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Hanzal S, Learmonth G, Thut G, Harvey M. Probing sustained attention and fatigue across the lifespan. PLoS One 2024; 19:e0292695. [PMID: 39018279 PMCID: PMC11253940 DOI: 10.1371/journal.pone.0292695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 04/24/2024] [Indexed: 07/19/2024] Open
Abstract
Trait fatigues reflects tiredness that persists throughout a prolonged period, whereas state fatigue is a short-term reaction to intense or prolonged effort. We investigated the impact of sustained attention (using the SART) on both trait and state fatigue levels in the general population. An online version of the SART was undertaken by 115 participants, stratified across the whole adult lifespan. While pre-task trait fatigue was a strong indicator of the initial state fatigue levels, undergoing the task itself induced an increase in reported subjective state fatigue, and an accompanying reduction in subjective energy rating. Consistent with this finding, greater subjective state fatigue levels were associated with reduced accuracy. In addition, age was the best predictor of inter-participant accuracy (the older the participants, the greater the accuracy), and learning (i.e., task duration reducing reaction times). Moreover, a ceiling effect occurred where participants with higher trait fatigue did not experience greater state fatigue changes relative to those with low trait scores. In summary, we found improved accuracy in older adults, as well as a tight coupling between state fatigue and SART performance decline (in an online environment). The findings warrant further investigation into fatigue as a dynamic, task-dependent state and into SART performance as an objective measure and inducer of fatigue.
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Affiliation(s)
- Simon Hanzal
- School of Psychology and Neuroscience University of Glasgow, Glasgow, United Kingdom
| | - Gemma Learmonth
- School of Psychology and Neuroscience University of Glasgow, Glasgow, United Kingdom
- Faculty of Natural Sciences, University of Stirling, Stirling, United Kingdom
| | - Gregor Thut
- School of Psychology and Neuroscience University of Glasgow, Glasgow, United Kingdom
| | - Monika Harvey
- School of Psychology and Neuroscience University of Glasgow, Glasgow, United Kingdom
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2
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Montemurro S, Borek D, Marinazzo D, Zago S, Masina F, Napoli E, Filippini N, Arcara G. Aperiodic component of EEG power spectrum and cognitive performance are modulated by education in aging. Sci Rep 2024; 14:15111. [PMID: 38956186 PMCID: PMC11220063 DOI: 10.1038/s41598-024-66049-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 06/26/2024] [Indexed: 07/04/2024] Open
Abstract
Recent studies have shown a growing interest in the so-called "aperiodic" component of the EEG power spectrum, which describes the overall trend of the whole spectrum with a linear or exponential function. In the field of brain aging, this aperiodic component is associated both with age-related changes and performance on cognitive tasks. This study aims to elucidate the potential role of education in moderating the relationship between resting-state EEG features (including aperiodic component) and cognitive performance in aging. N = 179 healthy participants of the "Leipzig Study for Mind-Body-Emotion Interactions" (LEMON) dataset were divided into three groups based on age and education. Older adults exhibited lower exponent, offset (i.e. measures of aperiodic component), and Individual Alpha Peak Frequency (IAPF) as compared to younger adults. Moreover, visual attention and working memory were differently associated with the aperiodic component depending on education: in older adults with high education, higher exponent predicted slower processing speed and less working memory capacity, while an opposite trend was found in those with low education. While further investigation is needed, this study shows the potential modulatory role of education in the relationship between the aperiodic component of the EEG power spectrum and aging cognition.
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Affiliation(s)
- Sonia Montemurro
- Department of Philosophy, Sociology, Pedagogy and Applied Psychology, FISPPA, University of Padova, Padua, Italy.
| | - Daniel Borek
- Department of Data-Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
| | - Daniele Marinazzo
- Department of Data-Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
| | - Sara Zago
- IRCCS San Camillo Hospital, Venice, Italy
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Krothapalli M, Buddendorff L, Yadav H, Schilaty ND, Jain S. From Gut Microbiota to Brain Waves: The Potential of the Microbiome and EEG as Biomarkers for Cognitive Impairment. Int J Mol Sci 2024; 25:6678. [PMID: 38928383 PMCID: PMC11203453 DOI: 10.3390/ijms25126678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 06/09/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024] Open
Abstract
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder and a leading cause of dementia. Aging is a significant risk factor for AD, emphasizing the importance of early detection since symptoms cannot be reversed once the advanced stage is reached. Currently, there is no established method for early AD diagnosis. However, emerging evidence suggests that the microbiome has an impact on cognitive function. The gut microbiome and the brain communicate bidirectionally through the gut-brain axis, with systemic inflammation identified as a key connection that may contribute to AD. Gut dysbiosis is more prevalent in individuals with AD compared to their cognitively healthy counterparts, leading to increased gut permeability and subsequent systemic inflammation, potentially causing neuroinflammation. Detecting brain activity traditionally involves invasive and expensive methods, but electroencephalography (EEG) poses as a non-invasive alternative. EEG measures brain activity and multiple studies indicate distinct patterns in individuals with AD. Furthermore, EEG patterns in individuals with mild cognitive impairment differ from those in the advanced stage of AD, suggesting its potential as a method for early indication of AD. This review aims to consolidate existing knowledge on the microbiome and EEG as potential biomarkers for early-stage AD, highlighting the current state of research and suggesting avenues for further investigation.
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Affiliation(s)
- Mahathi Krothapalli
- USF Center for Microbiome Research, Microbiomes Institute, University of South Florida, Tampa, FL 33612, USA; (M.K.); (L.B.); (H.Y.)
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL 33612, USA;
| | - Lauren Buddendorff
- USF Center for Microbiome Research, Microbiomes Institute, University of South Florida, Tampa, FL 33612, USA; (M.K.); (L.B.); (H.Y.)
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL 33612, USA;
| | - Hariom Yadav
- USF Center for Microbiome Research, Microbiomes Institute, University of South Florida, Tampa, FL 33612, USA; (M.K.); (L.B.); (H.Y.)
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL 33612, USA;
| | - Nathan D. Schilaty
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL 33612, USA;
- Center for Neuromusculoskeletal Research, University of South Florida, Tampa, FL 33612, USA
| | - Shalini Jain
- USF Center for Microbiome Research, Microbiomes Institute, University of South Florida, Tampa, FL 33612, USA; (M.K.); (L.B.); (H.Y.)
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL 33612, USA;
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Hebron H, Lugli B, Dimitrova R, Jaramillo V, Yeh LR, Rhodes E, Grossman N, Dijk DJ, Violante IR. A closed-loop auditory stimulation approach selectively modulates alpha oscillations and sleep onset dynamics in humans. PLoS Biol 2024; 22:e3002651. [PMID: 38889194 PMCID: PMC11185466 DOI: 10.1371/journal.pbio.3002651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/01/2024] [Indexed: 06/20/2024] Open
Abstract
Alpha oscillations play a vital role in managing the brain's resources, inhibiting neural activity as a function of their phase and amplitude, and are changed in many brain disorders. Developing minimally invasive tools to modulate alpha activity and identifying the parameters that determine its response to exogenous modulators is essential for the implementation of focussed interventions. We introduce Alpha Closed-Loop Auditory Stimulation (αCLAS) as an EEG-based method to modulate and investigate these brain rhythms in humans with specificity and selectivity, using targeted auditory stimulation. Across a series of independent experiments, we demonstrate that αCLAS alters alpha power, frequency, and connectivity in a phase, amplitude, and topography-dependent manner. Using single-pulse-αCLAS, we show that the effects of auditory stimuli on alpha oscillations can be explained within the theoretical framework of oscillator theory and a phase-reset mechanism. Finally, we demonstrate the functional relevance of our approach by showing that αCLAS can interfere with sleep onset dynamics in a phase-dependent manner.
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Affiliation(s)
- Henry Hebron
- School of Psychology, University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, United Kingdom
| | - Beatrice Lugli
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Radost Dimitrova
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Valeria Jaramillo
- School of Psychology, University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, United Kingdom
| | - Lisa R. Yeh
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Edward Rhodes
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute Imperial College London, United Kingdom
| | - Nir Grossman
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute Imperial College London, United Kingdom
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, United Kingdom
| | - Ines R. Violante
- School of Psychology, University of Surrey, Guildford, United Kingdom
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Huang Y, Cao C, Dai S, Deng H, Su L, Zheng JS. Magnetoencephalography-derived oscillatory microstate patterns across lifespan: the Cambridge centre for ageing and neuroscience cohort. Brain Commun 2024; 6:fcae150. [PMID: 38745970 PMCID: PMC11091929 DOI: 10.1093/braincomms/fcae150] [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: 08/16/2023] [Revised: 03/01/2024] [Accepted: 04/26/2024] [Indexed: 05/16/2024] Open
Abstract
The aging brain represents the primary risk factor for many neurodegenerative disorders. Whole-brain oscillations may contribute novel early biomarkers of aging. Here, we investigated the dynamic oscillatory neural activities across lifespan (from 18 to 88 years) using resting Magnetoencephalography (MEG) in a large cohort of 624 individuals. Our aim was to examine the patterns of oscillation microstates during the aging process. By using a machine-learning algorithm, we identify four typical clusters of microstate patterns across different age groups and different frequency bands: left-to-right topographic MS1, right-to-left topographic MS2, anterior-posterior MS3 and fronto-central MS4. We observed a decreased alpha duration and an increased alpha occurrence for sensory-related microstate patterns (MS1 & MS2). Accordingly, theta and beta changes from MS1 & MS2 may be related to motor decline that increased with age. Furthermore, voluntary 'top-down' saliency/attention networks may be reflected by the increased MS3 & MS4 alpha occurrence and complementary beta activities. The findings of this study advance our knowledge of how the aging brain shows dysfunctions in neural state transitions. By leveraging the identified microstate patterns, this study provides new insights into predicting healthy aging and the potential neuropsychiatric cognitive decline.
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Affiliation(s)
- Yujing Huang
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, Zhejiang Province, China
- Research Center for Industries of the Future, School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang Province, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, Zhejiang Province, China
- Institute of Biology, Westlake Institute for Advanced Study, Hangzhou 310024, Zhejiang Province, China
| | - Chenglong Cao
- Department of Neurosurgery, The First Affiliated Hospital of University of Science and Technology of China, Hefei 230001, Anhui, China
| | - Shenyi Dai
- Department of Economics and Management, China Jiliang University, Hangzhou 310024, Zhejiang Province, China
- Hangzhou iNeuro Technology Co., LTD, Hangzhou 310024, Zhejiang Province, China
| | - Hu Deng
- Peking University Huilongguan Clinical Medical School, Beijing Huilongguan Hospital, Beijing 100096, China
| | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridge CB20SZ, United Kingdom
- Neuroscience Institute, University of Sheffield, Sheffield, South Yorkshire S102HQ, United Kingdom
| | - Ju-Sheng Zheng
- Zhejiang Key Laboratory of Multi-Omics in Infection and Immunity, Center for Infectious Disease Research, School of Medicine, Westlake University, Hangzhou 310024, Zhejiang Province, China
- Research Center for Industries of the Future, School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang Province, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, Zhejiang Province, China
- Institute of Biology, Westlake Institute for Advanced Study, Hangzhou 310024, Zhejiang Province, China
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Kang JH, Bae JH, Jeon YJ. Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review. Bioengineering (Basel) 2024; 11:418. [PMID: 38790286 PMCID: PMC11118246 DOI: 10.3390/bioengineering11050418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024] Open
Abstract
The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.
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Affiliation(s)
- Jae-Hwan Kang
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Jang-Han Bae
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Young-Ju Jeon
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
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7
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Auer T, Goldthorpe R, Peach R, Hebron H, Violante IR. Functionally annotated electrophysiological neuromarkers of healthy ageing and memory function. Hum Brain Mapp 2024; 45:e26687. [PMID: 38651629 PMCID: PMC11036379 DOI: 10.1002/hbm.26687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 02/22/2024] [Accepted: 04/05/2024] [Indexed: 04/25/2024] Open
Abstract
The unprecedented increase in life expectancy presents a unique opportunity and the necessity to explore both healthy and pathological aspects of ageing. Electroencephalography (EEG) has been widely used to identify neuromarkers of cognitive ageing due to its affordability and richness in information. However, despite the growing volume of data and methodological advancements, the abundance of contradictory and non-reproducible findings has hindered clinical translation. To address these challenges, our study introduces a comprehensive workflow expanding on previous EEG studies and investigates various static and dynamic power and connectivity estimates as potential neuromarkers of cognitive ageing in a large dataset. We also assess the robustness of our findings by testing their susceptibility to band specification. Finally, we characterise our findings using functionally annotated brain networks to improve their interpretability and multi-modal integration. Our analysis demonstrates the effect of methodological choices on findings and that dynamic rather than static neuromarkers are not only more sensitive but also more robust. Consequently, they emerge as strong candidates for cognitive ageing neuromarkers. Moreover, we were able to replicate the most established EEG findings in cognitive ageing, such as alpha oscillation slowing, increased beta power, reduced reactivity across multiple bands, and decreased delta connectivity. Additionally, when considering individual variations in the alpha band, we clarified that alpha power is characteristic of memory performance rather than ageing, highlighting its potential as a neuromarker for cognitive ageing. Finally, our approach using functionally annotated source reconstruction allowed us to provide insights into domain-specific electrophysiological mechanisms underlying memory performance and ageing. HIGHLIGHTS: We provide an open and reproducible pipeline with a comprehensive workflow to investigate static and dynamic EEG neuromarkers. Neuromarkers related to neural dynamics are sensitive and robust. Individualised alpha power characterises cognitive performance rather than ageing. Functional annotation allows cross-modal interpretation of EEG findings.
