result indicates that AD patients showed a significantly higher variability than controls. The highest accuracy of 85.4% (90.5% sensitivity, 80.0% specificity) was achieved using simultaneously the mean value and the standard deviation of the SCF. We conclude that the variability of the spectral parameters can yield complementary information to the mean values, useful to help in AD detection.
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Affiliation(s)
- Jesus Poza
- Biomedical Engineering Group (GIB), Dpt. TSCIT, University of Valladolid, Camino del Cementerio s/n, 47011, Spain.
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