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Zhang J, Yang Y, Liu T, Shi Z, Pei G, Wang L, Wu J, Funahashi S, Suo D, Wang C, Yan T. Functional connectivity in people at clinical and familial high risk for schizophrenia. Psychiatry Res 2023; 328:115464. [PMID: 37690192 DOI: 10.1016/j.psychres.2023.115464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 09/03/2023] [Accepted: 09/04/2023] [Indexed: 09/12/2023]
Abstract
Patients diagnosed with schizophrenia (SZ) exhibit compromised functional connectivity within extensive brain networks. However, the precise development of this impairment during disease progression in the clinical high-risk (CHR) population and their relatives remains unclear. Our study leveraged data from 128 resting electroencephalography (EEG) channels acquired from 30 SZ patients, 21 CHR individuals, 17 unaffected healthy relatives (RSs; those at heightened SZ risk due to family history), and 31 healthy controls (HCs). These data were harnessed to establish functional connectivity patterns. By calculating the geometric distance between EEG sequences, we unveiled local and global nonlinear relationships within the entire brain. The process of dimensionality reduction led to low-dimensional representations, providing insights into high-dimensional EEG data. Our findings indicated that CHR participants exhibited aberrant functional connectivity across hemispheres, whereas RS individuals showcased anomalies primarily concentrated within hemispheres. In the realm of low-dimensional analysis, RS participants' third-dimensional occipital lobe values lay between those of the CHR individuals and HCs, significantly correlating with scale scores. This low-dimensional approach facilitated the visualization of brain states, potentially offering enhanced comprehension of brain structure, function, and early-stage functional impairment, such as occipital visual deficits, in RS individuals before cognitive decline onset.
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Affiliation(s)
- Jian Zhang
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Yaxin Yang
- School of Life Science, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Tiantian Liu
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Zhongyan Shi
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Guangying Pei
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Li Wang
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Shintaro Funahashi
- Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Dingjie Suo
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China
| | - Changming Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Tianyi Yan
- School of Medical Technology, Beijing Institute of Technology, 5 South Zhongguancun St, Haidian District, Beijing 100081, China.
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Singh P, Tripathi A, Kumar L, Gandhi TK. Brain Connectivity Features-based Age Group Classification using Temporal Asynchrony Audio-Visual Integration Task. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38082671 DOI: 10.1109/embc40787.2023.10341177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The process of integration of inputs from several sensory modalities in the human brain is referred to as multisensory integration. Age-related cognitive decline leads to a loss in the ability of the brain to conceive multisensory inputs. There has been considerable work done in the study of such cognitive changes for the old age groups. However, in the case of middle age groups, such analysis is limited. Motivated by this, in the current work, EEG-based functional connectivity during audiovisual temporal asynchrony integration task for middle-aged groups is explored. Investigation has been carried out during different tasks such as: unimodal audio, unimodal visual, and variations of audio-visual stimulus. A correlation-based functional connectivity analysis is done, and the changes among different age groups including: young (18-25 years), transition from young to medium age (25-33 years), and medium (33-41 years), are observed. Furthermore, features extracted from the connectivity graphs have been used to classify among the different age groups. Classification accuracies of 89.4% and 88.4% are obtained for the Audio and Audio-50-Visual stimuli cases with a Random Forest based classifier, thereby validating the efficacy of the proposed method.
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3
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Ren Y, Li Y, Xu Z, Luo R, Qian R, Duan J, Yang J, Yang W. Aging effect of cross-modal interactions during audiovisual detection and discrimination by behavior and ERPs. Front Aging Neurosci 2023; 15:1151652. [PMID: 37181627 PMCID: PMC10169674 DOI: 10.3389/fnagi.2023.1151652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/06/2023] [Indexed: 05/16/2023] Open
Abstract
Introduction Numerous studies have shown that aging greatly affects audiovisual integration; however, it is still unclear when the aging effect occurs, and its neural mechanism has yet to be fully elucidated. Methods We assessed the audiovisual integration (AVI) of older (n = 40) and younger (n = 45) adults using simple meaningless stimulus detection and discrimination tasks. The results showed that the response was significantly faster and more accurate for younger adults than for older adults in both the detection and discrimination tasks. The AVI was comparable for older and younger adults during stimulus detection (9.37% vs. 9.43%); however, the AVI was lower for older than for younger adults during stimulus discrimination (9.48% vs. 13.08%) behaviorally. The electroencephalography (EEG) analysis showed that comparable AVI amplitude was found at 220-240 ms for both groups during stimulus detection and discrimination, but there was no significant difference between brain regions for older adults but a higher AVI amplitude in the right posterior for younger adults. Additionally, a significant AVI was found for younger adults in 290-310 ms but was absent for older adults during stimulus discrimination. Furthermore, significant AVI was found in the left anterior and right anterior at 290-310 ms for older adults but in the central, right posterior and left posterior for younger adults. Discussion These results suggested that the aging effect of AVI occurred in multiple stages, but the attenuated AVI mainly occurred in the later discriminating stage attributed to attention deficit.
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Affiliation(s)
- Yanna Ren
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Yan Li
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Zhihan Xu
- Department of Foreign Language, Ningbo University of Technology, Ningbo, China
| | - Rui Luo
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Runqi Qian
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Jieping Duan
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Jiajia Yang
- Applied Brain Science Lab Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
| | - Weiping Yang
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
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4
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Ren Y, Li H, Li Y, Xu Z. Sustained visual attentional load modulates audiovisual integration in older and younger adults. Iperception 2023; 14:20416695231157348. [PMID: 36845028 PMCID: PMC9950617 DOI: 10.1177/20416695231157348] [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: 08/25/2022] [Accepted: 01/30/2023] [Indexed: 02/25/2023] Open
Abstract
Previous studies have shown that attention influences audiovisual integration (AVI) in multiple stages, but it remains unclear how AVI interacts with attentional load. In addition, while aging has been associated with sensory-functional decline, little is known about how older individuals integrate cross-modal information under attentional load. To investigate these issues twenty older adults and 20 younger adults were recruited to conduct a dual task including a multiple object tracking (MOT) task, which manipulated sustained visual attentional load, and an audiovisual discrimination task, which assesses AVI. The results showed that response times were shorter and hit rate was higher for audiovisual stimuli than for auditory or visual stimuli alone and in younger adults than in older adults. The race model analysis showed that AVI was higher under the load_3 condition (monitoring two targets of the MOT task) than under any other load condition (no-load [NL], one or three targets monitoring). This effect was found regardless of age. However, AVI was lower in older adults than younger adults under NL condition. Moreover, the peak latency was longer, and the time window of AVI was delayed in older adults compared to younger adults under all conditions. These results suggest that slight visual sustained attentional load increased AVI but that heavy visual sustained attentional load decreased AVI, which supports the claim that attention resource was limited, and we further proposed that AVI was positively modulated by attentional resource. Finally, there were substantial impacts of aging on AVI; AVI was delayed in older adults.
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Affiliation(s)
- Yanna Ren
- Weiping Yang, Department of Psychology,
Faculty of Education, Hubei University, Wuhan, 430062, China.
| | | | - Yan Li
- Department of Psychology, College of
Humanities and Management, Guizhou University of Traditional
Chinese Medicine, Guiyang, China
| | - Zhihan Xu
- Department of Foreign Language, Ningbo University of
Technology, Ningbo, China
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5
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Alves CL, Cury RG, Roster K, Pineda AM, Rodrigues FA, Thielemann C, Ciba M. Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments. PLoS One 2022; 17:e0277257. [PMID: 36525422 PMCID: PMC9757568 DOI: 10.1371/journal.pone.0277257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/23/2022] [Indexed: 12/23/2022] Open
Abstract
Ayahuasca is a blend of Amazonian plants that has been used for traditional medicine by the inhabitants of this region for hundreds of years. Furthermore, this plant has been demonstrated to be a viable therapy for a variety of neurological and mental diseases. EEG experiments have found specific brain regions that changed significantly due to ayahuasca. Here, we used an EEG dataset to investigate the ability to automatically detect changes in brain activity using machine learning and complex networks. Machine learning was applied at three different levels of data abstraction: (A) the raw EEG time series, (B) the correlation of the EEG time series, and (C) the complex network measures calculated from (B). Further, at the abstraction level of (C), we developed new measures of complex networks relating to community detection. As a result, the machine learning method was able to automatically detect changes in brain activity, with case (B) showing the highest accuracy (92%), followed by (A) (88%) and (C) (83%), indicating that connectivity changes between brain regions are more important for the detection of ayahuasca. The most activated areas were the frontal and temporal lobe, which is consistent with the literature. F3 and PO4 were the most important brain connections, a significant new discovery for psychedelic literature. This connection may point to a cognitive process akin to face recognition in individuals during ayahuasca-mediated visual hallucinations. Furthermore, closeness centrality and assortativity were the most important complex network measures. These two measures are also associated with diseases such as Alzheimer's disease, indicating a possible therapeutic mechanism. Moreover, the new measures were crucial to the predictive model and suggested larger brain communities associated with the use of ayahuasca. This suggests that the dissemination of information in functional brain networks is slower when this drug is present. Overall, our methodology was able to automatically detect changes in brain activity during ayahuasca consumption and interpret how these psychedelics alter brain networks, as well as provide insights into their mechanisms of action.