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Affiliation(s)
- Tibor Auer
- School of PsychologyUniversity of SurreyGuildfordUK
| | | | | | - Henry Hebron
- School of PsychologyUniversity of SurreyGuildfordUK
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8
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Park J, Ho RLM, Wang WE, Nguyen VQ, Coombes SA. The effect of age on alpha rhythms in the human brain derived from source localized resting-state electroencephalography. Neuroimage 2024; 292:120614. [PMID: 38631618 DOI: 10.1016/j.neuroimage.2024.120614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 04/12/2024] [Accepted: 04/15/2024] [Indexed: 04/19/2024] Open
Abstract
With increasing age, peak alpha frequency (PAF) is slowed, and alpha power is reduced during resting-states with eyes closed. These age-related changes are evident across the whole scalp but remained unclear at the source level. The purpose of this study was to determine whether age impacts the power and frequency of the dominant alpha rhythm equally across source generators or whether the impact of age varies across sources. A total of 28 young adults and 26 elderly adults were recruited. High-density EEG was recorded for 10 mins with eyes closed. Single dipoles for each independent component were localized and clustered based on their anatomical label, resulting in 36 clusters. Meta-analyses were then conducted to assess effect sizes for PAF and power at PAF for all 36 clusters. Subgroup analyses were then implemented for frontal, sensorimotor, parietal, temporal, and occipital regions. The results of the meta-analyses showed that the elderly group exhibited slower PAF and less power at PAF compared to the young group. Subgroup analyses revealed age effects on PAF in parietal (g = 0.38), temporal (g = 0.65), and occipital regions (g = 1.04), with the largest effects observed in occipital regions. For power at PAF, age effects were observed in sensorimotor (g = 0.84) and parietal regions (g = 0.80), with the sensorimotor region showing the largest effect. Our findings show that age-related slowing and attenuation of the alpha rhythm manifests differentially across cortical regions, with sensorimotor and occipital regions most susceptible to age effects.
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Affiliation(s)
- Jinhan Park
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32611, USA
| | - Rachel L M Ho
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32611, USA
| | - Wei-En Wang
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32611, USA
| | - Vinh Q Nguyen
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32611, USA
| | - Stephen A Coombes
- Laboratory for Rehabilitation Neuroscience, Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL 32611, USA; Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA.
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Klein A, Aeschlimann SA, Zubler F, Scutelnic A, Riederer F, Ertl M, Schankin CJ. Alterations of the alpha rhythm in visual snow syndrome: a case-control study. J Headache Pain 2024; 25:53. [PMID: 38584260 PMCID: PMC11000394 DOI: 10.1186/s10194-024-01754-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 03/19/2024] [Indexed: 04/09/2024] Open
Abstract
BACKGROUND Visual snow syndrome is a disorder characterized by the combination of typical perceptual disturbances. The clinical picture suggests an impairment of visual filtering mechanisms and might involve primary and secondary visual brain areas, as well as higher-order attentional networks. On the level of cortical oscillations, the alpha rhythm is a prominent EEG pattern that is involved in the prioritisation of visual information. It can be regarded as a correlate of inhibitory modulation within the visual network. METHODS Twenty-one patients with visual snow syndrome were compared to 21 controls matched for age, sex, and migraine. We analysed the resting-state alpha rhythm by identifying the individual alpha peak frequency using a Fast Fourier Transform and then calculating the power spectral density around the individual alpha peak (+/- 1 Hz). We anticipated a reduced power spectral density in the alpha band over the primary visual cortex in participants with visual snow syndrome. RESULTS There were no significant differences in the power spectral density in the alpha band over the occipital electrodes (O1 and O2), leading to the rejection of our primary hypothesis. However, the power spectral density in the alpha band was significantly reduced over temporal and parietal electrodes. There was also a trend towards increased individual alpha peak frequency in the subgroup of participants without comorbid migraine. CONCLUSIONS Our main finding was a decreased power spectral density in the alpha band over parietal and temporal brain regions corresponding to areas of the secondary visual cortex. These findings complement previous functional and structural imaging data at a electrophysiological level. They underscore the involvement of higher-order visual brain areas, and potentially reflect a disturbance in inhibitory top-down modulation. The alpha rhythm alterations might represent a novel target for specific neuromodulation. TRIAL REGISTRATION we preregistered the study before preprocessing and data analysis on the platform osf.org (DOI: https://doi.org/10.17605/OSF.IO/XPQHF , date of registration: November 19th 2022).
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Affiliation(s)
- Antonia Klein
- Department of Neurology Inselspital, Bern University Hospital, University of Bern, Rosenbühlgasse 25, Bern, CH-3010, Switzerland
| | - Sarah A Aeschlimann
- Department of Neurology Inselspital, Bern University Hospital, University of Bern, Rosenbühlgasse 25, Bern, CH-3010, Switzerland
| | - Frederic Zubler
- Department of Neurology Inselspital, Bern University Hospital, University of Bern, Rosenbühlgasse 25, Bern, CH-3010, Switzerland
| | - Adrian Scutelnic
- Department of Neurology Inselspital, Bern University Hospital, University of Bern, Rosenbühlgasse 25, Bern, CH-3010, Switzerland
| | - Franz Riederer
- Department of Neurology Inselspital, Bern University Hospital, University of Bern, Rosenbühlgasse 25, Bern, CH-3010, Switzerland
| | - Matthias Ertl
- Department of Psychology, University of Bern, Bern, CH 3010, Switzerland
- Neurocenter, Luzerner Kantonsspital, Lucerne, 6000, Switzerland
| | - Christoph J Schankin
- Department of Neurology Inselspital, Bern University Hospital, University of Bern, Rosenbühlgasse 25, Bern, CH-3010, Switzerland.
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10
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Issabekov G, Matsumoto T, Hoshi H, Fukasawa K, Ichikawa S, Shigihara Y. Resting-state brain activity distinguishes patients with generalised epilepsy from others. Seizure 2024; 115:50-58. [PMID: 38183828 DOI: 10.1016/j.seizure.2024.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/14/2023] [Accepted: 01/01/2024] [Indexed: 01/08/2024] Open
Abstract
PURPOSE Epilepsy is a prevalent neurological disorder characterised by repetitive seizures. It is categorised into three types: generalised epilepsy (GE), focal epilepsy (FE), and combined generalised and focal epilepsy. Correctly subtyping the epilepsy is important to select appropriate treatments. The types are mainly determined (i.e., diagnosed) by their semiologies supported by clinical examinations, such as electroencephalography and magnetoencephalography (MEG). Although these examinations are traditionally based on visual inspections of interictal epileptic discharges (IEDs), which are not always visible, alternative analyses have been anticipated. We examined if resting-state brain activities can distinguish patients with GE, which would help us to diagnose the type of epilepsy. METHODS The 5 min resting-state brain activities acquired using MEG were obtained retrospectively from 15 patients with GE. The cortical source of the activities was estimated at each frequency band from delta to high-frequency oscillation (HFO). These estimated activities were compared with reference datasets from 133 healthy individuals and control data from 29 patients with FE. RESULTS Patients with GE showed larger theta in the occipital, alpha in the left temporal, HFO in the rostral deep regions, and smaller HFO in the caudal ventral regions. Their area under the curves of the receiver operating characteristic curves was around 0.8-0.9. The distinctive pattern was not found for data from FE. CONCLUSION Patients with GE show distinctive resting-state brain activity, which could be a potential biomarker and used complementarily to classical analysis based on the visual inspection of IEDs.
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Affiliation(s)
- Galymzhan Issabekov
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Takahiro Matsumoto
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro 080-0833, Japan
| | - Keisuke Fukasawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Sayuri Ichikawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya 360-8567, Japan
| | - Yoshihito Shigihara
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya 360-8567, Japan; Precision Medicine Centre, Hokuto Hospital, Obihiro 080-0833, Japan.
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11
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Chino B, López-Sanz D, Doval S, Torres-Simón L, de Frutos Lucas J, Giménez-Llort L, Zegarra-Valdivia J, Maestú F. Resting State Electrophysiological Profiles and Their Relationship with Cognitive Performance in Cognitively Unimpaired Older Adults: A Systematic Review. J Alzheimers Dis 2024; 100:453-468. [PMID: 38875030 PMCID: PMC11307078 DOI: 10.3233/jad-231009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/11/2024] [Indexed: 06/16/2024]
Abstract
Background Aging is a complex and natural process. The physiological decline related to aging is accompanied by a slowdown in cognitive processes, which begins shortly after individuals reach maturity. These changes have been sometimes interpreted as a compensatory sign and others as a fingerprint of deterioration. Objective In this context, our aim is to uncover the mechanisms that underlie and support normal cognitive functioning in the brain during the later stages of life. Methods With this purpose, a systematic literature search was conducted using PubMed, Scopus, and Web of Science databases, which identified 781 potential articles. After applying inclusion and exclusion criteria, we selected 12 studies that examined the brain oscillations patterns in resting-state conditions associated with cognitive performance in cognitively unimpaired older adults. Results Although cognitive healthy aging was characterized differently across studies, and various approaches to analyzing brain activity were employed, our review indicates a relationship between alpha peak frequency (APF) and improved performance in neuropsychological scores among cognitively unimpaired older adults. Conclusions A higher APF is linked with a higher score in intelligence, executive function, and general cognitive performance, and could be considered an optimal, and easy-to-assess, electrophysiological marker of cognitive health in older adults.
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Affiliation(s)
- Brenda Chino
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Institute of Neuroscience, Autonomous University of Barcelona (UAB), Barcelona, Spain
- Achucarro Basque Center for Neuroscience, Leioa, Spain
| | - David López-Sanz
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Sandra Doval
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Lucía Torres-Simón
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Jaisalmer de Frutos Lucas
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
| | - Lydia Giménez-Llort
- Institute of Neuroscience, Autonomous University of Barcelona (UAB), Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona (UAB), Barcelona, Spain
| | | | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
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12
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Löffler BS, Stecher HI, Meiser A, Fudickar S, Hein A, Herrmann CS. Attempting to counteract vigilance decrement in older adults with brain stimulation. FRONTIERS IN NEUROERGONOMICS 2023; 4:1201702. [PMID: 38234473 PMCID: PMC10790873 DOI: 10.3389/fnrgo.2023.1201702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 11/23/2023] [Indexed: 01/19/2024]
Abstract
Introduction Against the background of demographic change and the need for enhancement techniques for an aging society, we set out to repeat a study that utilized 40-Hz transcranial alternating current stimulation (tACS) to counteract the slowdown of reaction times in a vigilance experiment but with participants aged 65 years and older. On an oscillatory level, vigilance decrement is linked to rising occipital alpha power, which has been shown to be downregulated using gamma-tACS. Method We applied tACS on the visual cortex and compared reaction times, error rates, and alpha power of a group stimulated with 40 Hz to a sham and a 5-Hz-stimulated control group. All groups executed two 30-min-long blocks of a visual task and were stimulated according to group in the second block. We hypothesized that the expected increase in reaction times and alpha power would be reduced in the 40-Hz group compared to the control groups in the second block (INTERVENTION). Results Statistical analysis with linear mixed models showed that reaction times increased significantly over time in the first block (BASELINE) with approximately 3 ms/min for the SHAM and 2 ms/min for the 5-Hz and 40-Hz groups, with no difference between the groups. The increase was less pronounced in the INTERVENTION block (1 ms/min for SHAM and 5-Hz groups, 3 ms/min for the 40-Hz group). Differences among groups in the INTERVENTION block were not significant if the 5-Hz or the 40-Hz group was used as the base group for the linear mixed model. Statistical analysis with a generalized linear mixed model showed that alpha power was significantly higher after the experiment (1.37 μV2) compared to before (1 μV2). No influence of stimulation (40 Hz, 5 Hz, or sham) could be detected. Discussion Although the literature has shown that tACS offers potential for older adults, our results indicate that findings from general studies cannot simply be transferred to an old-aged group. We suggest adjusting stimulation parameters to the neurophysiological features expected in this group. Next to heterogeneity and cognitive fitness, the influence of motivation and medication should be considered.
