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Quercetin ameliorates memory impairment by inhibiting abnormal microglial activation in a mouse model of paradoxical sleep deprivation. Biochem Biophys Res Commun 2022; 632:10-16. [DOI: 10.1016/j.bbrc.2022.09.088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 09/12/2022] [Accepted: 09/22/2022] [Indexed: 11/18/2022]
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Ma J, Liu F, Wang Y, Ma L, Niu Y, Wang J, Ye Z, Zhang J. Frequency-dependent white-matter functional network changes associated with cognitive deficits in subcortical vascular cognitive impairment. Neuroimage Clin 2022; 36:103245. [PMID: 36451351 PMCID: PMC9668649 DOI: 10.1016/j.nicl.2022.103245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/07/2022] [Accepted: 10/21/2022] [Indexed: 11/11/2022]
Abstract
Vascular cognitive impairment (VCI) refers to all forms of cognitive decline associated with cerebrovascular diseases, in which white matter (WM) is highly vulnerable. Although previous studies have shown that blood oxygen level-dependent (BOLD) signals inside WM can effectively reflect neural activities, whether WM BOLD signal alterations are present and their roles underlying cognitive impairment in VCI remain largely unknown. In this study, 36 subcortical VCI (SVCI) patients and 36 healthy controls were enrolled to evaluate WM dysfunction. Specifically, fourteen distinct WM networks were identified from resting-state functional MRI using K-means clustering analysis. Subsequently, between-network functional connectivity (FC) and within-network BOLD signal amplitude of WM networks were calculated in three frequency bands (band A: 0.01-0.15 Hz, band B: 0.08-0.15 Hz, and band C: 0.01-0.08 Hz). Patients with SVCI manifested decreased FC mainly in bilateral parietal WM regions, forceps major, superior and inferior longitudinal fasciculi. These connections extensively linked with distinct WM networks and with gray-matter networks such as frontoparietal control, dorsal and ventral attention networks, which exhibited frequency-specific alterations in SVCI. Additionally, extensive amplitude reductions were found in SVCI, showing frequency-dependent properties in parietal, anterior corona radiate, pre/post central, superior and inferior longitudinal fasciculus networks. Furthermore, these decreased FC and amplitudes showed significant positive correlations with cognitive performances in SVCI, and high diagnostic performances for SVCI especially combining all bands. Our study indicated that VCI-related cognitive deficits were characterized by frequency-dependent WM functional abnormalities, which offered novel applicable neuromarkers for VCI.
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Affiliation(s)
- Juanwei Ma
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China,National Clinical Research Center for Cancer, Tianjin, China,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China,Tianjin’s Clinical Research Center for Cancer, Tianjin, China,Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yang Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Lin Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Yali Niu
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jing Wang
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China,National Clinical Research Center for Cancer, Tianjin, China,Key Laboratory of Cancer Prevention and Therapy, Tianjin, China,Tianjin’s Clinical Research Center for Cancer, Tianjin, China,Corresponding authors at: Department of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin 300052, China (J. Zhang). Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Huan-Hu-West Road, Ti-Yuan-Bei, Hexi District, Tianjin 300060, China (Z. Ye).
| | - Jing Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China,Corresponding authors at: Department of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin 300052, China (J. Zhang). Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Huan-Hu-West Road, Ti-Yuan-Bei, Hexi District, Tianjin 300060, China (Z. Ye).
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Mai Z, Li M, Pan L, Ma N. Temporal fluctuations in vigilance and neural networks after sleep deprivation. Eur J Neurosci 2022; 55:1947-1960. [PMID: 35388523 DOI: 10.1111/ejn.15663] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 03/11/2022] [Accepted: 03/29/2022] [Indexed: 11/29/2022]
Abstract
Vigilance instability in the sleep-deprived state was deemed to result from the imbalance in thalamic-FPN-DMN circuits (FPN: frontoparietal network; DMN: default mode network), but the behavioral correlation of this neural hypothesis is still unclear. To address this issue, we applied dynamic functional connectivity (DFC) analysis on the task-based fMRI data and detected high arousal state (HAS) and low arousal state (LAS). Relative to HAS, LAS demonstrated higher positive connectivity within task-positive networks (TPN), attenuated TPN-DMN anti-correlation, and greater anti-correlation between cerebral and subcortico-cerebellar networks. Critically, DFC differences between HAS and LAS were correlated with the ongoing vigilance performance in the sleep-deprived state. The current findings confirmed a direct link between vigilance instability and DFC in the thalamic-FPN-DMN circuits. In particular, we postulated that the integration within task-related system and segregation between task-related system and the subcortico-cerebellar system might be the critical neural markers underlying vigilance instability in the sleep-deprived state.