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Affiliation(s)
- Caroline L. Alves
- BioMEMS Lab, Aschaffenburg University of Applied Sciences (UAS), Aschaffenburg, Germany
- Institute of Mathematical and Computer Sciences, University of São Paulo (USP), São Paulo, Brazil
- * E-mail:
| | - Rubens Gisbert Cury
- Department of Neurology, Movement Disorders Center, University of São Paulo (USP), São Paulo, Brazil
| | - Kirstin Roster
- Institute of Mathematical and Computer Sciences, University of São Paulo (USP), São Paulo, Brazil
| | - Aruane M. Pineda
- Institute of Mathematical and Computer Sciences, University of São Paulo (USP), São Paulo, Brazil
| | - Francisco A. Rodrigues
- Institute of Mathematical and Computer Sciences, University of São Paulo (USP), São Paulo, Brazil
| | - Christiane Thielemann
- BioMEMS Lab, Aschaffenburg University of Applied Sciences (UAS), Aschaffenburg, Germany
| | - Manuel Ciba
- BioMEMS Lab, Aschaffenburg University of Applied Sciences (UAS), Aschaffenburg, Germany
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6
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Conti M, Stefani A, Bovenzi R, Cerroni R, Garasto E, Placidi F, Liguori C, Schirinzi T, Mercuri NB, Pierantozzi M. STN-DBS Induces Acute Changes in β-Band Cortical Functional Connectivity in Patients with Parkinson's Disease. Brain Sci 2022; 12:brainsci12121606. [PMID: 36552066 PMCID: PMC9775160 DOI: 10.3390/brainsci12121606] [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: 11/01/2022] [Revised: 11/18/2022] [Accepted: 11/22/2022] [Indexed: 11/25/2022] Open
Abstract
Subthalamic nucleus deep-brain stimulation (STN-DBS), in addition to a rapid improvement of Parkinson's disease (PD) motor symptoms, can exert fast, local, neuromodulator activity, reducing β-synchronous oscillations between STN and the motor cortex with possible antikinetic features. However, STN-DBS modulation of β-band synchronization in extramotor cortical areas has been scarcely explored. For this aim, we investigated DBS-induced short-term effects on EEG-based cortical functional connectivity (FC) in β bands in six PD patients who underwent STN-DBS within the past year. A 10 min, 64-channel EEG recording was performed twice: in DBS-OFF and 60 min after DBS activation. Seven age-matched controls performed EEG recordings as the control group. A source-reconstruction method was used to identify brain-region activity. The FC was calculated using a weighted phase-lag index in β bands. Group comparisons were made using the Wilcoxon test. The PD patients showed a widespread cortical hyperconnectivity in β bands in both DBS-OFF and -ON states compared to the controls. Moreover, switching on STN-DBS determined an acute reduction in β FC, primarily involving corticocortical links of frontal, sensorimotor and limbic lobes. We hypothesize that an increase in β-band connectivity in PD is a widespread cortical phenomenon and that STN-DBS could quickly reduce it in the cortical regions primarily involved in basal ganglia-cortical circuits.
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Affiliation(s)
- Matteo Conti
- Parkinson Centre, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Alessandro Stefani
- Parkinson Centre, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
- Correspondence:
| | - Roberta Bovenzi
- Parkinson Centre, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Rocco Cerroni
- Parkinson Centre, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Elena Garasto
- Parkinson Centre, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Fabio Placidi
- Neurology Unit, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Claudio Liguori
- Neurology Unit, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Tommaso Schirinzi
- Parkinson Centre, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Nicola B. Mercuri
- Neurology Unit, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
| | - Mariangela Pierantozzi
- Parkinson Centre, Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
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7
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Yang W, Li S, Guo A, Li Z, Yang X, Ren Y, Yang J, Wu J, Zhang Z. Auditory attentional load modulates the temporal dynamics of audiovisual integration in older adults: An ERPs study. Front Aging Neurosci 2022; 14:1007954. [PMID: 36325188 PMCID: PMC9618958 DOI: 10.3389/fnagi.2022.1007954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 09/23/2022] [Indexed: 12/02/2022] Open
Abstract
As older adults experience degenerations in perceptual ability, it is important to gain perception from audiovisual integration. Due to attending to one or more auditory stimuli, performing other tasks is a common challenge for older adults in everyday life. Therefore, it is necessary to probe the effects of auditory attentional load on audiovisual integration in older adults. The present study used event-related potentials (ERPs) and a dual-task paradigm [Go / No-go task + rapid serial auditory presentation (RSAP) task] to investigate the temporal dynamics of audiovisual integration. Behavioral results showed that both older and younger adults responded faster and with higher accuracy to audiovisual stimuli than to either visual or auditory stimuli alone. ERPs revealed weaker audiovisual integration under the no-attentional auditory load condition at the earlier processing stages and, conversely, stronger integration in the late stages. Moreover, audiovisual integration was greater in older adults than in younger adults at the following time intervals: 60–90, 140–210, and 430–530 ms. Notably, only under the low load condition in the time interval of 140–210 ms, we did find that the audiovisual integration of older adults was significantly greater than that of younger adults. These results delineate the temporal dynamics of the interactions with auditory attentional load and audiovisual integration in aging, suggesting that modulation of auditory attentional load affects audiovisual integration, enhancing it in older adults.
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Affiliation(s)
- Weiping Yang
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
- Brain and Cognition Research Center (BCRC), Faculty of Education, Hubei University, Wuhan, China
| | - Shengnan Li
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
| | - Ao Guo
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
| | - Zimo Li
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
| | - Xiangfu Yang
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
| | - Yanna Ren
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
- *Correspondence: Yanna Ren
| | - Jiajia Yang
- Applied Brain Science Lab, Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
| | - Jinglong Wu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
- Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
| | - Zhilin Zhang
- Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen, China
- Zhilin Zhang
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8
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Gu F, Gong A, Qu Y, Lu L, Shi Q, Fu Y. Brain Network Research of Skilled Shooters in the Shooting Preparation Stage under the Condition of Limited Sensory Function. Brain Sci 2022; 12:brainsci12101373. [PMID: 36291306 PMCID: PMC9599685 DOI: 10.3390/brainsci12101373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/01/2022] [Accepted: 10/07/2022] [Indexed: 11/16/2022] Open
Abstract
Shooting is a sport dominated by psychological factors. Hence, disturbing the shooter's sensory function during aiming will seriously affect his psychological state and shooting performance. Electroencephalograph (EEG) measurements of 30 skilled marksmen in the shooting preparation stage under noisy disturbance, weak light, and normal conditions were recorded. Therefore, the differences in neural mechanisms in the shooter's brain during shooting aiming in different disturbance conditions were explored using an analytical approach that employs functional connectivity and brain network analysis based on graph theory. The relationship between these brain network characteristics and shooting performance was also compared. The results showed that (1) the average connection strength in the beta frequency band and connection intensity in the left and right temporal lobes of the shooters under noise disturbance were significantly higher than those under the other two conditions, and their brain networks also showed a higher global and local efficiency. In addition, (2) the functional connection intensity in the occipital region of the beta band was higher than that in the normal condition in the weak-light condition. The information interaction in the left parietal region also increased continually during the shooting process. (3) Furthermore, the shooters' eigenvector centrality in the temporal and occipital regions with limited sensory function in the two conditions was lower than those in the normal condition. These findings suggest that noise disturbance activates the arousal level of the shooter's brain and enhances the information processing efficiency of the brain network; however, it increases the mental workload. In weak-light conditions, shooters focus more on visual information processing during aiming and strengthen the inhibition of functions in the brain regions unrelated to shooting behavior. Audiovisual disturbance renders the cortical regions equivalent to the audiovisual perception function in the shooter's brain less important in the entire brain network than in the normal condition. Therefore, these findings reveal the effect of audiovisual disturbance on the functional network of the cortex in the shooting preparation stage and provide a theoretical basis for further understanding the neural mechanism of the shooting process under sensory disturbances.
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Affiliation(s)
- Feng Gu
- School of Information Engineering, Engineering University of People’s Armed Police, Xi’an 710086, China
| | - Anmin Gong
- School of Information Engineering, Engineering University of People’s Armed Police, Xi’an 710086, China
| | - Yi Qu
- School of Information Engineering, Engineering University of People’s Armed Police, Xi’an 710086, China
| | - Ling Lu
- School of Information Engineering, Engineering University of People’s Armed Police, Xi’an 710086, China
| | - Qidi Shi
- School of Automation and Information Engineering, Kunming University of Science and Technology, Kunming 650032, China
| | - Yunfa Fu
- School of Automation and Information Engineering, Kunming University of Science and Technology, Kunming 650032, China
- Correspondence:
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9
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Ren Y, Li S, Zhao N, Hou Y, Wang T, Ren Y, Yang W. Auditory attentional load attenuates age-related audiovisual integration: An EEG study. Neuropsychologia 2022; 174:108346. [PMID: 35973479 DOI: 10.1016/j.neuropsychologia.2022.108346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 12/07/2021] [Accepted: 08/06/2022] [Indexed: 11/25/2022]
Abstract
Studies have revealed that visual attentional load modulated audiovisual integration (AVI) greatly; however, auditory and visual attentional resources are separate to some degree, and task-irrelevant auditory information could arouse much faster and larger attentional alerting effects than visible information. Here, we aimed to explore how auditory attentional load influences AVI and how aging could have an effect. Thirty older and 30 younger adults participated in an AV discrimination task with an additional auditory distractor competing for attentional resources. The race model analysis revealed highest AVI in the low auditory attentional load condition (low > no > medium > high, pairwise comparison, all p ≤ 0.047) for younger adults and a higher AVI under the no auditory attentional-load condition (p = 0.008), but there was a lower AVI under the low (p = 0.019), medium (p < 0.001), and high (p = 0.021) auditory attentional-load conditions for older adults than for younger adults. The time-frequency analysis revealed higher theta- and alpha-band AVI oscillation under no and low auditory attentional-load conditions than under medium and high auditory attentional-load conditions for both older (all p ≤ 0.011) and younger (all p ≤ 0.024) adults. Additionally, Weighted Phase lag index (WPLI) analysis revealed higher theta-band and lower alpha-band global functional connectivity for older adults during AV stimuli processing (all p ≤ 0.031). These results suggested that the AVI was higher in the low attentional-load condition than in the no attentional-load condition but decreased inversely with increasing of attentional load and that there was a significant aging effect in older adults. In addition, the strengthened theta-band global functional connectivity in older adults during AV stimuli processing might be an adaptive phenomenon for age-related perceptual decline.