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Affiliation(s)
- Birte S. Löffler
- Assistance Systems and Medical Device Technology, Department of Health Services Research, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
| | - Heiko I. Stecher
- Experimental Psychology Lab, Department of Psychology, European Medical School, Cluster of Excellence “Hearing4all”, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
| | - Arnd Meiser
- Experimental Psychology Lab, Department of Psychology, European Medical School, Cluster of Excellence “Hearing4all”, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
| | - Sebastian Fudickar
- Assistance Systems and Medical Device Technology, Department of Health Services Research, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
| | - Andreas Hein
- Assistance Systems and Medical Device Technology, Department of Health Services Research, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
| | - Christoph S. Herrmann
- Experimental Psychology Lab, Department of Psychology, European Medical School, Cluster of Excellence “Hearing4all”, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
- Research Center Neurosensory Science, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
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13
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Rabiller G, Ip Z, Zarrabian S, Zhang H, Sato Y, Yazdan-Shahmorad A, Liu J. Type-2 Diabetes Alters Hippocampal Neural Oscillations and Disrupts Synchrony between the Hippocampus and Cortex. Aging Dis 2023:AD.2023.1106. [PMID: 38029397 DOI: 10.14336/ad.2023.1106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 11/06/2023] [Indexed: 12/01/2023] Open
Abstract
Type 2 diabetes mellitus (T2DM) increases the risk of neurological diseases, yet how brain oscillations change as age and T2DM interact is not well characterized. To delineate the age and diabetic effect on neurophysiology, we recorded local field potentials with multichannel electrodes spanning the somatosensory cortex and hippocampus (HPC) under urethane anesthesia in diabetic and normoglycemic control mice, at 200 and 400 days of age. We analyzed the signal power of brain oscillations, brain state, sharp wave associate ripples (SPW-Rs), and functional connectivity between the cortex and HPC. We found that while both age and T2DM were correlated with a breakdown in long-range functional connectivity and reduced neurogenesis in the dentate gyrus and subventricular zone, T2DM further slowed brain oscillations and reduced theta-gamma coupling. Age and T2DM also prolonged the duration of SPW-Rs and increased gamma power during SPW-R phase. Our results have identified potential electrophysiological substrates of hippocampal changes associated with T2DM and age. The perturbed brain oscillation features and diminished neurogenesis may underlie T2DM-accelerated cognitive impairment.
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Affiliation(s)
- Gratianne Rabiller
- Department of Neurological Surgery, University of California at San Francisco, San Francisco, CA, USA
- San Francisco VA medical Center, San Francisco, CA, USA
| | - Zachary Ip
- Departments of Bioengineering, University of Washington, Seattle, WA, USA
| | - Shahram Zarrabian
- Department of Neurological Surgery, University of California at San Francisco, San Francisco, CA, USA
- San Francisco VA medical Center, San Francisco, CA, USA
| | - Hongxia Zhang
- Department of Neurological Surgery, University of California at San Francisco, San Francisco, CA, USA
- San Francisco VA medical Center, San Francisco, CA, USA
| | - Yoshimichi Sato
- Department of Neurological Surgery, University of California at San Francisco, San Francisco, CA, USA
- San Francisco VA medical Center, San Francisco, CA, USA
- Department of Neurosurgery, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Azadeh Yazdan-Shahmorad
- Departments of Bioengineering, University of Washington, Seattle, WA, USA
- Electrical and Computer Engineering, University of Washington, Seattle, WA, USA
| | - Jialing Liu
- Department of Neurological Surgery, University of California at San Francisco, San Francisco, CA, USA
- San Francisco VA medical Center, San Francisco, CA, USA
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14
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Turner C, Baylan S, Bracco M, Cruz G, Hanzal S, Keime M, Kuye I, McNeill D, Ng Z, van der Plas M, Ruzzoli M, Thut G, Trajkovic J, Veniero D, Wale SP, Whear S, Learmonth G. Developmental changes in individual alpha frequency: Recording EEG data during public engagement events. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2023; 1:1-14. [PMID: 37719836 PMCID: PMC10503479 DOI: 10.1162/imag_a_00001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 09/19/2023]
Abstract
Statistical power in cognitive neuroimaging experiments is often very low. Low sample size can reduce the likelihood of detecting real effects (false negatives) and increase the risk of detecting non-existing effects by chance (false positives). Here, we document our experience of leveraging a relatively unexplored method of collecting a large sample size for simple electroencephalography (EEG) studies: by recording EEG in the community during public engagement and outreach events. We collected data from 346 participants (189 females, age range 6-76 years) over 6 days, totalling 29 hours, at local science festivals. Alpha activity (6-15 Hz) was filtered from 30 seconds of signal, recorded from a single electrode placed between the occipital midline (Oz) and inion (Iz) while the participants rested with their eyes closed. A total of 289 good-quality datasets were obtained. Using this community-based approach, we were able to replicate controlled, lab-based findings: individual alpha frequency (IAF) increased during childhood, reaching a peak frequency of 10.28 Hz at 28.1 years old, and slowed again in middle and older age. Total alpha power decreased linearly, but the aperiodic-adjusted alpha power did not change over the lifespan. Aperiodic slopes and intercepts were highest in the youngest participants. There were no associations between these EEG indexes and self-reported fatigue, measured by the Multidimensional Fatigue Inventory. Finally, we present a set of important considerations for researchers who wish to collect EEG data within public engagement and outreach environments.
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Affiliation(s)
- Christopher Turner
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Satu Baylan
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Martina Bracco
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Gabriela Cruz
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Simon Hanzal
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Marine Keime
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Isaac Kuye
- School of Molecular Biosciences, University of Glasgow, Glasgow, Scotland
| | - Deborah McNeill
- School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow, Glasgow, Scotland
| | - Zika Ng
- School of Molecular Biosciences, University of Glasgow, Glasgow, Scotland
| | - Mircea van der Plas
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Manuela Ruzzoli
- Basque Center on Cognition Brain and Language (BCBL), Donostia/San Sebastian, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Gregor Thut
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Jelena Trajkovic
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Domenica Veniero
- School of Psychology, University of Nottingham, Nottingham, United Kingdom
| | - Sarah P. Wale
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Sarah Whear
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
| | - Gemma Learmonth
- School of Psychology & Neuroscience, University of Glasgow, Glasgow, Scotland
- Division of Psychology, University of Stirling, Stirling, Scotland
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15
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Ibitoye RT, Castro P, Ellmers TJ, Kaski DN, Bronstein AM. Vestibular loss disrupts visual reactivity in the alpha EEG rhythm. Neuroimage Clin 2023; 39:103469. [PMID: 37459699 PMCID: PMC10368920 DOI: 10.1016/j.nicl.2023.103469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/11/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023]
Abstract
The alpha rhythm is a dominant electroencephalographic oscillation relevant to sensory-motor and cognitive function. Alpha oscillations are reactive, being for example enhanced by eye closure, and suppressed following eye opening. The determinants of inter-individual variability in reactivity in the alpha rhythm (e.g. changes with amplitude following eye closure) are not fully understood despite the physiological and clinical applicability of this phenomenon, as indicated by the fact that ageing and neurodegeneration reduce reactivity. Strong interactions between visual and vestibular systems raise the theoretical possibility that the vestibular system plays a role in alpha reactivity. To test this hypothesis, we applied electroencephalography in sitting and standing postures in 15 participants with reduced vestibular function (bilateral vestibulopathy, median age = 70 years, interquartile range = 51-77 years) and 15 age-matched controls. We found participants with reduced vestibular function showed less enhancement of alpha electroencephalography power on eye closure in frontoparietal areas, compared to controls. In participants with reduced vestibular function, video head impulse test gain - as a measure of residual vestibulo-ocular reflex function - correlated with reactivity in alpha power across most of the head. Greater reliance on visual input for spatial orientation ('visual dependence', measured with the rod-and-disc test) correlated with less alpha enhancement on eye closure only in participants with reduced vestibular function, and this was partially moderated by video head impulse test gain. Our results demonstrate for the first time that vestibular function influences alpha reactivity. The results are partly explained by the lack of ascending peripheral vestibular input but also by central reorganisation of processing relevant to visuo-vestibular judgements.
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Affiliation(s)
- Richard T Ibitoye
- Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London, London W6 8RP, United Kingdom; Department of Neurology, Gloucestershire Hospital NHS Foundation Trust, Gloucester GL1 3NN, United Kingdom; Department of Clinical and Motor Neurosciences, Centre for Vestibular and Behavioural Neurosciences, University College London, London WC1N 3BG, United Kingdom
| | - Patricia Castro
- Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London, London W6 8RP, United Kingdom; Universidad del Desarrollo, Escuela de Fonoaudiología, Facultad de Medicina Clínica Alemana, Santiago, Chile
| | - Toby J Ellmers
- Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London, London W6 8RP, United Kingdom
| | - Diego N Kaski
- Universidad del Desarrollo, Escuela de Fonoaudiología, Facultad de Medicina Clínica Alemana, Santiago, Chile
| | - Adolfo M Bronstein
- Centre for Vestibular Neurology, Department of Brain Sciences, Imperial College London, London W6 8RP, United Kingdom.
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16
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Rabiller G, Ip Z, Zarrabian S, Zhang H, Sato Y, Yazdan-Shahmorad A, Liu J. Type-2 diabetes alters hippocampal neural oscillations and disrupts synchrony between hippocampus and cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.25.542288. [PMID: 37292743 PMCID: PMC10245872 DOI: 10.1101/2023.05.25.542288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Type 2 diabetes mellitus (T2DM) increases the risk of neurological diseases, yet how brain oscillations change as age and T2DM interact is not well characterized. To delineate the age and diabetic effect on neurophysiology, we recorded local field potentials with multichannel electrodes spanning the somatosensory cortex and hippocampus (HPC) under urethane anesthesia in diabetic and normoglycemic control mice, at 200 and 400 days of age. We analyzed the signal power of brain oscillations, brain state, sharp wave associate ripples (SPW-Rs), and functional connectivity between the cortex and HPC. We found that while both age and T2DM were correlated with a breakdown in long-range functional connectivity and reduced neurogenesis in the dentate gyrus and subventricular zone, T2DM further slowed brain oscillations and reduced theta-gamma coupling. Age and T2DM also prolonged the duration of SPW-Rs and increased gamma power during SPW-R phase. Our results have identified potential electrophysiological substrates of hippocampal changes associated with T2DM and age. The perturbed brain oscillation features and diminished neurogenesis may underlie T2DM-accelerated cognitive impairment.
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17
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Küçük KM, Wienke AS, Mathes B, Başar-Eroğlu C. Multistable perception elicits compensatory alpha activity in older adults. Front Aging Neurosci 2023; 15:1136124. [PMID: 37304078 PMCID: PMC10249475 DOI: 10.3389/fnagi.2023.1136124] [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: 01/02/2023] [Accepted: 05/08/2023] [Indexed: 06/13/2023] Open
Abstract
Multistable stimuli lead to the perception of two or more alternative perceptual experiences that spontaneously reverse from one to the other. This property allows researchers to study perceptual processes that endogenously generate and integrate perceptual information. These endogenous processes appear to be slowed down around the age of 55 where participants report significantly lower perceptual reversals. This study aimed to identify neural correlates of this aging effect during multistable perception utilizing a multistable version of the stroboscopic alternative motion paradigm (SAM: endogenous task) and a control condition (exogenous task). Specifically, age-related differences in perceptual destabilization and maintenance processes were examined through alpha responses. Electroencephalography (EEG) of 12 older and 12 young adults were recorded during SAM and control tasks. Alpha band activity (8-14 Hz) was obtained by wavelet-transformation of the EEG signal and analyzed for each experimental condition. Endogenous reversals induced gradual decrease in posterior alpha activity in young adults which is a replication of previous studies' findings. Alpha desynchronization was shifted to anterior areas and prevalent across the cortex except the occipital area for older adults. Alpha responses did not differ between the groups in the control condition. These findings point to recruitment of compensatory alpha networks for maintenance of endogenously generated percepts. Increased number of networks responsible for maintenance might have extended the neural satiation duration and led to decreased reversal rates in older adults.