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Affiliation(s)
- Zifeng Mai
- Key Laboratory of Brain, Cognition and Education Sciences (Ministry of Education), Center for Sleep Research, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health & Cognitive Science, School of Psychology, South China Normal University, Guangzhou, China
| | - Mingzhu Li
- Key Laboratory of Brain, Cognition and Education Sciences (Ministry of Education), Center for Sleep Research, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health & Cognitive Science, School of Psychology, South China Normal University, Guangzhou, China
| | - Leyao Pan
- Key Laboratory of Brain, Cognition and Education Sciences (Ministry of Education), Center for Sleep Research, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health & Cognitive Science, School of Psychology, South China Normal University, Guangzhou, China
| | - Ning Ma
- Key Laboratory of Brain, Cognition and Education Sciences (Ministry of Education), Center for Sleep Research, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health & Cognitive Science, School of Psychology, South China Normal University, Guangzhou, China
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Abstract
Neuroelectrophysiology is an old science, dating to the 18th century when electrical activity in nerves was discovered. Such discoveries have led to a variety of neurophysiological techniques, ranging from basic neuroscience to clinical applications. These clinical applications allow assessment of complex neurological functions such as (but not limited to) sensory perception (vision, hearing, somatosensory function), and muscle function. The ability to use similar techniques in both humans and animal models increases the ability to perform mechanistic research to investigate neurological problems. Good animal to human homology of many neurophysiological systems facilitates interpretation of data to provide cause-effect linkages to epidemiological findings. Mechanistic cellular research to screen for toxicity often includes gaps between cellular and whole animal/person neurophysiological changes, preventing understanding of the complete function of the nervous system. Building Adverse Outcome Pathways (AOPs) will allow us to begin to identify brain regions, timelines, neurotransmitters, etc. that may be Key Events (KE) in the Adverse Outcomes (AO). This requires an integrated strategy, from in vitro to in vivo (and hypothesis generation, testing, revision). Scientists need to determine intermediate levels of nervous system organization that are related to an AO and work both upstream and downstream using mechanistic approaches. Possibly more than any other organ, the brain will require networks of pathways/AOPs to allow sufficient predictive accuracy. Advancements in neurobiological techniques should be incorporated into these AOP-base neurotoxicological assessments, including interactions between many regions of the brain simultaneously. Coupled with advancements in optogenetic manipulation, complex functions of the nervous system (such as acquisition, attention, sensory perception, etc.) can be examined in real time. The integration of neurophysiological changes with changes in gene/protein expression can begin to provide the mechanistic underpinnings for biological changes. Establishment of linkages between changes in cellular physiology and those at the level of the AO will allow construction of biological pathways (AOPs) and allow development of higher throughput assays to test for changes to critical physiological circuits. To allow mechanistic/predictive toxicology of the nervous system to be protective of human populations, neuroelectrophysiology has a critical role in our future.
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Affiliation(s)
- David W Herr
- Neurological and Endocrine Toxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, U.S. Environmental Protection Agency, Washington, NC, United States
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Saha S, Mamun KA, Ahmed K, Mostafa R, Naik GR, Darvishi S, Khandoker AH, Baumert M. Progress in Brain Computer Interface: Challenges and Opportunities. Front Syst Neurosci 2021; 15:578875. [PMID: 33716680 PMCID: PMC7947348 DOI: 10.3389/fnsys.2021.578875] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 01/06/2021] [Indexed: 12/13/2022] Open
Abstract
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
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Affiliation(s)
- Simanto Saha
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Khondaker A. Mamun
- Advanced Intelligent Multidisciplinary Systems (AIMS) Lab, Department of Computer Science and Engineering, United International University, Dhaka, Bangladesh
| | - Khawza Ahmed
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Raqibul Mostafa
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Ganesh R. Naik
- Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - Sam Darvishi
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
| | - Ahsan H. Khandoker
- Healthcare Engineering Innovation Center, Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Mathias Baumert
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
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Farahani ED, Wouters J, van Wieringen A. Brain mapping of auditory steady-state responses: A broad view of cortical and subcortical sources. Hum Brain Mapp 2021; 42:780-796. [PMID: 33166050 PMCID: PMC7814770 DOI: 10.1002/hbm.25262] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 10/13/2020] [Accepted: 10/15/2020] [Indexed: 12/21/2022] Open
Abstract
Auditory steady-state responses (ASSRs) are evoked brain responses to modulated or repetitive acoustic stimuli. Investigating the underlying neural generators of ASSRs is important to gain in-depth insight into the mechanisms of auditory temporal processing. The aim of this study is to reconstruct an extensive range of neural generators, that is, cortical and subcortical, as well as primary and non-primary ones. This extensive overview of neural generators provides an appropriate basis for studying functional connectivity. To this end, a minimum-norm imaging (MNI) technique is employed. We also present a novel extension to MNI which facilitates source analysis by quantifying the ASSR for each dipole. Results demonstrate that the proposed MNI approach is successful in reconstructing sources located both within (primary) and outside (non-primary) of the auditory cortex (AC). Primary sources are detected in different stimulation conditions (four modulation frequencies and two sides of stimulation), thereby demonstrating the robustness of the approach. This study is one of the first investigations to identify non-primary sources. Moreover, we show that the MNI approach is also capable of reconstructing the subcortical activities of ASSRs. Finally, the results obtained using the MNI approach outperform the group-independent component analysis method on the same data, in terms of detection of sources in the AC, reconstructing the subcortical activities and reducing computational load.