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Affiliation(s)
- Yanna Ren
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, 550025, China
| | - Shengnan Li
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, 430062, China
| | - Nengwu Zhao
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, 550025, China
| | - Yawei Hou
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, 550025, China
| | - Tao Wang
- Department of Light and Chemical Engineering, Guizhou Light Industry Technical College, Guiyang, 550025, China
| | - Yanling Ren
- Department of Light and Chemical Engineering, Guizhou Light Industry Technical College, Guiyang, 550025, China
| | - Weiping Yang
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, 430062, China.
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10
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Güntekin B, Aktürk T, Arakaki X, Bonanni L, Del Percio C, Edelmayer R, Farina F, Ferri R, Hanoğlu L, Kumar S, Lizio R, Lopez S, Murphy B, Noce G, Randall F, Sack AT, Stocchi F, Yener G, Yıldırım E, Babiloni C. Are there consistent abnormalities in event-related EEG oscillations in patients with Alzheimer's disease compared to other diseases belonging to dementia? Psychophysiology 2022; 59:e13934. [PMID: 34460957 DOI: 10.1111/psyp.13934] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 07/31/2021] [Accepted: 08/09/2021] [Indexed: 01/30/2023]
Abstract
Cerebrospinal and structural-molecular neuroimaging in-vivo biomarkers are recommended for diagnostic purposes in Alzheimer's disease (AD) and other dementias; however, they do not explain the effects of AD neuropathology on neurophysiological mechanisms underpinning cognitive processes. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association reviewed the field literature and reached consensus on the event-related electroencephalographic oscillations (EROs) that show consistent abnormalities in patients with significant cognitive deficits due to Alzheimer's, Parkinson's (PD), Lewy body (LBD), and cerebrovascular diseases. Converging evidence from oddball paradigms showed that, as compared to cognitively unimpaired (CU) older adults, AD patients had lower amplitude in widespread delta (>4 Hz) and theta (4-7 Hz) phase-locked EROs as a function of disease severity. Similar effects were also observed in PD, LBD, and/or cerebrovascular cognitive impairment patients. Non-phase-locked alpha (8-12 Hz) and beta (13-30 Hz) oscillations were abnormally reduced (event-related desynchronization, ERD) in AD patients relative to CU. However, studies on patients with other dementias remain lacking. Delta and theta phase-locked EROs during oddball tasks may be useful neurophysiological biomarkers of cognitive systems at work in heuristic and intervention clinical trials performed in AD patients, but more research is needed regarding their potential role for other dementias.
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Affiliation(s)
- Bahar Güntekin
- Research Institute for Health Sciences and Technologies (SABITA), Regenerative and Restorative Medicine Research Center (REMER), Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Tuba Aktürk
- Research Institute for Health Sciences and Technologies (SABITA), Regenerative and Restorative Medicine Research Center (REMER), Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
- Vocational School, Program of Electroneurophysiology, Istanbul Medipol University, Istanbul, Turkey
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Francesca Farina
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | | | - Lütfü Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Sanjeev Kumar
- Adult Neurodevelopmental and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | | | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | | | - Fiona Randall
- Vertex Pharmaceuticals Incorporated, Boston, Massachusetts, USA
| | - Alexander T Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Görsev Yener
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Ebru Yıldırım
- Research Institute for Health Sciences and Technologies (SABITA), Regenerative and Restorative Medicine Research Center (REMER), Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
- Vocational School, Program of Electroneurophysiology, Istanbul Medipol University, Istanbul, Turkey
| | - Claudio Babiloni
- Alzheimer's Association, Chicago, Illinois, USA
- Institute for Research and Medical Care, Hospital San Raffaele of Cassino, Cassino, Italy
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11
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Wang L, Zhang J, Liu T, Chen D, Yang D, Go R, Wu J, Yan T. Prediction of Cognitive Task Activations via Resting-State Functional Connectivity Networks: An EEG Study. IEEE Trans Cogn Dev Syst 2022. [DOI: 10.1109/tcds.2020.3031604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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12
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Zhang J, Liu T, Shi Z, Tan S, Suo D, Dai C, Wang L, Wu J, Funahashi S, Liu M. Impaired Self-Referential Cognitive Processing in Bipolar Disorder: A Functional Connectivity Analysis. Front Aging Neurosci 2022; 14:754600. [PMID: 35197839 PMCID: PMC8859154 DOI: 10.3389/fnagi.2022.754600] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 01/10/2022] [Indexed: 11/21/2022] Open
Abstract
Patients with bipolar disorder have deficits in self-referenced information. The brain functional connectivity during social cognitive processing in bipolar disorder is unclear. Electroencephalogram (EEG) was recorded in 23 patients with bipolar disorder and 19 healthy comparison subjects. We analyzed the time-frequency distribution of EEG power for each electrode associated with self, other, and font reflection conditions and used the phase lag index to characterize the functional connectivity between electrode pairs for 4 frequency bands. Then, the network properties were assessed by graph theoretic analysis. The results showed that bipolar disorder induced a weaker response power and phase lag index values over the whole brain in both self and other reflection conditions. Moreover, the characteristic path length was increased in patients during self-reflection processing, whereas the global efficiency and the node degree were decreased. In addition, when discriminating patients from normal controls, we found that the classification accuracy was high. These results suggest that patients have impeded integration of attention, memory, and other resources of the whole brain, resulting in a deficit of efficiency and ability in self-referential processing.
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Affiliation(s)
- Jian Zhang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Tiantian Liu
- School of Life Sciences, Beijing Institute of Technology, Beijing, China
| | - Zhongyan Shi
- School of Life Sciences, Beijing Institute of Technology, Beijing, China
| | - Shuping Tan
- Center for Psychiatric Research, Beijing Huilongguan Hospital, Beijing, China
| | - Dingjie Suo
- School of Life Sciences, Beijing Institute of Technology, Beijing, China
| | - Chunyang Dai
- School of Life Sciences, Beijing Institute of Technology, Beijing, China
| | - Li Wang
- School of Life Sciences, Beijing Institute of Technology, Beijing, China
- *Correspondence: Li Wang,
| | - Jinglong Wu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
- Cognitive Neuroscience Laboratory, Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan
| | - Shintaro Funahashi
- Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing, China
| | - Miaomiao Liu
- School of Psychology, Shenzhen University, Shenzhen, China
- Miaomiaos Liu,
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13
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Javaid H, Kumarnsit E, Chatpun S. Age-Related Alterations in EEG Network Connectivity in Healthy Aging. Brain Sci 2022; 12:brainsci12020218. [PMID: 35203981 PMCID: PMC8870284 DOI: 10.3390/brainsci12020218] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 01/28/2022] [Accepted: 02/01/2022] [Indexed: 02/01/2023] Open
Abstract
Emerging studies have reported that functional brain networks change with increasing age. Graph theory is applied to understand the age-related differences in brain behavior and function, and functional connectivity between the regions is examined using electroencephalography (EEG). The effect of normal aging on functional networks and inter-regional synchronization during the working memory (WM) state is not well known. In this study, we applied graph theory to investigate the effect of aging on network topology in a resting state and during performing a visual WM task to classify aging EEG signals. We recorded EEGs from 20 healthy middle-aged and 20 healthy elderly subjects with their eyes open, eyes closed, and during a visual WM task. EEG signals were used to construct the functional network; nodes are represented by EEG electrodes; and edges denote the functional connectivity. Graph theory matrices including global efficiency, local efficiency, clustering coefficient, characteristic path length, node strength, node betweenness centrality, and assortativity were calculated to analyze the networks. We applied the three classifiers of K-nearest neighbor (KNN), a support vector machine (SVM), and random forest (RF) to classify both groups. The analyses showed the significantly reduced network topology features in the elderly group. Local efficiency, global efficiency, and clustering coefficient were significantly lower in the elderly group with the eyes-open, eyes-closed, and visual WM task states. KNN achieved its highest accuracy of 98.89% during the visual WM task and depicted better classification performance than other classifiers. Our analysis of functional network connectivity and topological characteristics can be used as an appropriate technique to explore normal age-related changes in the human brain.