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Affiliation(s)
| | - Annika S. Wienke
- Bremen Initiative to Foster Early Childhood Development (BRISE), University of Bremen, Bremen, Germany
| | - Birgit Mathes
- Bremen Initiative to Foster Early Childhood Development (BRISE), University of Bremen, Bremen, Germany
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18
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Fingelkurts AA, Fingelkurts AA. Turning Back the Clock: A Retrospective Single-Blind Study on Brain Age Change in Response to Nutraceuticals Supplementation vs. Lifestyle Modifications. Brain Sci 2023; 13:brainsci13030520. [PMID: 36979330 PMCID: PMC10046544 DOI: 10.3390/brainsci13030520] [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: 02/20/2023] [Revised: 03/17/2023] [Accepted: 03/19/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND There is a growing consensus that chronological age (CA) is not an accurate indicator of the aging process and that biological age (BA) instead is a better measure of an individual's risk of age-related outcomes and a more accurate predictor of mortality than actual CA. In this context, BA measures the "true" age, which is an integrated result of an individual's level of damage accumulation across all levels of biological organization, along with preserved resources. The BA is plastic and depends upon epigenetics. Brain state is an important factor contributing to health- and lifespan. METHODS AND OBJECTIVE Quantitative electroencephalography (qEEG)-derived brain BA (BBA) is a suitable and promising measure of brain aging. In the present study, we aimed to show that BBA can be decelerated or even reversed in humans (N = 89) by using customized programs of nutraceutical compounds or lifestyle changes (mean duration = 13 months). RESULTS We observed that BBA was younger than CA in both groups at the end of the intervention. Furthermore, the BBA of the participants in the nutraceuticals group was 2.83 years younger at the endpoint of the intervention compared with their BBA score at the beginning of the intervention, while the BBA of the participants in the lifestyle group was only 0.02 years younger at the end of the intervention. These results were accompanied by improvements in mental-physical health comorbidities in both groups. The pre-intervention BBA score and the sex of the participants were considered confounding factors and analyzed separately. CONCLUSIONS Overall, the obtained results support the feasibility of the goal of this study and also provide the first robust evidence that halting and reversal of brain aging are possible in humans within a reasonable (practical) timeframe of approximately one year.
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19
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Cesnaite E, Steinfath P, Jamshidi Idaji M, Stephani T, Kumral D, Haufe S, Sander C, Hensch T, Hegerl U, Riedel-Heller S, Röhr S, Schroeter ML, Witte AV, Villringer A, Nikulin VV. Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age. Neuroimage 2023; 268:119810. [PMID: 36587708 DOI: 10.1016/j.neuroimage.2022.119810] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 12/31/2022] Open
Abstract
While many structural and biochemical changes in the brain have previously been associated with older age, findings concerning functional properties of neuronal networks, as reflected in their electrophysiological signatures, remain rather controversial. These discrepancies might arise due to several reasons, including diverse factors determining general spectral slowing in the alpha frequency range as well as amplitude mixing between the rhythmic and non-rhythmic parameters. We used a large dataset (N = 1703, mean age 70) to comprehensively investigate age-related alterations in multiple EEG biomarkers taking into account rhythmic and non-rhythmic activity and their individual contributions to cognitive performance. While we found strong evidence for an individual alpha peak frequency (IAF) decline in older age, we did not observe a significant relationship between theta power and age while controlling for IAF. Not only did IAF decline with age, but it was also positively associated with interference resolution in a working memory task primarily in the right and left temporal lobes suggesting its functional role in information sampling. Critically, we did not detect a significant relationship between alpha power and age when controlling for the 1/f spectral slope, while the latter one showed age-related alterations. These findings thus suggest that the entanglement of IAF slowing and power in the theta frequency range, as well as 1/f slope and alpha power measures, might explain inconsistencies reported previously in the literature. Finally, despite the absence of age-related alterations, alpha power was negatively associated with the speed of processing in the right frontal lobe while 1/f slope showed no consistent relationship to cognitive performance. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered for the comprehensive assessment of association between age, neuronal activity, and cognitive performance.
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Affiliation(s)
- Elena Cesnaite
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Paul Steinfath
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany
| | - Mina Jamshidi Idaji
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany; Machine Learning Group, Technical University Berlin, Berlin, Germany
| | - Tilman Stephani
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; International Max Planck Research School NeuroCom, Leipzig, Germany
| | - Deniz Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg im Breisgau, Germany; Institute of Psychology, Clinical Psychology and Psychotherapy Unit, University of Freiburg, Freiburg im Breisgau, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; IUBH International University, Erfurt, Germany
| | - Ulrich Hegerl
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Department of Psychiatry, Psychosomatics and Psychotherapy, Goethe University Frankfurt, Frankfurt, Germany
| | - Steffi Riedel-Heller
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany
| | - Susanne Röhr
- LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig, Germany; Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Matthias L Schroeter
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - A Veronica Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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20
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Qiao J, Wang Y, Wang S. Natural frequencies of neural activities and cognitions may serve as precise targets of rhythmic interventions to the aging brain. Front Aging Neurosci 2022; 14:988193. [PMID: 36172484 PMCID: PMC9510897 DOI: 10.3389/fnagi.2022.988193] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
Rhythmic neural activities are critical to the efficiency of regulatory procedures in brain functions. However, brain functions usually decline in aging as accompanied by frequency shift and temporal dedifferentiation of neural activities. Considering the strong oscillations and long-lasting after-effects induced by rhythmic brain stimulations, we suggest that non-invasive rhythmic brain stimulation technique may help restore the natural frequencies of neural activities in aging to that in younger and healthy brains. Although with tremendous work to do, this technique offers great opportunities for the restoration of normal brain functions in aging, or even in those suffering from neurodegenerative diseases and neuropsychiatric disorders.
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Affiliation(s)
- Jingwen Qiao
- Academy for Engineering and Technology, Fudan University, Shanghai, China
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China
- Yifeng Wang,
| | - Shouyan Wang
- Academy for Engineering and Technology, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- *Correspondence: Shouyan Wang,
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21
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Han C, Wang T, Wu Y, Li H, Wang E, Zhao X, Cao Q, Qian Q, Wang Y, Dou F, Liu JK, Sun L, Xing D. Compensatory mechanism of attention-deficit/hyperactivity disorder recovery in resting state alpha rhythms. Front Comput Neurosci 2022; 16:883065. [PMID: 36157841 PMCID: PMC9490822 DOI: 10.3389/fncom.2022.883065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
Alpha rhythms in the human electroencephalogram (EEG), oscillating at 8-13 Hz, are located in parieto-occipital cortex and are strongest when awake people close their eyes. It has been suggested that alpha rhythms were related to attention-related functions and mental disorders (e.g., Attention-deficit/hyperactivity disorder (ADHD)). However, many studies have shown inconsistent results on the difference in alpha oscillation between ADHD and control groups. Hence it is essential to verify this difference. In this study, a dataset of EEG recording (128 channel EGI) from 87 healthy controls (HC) and 162 ADHD (141 persisters and 21 remitters) adults in a resting state with their eyes closed was used to address this question and a three-gauss model (summation of baseline and alpha components) was conducted to fit the data. To our surprise, the power of alpha components was not a significant difference among the three groups. Instead, the baseline power of remission and HC group in the alpha band is significantly stronger than that of persister groups. Our results suggest that ADHD recovery may have compensatory mechanisms and many abnormalities in EEG may be due to the influence of behavior rather than the difference in brain signals.
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Affiliation(s)
- Chuanliang Han
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- College of Life Sciences, Beijing Normal University, Beijing, China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Hui Li
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Encong Wang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Xixi Zhao
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Qingjiu Cao
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Qiujin Qian
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Yufeng Wang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Fei Dou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- College of Life Sciences, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Genetic Engineering Drugs and Biotechnology, Beijing Normal University, Beijing, China
| | - Jian K. Liu
- School of Computing, University of Leeds, Leeds, United Kingdom
| | - Li Sun
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
- Li Sun,
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- *Correspondence: Dajun Xing,
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22
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Biophysical mechanism underlying compensatory preservation of neural synchrony over the adult lifespan. Commun Biol 2022; 5:567. [PMID: 35681107 PMCID: PMC9184644 DOI: 10.1038/s42003-022-03489-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 05/12/2022] [Indexed: 11/17/2022] Open
Abstract
We propose that the preservation of functional integration, estimated from measures of neural synchrony, is a key objective of neurocompensatory mechanisms associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at the peak alpha frequency in Magnetoencephalography recordings remains invariant over the lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delays associated with age-related degeneration of white matter tracts, albeit at slower network frequencies. By deriving analytical solutions for simplified connection topologies, we further establish the theoretical principles underlying compensatory network re-organization. Our findings suggest that frequency slowing with age- frequently observed in the alpha band in diverse populations- may be viewed as an epiphenomenon of the underlying compensatory mechanism. Analysis of MEG data from healthy participants and whole-brain network modeling suggests that the brain compensates for age-related disruptions in connectivity by slowing down the frequency of neural synchronization.
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23
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Hommelsen M, Viswanathan S, Daun S. Robustness of individualized inferences from longitudinal resting state EEG dynamics. Eur J Neurosci 2022; 56:3613-3644. [PMID: 35445438 DOI: 10.1111/ejn.15673] [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: 10/11/2021] [Revised: 03/21/2022] [Accepted: 04/08/2022] [Indexed: 11/27/2022]
Abstract
Tracking how individual human brains change over extended timescales is crucial to clinical scenarios ranging from stroke recovery to healthy aging. The use of resting state (RS) activity for tracking is a promising possibility. However, it is unresolved how a person's RS activity over time can be decoded to distinguish neurophysiological changes from confounding cognitive variability. Here, we develop a method to screen RS activity changes for these confounding effects by formulating it as a problem of change classification. We demonstrate a novel solution to change classification by linking individual-specific change to inter-individual differences. Individual RS-EEG was acquired over five consecutive days including task states devised to simulate the effects of inter-day cognitive variation. As inter-individual differences are shaped by neurophysiological differences, the inter-individual differences in RS activity on one day were analyzed (using machine learning) to identify distinctive configurations in each individual's RS activity. Using this configuration as a decision-rule, an individual could be re-identified from 2-second samples of the instantaneous oscillatory power spectrum acquired on a different day both from RS and confounded-RS with a limited loss in accuracy. Importantly, the low loss in accuracy in cross-day vs same-day classification was achieved with classifiers that combined information from multiple frequency bands at channels across the scalp (with a concentration at characteristic fronto-central and occipital zones). Taken together, these findings support the technical feasibility of screening RS activity for confounding effects and the suitability of longitudinal RS for robust individualized inferences about neurophysiological change in health and disease.
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Affiliation(s)
- Maximilian Hommelsen
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich, Germany
| | | | - Silvia Daun
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich, Germany.,Institute of Zoology, University of Cologne, Cologne, Germany
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24
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Varatharajah Y, Joseph B, Brinkmann B, Morita-Sherman M, Fitzgerald Z, Vegh D, Nair D, Burgess R, Cendes F, Jehi L, Worrell G. Quantitative Analysis of Visually Reviewed Normal Scalp EEG Predicts Seizure Freedom Following Anterior Temporal Lobectomy. Epilepsia 2022; 63:1630-1642. [PMID: 35416285 PMCID: PMC9283304 DOI: 10.1111/epi.17257] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 04/10/2022] [Accepted: 04/11/2022] [Indexed: 11/28/2022]
Abstract
Objective Anterior temporal lobectomy (ATL) is a widely performed and successful intervention for drug‐resistant temporal lobe epilepsy (TLE). However, up to one third of patients experience seizure recurrence within 1 year after ATL. Despite the extensive literature on presurgical electroencephalography (EEG) and magnetic resonance imaging (MRI) abnormalities to prognosticate seizure freedom following ATL, the value of quantitative analysis of visually reviewed normal interictal EEG in such prognostication remains unclear. In this retrospective multicenter study, we investigate whether machine learning analysis of normal interictal scalp EEG studies can inform the prediction of postoperative seizure freedom outcomes in patients who have undergone ATL. Methods We analyzed normal presurgical scalp EEG recordings from 41 Mayo Clinic (MC) and 23 Cleveland Clinic (CC) patients. We used an unbiased automated algorithm to extract eyes closed awake epochs from scalp EEG studies that were free of any epileptiform activity and then extracted spectral EEG features representing (a) spectral power and (b) interhemispheric spectral coherence in frequencies between 1 and 25 Hz across several brain regions. We analyzed the differences between the seizure‐free and non–seizure‐free patients and employed a Naïve Bayes classifier using multiple spectral features to predict surgery outcomes. We trained the classifier using a leave‐one‐patient‐out cross‐validation scheme within the MC data set and then tested using the out‐of‐sample CC data set. Finally, we compared the predictive performance of normal scalp EEG‐derived features against MRI abnormalities. Results We found that several spectral power and coherence features showed significant differences correlated with surgical outcomes and that they were most pronounced in the 10–25 Hz range. The Naïve Bayes classification based on those features predicted 1‐year seizure freedom following ATL with area under the curve (AUC) values of 0.78 and 0.76 for the MC and CC data sets, respectively. Subsequent analyses revealed that (a) interhemispheric spectral coherence features in the 10–25 Hz range provided better predictability than other combinations and (b) normal scalp EEG‐derived features provided superior and potentially distinct predictive value when compared with MRI abnormalities (>10% higher F1 score). Significance These results support that quantitative analysis of even a normal presurgical scalp EEG may help prognosticate seizure freedom following ATL in patients with drug‐resistant TLE. Although the mechanism for this result is not known, the scalp EEG spectral and coherence properties predicting seizure freedom may represent activity arising from the neocortex or the networks responsible for temporal lobe seizure generation within vs outside the margins of an ATL.