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Affiliation(s)
- Ehsan Darestani Farahani
- Research Group Experimental ORL, Department of NeurosciencesKatholieke Universiteit LeuvenLeuvenBelgium
| | - Jan Wouters
- Research Group Experimental ORL, Department of NeurosciencesKatholieke Universiteit LeuvenLeuvenBelgium
| | - Astrid van Wieringen
- Research Group Experimental ORL, Department of NeurosciencesKatholieke Universiteit LeuvenLeuvenBelgium
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Min BK, Kim HS, Pinotsis DA, Pantazis D. Thalamocortical inhibitory dynamics support conscious perception. Neuroimage 2020; 220:117066. [PMID: 32565278 DOI: 10.1016/j.neuroimage.2020.117066] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 05/25/2020] [Accepted: 06/14/2020] [Indexed: 11/28/2022] Open
Abstract
Whether thalamocortical interactions play a decisive role in conscious perception remains an open question. We presented rapid red/green color flickering stimuli, which induced the mental perception of either an illusory orange color or non-fused red and green colors. Using magnetoencephalography, we observed 6-Hz thalamic activity associated with thalamocortical inhibitory coupling only during the conscious perception of the illusory orange color. This sustained thalamic disinhibition was temporally coupled with higher visual cortical activation during the conscious perception of the orange color, providing neurophysiological evidence of the role of thalamocortical synchronization in conscious awareness of mental representation. Bayesian model comparison consistently supported the thalamocortical model in conscious perception. Taken together, experimental and theoretical evidence established the thalamocortical inhibitory network as a gateway to conscious mental representations.
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Affiliation(s)
- Byoung-Kyong Min
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Hyun Seok Kim
- Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Dimitris A Pinotsis
- Center for Mathematical Neuroscience and Psychology, Department of Psychology, City-University of London, London, EC1V 0HB, UK; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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Dong X, Hao X, Xu P, Fan M, Wang X, Huang X, Jiang P, Zeng L, Xie Y. RNA sequencing analysis of cortex and hippocampus in a kainic acid rat model of temporal lobe epilepsy to identify mechanisms and therapeutic targets related to inflammation, immunity and cognition. Int Immunopharmacol 2020; 87:106825. [DOI: 10.1016/j.intimp.2020.106825] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 07/16/2020] [Accepted: 07/19/2020] [Indexed: 01/31/2023]
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Kim DJ, Min BK. Rich-club in the brain's macrostructure: Insights from graph theoretical analysis. Comput Struct Biotechnol J 2020; 18:1761-1773. [PMID: 32695269 PMCID: PMC7355726 DOI: 10.1016/j.csbj.2020.06.039] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 06/19/2020] [Accepted: 06/22/2020] [Indexed: 02/07/2023] Open
Abstract
The brain is a complex network. Growing evidence supports the critical roles of a set of brain regions within the brain network, known as the brain’s cores or hubs. These regions require high energy cost but possess highly efficient neural information transfer in the brain’s network and are termed the rich-club. The rich-club of the brain network is essential as it directly regulates functional integration across multiple segregated regions and helps to optimize cognitive processes. Here, we review the recent advances in rich-club organization to address the fundamental roles of the rich-club in the brain and discuss how these core brain regions affect brain development and disorders. We describe the concepts of the rich-club behind network construction in the brain using graph theoretical analysis. We also highlight novel insights based on animal studies related to the rich-club and illustrate how human studies using neuroimaging techniques for brain development and psychiatric/neurological disorders may be relevant to the rich-club phenomenon in the brain network.
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Key Words
- AD, Alzheimer’s disease
- ADHD, attention deficit hyperactivity disorder
- ASD, autism spectrum disorder
- BD, bipolar disorder
- Brain connectivity
- Brain network
- DTI, diffusion tensor imaging
- EEG, electroencephalography
- Graph theory
- MDD, major depressive disorder
- MEG, magnetoencephalography
- MRI, magnetic resonance imaging
- Neuroimaging
- Rich-club
- TBI, traumatic brain injury
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Affiliation(s)
- Dae-Jin Kim
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Byoung-Kyong Min
- Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea
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