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Affiliation(s)
- Hamad Javaid
- Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand;
| | - Ekkasit Kumarnsit
- Physiology Program, Division of Health and Applied Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90112, Thailand;
- Biosignal Research Centre for Health, Prince of Songkla University, Hat Yai, Songkhla 90112, Thailand
| | - Surapong Chatpun
- Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand;
- Biosignal Research Centre for Health, Prince of Songkla University, Hat Yai, Songkhla 90112, Thailand
- Institute of Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand
- Correspondence:
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Basharat A, Thayanithy A, Barnett-Cowan M. A Scoping Review of Audiovisual Integration Methodology: Screening for Auditory and Visual Impairment in Younger and Older Adults. Front Aging Neurosci 2022; 13:772112. [PMID: 35153716 PMCID: PMC8829696 DOI: 10.3389/fnagi.2021.772112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 12/17/2021] [Indexed: 11/13/2022] Open
Abstract
With the rise of the aging population, many scientists studying multisensory integration have turned toward understanding how this process may change with age. This scoping review was conducted to understand and describe the scope and rigor with which researchers studying audiovisual sensory integration screen for hearing and vision impairment. A structured search in three licensed databases (Scopus, PubMed, and PsychInfo) using the key concepts of multisensory integration, audiovisual modality, and aging revealed 2,462 articles, which were screened for inclusion by two reviewers. Articles were included if they (1) tested healthy older adults (minimum mean or median age of 60) with younger adults as a comparison (mean or median age between 18 and 35), (2) measured auditory and visual integration, (3) were written in English, and (4) reported behavioral outcomes. Articles that included the following were excluded: (1) tested taste exclusively, (2) tested olfaction exclusively, (3) tested somatosensation exclusively, (4) tested emotion perception, (5) were not written in English, (6) were clinical commentaries, editorials, interviews, letters, newspaper articles, abstracts only, or non-peer reviewed literature (e.g., theses), and (7) focused on neuroimaging without a behavioral component. Data pertaining to the details of the study (e.g., country of publication, year of publication, etc.) were extracted, however, of higher importance to our research question, data pertaining to screening measures used for hearing and vision impairment (e.g., type of test used, whether hearing- and visual-aids were worn, thresholds used, etc.) were extracted, collated, and summarized. Our search revealed that only 64% of studies screened for age-abnormal hearing impairment, 51% screened for age-abnormal vision impairment, and that consistent definitions of normal or abnormal vision and hearing were not used among the studies that screened for sensory abilities. A total of 1,624 younger adults and 4,778 older participants were included in the scoping review with males composing approximately 44% and females composing 56% of the total sample and most of the data was obtained from only four countries. We recommend that studies investigating the effects of aging on multisensory integration should screen for normal vision and hearing by using the World Health Organization's (WHO) hearing loss and visual impairment cut-off scores in order to maintain consistency among other aging researchers. As mild cognitive impairment (MCI) has been defined as a “transitional” or a “transitory” stage between normal aging and dementia and because approximately 3–5% of the aging population will develop MCI each year, it is therefore important that when researchers aim to study a healthy aging population, that they appropriately screen for MCI. One of our secondary aims was to determine how often researchers were screening for cognitive impairment and the types of tests that were used to do so. Our results revealed that only 55 out of 72 studies tested for neurological and cognitive function, and only a subset used standardized tests. Additionally, among the studies that used standardized tests, the cut-off scores used were not always adequate for screening out mild cognitive impairment. An additional secondary aim of this scoping review was to determine the feasibility of whether a meta-analysis could be conducted in the future to further quantitatively evaluate the results (i.e., are the findings obtained from studies using self-reported vision and hearing impairment screening methods significantly different from those measuring vision and hearing impairment in the lab) and to assess the scope of this problem. We found that it may not be feasible to conduct a meta-analysis with the entire dataset of this scoping review. However, a meta-analysis can be conducted if stricter parameters are used (e.g., focusing on accuracy or response time data only).Systematic Review Registration:https://doi.org/10.17605/OSF.IO/GTUHD.
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15
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Karthik G, Plass J, Beltz AM, Liu Z, Grabowecky M, Suzuki S, Stacey WC, Wasade VS, Towle VL, Tao JX, Wu S, Issa NP, Brang D. Visual speech differentially modulates beta, theta, and high gamma bands in auditory cortex. Eur J Neurosci 2021; 54:7301-7317. [PMID: 34587350 DOI: 10.1111/ejn.15482] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/20/2021] [Accepted: 08/28/2021] [Indexed: 12/13/2022]
Abstract
Speech perception is a central component of social communication. Although principally an auditory process, accurate speech perception in everyday settings is supported by meaningful information extracted from visual cues. Visual speech modulates activity in cortical areas subserving auditory speech perception including the superior temporal gyrus (STG). However, it is unknown whether visual modulation of auditory processing is a unitary phenomenon or, rather, consists of multiple functionally distinct processes. To explore this question, we examined neural responses to audiovisual speech measured from intracranially implanted electrodes in 21 patients with epilepsy. We found that visual speech modulated auditory processes in the STG in multiple ways, eliciting temporally and spatially distinct patterns of activity that differed across frequency bands. In the theta band, visual speech suppressed the auditory response from before auditory speech onset to after auditory speech onset (-93 to 500 ms) most strongly in the posterior STG. In the beta band, suppression was seen in the anterior STG from -311 to -195 ms before auditory speech onset and in the middle STG from -195 to 235 ms after speech onset. In high gamma, visual speech enhanced the auditory response from -45 to 24 ms only in the posterior STG. We interpret the visual-induced changes prior to speech onset as reflecting crossmodal prediction of speech signals. In contrast, modulations after sound onset may reflect a decrease in sustained feedforward auditory activity. These results are consistent with models that posit multiple distinct mechanisms supporting audiovisual speech perception.
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Affiliation(s)
- G Karthik
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
| | - John Plass
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
| | - Adriene M Beltz
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
| | - Zhongming Liu
- Department of Biomedical Engineering and Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
| | - Marcia Grabowecky
- Department of Psychology, Northwestern University, Evanston, Illinois, USA
| | - Satoru Suzuki
- Department of Psychology, Northwestern University, Evanston, Illinois, USA
| | - William C Stacey
- Department of Neurology and Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Vibhangini S Wasade
- Department of Neurology, Henry Ford Hospital, Detroit, Michigan, USA.,Department of Neurology, Wayne State University School of Medicine, Detroit, Michigan, USA
| | - Vernon L Towle
- Department of Neurology, The University of Chicago, Chicago, Illinois, USA
| | - James X Tao
- Department of Neurology, The University of Chicago, Chicago, Illinois, USA
| | - Shasha Wu
- Department of Neurology, The University of Chicago, Chicago, Illinois, USA
| | - Naoum P Issa
- Department of Neurology, The University of Chicago, Chicago, Illinois, USA
| | - David Brang
- Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA
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16
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Momtaz S, Moncrieff D, Bidelman GM. Dichotic listening deficits in amblyaudia are characterized by aberrant neural oscillations in auditory cortex. Clin Neurophysiol 2021; 132:2152-2162. [PMID: 34284251 DOI: 10.1016/j.clinph.2021.04.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Revised: 04/16/2021] [Accepted: 04/29/2021] [Indexed: 12/25/2022]
Abstract
OBJECTIVE Children diagnosed with auditory processing disorder (APD) show deficits in processing complex sounds that are associated with difficulties in higher-order language, learning, cognitive, and communicative functions. Amblyaudia (AMB) is a subcategory of APD characterized by abnormally large ear asymmetries in dichotic listening tasks. METHODS Here, we examined frequency-specific neural oscillations and functional connectivity via high-density electroencephalography (EEG) in children with and without AMB during passive listening of nonspeech stimuli. RESULTS Time-frequency maps of these "brain rhythms" revealed stronger phase-locked beta-gamma (~35 Hz) oscillations in AMB participants within bilateral auditory cortex for sounds presented to the right ear, suggesting a hypersynchronization and imbalance of auditory neural activity. Brain-behavior correlations revealed neural asymmetries in cortical responses predicted the larger than normal right-ear advantage seen in participants with AMB. Additionally, we found weaker functional connectivity in the AMB group from right to left auditory cortex, despite their stronger neural responses overall. CONCLUSION Our results reveal abnormally large auditory sensory encoding and an imbalance in communication between cerebral hemispheres (ipsi- to -contralateral signaling) in AMB. SIGNIFICANCE These neurophysiological changes might lead to the functionally poorer behavioral capacity to integrate information between the two ears in children with AMB.
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Affiliation(s)
- Sara Momtaz
- School of Communication Sciences & Disorders, University of Memphis, Memphis, TN, USA.
| | - Deborah Moncrieff
- School of Communication Sciences & Disorders, University of Memphis, Memphis, TN, USA
| | - Gavin M Bidelman
- School of Communication Sciences & Disorders, University of Memphis, Memphis, TN, USA; Institute for Intelligent Systems, University of Memphis, Memphis, TN, USA; University of Tennessee Health Sciences Center, Department of Anatomy and Neurobiology, Memphis, TN, USA
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17
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Zhao Z, Li J, Niu Y, Wang C, Zhao J, Yuan Q, Ren Q, Xu Y, Yu Y. Classification of Schizophrenia by Combination of Brain Effective and Functional Connectivity. Front Neurosci 2021; 15:651439. [PMID: 34149345 PMCID: PMC8209471 DOI: 10.3389/fnins.2021.651439] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 04/19/2021] [Indexed: 11/13/2022] Open
Abstract
At present, lots of studies have tried to apply machine learning to different electroencephalography (EEG) measures for diagnosing schizophrenia (SZ) patients. However, most EEG measures previously used are either a univariate measure or a single type of brain connectivity, which may not fully capture the abnormal brain changes of SZ patients. In this paper, event-related potentials were collected from 45 SZ patients and 30 healthy controls (HCs) during a learning task, and then a combination of partial directed coherence (PDC) effective and phase lag index (PLI) functional connectivity were used as features to train a support vector machine classifier with leave-one-out cross-validation for classification of SZ from HCs. Our results indicated that an excellent classification performance (accuracy = 95.16%, specificity = 94.44%, and sensitivity = 96.15%) was obtained when the combination of functional and effective connectivity features was used, and the corresponding optimal feature number was 15, which included 12 PDC and three PLI connectivity features. The selected effective connectivity features were mainly located between the frontal/temporal/central and visual/parietal lobes, and the selected functional connectivity features were mainly located between the frontal/temporal and visual cortexes of the right hemisphere. In addition, most of the selected effective connectivity abnormally enhanced in SZ patients compared with HCs, whereas all the selected functional connectivity features decreased in SZ patients. The above results showed that our proposed method has great potential to become a tool for the auxiliary diagnosis of SZ.