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Affiliation(s)
- Yogatheesan Varatharajah
- Department of Bioengineering, University of Illinois, Urbana, IL, 61801, USA.,Departments of Neurology and Physiology & Biomedical Engineering, Mayo Clinic, Rochester, MN, 55905, USA
| | - Boney Joseph
- Departments of Neurology and Physiology & Biomedical Engineering, Mayo Clinic, Rochester, MN, 55905, USA
| | - Benjamin Brinkmann
- Departments of Neurology and Physiology & Biomedical Engineering, Mayo Clinic, Rochester, MN, 55905, USA
| | | | | | - Deborah Vegh
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, 44195, USA
| | - Dileep Nair
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, 44195, USA
| | - Richard Burgess
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, 44195, USA
| | - Fernando Cendes
- Department of Neurology, University of Campinas UNICAMP, Campinas, Brazil
| | - Lara Jehi
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, 44195, USA
| | - Gregory Worrell
- Departments of Neurology and Physiology & Biomedical Engineering, Mayo Clinic, Rochester, MN, 55905, USA
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25
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Zhong XZ, Chen JJ. Resting-state functional magnetic resonance imaging signal variations in aging: The role of neural activity. Hum Brain Mapp 2022; 43:2880-2897. [PMID: 35293656 PMCID: PMC9120570 DOI: 10.1002/hbm.25823] [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: 10/04/2021] [Revised: 01/20/2022] [Accepted: 02/23/2022] [Indexed: 11/23/2022] Open
Abstract
Resting‐state functional magnetic resonance imaging (rs‐fMRI) has been extensively used to study brain aging, but the age effect on the frequency content of the rs‐fMRI signal has scarcely been examined. Moreover, the neuronal implications of such age effects and age–sex interaction remain unclear. In this study, we examined the effects of age and sex on the rs‐fMRI signal frequency using the Leipzig mind–brain–body data set. Over a frequency band of up to 0.3 Hz, we found that the rs‐fMRI fluctuation frequency is higher in the older adults, although the fluctuation amplitude is lower. The rs‐fMRI signal frequency is also higher in men than in women. Both age and sex effects on fMRI frequency vary with the frequency band examined but are not found in the frequency of physiological‐noise components. This higher rs‐fMRI frequency in older adults is not mediated by the electroencephalograph (EEG)‐frequency increase but a likely link between fMRI signal frequency and EEG entropy, which vary with age and sex. Additionally, in different rs‐fMRI frequency bands, the fMRI‐EEG amplitude ratio is higher in young adults. This is the first study to investigate the neuronal contribution to age and sex effects in the frequency dimension of the rs‐fMRI signal and may lead to the development of new, frequency‐based rs‐fMRI metrics. Our study demonstrates that Fourier analysis of the fMRI signal can reveal novel information about aging. Furthermore, fMRI and EEG signals reflect different aspects of age‐ and sex‐related brain differences, but the signal frequency and complexity, instead of amplitude, may hold their link.
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Affiliation(s)
- Xiaole Z Zhong
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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26
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Hoshi H, Hirata Y, Kobayashi M, Sakamoto Y, Fukasawa K, Ichikawa S, Poza J, Rodríguez-González V, Gómez C, Shigihara Y. Distinctive effects of executive dysfunction and loss of learning/memory abilities on resting-state brain activity. Sci Rep 2022; 12:3459. [PMID: 35236888 PMCID: PMC8891272 DOI: 10.1038/s41598-022-07202-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 02/11/2022] [Indexed: 01/08/2023] Open
Abstract
Dementia is a syndrome characterised by cognitive impairments, with a loss of learning/memory abilities at the earlier stages and executive dysfunction at the later stages. However, recent studies have suggested that impairments in both learning/memory abilities and executive functioning might co-exist. Cognitive impairments have been primarily evaluated using neuropsychological assessments, such as the Mini-Mental State Examination (MMSE). Recently, neuroimaging techniques such as magnetoencephalography (MEG), which assess changes in resting-state brain activity, have also been used as biomarkers for cognitive impairment. However, it is unclear whether these changes reflect dysfunction in executive function as well as learning and memory. In this study, parameters from the MEG for brain activity, MMSE for learning/memory, and Frontal Assessment Battery (FAB) for executive function were compared within 207 individuals. Three MEG parameters were used as representatives of resting-state brain activity: median frequency, individual alpha frequency, and Shannon’s spectral entropy. Regression analysis showed that median frequency was predicted by both the MMSE and FAB scores, while individual alpha frequency and Shannon’s spectral entropy were predicted by MMSE and FAB scores, respectively. Our results indicate that MEG spectral parameters reflect both learning/memory and executive functions, supporting the utility of MEG as a biomarker of cognitive impairment.
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Affiliation(s)
- Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan
| | - Yoko Hirata
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Momoko Kobayashi
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Yuki Sakamoto
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Keisuke Fukasawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Sayuri Ichikawa
- Clinical Laboratory, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan
| | - Jesús Poza
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, 47011, Valladolid, Castilla y León, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina, (CIBER-BBN), 47011, Valladolid, Castilla y León, Spain.,Instituto de Investigación en Matemáticas (IMUVA), University of Valladolid, 47011, Valladolid, Castilla y León, Spain
| | - Víctor Rodríguez-González
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, 47011, Valladolid, Castilla y León, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina, (CIBER-BBN), 47011, Valladolid, Castilla y León, Spain
| | - Carlos Gómez
- Biomedical Engineering Group, Higher Technical School of Telecommunications Engineering, University of Valladolid, 47011, Valladolid, Castilla y León, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales Y Nanomedicina, (CIBER-BBN), 47011, Valladolid, Castilla y León, Spain
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan. .,Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, 360‑8567, Japan.
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27
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Alatorre-Cruz GC, Fernández T, Castro-Chavira SA, González-López M, Sánchez-Moguel SM, Silva-Pereyra J. One-Year Follow-Up of Healthy Older Adults with Electroencephalographic Risk for Neurocognitive Disorder After Neurofeedback Training. J Alzheimers Dis 2022; 85:1767-1781. [PMID: 34974435 PMCID: PMC8925127 DOI: 10.3233/jad-215538] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Background: In healthy older adults, excess theta activity is an electroencephalographic (EEG) predictor of cognitive impairment. In a previous study, neurofeedback (NFB) treatment reinforcing reductions theta activity resulted in EEG reorganization and cognitive improvement. Objective: To explore the clinical applicability of this NFB treatment, the present study performed a 1-year follow-up to determine its lasting effects. Methods: Twenty seniors with excessive theta activity in their EEG were randomly assigned to the experimental or control group. The experimental group received an auditory reward when the theta absolute power (AP) was reduced. The control group received the reward randomly. Results: Both groups showed a significant decrease in theta activity at the training electrode. However, the EEG results showed that only the experimental group underwent global changes after treatment. These changes consisted of delta and theta decreases and beta increases. Although no changes were found in any group during the period between the posttreatment evaluation and follow-up, more pronounced theta decreases and beta increases were observed in the experimental group when the follow-up and pretreatment measures were compared. Executive functions showed a tendency to improve two months after treatment which became significant one year later. Conclusion: These results suggest that the EEG and behavioral benefits of this NFB treatment persist for at least one year, which adds up to the available evidence contributing to identifying factors that increase its efficacy level. The relevance of this study lies in its prophylactic features of addressing a clinically healthy population with EEG risk of cognitive decline.
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Affiliation(s)
- Graciela C Alatorre-Cruz
- Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Estado de México, México.,Department of Pediatrics. University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Thalía Fernández
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, México
| | - Susana A Castro-Chavira
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, México.,Institutt for Psykologi, Det Helsevitenskapelige Fakultet, Universitetet i Tromsø Norges Arktiske Universitet, Tromsø, Tromsø, Norway
| | - Mauricio González-López
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, México
| | - Sergio M Sánchez-Moguel
- Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, México.,Escuela Superior de Atotonilco de Tula, Universidad Autónoma del Estado de Hidalgo, Hidalgo, México
| | - Juan Silva-Pereyra
- Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, Estado de México, México
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28
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Griffa A, Legdeur N, Badissi M, van den Heuvel MP, Stam CJ, Visser PJ, Hillebrand A. Magnetoencephalography Brain Signatures Relate to Cognition and Cognitive Reserve in the Oldest-Old: The EMIF-AD 90 + Study. Front Aging Neurosci 2021; 13:746373. [PMID: 34899269 PMCID: PMC8656941 DOI: 10.3389/fnagi.2021.746373] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/01/2021] [Indexed: 11/25/2022] Open
Abstract
The oldest-old subjects represent the fastest growing segment of society and are at high risk for dementia with a prevalence of up to 40%. Lifestyle factors, such as lifelong participation in cognitive and leisure activities, may contribute to individual cognitive reserve and reduce the risk for cognitive impairments. However, the neural bases underlying cognitive functioning and cognitive reserve in this age range are still poorly understood. Here, we investigate spectral and functional connectivity features obtained from resting-state MEG recordings in a cohort of 35 cognitively normal (92.2 ± 1.8 years old, 19 women) and 11 cognitively impaired (90.9 ± 1.9 years old, 1 woman) oldest-old participants, in relation to cognitive traits and cognitive reserve. The latter was approximated with a self-reported scale on lifelong engagement in cognitively demanding activities. Cognitively impaired oldest-old participants had slower cortical rhythms in frontal, parietal and default mode network regions compared to the cognitively normal subjects. These alterations mainly concerned the theta and beta band and partially explained inter-subject variability of episodic memory scores. Moreover, a distinct spectral pattern characterized by higher relative power in the alpha band was specifically associated with higher cognitive reserve while taking into account the effect of age and education level. Finally, stronger functional connectivity in the alpha and beta band were weakly associated with better cognitive performances in the whole group of subjects, although functional connectivity effects were less prominent than the spectral ones. Our results shed new light on the neural underpinnings of cognitive functioning in the oldest-old population and indicate that cognitive performance and cognitive reserve may have distinct spectral electrophysiological substrates.
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Affiliation(s)
- Alessandra Griffa
- Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Center of Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.,Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Nienke Legdeur
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Maryam Badissi
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Martijn P van den Heuvel
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neuroscience and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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29
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Jabès A, Klencklen G, Ruggeri P, Antonietti JP, Banta Lavenex P, Lavenex P. Age-Related Differences in Resting-State EEG and Allocentric Spatial Working Memory Performance. Front Aging Neurosci 2021; 13:704362. [PMID: 34803651 PMCID: PMC8600362 DOI: 10.3389/fnagi.2021.704362] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 10/04/2021] [Indexed: 12/31/2022] Open
Abstract
During normal aging resting-state brain activity changes and working memory performance declines as compared to young adulthood. Interestingly, previous studies reported that different electroencephalographic (EEG) measures of resting-state brain activity may correlate with working memory performance at different ages. Here, we recorded resting-state EEG activity and tested allocentric spatial working memory in healthy young (20-30 years) and older (65-75 years) adults. We adapted standard EEG methods to record brain activity in mobile participants in a non-shielded environment, in both eyes closed and eyes open conditions. Our study revealed some age-group differences in resting-state brain activity that were consistent with previous results obtained in different recording conditions. We confirmed that age-group differences in resting-state EEG activity depend on the recording conditions and the specific parameters considered. Nevertheless, lower theta-band and alpha-band frequencies and absolute powers, and higher beta-band and gamma-band relative powers were overall observed in healthy older adults, as compared to healthy young adults. In addition, using principal component and regression analyses, we found that the first extracted EEG component, which represented mainly theta, alpha and beta powers, correlated with spatial working memory performance in older adults, but not in young adults. These findings are consistent with the theory that the neurobiological bases of working memory performance may differ between young and older adults. However, individual measures of resting-state EEG activity could not be used as reliable biomarkers to predict individual allocentric spatial working memory performance in young or older adults.