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Affiliation(s)
- Zongya Zhao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Xinxiang city, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Xinxiang Key Laboratory of Biomedical Information Research, Henan Engineering Laboratory of Combinatorial Technique for Clinical and Biomedical Big Data, Xinxiang, China
| | - Jun Li
- School of International Education, Xinxiang Medical University, Xinxiang, China
| | - Yanxiang Niu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
| | - Chang Wang
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Xinxiang city, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Xinxiang Key Laboratory of Biomedical Information Research, Henan Engineering Laboratory of Combinatorial Technique for Clinical and Biomedical Big Data, Xinxiang, China
| | - Junqiang Zhao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Xinxiang city, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Xinxiang Key Laboratory of Biomedical Information Research, Henan Engineering Laboratory of Combinatorial Technique for Clinical and Biomedical Big Data, Xinxiang, China
| | - Qingli Yuan
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
| | - Qiongqiong Ren
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Xinxiang city, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
| | - Yongtao Xu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Xinxiang city, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Xinxiang Key Laboratory of Biomedical Information Research, Henan Engineering Laboratory of Combinatorial Technique for Clinical and Biomedical Big Data, Xinxiang, China
| | - Yi Yu
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Xinxiang city, Xinxiang, China
- Engineering Technology Research Center of Neurosense and Control of Henan Province, Xinxiang, China
- Xinxiang Key Laboratory of Biomedical Information Research, Henan Engineering Laboratory of Combinatorial Technique for Clinical and Biomedical Big Data, Xinxiang, China
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18
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Tarasova IV, Razumnikova OA, Trubnikova OA, Mezentsev YA, Kupriyanova DS, Barbarash OL. [Neurophysiological correlates of postoperative cognitive disorders]. Zh Nevrol Psikhiatr Im S S Korsakova 2021; 121:18-23. [PMID: 33728846 DOI: 10.17116/jnevro202112102118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
OBJECTIVE A special place among cognitive disorders in patients with cardiovascular diseases is given to postoperative cognitive dysfunction (POCD). The study aimed at investigating the patterns of beta-2 activity associated with postoperative cognitive dysfunction (POCD) in patients after coronary artery bypass grafting (CABG). MATERIAL AND METHODS The study included 60 patients who underwent neuropsychological testing 3-5 days before surgery and on the 7-10th day of CABG. A multichannel electroencephalogram of resting state with eyes closed in 62 standard leads was recorded. Statistical processing of the results was carried out using Statistica 10 (StatSoft Inc, USA) and the developed method of data clustering with a minimax criterion, a software implementation of the binary clipping and branching algorithm was used to find optimal solutions. RESULTS Patients with POCD had higher pre- and postoperative high-frequency beta-2 rhythm power (20-30 Hz) compared with patients without cognitive impairment. The regression model demonstrated that POCD was associated with high values of preoperative beta-2 activity in the right frontal cortex and with low values in the left parietal areas after CABG. The clustering of beta-2 rhythm power before and after CABG revealed that the best cognitive status corresponded to a stable affiliation of patients with the selected clusters. CONCLUSION The specific POCD correlates were established in patients after CABG. Low cognitive status was characterized by the preoperative beta-2 power increase in the right frontal areas and postoperative decrease in the left parietal cortex. The developed method for classifying patients according to the level of pre- and postoperative beta-2 rhythm power has a good discriminant ability. Stable patient affiliation with the selected clusters was associated with a higher level of cognitive status.
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Affiliation(s)
- I V Tarasova
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | | | - O A Trubnikova
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Yu A Mezentsev
- Novosibirsk State Technical University, Novosibirsk, Russia
| | - D S Kupriyanova
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - O L Barbarash
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
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Kim JH, Kim CM, Jung ES, Yim MS. Biosignal-Based Attention Monitoring to Support Nuclear Operator Safety-Relevant Tasks. Front Comput Neurosci 2020; 14:596531. [PMID: 33408623 PMCID: PMC7780753 DOI: 10.3389/fncom.2020.596531] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 11/18/2020] [Indexed: 11/30/2022] Open
Abstract
In the main control room (MCR) of a nuclear power plant (NPP), the quality of an operator's performance can depend on their level of attention to the task. Insufficient operator attention accounted for more than 26% of the total causes of human errors and is the highest category for errors. It is therefore necessary to check whether operators are sufficiently attentive either as supervisors or peers during reactor operation. Recently, digital control technologies have been introduced to the operating environment of an NPP MCR. These upgrades are expected to enhance plant and operator performance. At the same time, because personal computers are used in the advanced MCR, the operators perform more cognitive works than physical work. However, operators may not consciously check fellow operators' attention in this environment indicating potentially higher importance of the role of operator attention. Therefore, remote measurement of an operator's attention in real time would be a useful tool, providing feedback to supervisors. The objective of this study is to investigate the development of quantitative indicators that can identify an operator's attention, to diagnose or detect a lack of operator attention thus preventing potential human errors in advanced MCRs. To establish a robust baseline of operator attention, this study used two of the widely used biosignals: electroencephalography (EEG) and eye movement. We designed an experiment to collect EEG and eye movements of the subjects who were monitoring and diagnosing nuclear operator safety-relevant tasks. There was a statistically significant difference between biosignals with and without appropriate attention. Furthermore, an average classification accuracy of about 90% was obtained by the k-nearest neighbors and support vector machine classifiers with a few EEG and eye movements features. Potential applications of EEG and eye movement measures in monitoring and diagnosis tasks in an NPP MCR are also discussed.
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Affiliation(s)
- Jung Hwan Kim
- Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Chul Min Kim
- Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Eun-Soo Jung
- Technology Research, Samsung SDS, Seoul, South Korea
| | - Man-Sung Yim
- Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
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20
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Miraglia F, Tomino C, Vecchio F, Gorgoni M, De Gennaro L, Rossini PM. The brain network organization during sleep onset after deprivation. Clin Neurophysiol 2020; 132:36-44. [PMID: 33254098 DOI: 10.1016/j.clinph.2020.10.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 07/13/2020] [Accepted: 10/11/2020] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Aim of the present study is to investigate the alterations of brain networks derived from EEG analysis in pre- and post-sleep onset conditions after 40 h of sleep deprivation (SD) compared to sleep onset after normal sleep in 39 healthy subjects. METHODS Functional connectivity analysis was made on electroencelographic (EEG) cortical sources of current density and small world (SW) index was evaluated in the EEG frequency bands (delta, theta, alpha, sigma and beta). RESULTS Comparing pre- vs. post-sleep onset conditions after a night of SD a significant decrease of SW in delta and theta bands in post-sleep onset condition was found together with an increase of SW in sigma band. Comparing pre-sleep onset after sleep SD versus pre-sleep onset after a night of normal sleep a decreased of SW index in beta band in pre-sleep onset in SD compared to pre-sleep onset in normal sleep was evidenced. CONCLUSIONS Brain functional network architecture is influenced by the SD in different ways. Brain networks topology during wake resting state needs to be further explored to reveal SD-related changes in order to prevent possible negative effects of SD on behaviour and brain function during wakefulness. SIGNIFICANCE The SW modulations as revealed by the current study could be used as an index of an altered balance between brain integration and segregation processes after SD.
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Affiliation(s)
- Francesca Miraglia
- Brain Connectivity Laboratory, Dept. Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, Rome, Italy.
| | - Carlo Tomino
- Scientific Directorate, IRCCS San Raffaele Pisana, Rome, Italy
| | - Fabrizio Vecchio
- Brain Connectivity Laboratory, Dept. Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, Rome, Italy
| | | | | | - Paolo Maria Rossini
- Brain Connectivity Laboratory, Dept. Neuroscience & Neurorehabilitation, IRCCS San Raffaele Pisana, Rome, Italy
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21
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Ren Y, Li S, Wang T, Yang W. Age-Related Shifts in Theta Oscillatory Activity During Audio-Visual Integration Regardless of Visual Attentional Load. Front Aging Neurosci 2020; 12:571950. [PMID: 33192463 PMCID: PMC7556010 DOI: 10.3389/fnagi.2020.571950] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Accepted: 09/15/2020] [Indexed: 12/20/2022] Open
Abstract
Audio-visual integration (AVI) is higher in attended conditions than in unattended conditions. Here, we explore the AVI effect when the attentional recourse is competed by additional visual distractors, and its aging effect using single- and dual-tasks. The results showed the highest AVI effect under single-task-attentional-load condition than under no- and dual-task-attentional-load conditions (all P < 0.05) in both older and younger groups, but the AVI effect was weaker and delayed for older adults compared to younger adults for all attentional-load conditions (all P < 0.05). The non-phase-locked oscillation for AVI analysis illustrated the highest theta and alpha oscillatory activity for single-task-attentional-load condition than for no- and dual-task-attentional-load conditions, and the AVI oscillatory activity mainly occurred in the Cz, CP1 and Oz of older adults but in the Fz, FC1, and Cz of younger adults. The AVI effect was significantly negatively correlated with FC1 (r2 = 0.1468, P = 0.05) and Cz (r2 = 0.1447, P = 0.048) theta activity and with Fz (r2 = 0.1557, P = 0.043), FC1 (r2 = 0.1042, P = 0.008), and Cz (r2 = 0.0897, P = 0.010) alpha activity for older adults but not for younger adults in dual task. These results suggested a reduction in AVI ability for peripheral stimuli and a shift in AVI oscillation from anterior to posterior regions in older adults as an adaptive mechanism.
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Affiliation(s)
- Yanna Ren
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Shengnan Li
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
| | - Tao Wang
- Department of Light and Chemical Engineering, Guizhou Light Industry Technical College, Guiyang, China
| | - Weiping Yang
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
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22
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Ren Y, Guo A, Xu Z, Wang T, Wu R, Yang W. Age-related functional brain connectivity during audio-visual hand-held tool recognition. Brain Behav 2020; 10:e01759. [PMID: 32683799 PMCID: PMC7507049 DOI: 10.1002/brb3.1759] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 07/01/2020] [Accepted: 07/02/2020] [Indexed: 11/26/2022] Open
Abstract
INTRODUCTION Previous studies have confirmed increased functional connectivity in elderly adults during processing of simple audio-visual stimuli; however, it is unclear whether elderly adults maximize their performance by strengthening their functional brain connectivity when processing dynamic audio-visual hand-held tool stimuli. The present study aimed to explore this question using global functional connectivity. METHODS Twenty-one healthy elderly adults and 21 healthy younger adults were recruited to conduct a dynamic hand-held tool recognition task with high/low-intensity stimuli. RESULTS Elderly adults exhibited higher areas under the curve for both the high-intensity (3.5 versus. 2.7) and low-intensity (3.0 versus. 1.2) stimuli, indicating a higher audio-visual integration ability, but a delayed and widened audio-visual integration window for elderly adults for both the high-intensity (390 - 690 ms versus. 360 - 560 ms) and low-intensity (460 - 690 ms versus. 430 - 500 ms) stimuli. Additionally, elderly adults exhibited higher theta-band (all p < .01) but lower alpha-, beta-, and gamma-band functional connectivity (all p < .05) than younger adults under both the high- and low-intensity-stimulus conditions when processing audio-visual stimuli, except for gamma-band functional connectivity under the high-intensity-stimulus condition. Furthermore, higher theta- and alpha-band functional connectivity were observed for the audio-visual stimuli than for the auditory and visual stimuli and under the high-intensity-stimulus condition than under the low-intensity-stimulus condition. CONCLUSION The higher theta-band functional connectivity in elderly adults was mainly due to higher attention allocation. The results further suggested that in the case of sensory processing, theta, alpha, beta, and gamma activity might participate in different stages of perception.
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Affiliation(s)
- Yanna Ren
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Ao Guo
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
| | - Zhihan Xu
- Department of Foreign Language, Ningbo University of Technology, Zhejiang, China
| | - Tao Wang
- Department of Light and Chemical Engineering, Guizhou Light Industry Technical College, Guiyang, China
| | - Rui Wu
- Department of Psychology, College of Humanities and Management, Guizhou University of Traditional Chinese Medicine, Guiyang, China
| | - Weiping Yang
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
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23
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Zhou G, Pan Y, Yang J, Zhang X, Guo X, Luo Y. Sleep Electroencephalographic Response to Respiratory Events in Patients With Moderate Sleep Apnea-Hypopnea Syndrome. Front Neurosci 2020; 14:310. [PMID: 32372906 PMCID: PMC7186482 DOI: 10.3389/fnins.2020.00310] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Accepted: 03/17/2020] [Indexed: 12/03/2022] Open
Abstract
Sleep apnea–hypopnea syndrome is a common breathing disorder that can lead to organic brain injury, prevent memory consolidation, and cause other adverse mental-related complications. Brain activity while sleeping during respiratory events is related to these dysfunctions. In this study, we analyzed variations in electroencephalography (EEG) signals before, during, and after such events. Absolute and relative powers, as well as symbolic transfer entropy (STE) of scalp EEG signals, were calculated to unveil the activity of brain regions and information interactions between them, respectively. During the respiratory events, only low-frequency power increased during rapid eye movement (REM) stage (δ-band absolute and relative power) and N1 (δ- and θ-band absolute power, δ-band relative power) sleep. But absolute power increased in low- and medium-frequency bands (δ, θ, α, and σ bands), and relative power increased mainly in the medium-frequency band (α and σ bands) during stage N2 sleep. After the respiratory events, absolute power increased in all frequency bands and sleep stages, but relative power increased in medium and high frequencies. Regarding information interactions, the β-band STE decreased during and after events. In the γ band, the intrahemispheric STE increased during events and decreased afterward. Moreover, the interhemisphere STE increased after events during REM and stage N1 sleep. The EEG changes throughout respiratory events are supporting evidence for previous EEG knowledge of the impact of sleep apnea on the brain. These findings may provide insights into the influence of the sleep apnea–hypopnea syndrome on cognitive function and neuropsychiatric defects.
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Affiliation(s)
- Guolin Zhou
- School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Yu Pan
- School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Juan Yang
- School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Xiangmin Zhang
- Sleep-Disordered Breathing Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xinwen Guo
- Department of Psychology, Guangdong 999 Brain Hospital, Guangzhou, China
| | - Yuxi Luo
- School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Sensing Technology and Biomedical Instruments, Sun Yat-sen University, Guangzhou, China
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24
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Rogala J, Kublik E, Krauz R, Wróbel A. Resting-state EEG activity predicts frontoparietal network reconfiguration and improved attentional performance. Sci Rep 2020; 10:5064. [PMID: 32193502 PMCID: PMC7081192 DOI: 10.1038/s41598-020-61866-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 03/05/2020] [Indexed: 12/21/2022] Open
Abstract
Mounting evidence indicates that resting-state EEG activity is related to various cognitive functions. To trace physiological underpinnings of this relationship, we investigated EEG and behavioral performance of 36 healthy adults recorded at rest and during visual attention tasks: visual search and gun shooting. All measures were repeated two months later to determine stability of the results. Correlation analyses revealed that within the range of 2–45 Hz, at rest, beta-2 band power correlated with the strength of frontoparietal connectivity and behavioral performance in both sessions. Participants with lower global beta-2 resting-state power (gB2rest) showed weaker frontoparietal connectivity and greater capacity for its modifications, as indicated by changes in phase correlations of the EEG signals. At the same time shorter reaction times and improved shooting accuracy were found, in both test and retest, in participants with low gB2rest compared to higher gB2rest values. We posit that weak frontoparietal connectivity permits flexible network reconfigurations required for improved performance in everyday tasks.
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Affiliation(s)
- Jacek Rogala
- Bioimaging Research Center, World Hearing Center, Institute of Physiology and Pathology of Hearing, Mokra 17 street, Kajetany, 05-830, Nadarzyn, Poland.
| | - Ewa Kublik
- Instytut Biologii Doświadczalnej im. Marcelego Nenckiego, 3 Pasteur Street, 02-093, Warsaw, Poland
| | - Rafał Krauz
- Military University of Technology, Physical Education, 3 gen, Sylwestra Kaliskiego street, 00-908, Warsaw, Poland
| | - Andrzej Wróbel
- Instytut Biologii Doświadczalnej im. Marcelego Nenckiego, 3 Pasteur Street, 02-093, Warsaw, Poland.,Department of Epistemology, Institute of Philosophy, University of Warsaw, 3 Krakowskie Przedmiescie street, 00-927, Warszawa, Poland
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25
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Auditory-frontal Channeling in α and β Bands is Altered by Age-related Hearing Loss and Relates to Speech Perception in Noise. Neuroscience 2019; 423:18-28. [PMID: 31705894 DOI: 10.1016/j.neuroscience.2019.10.044] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Revised: 09/19/2019] [Accepted: 10/27/2019] [Indexed: 01/16/2023]
Abstract
Difficulty understanding speech-in-noise (SIN) is a pervasive problem faced by older adults particularly those with hearing loss. Previous studies have identified structural and functional changes in the brain that contribute to older adults' speech perception difficulties. Yet, many of these studies use neuroimaging techniques that evaluate only gross activation in isolated brain regions. Neural oscillations may provide further insight into the processes underlying SIN perception as well as the interaction between auditory cortex and prefrontal linguistic brain regions that mediate complex behaviors. We examined frequency-specific neural oscillations and functional connectivity of the EEG in older adults with and without hearing loss during an active SIN perception task. Brain-behavior correlations revealed listeners who were more resistant to the detrimental effects of noise also demonstrated greater modulation of α phase coherence between clean and noise-degraded speech, suggesting α desynchronization reflects release from inhibition and more flexible allocation of neural resources. Additionally, we found top-down β connectivity between prefrontal and auditory cortices strengthened with poorer hearing thresholds despite minimal behavioral differences. This is consistent with the proposal that linguistic brain areas may be recruited to compensate for impoverished auditory inputs through increased top-down predictions to assist SIN perception. Overall, these results emphasize the importance of top-down signaling in low-frequency brain rhythms that help compensate for hearing-related declines and facilitate efficient SIN processing.