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Affiliation(s)
- Adeline Jabès
- Institute of Psychology, University of Lausanne, Lausanne, Switzerland
| | - Giuliana Klencklen
- Institute of Psychology, University of Lausanne, Lausanne, Switzerland.,Faculty of Psychology, UniDistance Suisse, Brig, Switzerland
| | - Paolo Ruggeri
- Institute of Psychology, University of Lausanne, Lausanne, Switzerland
| | | | - Pamela Banta Lavenex
- Institute of Psychology, University of Lausanne, Lausanne, Switzerland.,Faculty of Psychology, UniDistance Suisse, Brig, Switzerland
| | - Pierre Lavenex
- Institute of Psychology, University of Lausanne, Lausanne, Switzerland
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30
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Kumral D, Cesnaite E, Beyer F, Hofmann SM, Hensch T, Sander C, Hegerl U, Haufe S, Villringer A, Witte AV, Nikulin VV. Relationship between regional white matter hyperintensities and alpha oscillations in older adults. Neurobiol Aging 2021; 112:1-11. [PMID: 35007997 DOI: 10.1016/j.neurobiolaging.2021.10.006] [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: 10/02/2020] [Revised: 09/22/2021] [Accepted: 10/12/2021] [Indexed: 11/17/2022]
Abstract
Aging is associated with increased white matter hyperintensities (WMHs) and with alterations of alpha oscillations (7-13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N = 907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and long-range temporal correlations. Finally, higher age was associated with elevated alpha power via total WMH volume. We suggest that an elevated alpha power is a consequence of WMHs affecting a spatial organization of alpha sources.
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Affiliation(s)
- Deniz Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg im Breisgau, Germany; Clinical Psychology and Psychotherapy Unit, Institute of Psychology, University of Freiburg, Freiburg im Breisgau, Germany.
| | - Elena Cesnaite
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Frauke Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; CRC Obesity Mechanisms, Subproject A1, University of Leipzig, Leipzig, Germany
| | - Simon M Hofmann
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Department of Psychology, IU International University of Applied Sciences, Erfurt, Germany
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics and Psychotherapy, Goethe University Frankfurt, Frankfurt, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic for Cognitive Neurology, University Medical Center Leipzig, Germany
| | - A Veronica Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; CRC Obesity Mechanisms, Subproject A1, University of Leipzig, Leipzig, Germany; Clinic for Cognitive Neurology, University Medical Center Leipzig, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany; Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia; Neurophysics Group, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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31
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Alejandro RJ, Packard PA, Steiger TK, Fuentemilla L, Bunzeck N. Semantic Congruence Drives Long-Term Memory and Similarly Affects Neural Retrieval Dynamics in Young and Older Adults. Front Aging Neurosci 2021; 13:683908. [PMID: 34594212 PMCID: PMC8477023 DOI: 10.3389/fnagi.2021.683908] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 06/16/2021] [Indexed: 11/25/2022] Open
Abstract
Learning novel information can be promoted if it is congruent with already stored knowledge. This so-called semantic congruence effect has been broadly studied in healthy young adults with a focus on neural encoding mechanisms. However, the impacts on retrieval, and possible impairments during healthy aging, which is typically associated with changes in declarative long-term memory, remain unclear. To investigate these issues, we used a previously established paradigm in healthy young and older humans with a focus on the neural activity at a final retrieval stage as measured with electroencephalography (EEG). In both age groups, semantic congruence at encoding enhanced subsequent long-term recognition memory of words. Compatible with this observation, semantic congruence led to differences in event-related potentials (ERPs) at retrieval, and this effect was not modulated by age. Specifically, congruence modulated old/new ERPs at a fronto-central (Fz) and left parietal (P3) electrode in a late (400–600 ms) time window, which has previously been associated with recognition memory processes. Importantly, ERPs to old items also correlated with the positive effect of semantic congruence on long-term memory independent of age. Together, our findings suggest that semantic congruence drives subsequent recognition memory across the lifespan through changes in neural retrieval processes.
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Affiliation(s)
- Ricardo J Alejandro
- Department of Psychology, University of Lübeck, Lübeck, Germany.,Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Pau A Packard
- Department of Psychology, University of Lübeck, Lübeck, Germany.,Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra Roc Boronat, Barcelona, Spain
| | | | - Lluis Fuentemilla
- Cognition and Brain Plasticity Group, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain.,Department of Cognition, Development and Educational Psychology, University of Barcelona, Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Nico Bunzeck
- Department of Psychology, University of Lübeck, Lübeck, Germany.,Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck Ratzeburger Allee, Lübeck, Germany
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Henderson SE, Hall SA, Callegari JM, Desjardins JA, Segalowitz SJ, Campbell KL. Increased alpha suppression with age during involuntary memory retrieval. Psychophysiology 2021; 59:e13947. [PMID: 34571578 DOI: 10.1111/psyp.13947] [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: 01/08/2021] [Revised: 07/03/2021] [Accepted: 09/13/2021] [Indexed: 11/30/2022]
Abstract
Recent work suggests that while voluntary episodic memory declines with age, involuntary episodic memory, which comes to mind spontaneously without intention, remains relatively intact. However, the neurophysiology underlying these differences has yet to be established. The current study used electroencephalography (EEG) to investigate voluntary and involuntary retrieval in older and younger adults. Participants first encoded sounds, half of which were paired with pictures, the other half unpaired. EEG was then recorded as they listened to the sounds, with participants in the involuntary group performing a sound localization cover task, and those in the voluntary group additionally attempting to recall the associated pictures. Participants later reported which sounds brought the paired picture to mind during the localization task. Reaction times on the localization task were slower for voluntary than involuntary retrieval and for paired than unpaired sounds, possibly reflecting increased attentional demands of voluntary retrieval and interference from reactivation of the associated pictures respectively. For the EEG analyses, young adults showed greater alpha event-related desynchronization (ERD) during voluntary than involuntary retrieval at frontal and occipital sites, while older adults showed pronounced alpha ERD regardless of intention. Additionally, older adults showed greater ERD for paired than unpaired sounds at occipital sites, likely reflecting visual reactivation of the associated pictures. Young adults did not show this alpha ERD memory effect. Taken together, these data suggest that involuntary memory is largely preserved with age, but this may be due to older adults' greater recruitment of top-down control even when demand for such control is limited.
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Affiliation(s)
- Sarah E Henderson
- Department of Psychology, Brock University, St. Catharines, Ontario, Canada
| | - Shana A Hall
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina, USA
| | | | - James A Desjardins
- Department of Psychology, Brock University, St. Catharines, Ontario, Canada
| | | | - Karen L Campbell
- Department of Psychology, Brock University, St. Catharines, Ontario, Canada
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33
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Babiloni C, Ferri R, Noce G, Lizio R, Lopez S, Lorenzo I, Tucci F, Soricelli A, Nobili F, Arnaldi D, Famà F, Orzi F, Buttinelli C, Giubilei F, Cipollini V, Marizzoni M, Güntekin B, Aktürk T, Hanoğlu L, Yener G, Özbek Y, Stocchi F, Vacca L, Frisoni GB, Del Percio C. Resting State Alpha Electroencephalographic Rhythms Are Differently Related to Aging in Cognitively Unimpaired Seniors and Patients with Alzheimer's Disease and Amnesic Mild Cognitive Impairment. J Alzheimers Dis 2021; 82:1085-1114. [PMID: 34151788 DOI: 10.3233/jad-201271] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
BACKGROUND In relaxed adults, staying in quiet wakefulness at eyes closed is related to the so-called resting state electroencephalographic (rsEEG) rhythms, showing the highest amplitude in posterior areas at alpha frequencies (8-13 Hz). OBJECTIVE Here we tested the hypothesis that age may affect rsEEG alpha (8-12 Hz) rhythms recorded in normal elderly (Nold) seniors and patients with mild cognitive impairment due to Alzheimer's disease (ADMCI). METHODS Clinical and rsEEG datasets in 63 ADMCI and 60 Nold individuals (matched for demography, education, and gender) were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands, as well as fixed beta (14-30 Hz) and gamma (30-40 Hz) bands. Each group was stratified into three subgroups based on age ranges (i.e., tertiles). RESULTS As compared to the younger Nold subgroups, the older one showed greater reductions in the rsEEG alpha rhythms with major topographical effects in posterior regions. On the contrary, in relation to the younger ADMCI subgroups, the older one displayed a lesser reduction in those rhythms. Notably, the ADMCI subgroups pointed to similar cerebrospinal fluid AD diagnostic biomarkers, gray and white matter brain lesions revealed by neuroimaging, and clinical and neuropsychological scores. CONCLUSION The present results suggest that age may represent a deranging factor for dominant rsEEG alpha rhythms in Nold seniors, while rsEEG alpha rhythms in ADMCI patients may be more affected by the disease variants related to earlier versus later onset of the AD.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino (FR), Italy
| | | | | | | | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Flavio Nobili
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy
| | - Dario Arnaldi
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy.,Dipartimento di Neuroscienze, Oftalmologia, Genetica, Riabilitazione e Scienze Materno-infantili (DiNOGMI), Università di Genova, Genova, Italy
| | - Francesco Famà
- Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Virginia Cipollini
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Bahar Güntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Laboratory, Istanbul Medipol University, Istanbul, Turkey
| | - Tuba Aktürk
- REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Laboratory, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Görsev Yener
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey.,Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Yağmur Özbek
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
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Courtney SM, Hinault T. When the time is right: Temporal dynamics of brain activity in healthy aging and dementia. Prog Neurobiol 2021; 203:102076. [PMID: 34015374 DOI: 10.1016/j.pneurobio.2021.102076] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 05/08/2021] [Accepted: 05/14/2021] [Indexed: 10/21/2022]
Abstract
Brain activity and communications are complex phenomena that dynamically unfold over time. However, in contrast with the large number of studies reporting neuroanatomical differences in activation relative to young adults, changes of temporal dynamics of neural activity during normal and pathological aging have been grossly understudied and are still poorly known. Here, we synthesize the current state of knowledge from MEG and EEG studies that aimed at specifying the effects of healthy and pathological aging on local and network dynamics, and discuss the clinical and theoretical implications of these findings. We argue that considering the temporal dynamics of brain activations and networks could provide a better understanding of changes associated with healthy aging, and the progression of neurodegenerative disease. Recent research has also begun to shed light on the association of these dynamics with other imaging modalities and with individual differences in cognitive performance. These insights hold great potential for driving new theoretical frameworks and development of biomarkers to aid in identifying and treating age-related cognitive changes.
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Affiliation(s)
- S M Courtney
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA; F.M. Kirby Research Center, Kennedy Krieger Institute, MD 21205, USA; Department of Neuroscience, Johns Hopkins University, MD 21205, USA
| | - T Hinault
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA; U1077 INSERM-EPHE-UNICAEN, Caen, France.
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35
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Varatharajah Y, Berry B, Joseph B, Balzekas I, Pal Attia T, Kremen V, Brinkmann B, Iyer R, Worrell G. Characterizing the electrophysiological abnormalities in visually reviewed normal EEGs of drug-resistant focal epilepsy patients. Brain Commun 2021; 3:fcab102. [PMID: 34131643 PMCID: PMC8196245 DOI: 10.1093/braincomms/fcab102] [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: 02/07/2021] [Revised: 03/28/2021] [Accepted: 04/08/2021] [Indexed: 11/13/2022] Open
Abstract
Routine scalp EEG is essential in the clinical diagnosis and management of epilepsy. However, a normal scalp EEG (based on expert visual review) recorded from a patient with epilepsy can cause delays in diagnosis and clinical care delivery. Here, we investigated whether normal EEGs might contain subtle electrophysiological clues of epilepsy. Specifically, we investigated (i) whether there are indicators of abnormal brain electrophysiology in normal EEGs of epilepsy patients, and (ii) whether such abnormalities are modulated by the side of the brain generating seizures in focal epilepsy. We analysed awake scalp EEG recordings of age-matched groups of 144 healthy individuals and 48 individuals with drug-resistant focal epilepsy who had normal scalp EEGs. After preprocessing, using a bipolar montage of eight channels, we extracted the fraction of spectral power in the alpha band (8-13 Hz) relative to a wide band of 0.5-40 Hz within 10-s windows. We analysed the extracted features for (i) the extent to which people with drug-resistant focal epilepsy differed from healthy subjects, and (ii) whether differences within the drug-resistant focal epilepsy patients were related to the hemisphere generating seizures. We then used those differences to classify whether an EEG is likely to have been recorded from a person with drug-resistant focal epilepsy, and if so, the epileptogenic hemisphere. Furthermore, we tested the significance of these differences while controlling for confounders, such as acquisition system, age and medications. We found that the fraction of alpha power is generally reduced (i) in drug-resistant focal epilepsy compared to healthy controls, and (ii) in right-handed drug-resistant focal epilepsy subjects with left hemispheric seizures compared to those with right hemispheric seizures, and that the differences are most prominent in the frontal and temporal regions. The fraction of alpha power yielded area under curve values of 0.83 in distinguishing drug-resistant focal epilepsy from healthy and 0.77 in identifying the epileptic hemisphere in drug-resistant focal epilepsy patients. Furthermore, our results suggest that the differences in alpha power are greater when compared with differences attributable to acquisition system differences, age and medications. Our findings support that EEG-based measures of normal brain function, such as the normalized spectral power of alpha activity, may help identify patients with epilepsy even when an EEG does not contain any epileptiform activity, recorded seizures or other abnormalities. Although alpha abnormalities are unlikely to be disease-specific, we propose that such abnormalities may provide a higher pre-test probability for epilepsy when an individual being screened for epilepsy has a normal EEG on visual assessment.