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26
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File B, Nánási T, Tóth E, Bokodi V, Tóth B, Hajnal B, Kardos Z, Entz L, Erőss L, Ulbert I, Fabó D. Reorganization of Large-Scale Functional Networks During Low-Frequency Electrical Stimulation of the Cortical Surface. Int J Neural Syst 2019; 30:1950022. [DOI: 10.1142/s0129065719500229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
We investigated the functional network reorganization caused by low-frequency electrical stimulation (LFES) of human brain cortical surface. Intracranial EEG data from subdural grid positions were analyzed in 16 pre-surgery epileptic patients. LFES was performed by injecting current pulses (10[Formula: see text]mA, 0.2[Formula: see text]ms pulse width, 0.5[Formula: see text]Hz, 25 trials) into all adjacent electrode contacts. Dynamic functional connectivity analysis was carried out on two frequency bands (low: 1–4[Formula: see text]Hz; high: 10–40[Formula: see text]Hz) to investigate the early, high frequency and late, low frequency responses elicited by the stimulation. The centralization increased in early compared to late responses, suggesting a more prominent role of direct neural links between primarily activated areas and distant brain regions. Injecting the current into the seizure onset zone (SOZ) evoked a more integrated functional topology during the early (N1) period of the response, whereas during the late (N2) period — regardless of the stimulation site — the connectedness of the SOZ was elevated compared to the non-SOZ tissue. The abnormal behavior of the epileptic sub-network during both part of the responses supports the idea of the pathogenic role of impaired inhibition and excitation mechanisms in epilepsy.
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Affiliation(s)
- Bálint File
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Computational Neuroscience Group, Wigner Research Centre for Physics, HAS, Budapest, H-1121, Hungary
| | - Tibor Nánási
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
- János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, H-1085, Hungary
| | - Emília Tóth
- Department of Neurology, University of Alabama at Birmingham, AL 35233, USA
| | - Virág Bokodi
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, H-1145, Hungary
| | - Brigitta Tóth
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
| | - Boglárka Hajnal
- Juhász Pál Epilepsy Centrum, National Institute of Clinical Neuroscience, Budapest, H-1145, Hungary
| | - Zsófia Kardos
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
| | - László Entz
- Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, H-1145, Hungary
| | - Loránd Erőss
- Department of Functional Neurosurgery, National Institute of Clinical Neurosciences, Budapest, H-1145, Hungary
| | - István Ulbert
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, H-1083, Hungary
- Institute of Cognitive Neuroscience and Psychology, RCNS, HAS, Budapest, H-1117, Hungary
| | - Dániel Fabó
- Juhász Pál Epilepsy Centrum, National Institute of Clinical Neuroscience, Budapest, H-1145, Hungary
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27
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Zhang J, Zhang Z, Go R, Li C, Wu J. Discrimination Thresholds for Passive Tactile Volume Perception by Fingertips. Perception 2019; 48:1252-1267. [PMID: 31558099 DOI: 10.1177/0301006619878560] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Haptic object perception is still poorly understood up to now. This study investigated the ability of human fingers to discriminate the volume of objects by passive touch. Experiments measured the discrimination threshold of volume using three tasks: passive tactile volume perception, passive tactile area perception, and active tactile volume perception. In each trial, we utilized two plastic cubes to successively stimulate the fingers, and participants were instructed to make comparisons between the stimulus objects’ volume and area. Results showed that there was no significant difference in the discrimination thresholds of tactile volume perception between passive touch and active touch, whereas significant differences in the discrimination thresholds between fingertips, such as the thumb versus the pinky finger. In passive touch, the discrimination thresholds of volume perception were larger than that with surface area perception. We found that the discrimination of the volume of objects is more difficult than the discrimination of the area of the objects.
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Affiliation(s)
- Jian Zhang
- Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, China
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Japan
| | - Ritsu Go
- Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, China
| | - Chunlin Li
- School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Jinglong Wu
- Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, China
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28
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Song P, Lin H, Liu C, Jiang Y, Lin Y, Xue Q, Xu P, Wang Y. Transcranial Magnetic Stimulation to the Middle Frontal Gyrus During Attention Modes Induced Dynamic Module Reconfiguration in Brain Networks. Front Neuroinform 2019; 13:22. [PMID: 31001103 PMCID: PMC6456710 DOI: 10.3389/fninf.2019.00022] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 03/14/2019] [Indexed: 01/11/2023] Open
Abstract
The interaction between dorsal and ventral attention networks (VANs) is mediated by the middle frontal gyrus (MFG), which is functionally connected to both networks. However, the direct role of the MFG in selective and sustained attention remains controversial. In the current study, we used transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to probe the connectivity dynamic changes of MFG-associated regions during different attention modes. The participants underwent visual, selective, and sustained attention tasks to observe TMS-induced network changes. Twenty healthy participants received single-pulse TMS over the left or right MFG during tasks, while synchronous EEG data was acquired. Behavioral results were recorded and time-varying brain network analyses were performed. We found that the MFG is involved in attention processing and that sustained attention was preferentially controlled by the right MFG. Moreover, compared with the right hemisphere, the left hemisphere was associated with selective attention tasks. Visual and selective attention tasks induced MFG-related changes in network nodes were within the left hemisphere; however, sustained attention induced changes in network nodes were in the bilateral posterior MFG. Our findings indicated that the MFG plays a crucial role in regulating attention networks. In particular, TMS-induced MFG alterations influenced key nodes of the time-varying brain network, leading to the reorganization of brain network modules.
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Affiliation(s)
- Penghui Song
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Hua Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Chunyan Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yuanling Jiang
- Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yicong Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Qing Xue
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Peng Xu
- Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neuromodulation, Beijing, China
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29
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Wang M, Li C, Zhang W, Wang Y, Feng Y, Liang Y, Wei J, Zhang X, Li X, Chen R. Support Vector Machine for Analyzing Contributions of Brain Regions During Task-State fMRI. Front Neuroinform 2019; 13:10. [PMID: 30894812 PMCID: PMC6414418 DOI: 10.3389/fninf.2019.00010] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 02/12/2019] [Indexed: 12/24/2022] Open
Abstract
The mainstream method used for the analysis of task functional Magnetic Resonance Imaging (fMRI) data, is to obtain task-related active brain regions based on generalized linear models. Machine learning as a data-driven technical method is increasingly used in fMRI data analysis. The language task data, including math task and story task, of the Human Connectome Project (HCP) was used in this work. We chose a linear support vector machine as a classifier to classify math and story tasks and compared them with the activated brain regions of a SPM statistical analysis. As a result, 13 of the 25 regions used for classification in SVM were activated regions, and 12 were non-activated regions. In particular, the right Paracentral Lobule and right Rolandic Operculum which belong to non-activated regions, contributed most to the classification. Therefore, the differences found in machine learning can provide a new understanding of the physiological mechanisms of brain regions under different tasks.
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Affiliation(s)
- Mengyue Wang
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Chunlin Li
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Wenjing Zhang
- Beijing Stomatological Hospital, Capital Medical University, Beijing, China
| | | | - Yuan Feng
- Beijing Institute of Technology, Beijing, China
| | - Ying Liang
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Jing Wei
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Xu Zhang
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Xia Li
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Renji Chen
- Beijing Stomatological Hospital, Capital Medical University, Beijing, China
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30
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Zuo R, Wei J, Li X, Li C, Zhao C, Ren Z, Liang Y, Geng X, Jiang C, Yang X, Zhang X. Automated Detection of High-Frequency Oscillations in Epilepsy Based on a Convolutional Neural Network. Front Comput Neurosci 2019; 13:6. [PMID: 30809142 PMCID: PMC6379273 DOI: 10.3389/fncom.2019.00006] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 01/18/2019] [Indexed: 11/17/2022] Open
Abstract
Epilepsy is one of the most common chronic neurological diseases. High-frequency oscillations (HFOs) have emerged as promising biomarkers for the epileptogenic zone. However, visual marking of HFOs is a time-consuming and laborious process. Several automated techniques have been proposed to detect HFOs, yet these are still far from being suitable for application in a clinical setting. Here, ripples and fast ripples from intracranial electroencephalograms were detected in six patients with intractable epilepsy using a convolutional neural network (CNN) method. This approach proved more accurate than using four other HFO detectors integrated in RIPPLELAB, providing a higher sensitivity (77.04% for ripples and 83.23% for fast ripples) and specificity (72.27% for ripples and 79.36% for fast ripples) for HFO detection. Furthermore, for one patient, the Cohen's kappa coefficients comparing automated detection and visual analysis results were 0.541 for ripples and 0.777 for fast ripples. Hence, our automated detector was capable of reliable estimates of ripples and fast ripples with higher sensitivity and specificity than four other HFO detectors. Our detector may be used to assist clinicians in locating epileptogenic zone in the future.