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Affiliation(s)
- Yogatheesan Varatharajah
- Department of Bioengineering, University of Illinois, Urbana, IL 61801, USA.,Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA.,Electrical and Computer Engineering, University of Illinois, Urbana, IL 61801, USA
| | - Brent Berry
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Boney Joseph
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Irena Balzekas
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Tal Pal Attia
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Vaclav Kremen
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA.,Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, 160 00 Prague 6, Czech Republic
| | - Benjamin Brinkmann
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ravishankar Iyer
- Electrical and Computer Engineering, University of Illinois, Urbana, IL 61801, USA
| | - Gregory Worrell
- Mayo Systems Electrophysiology Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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36
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Ghazi TR, Blacker KJ, Hinault TT, Courtney SM. Modulation of Peak Alpha Frequency Oscillations During Working Memory Is Greater in Females Than Males. Front Hum Neurosci 2021; 15:626406. [PMID: 33967720 PMCID: PMC8102793 DOI: 10.3389/fnhum.2021.626406] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 03/24/2021] [Indexed: 01/05/2023] Open
Abstract
Peak alpha frequency is known to vary not just between individuals, but also within an individual over time. While variance in this metric between individuals has been tied to working memory performance, less understood are how short timescale modulations of peak alpha frequency during task performance may facilitate behavior. This gap in understanding may be bridged by consideration of a key difference between individuals: sex. Inconsistent findings in the literature regarding the relationship between peak alpha frequency and cognitive performance, as well as known sex-related-differences in peak alpha frequency and its modulation motivated our hypothesis that cognitive and neural processes underlying working memory-modulation of peak alpha frequency in particular-may differ based upon sex. Targeting sex as a predictive factor, we analyzed the EEG data of participants recorded while they performed four versions of a visual spatial working memory task. A significant difference between groups was present: females modulated peak alpha frequency more than males. Task performance did not differ by sex, yet a relationship between accuracy and peak alpha frequency was present in males, but not in females. These findings highlight the importance of considering sex as a factor in the study of oscillatory activity, particularly to further understanding of the neural mechanisms that underlie working memory.
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Affiliation(s)
- Tara R. Ghazi
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
| | - Kara J. Blacker
- Naval Medical Research Unit Dayton, Dayton, OH, United States
| | - Thomas T. Hinault
- INSERM-EPHE-UNICAEN, U1077, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Susan M. Courtney
- Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD, United States
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, United States
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37
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Lehnertz K, Rings T, Bröhl T. Time in Brain: How Biological Rhythms Impact on EEG Signals and on EEG-Derived Brain Networks. FRONTIERS IN NETWORK PHYSIOLOGY 2021; 1:755016. [PMID: 36925573 PMCID: PMC10013076 DOI: 10.3389/fnetp.2021.755016] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 09/13/2021] [Indexed: 11/13/2022]
Abstract
Electroencephalography (EEG) is a widely employed tool for exploring brain dynamics and is used extensively in various domains, ranging from clinical diagnosis via neuroscience, cognitive science, cognitive psychology, psychophysiology, neuromarketing, neurolinguistics, and pharmacology to research on brain computer interfaces. EEG is the only technique that enables the continuous recording of brain dynamics over periods of time that range from a few seconds to hours and days and beyond. When taking long-term recordings, various endogenous and exogenous biological rhythms may impinge on characteristics of EEG signals. While the impact of the circadian rhythm and of ultradian rhythms on spectral characteristics of EEG signals has been investigated for more than half a century, only little is known on how biological rhythms influence characteristics of brain dynamics assessed with modern EEG analysis techniques. At the example of multiday, multichannel non-invasive and invasive EEG recordings, we here discuss the impact of biological rhythms on temporal changes of various characteristics of human brain dynamics: higher-order statistical moments and interaction properties of multichannel EEG signals as well as local and global characteristics of EEG-derived evolving functional brain networks. Our findings emphasize the need to take into account the impact of biological rhythms in order to avoid erroneous statements about brain dynamics and about evolving functional brain networks.
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Affiliation(s)
- Klaus Lehnertz
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany.,Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany.,Interdisciplinary Center for Complex Systems, University of Bonn, Bonn, Germany
| | - Thorsten Rings
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany.,Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Timo Bröhl
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany.,Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
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38
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López ME, Turrero A, Cuesta P, Rodríguez-Rojo IC, Barabash A, Marcos A, Maestú F, Fernández A. A multivariate model of time to conversion from mild cognitive impairment to Alzheimer's disease. GeroScience 2020; 42:1715-1732. [PMID: 32886293 PMCID: PMC7732920 DOI: 10.1007/s11357-020-00260-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 08/24/2020] [Indexed: 11/26/2022] Open
Abstract
The present study was aimed at determining which combination of demographic, genetic, cognitive, neurophysiological, and neuroanatomical factors may predict differences in time to progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD). To this end, a sample of 121 MCIs was followed up during a 5-year period. According to their clinical outcome, MCIs were divided into two subgroups: (i) the "progressive" MCI group (n = 46; mean time to progression 17 ± 9.73 months) and (ii) the "stable" MCI group (n = 75; mean time of follow-up 31.37 ± 14.58 months). Kaplan-Meier survival analyses were applied to explore each variable's relationship with the progression to AD. Once potential predictors were detected, Cox regression analyses were utilized to calculate a parsimonious model to estimate differences in time to progression. The final model included three variables (in order of relevance): left parahippocampal volume (corrected by intracranial volume, LP_ ICV), delayed recall (DR), and left inferior occipital lobe individual alpha peak frequency (LIOL_IAPF). Those MCIs with LP_ICV volume, DR score, and LIOL_IAPF value lower than the defined cutoff had 6 times, 5.5 times, and 3 times higher risk of progression to AD, respectively. Besides, when the categories of the three variables were "unfavorable" (i.e., values below the cutoff), 100% of cases progressed to AD at the end of follow-up. Our results highlighted the relevance of neurophysiological markers as predictors of conversion (LIOL_IAPF) and the importance of multivariate models that combine markers of different nature to predict time to progression from MCI to dementia.
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Affiliation(s)
- María Eugenia López
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Complutense University of Madrid, Madrid, Spain.
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Polytechnic University of Madrid, Madrid, Spain.
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain.
| | - Agustín Turrero
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Statistics and Operational Research, Complutense University of Madrid, Madrid, Spain
| | - Pablo Cuesta
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Complutense University of Madrid, Madrid, Spain
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Polytechnic University of Madrid, Madrid, Spain
| | - Inmaculada Concepción Rodríguez-Rojo
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Polytechnic University of Madrid, Madrid, Spain
- Psychology Faculty, Centro Universitario Villanueva, Madrid, Spain
- Physiotherapy and Nursing Faculty, University of Castilla-La Mancha, Toledo, Spain
| | - Ana Barabash
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Laboratory of Psychoneuroendocrinology and Genetics, San Carlos University Hospital, Madrid, Spain
| | - Alberto Marcos
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Neurology Department, San Carlos University Hospital, Madrid, Spain
| | - Fernando Maestú
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Complutense University of Madrid, Madrid, Spain
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Polytechnic University of Madrid, Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Polytechnic University of Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Legal Medicine, Psychiatry and Pathology, Complutense University of Madrid, Madrid, Spain
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39
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Transcutaneous Vagus Nerve Stimulation in Humans Induces Pupil Dilation and Attenuates Alpha Oscillations. J Neurosci 2020; 41:320-330. [PMID: 33214317 DOI: 10.1523/jneurosci.1361-20.2020] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 10/28/2020] [Accepted: 10/30/2020] [Indexed: 01/19/2023] Open
Abstract
Vagus nerve stimulation (VNS) is widely used to treat drug-resistant epilepsy and depression. While the precise mechanisms mediating its long-term therapeutic effects are not fully resolved, they likely involve locus coeruleus (LC) stimulation via the nucleus of the solitary tract, which receives afferent vagal inputs. In rats, VNS elevates LC firing and forebrain noradrenaline levels, whereas LC lesions suppress VNS therapeutic efficacy. Noninvasive transcutaneous VNS (tVNS) uses electrical stimulation that targets the auricular branch of the vagus nerve at the cymba conchae of the ear. However, the extent to which tVNS mimics VNS remains unclear. Here, we investigated the short-term effects of tVNS in healthy human male volunteers (n = 24), using high-density EEG and pupillometry during visual fixation at rest. We compared short (3.4 s) trials of tVNS to sham electrical stimulation at the earlobe (far from the vagus nerve branch) to control for somatosensory stimulation. Although tVNS and sham stimulation did not differ in subjective intensity ratings, tVNS led to robust pupil dilation (peaking 4-5 s after trial onset) that was significantly higher than following sham stimulation. We further quantified, using parallel factor analysis, how tVNS modulates idle occipital alpha (8-13Hz) activity identified in each participant. We found greater attenuation of alpha oscillations by tVNS than by sham stimulation. This demonstrates that tVNS reliably induces pupillary and EEG markers of arousal beyond the effects of somatosensory stimulation, thus supporting the hypothesis that tVNS elevates noradrenaline and other arousal-promoting neuromodulatory signaling, and mimics invasive VNS.SIGNIFICANCE STATEMENT Current noninvasive brain stimulation techniques are mostly confined to modulating cortical activity, as is typical with transcranial magnetic or transcranial direct/alternating current electrical stimulation. Transcutaneous vagus nerve stimulation (tVNS) has been proposed to stimulate subcortical arousal-promoting nuclei, though previous studies yielded inconsistent results. Here we show that short (3.4 s) tVNS pulses in naive healthy male volunteers induced transient pupil dilation and attenuation of occipital alpha oscillations. These markers of brain arousal are in line with the established effects of invasive VNS on locus coeruleus-noradrenaline signaling, and support that tVNS mimics VNS. Therefore, tVNS can be used as a tool for studying how endogenous subcortical neuromodulatory signaling affects human cognition, including perception, attention, memory, and decision-making; and also for developing novel clinical applications.
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40
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Lejko N, Larabi DI, Herrmann CS, Aleman A, Ćurčić-Blake B. Alpha Power and Functional Connectivity in Cognitive Decline: A Systematic Review and Meta-Analysis. J Alzheimers Dis 2020; 78:1047-1088. [PMID: 33185607 PMCID: PMC7739973 DOI: 10.3233/jad-200962] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Background: Mild cognitive impairment (MCI) is a stage between expected age-related cognitive decline and dementia. Dementias have been associated with changes in neural oscillations across the frequency spectrum, including the alpha range. Alpha is the most prominent rhythm in human EEG and is best detected during awake resting state (RS). Though several studies measured alpha power and synchronization in MCI, findings have not yet been integrated. Objective: To consolidate findings on power and synchronization of alpha oscillations across stages of cognitive decline. Methods: We included studies published until January 2020 that compared power or functional connectivity between 1) people with MCI and cognitively healthy older adults (OA) or people with a neurodegenerative dementia, and 2) people with progressive and stable MCI. Random-effects meta-analyses were performed when enough data was available. Results: Sixty-eight studies were included in the review. Global RS alpha power was lower in AD than in MCI (ES = –0.30; 95% CI = –0.51, –0.10; k = 6), and in MCI than in OA (ES = –1.49; 95% CI = –2.69, –0.29; k = 5). However, the latter meta-analysis should be interpreted cautiously due to high heterogeneity. The review showed lower RS alpha power in progressive than in stable MCI, and lower task-related alpha reactivity in MCI than in OA. People with MCI had both lower and higher functional connectivity than OA. Publications lacked consistency in MCI diagnosis and EEG measures. Conclusion: Research indicates that RS alpha power decreases with increasing impairment, and could—combined with measures from other frequency bands—become a biomarker of early cognitive decline.
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Affiliation(s)
- Nena Lejko
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands
| | - Daouia I Larabi
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.,Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - André Aleman
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands
| | - Branislava Ćurčić-Blake
- University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, The Netherlands
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41
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Hoshi H, Shigihara Y. Age- and gender-specific characteristics of the resting-state brain activity: a magnetoencephalography study. Aging (Albany NY) 2020; 12:21613-21637. [PMID: 33147568 PMCID: PMC7695396 DOI: 10.18632/aging.103956] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 08/01/2020] [Indexed: 12/29/2022]
Abstract
Aging and gender influence regional brain activities. Although these biases should be considered during the clinical examinations using magnetoencephalography, they have yet to be standardized. In the present study, resting-state magnetoencephalography data were recorded from 54 healthy females and 48 males aged 22 to 75 years, who were controlled for cognitive performance. The regional oscillatory power was estimated for each frequency band (delta, theta, alpha, beta, low-gamma, and high-gamma) using the sLORETA-like algorithm and the biases of age and gender were evaluated, respectively. The results showed that faster oscillatory powers increased with age in the rostral regions and decreased in the caudal regions, while few slower oscillatory powers changed with age. Gender differences in oscillatory powers were found in a broad frequency range, mostly in the caudal brain regions. The present study characterized the effects of healthy aging and gender asymmetricity on the regional resting-state brain activity, with the aim to facilitate the accurate and efficient use of magnetoencephalography in clinical practice.
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Affiliation(s)
- Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro-shi, Hokkaido, Japan
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42
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Varatharajah Y, Berry B, Joseph B, Balzekas I, Kremen V, Brinkmann B, Worrell G, Iyer R. Electrophysiological Correlates of Brain Health Help Diagnose Epilepsy and Lateralize Seizure Focus. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3460-3464. [PMID: 33018748 DOI: 10.1109/embc44109.2020.9176668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The absence of epileptiform activity in a scalp electroencephalogram (EEG) recorded from a potential epilepsy patient can cause delays in clinical care delivery. Here we present a machine-learning-based approach to find evidence for epilepsy in scalp EEGs that do not contain any epileptiform activity, according to expert visual review (i.e., "normal" EEGs). We found that deviations in the EEG features representing brain health, such as the alpha rhythm, can indicate the potential for epilepsy and help lateralize seizure focus, even when commonly recognized epileptiform features are absent. Hence, we developed a machine-learning-based approach that utilizes alpha-rhythm-related features to classify 1) whether an EEG was recorded from an epilepsy patient, and 2) if so, the seizure-generating side of the patient's brain. We evaluated our approach using "normal" scalp EEGs of 48 patients with drug-resistant focal epilepsy and 144 healthy individuals, and a naive Bayes classifier achieved area under ROC curve (AUC) values of 0.81 and 0.72 for the two classification tasks, respectively. These findings suggest that our methodology is useful in the absence of interictal epileptiform activity and can enhance the probability of diagnosing epilepsy at the earliest possible time.
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43
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Fresnoza S, Christova M, Bieler L, Körner C, Zimmer U, Gallasch E, Ischebeck A. Age-Dependent Effect of Transcranial Alternating Current Stimulation on Motor Skill Consolidation. Front Aging Neurosci 2020; 12:25. [PMID: 32116653 PMCID: PMC7016219 DOI: 10.3389/fnagi.2020.00025] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 01/22/2020] [Indexed: 12/30/2022] Open
Abstract
Transcranial alternating current stimulation (tACS) is the application of subthreshold, sinusoidal current to modulate ongoing brain rhythms related to sensory, motor and cognitive processes. Electrophysiological studies suggested that the effect of tACS applied at an alpha frequency (8–12 Hz) was state-dependent. The effects of tACS, that is, an increase in parieto-occipital electroencephalography (EEG) alpha power and magnetoencephalography (MEG) phase coherence, was only observed when the eyes were open (low alpha power) and not when the eyes were closed (high alpha power). This state-dependency of the effects of alpha tACS might extend to the aging brain characterized by general slowing and decrease in spectral power of the alpha rhythm. We additionally hypothesized that tACS will influence the motor cortex, which is involved in motor skill learning and consolidation. A group of young and old healthy adults performed a serial reaction time task (SRTT) with their right hand before and after the tACS stimulation. Each participant underwent three sessions of stimulation: sham, stimulation applied at the individual participant’s alpha peak frequency or individual alpha peak frequency (iAPF; α-tACS) and stimulation with iAPF plus 2 Hz (α2-tACS) to the left motor cortex for 10 min (1.5 mA). We measured the effect of stimulation on general motor skill (GMS) and sequence-specific skill (SS) consolidation. We found that α-tACS and α2-tACS improved GMS and SS consolidation in the old group. In contrast, α-tACS minimally improved GMS consolidation but impaired SS consolidation in the young group. On the other hand, α2-tACS was detrimental to the consolidation of both skills in the young group. Our results suggest that individuals with aberrant alpha rhythm such as the elderly could benefit more from tACS stimulation, whereas for young healthy individuals with intact alpha rhythm the stimulation could be detrimental.
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Affiliation(s)
- Shane Fresnoza
- Institute of Psychology University of Graz, Graz, Austria.,BioTechMed, Graz, Austria
| | - Monica Christova
- Otto Loewi Research Center, Division of Physiology, Medical University of Graz, Graz, Austria.,Institute of Physiotherapy, University of Applied Sciences FH-JOANNEUM, Graz, Austria
| | - Lara Bieler
- Institute of Psychology University of Graz, Graz, Austria.,Otto Loewi Research Center, Division of Physiology, Medical University of Graz, Graz, Austria
| | - Christof Körner
- Institute of Psychology University of Graz, Graz, Austria.,BioTechMed, Graz, Austria
| | - Ulrike Zimmer
- Institute of Psychology University of Graz, Graz, Austria.,Faculty of Human Sciences, Medical School Hamburg (MSH), Hamburg, Germany
| | - Eugen Gallasch
- BioTechMed, Graz, Austria.,Otto Loewi Research Center, Division of Physiology, Medical University of Graz, Graz, Austria
| | - Anja Ischebeck
- Institute of Psychology University of Graz, Graz, Austria.,Otto Loewi Research Center, Division of Physiology, Medical University of Graz, Graz, Austria
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Benwell CSY, Davila-Pérez P, Fried PJ, Jones RN, Travison TG, Santarnecchi E, Pascual-Leone A, Shafi MM. EEG spectral power abnormalities and their relationship with cognitive dysfunction in patients with Alzheimer's disease and type 2 diabetes. Neurobiol Aging 2020; 85:83-95. [PMID: 31727363 PMCID: PMC6942171 DOI: 10.1016/j.neurobiolaging.2019.10.004] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 09/30/2019] [Accepted: 10/07/2019] [Indexed: 12/13/2022]
Abstract
Rhythmic neural activity has been proposed to play a fundamental role in cognition. Both healthy and pathological aging are characterized by frequency-specific changes in oscillatory activity. However, the cognitive relevance of these changes across the spectrum from normal to pathological aging remains unknown. We examined electroencephalography (EEG) correlates of cognitive function in healthy aging and 2 of the most prominent and debilitating age-related disorders: type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD). Relative to healthy controls (HC), patients with AD were impaired on nearly every cognitive measure, whereas patients with T2DM performed worse mainly on learning and memory tests. A continuum of alterations in resting-state EEG was associated with pathological aging, generally characterized by reduced alpha (α) and beta (β) power (AD < T2DM < HC) and increased delta (δ) and theta (θ) power (AD > T2DM > HC), with some variations across different brain regions. There were also reductions in the frequency and power density of the posterior dominant rhythm in AD. The ratio of (α + β)/(δ + θ) was specifically associated with cognitive function in a domain- and diagnosis-specific manner. The results thus captured both similarities and differences in the pathophysiology of cerebral oscillations in T2DM and AD. Overall, pathological brain aging is marked by a shift in oscillatory power from higher to lower frequencies, which can be captured by a single cognitively relevant measure of the ratio of (α + β) over (δ + θ) power.
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Affiliation(s)
- Christopher S Y Benwell
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Psychology, School of Social Sciences, University of Dundee, Dundee, UK.
| | - Paula Davila-Pérez
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Neuroscience and Motor Control Group (NEUROcom), Institute for Biomedical Research (INIBIC), Universidade da Coruña, A Coruña, Spain
| | - Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Richard N Jones
- Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Butler Hospital, Providence, RI, USA
| | - Thomas G Travison
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA
| | - Emiliano Santarnecchi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Hinda and Arthur Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA, USA; Institut Guttman, Universitat Autonoma de Barcelona, Badalona, Barcelona, Spain; Center for Memory Health, Hebrew Senior Life, Boston, MA, USA
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA; Comprehensive Epilepsy Center, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
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45
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Barzegaran E, Bosse S, Kohler PJ, Norcia AM. EEGSourceSim: A framework for realistic simulation of EEG scalp data using MRI-based forward models and biologically plausible signals and noise. J Neurosci Methods 2019; 328:108377. [PMID: 31381946 PMCID: PMC6815881 DOI: 10.1016/j.jneumeth.2019.108377] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 07/13/2019] [Accepted: 07/29/2019] [Indexed: 02/02/2023]
Abstract
BACKGROUND Electroencephalography (EEG) is widely used to investigate human brain function. Simulation studies are essential for assessing the validity of EEG analysis methods and the interpretability of results. NEW METHOD Here we present a simulation environment for generating EEG data by embedding biologically plausible signal and noise into MRI-based forward models that incorporate individual-subject variability in structure and function. RESULTS The package includes pipelines for the evaluation and validation of EEG analysis tools for source estimation, functional connectivity, and spatial filtering. EEG dynamics can be simulated using realistic noise and signal models with user specifiable signal-to-noise ratio (SNR). We also provide a set of quantitative metrics tailored to source estimation, connectivity and spatial filtering applications. COMPARISON WITH EXISTING METHOD(S) We provide a larger set of forward solutions for individual MRI-based head models than has been available previously. These head models are surface-based and include two sets of regions-of-interest (ROIs) that have been brought into registration with the brain of each individual using surface-based alignment - one from a whole brain and the other from a visual cortex atlas. We derive a realistic model of noise by fitting different model components to measured resting state EEG. We also provide a set of quantitative metrics for evaluating source-localization, functional connectivity and spatial filtering methods. CONCLUSIONS The inclusion of a larger number of individual head-models, combined with surface-atlas based labeling of ROIs and plausible models of signal and noise, allows for simulation of EEG data with greater realism than previous packages.
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Affiliation(s)
- Elham Barzegaran
- Department of Psychology, Jordan Hall, Building 420, Stanford University, Stanford, CA 94305, USA.
| | - Sebastian Bosse
- Department of Video Coding & Analytics, Fraunhofer Heinrich Hertz Institute, 10587 Berlin, Germany.
| | - Peter J Kohler
- Department of Psychology, Jordan Hall, Building 420, Stanford University, Stanford, CA 94305, USA; Department of Psychology and Centre for Vision Research, Core Member, Vision: Science to Applications (VISTA), York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.
| | - Anthony M Norcia
- Department of Psychology, Jordan Hall, Building 420, Stanford University, Stanford, CA 94305, USA.
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Alatorre-Cruz GC, Silva-Pereyra J, Fernández T, Rodríguez-Camacho MA. Poor working memory performance in healthy elderly adults with electroencephalographic risk of cognitive decline affects syntactic processing. Clin Neurophysiol 2019; 130:2222-2230. [PMID: 31698266 DOI: 10.1016/j.clinph.2019.09.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 07/26/2019] [Accepted: 09/15/2019] [Indexed: 11/19/2022]
Abstract
OBJECTIVE To examine the effects of working memory (WM) load and gender agreement on sentence processing as a function of the electroencephalographic risk (i.e., abnormally high values of theta absolute power) of cognitive decline in older adults. METHODS Event-related potentials (ERPs) were collected from Spanish speakers (22 older adults belonged to the Risk group, mean age = 67.7 years; 22 older adults belonged to the Control group, mean age = 65.2 years) while reading sentences to detect grammatical errors. Sentences varied with regard to (1) the gender agreement of the noun and adjective, where gender of the adjective either agreed or disagreed with the noun, and (2) WM load (i.e., the number of words between the noun and adjective in the sentence). RESULTS The Risk group showed a lower percentage of correct answers and longer reaction times than the Control group. The Risk group also showed a different pattern of ERP components, which was characterized by smaller amplitude and longer latency of the P600a component under high WM load conditions. CONCLUSION The findings suggest that the Risk group shows difficulties integrating information associated with the previous sentence context. SIGNIFICANCE The electroencephalographic risk factor of cognitive decline might be not only a predictor of but also an indicator of current decline.
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Affiliation(s)
- Graciela Catalina Alatorre-Cruz
- Laboratorio de Neurometría, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, 1 de los Barrios Avenue, Tlalnepantla, Estado de México 54090, Mexico
| | - Juan Silva-Pereyra
- Laboratorio de Neurometría, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, 1 de los Barrios Avenue, Tlalnepantla, Estado de México 54090, Mexico.
| | - Thalía Fernández
- Laboratorio de Psicofisiología, Instituto de Neurobiología, Universidad Nacional Autónoma de México, 3001 Juriquilla Boulevard, Santiago de Querétaro, Querétaro 76230, Mexico
| | - Mario A Rodríguez-Camacho
- Laboratorio de Neurometría, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México, 1 de los Barrios Avenue, Tlalnepantla, Estado de México 54090, Mexico
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