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Affiliation(s)
- Rui Zuo
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Jing Wei
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Xiaonan Li
- Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Beijing, China
| | - Chunlin Li
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Cui Zhao
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Zhaohui Ren
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Ying Liang
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Xinling Geng
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
| | - Chenxi Jiang
- Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Beijing, China
| | - Xiaofeng Yang
- Neuroelectrophysiological Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Beijing, China
| | - Xu Zhang
- School of Biomedical Engineering, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China
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31
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Liu T, Zhang J, Dong X, Li Z, Shi X, Tong Y, Yang R, Wu J, Wang C, Yan T. Occipital Alpha Connectivity During Resting-State Electroencephalography in Patients With Ultra-High Risk for Psychosis and Schizophrenia. Front Psychiatry 2019; 10:553. [PMID: 31474882 PMCID: PMC6706463 DOI: 10.3389/fpsyt.2019.00553] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Accepted: 07/15/2019] [Indexed: 12/27/2022] Open
Abstract
Schizophrenia patients always show cognitive impairment, which is proved to be related to hypo-connectivity or hyper-connectivity. Further, individuals with an ultra-high risk for psychosis also show abnormal functional connectivity-related cognitive impairment, especially in the alpha rhythm. Thus, the identification of functional networks is essential to our understanding of the disorder. We investigated the resting-state functional connectivity of the alpha rhythm measured by electroencephalography (EEG) to reveal the relation between functional network and clinical symptoms. The participants included 28 patients with first-episode schizophrenia (FES), 28 individuals with ultra-high risk for psychosis (UHR), and 28 healthy controls (HC). After the professional clinical symptoms evaluation, all the participants were instructed to keep eyes closed for 3-min resting-state EEG recording. The 3-min EEG data were segmented into artefact-free epochs (the length was 3 s), and the functional connectivity of the alpha phase was estimated using the phase lag index (PLI), which measures the phase differences of EEG signals. The FES and UHR groups displayed increased resting-state PLI connectivity compared with the HC group [F(2,74) = 10.804, p < 0.001]. Significant increases in the global efficiency, the local efficiency, and the path length were found in the FES and UHR groups compared with those of the HC group. FES and UHR showed an increased degree of connectivity compared with HC. The degree of the left occipital lobe area was higher in the UHR group than in the FES group. The hypothesis of disconnection is confirmed. Furthermore, differences between the UHR and FES group were found, which is valuable for producing clinical significance before the onset of schizophrenia.
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Affiliation(s)
- Tiantian Liu
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Jian Zhang
- Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Xiaonan Dong
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Zhucheng Li
- College of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China
| | - Xiaorui Shi
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Yizhou Tong
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Ruobing Yang
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Jinglong Wu
- Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Changming Wang
- Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Tianyi Yan
- School of Life Science, Beijing Institute of Technology, Beijing, China
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32
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Wang B, Li P, Li D, Niu Y, Yan T, Li T, Cao R, Yan P, Guo Y, Yang W, Ren Y, Li X, Wang F, Yan T, Wu J, Zhang H, Xiang J. Increased Functional Brain Network Efficiency During Audiovisual Temporal Asynchrony Integration Task in Aging. Front Aging Neurosci 2018; 10:316. [PMID: 30356825 PMCID: PMC6189604 DOI: 10.3389/fnagi.2018.00316] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 09/19/2018] [Indexed: 01/05/2023] Open
Abstract
Audiovisual integration significantly changes over the lifespan, but age-related functional connectivity in audiovisual temporal asynchrony integration tasks remains underexplored. In the present study, electroencephalograms (EEGs) of 27 young adults (22–25 years) and 25 old adults (61–76 years) were recorded during an audiovisual temporal asynchrony integration task with seven conditions [auditory (A), visual (V), AV, A50V, A100V, V50A and V100A]. We calculated the phase lag index (PLI)-weighted connectivity networks modulated by the audiovisual tasks and found that the PLI connections showed obvious dynamic changes after stimulus onset. In the theta (4–7 Hz) and alpha (8–13 Hz) bands, the AV and V50A conditions induced stronger functional connections and higher global and local efficiencies, reflecting a stronger audiovisual integration effect, which was attributed to the auditory information arriving at the primary auditory cortex earlier than the visual information reaching the primary visual cortex. Importantly, the functional connectivity and network efficiencies of old adults revealed higher global and local efficiencies and higher degree in both the theta and alpha bands. These larger network efficiencies indicated that old adults might experience more difficulties in attention and cognitive control during the audiovisual integration task with temporal asynchrony than young adults. There were significant associations between network efficiencies and peak time of integration only in young adults. We propose that an audiovisual task with multiple conditions might arouse the appropriate attention in young adults but would lead to a ceiling effect in old adults. Our findings provide new insights into the network topography of old adults during audiovisual integration and highlight higher functional connectivity and network efficiencies due to greater cognitive demand.
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Affiliation(s)
- Bin Wang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China.,Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Peizhen Li
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Dandan Li
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Yan Niu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Ting Yan
- Translational Medicine Research Center, Shanxi Medical University, Taiyuan, China
| | - Ting Li
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Rui Cao
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Pengfei Yan
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Yuxiang Guo
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Weiping Yang
- Department of Psychology, Faculty of Education, Hubei University, Wuhan, China
| | - Yanna Ren
- Medical Humanities College, Guiyang University of Traditional Chinese Medicine, Guiyang, China
| | - Xinrui Li
- Suzhou North America High School, Suzhou, China
| | | | - Tianyi Yan
- School of Life Science, Beijing Institute of Technology, Beijing, China.,Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China.,Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing Institute of Technology, Beijing, China
| | - Jinglong Wu
- Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing Institute of Technology, Beijing, China.,Graduate School of Natural Science and Technology, Okayama University, Okayama, Japan
| | - Hui Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Jie Xiang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
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Zhang J, Dong X, Wang L, Zhao L, Weng Z, Zhang T, Sui J, Go R, Huang Q, Wu J, Yan T. Gender Differences in Global Functional Connectivity During Facial Emotion Processing: A Visual MMN Study. Front Behav Neurosci 2018; 12:220. [PMID: 30319370 PMCID: PMC6167960 DOI: 10.3389/fnbeh.2018.00220] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2018] [Accepted: 08/30/2018] [Indexed: 11/21/2022] Open
Abstract
To investigate gender differences in functional connectivity during the unattended processing of facial expressions, we recorded visual mismatch negativity (vMMN) in 34 adults using a deviant-standard reverse oddball paradigm. Using wavelet analysis, we calculated the time-frequency (TF) power at each electrode associated with happy-deviant, sad-deviant, happy-standard and sad-standard conditions. We also calculated the phase lag index (PLI) between electrode pairs and analyzed the dynamic network topologies of the functional connectivity for happy and sad vMMNs in the delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz) and gamma (30-45 Hz) bands. The results showed that females induced stronger TF power and PLI values than males in only the alpha band over the whole brain regarding the vMMN. Moreover, females had a higher ratio of the number of connections between long-distance electrode pairs than males. While theoretical analysis of dynamic network topologies indicated that high node degree values were found in local brain regions of males and in almost the entire female brain, our findings suggested that female brain activation and connections between brain regions are not only stronger but also more widely distributed during the unattended processing of facial expressions than those in males.
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Affiliation(s)
- Jian Zhang
- School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing, China
| | - Xiaonan Dong
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Luyao Wang
- School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing, China
| | - Lun Zhao
- School of Psychological Research, Beijing Yiran Sunny Technology Co. Ltd., Beijing, China
| | - Zizheng Weng
- Engineering and Computer Science, University of Denver, Denver, CO, United States
| | | | - Junyu Sui
- Shouguang Xiandai High School, Shandong, China
| | - Ritsu Go
- School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing, China
| | - Qiang Huang
- School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing, China
| | - Jinglong Wu
- School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing, China
| | - Tianyi Yan
- School of Life Science, Beijing Institute of Technology, Beijing, China
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Deng Y, Wang L, Sun X, Liu L, Zhu M, Wang C, Sui B, Shen M, Gu W, Mo D, Ma N, Song L, Li X, Huo X, Miao Z, Chen D, Gao F. Association Between Cerebral Hypoperfusion and Cognitive Impairment in Patients With Chronic Vertebra-Basilar Stenosis. Front Psychiatry 2018; 9:455. [PMID: 30319462 PMCID: PMC6168951 DOI: 10.3389/fpsyt.2018.00455] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 08/31/2018] [Indexed: 12/02/2022] Open
Abstract
Objective: This study aimed to investigate the association between cognitive impairment and cerebral haemodynamic changes in patients with chronic vertebra-basilar (VB) stenosis. Methods: Patients with severe posterior circulation VB stenosis and infarction or a history of infarction for more than 2 weeks from January 2014 to January 2015 were enrolled (n = 96). They were divided into three groups, namely, the computed tomography perfusion (CTP) normal group, the CTP compensated group, and the CTP decompensated group. Cognitive function was assessed using a validated Chinese version of the Mini-Mental State Examination (MMSE), the Frontal Assessment Battery (FAB), and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Regression models were used to identify independent risk factors for cognitive impairment. Results: The MMSE and FAB scores of patients in the CTP decompensated group were significantly lower than those of patients in the CTP normal and CTP compensated groups (all p < 0.05). The RBANS total and its domain scores, including immediate memory, visual acuity, and delayed memory, in the CTP compensated and CTP decompensated groups were significantly lower than those in the CTP normal group (all p < 0.05). Multiple regression analyses showed that CTP compensation, CTP decompensation, severe VB tandem stenosis, and multiple infarctions were independent risk factors for cognitive impairment. Conclusions: Low perfusion caused by severe VB stenosis can lead to extensive cognitive impairments in areas such as immediate memory, visual span, and delayed memory.
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Affiliation(s)
- Yiming Deng
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Luyao Wang
- Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Xuan Sun
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Lian Liu
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Meifang Zhu
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Departments of Neuropsychiatry and Clinical Psychology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunxue Wang
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Departments of Neuropsychiatry and Clinical Psychology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Binbin Sui
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Mi Shen
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Weibin Gu
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China.,Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Dapeng Mo
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Ning Ma
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Ligang Song
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Xiaoqing Li
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Xiaochuan Huo
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Zhongrong Miao
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
| | - Duanduan Chen
- School of Life Science, Beijing Institute of Technology, Beijing, China.,Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, The Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China
| | - Feng Gao
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Center of Stroke, Beijing Institute for Brain Disorders, Beijing, China
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