1
|
Li S, Rosen MC, Chang S, David S, Freedman DJ. Alterations of neural activity in the prefrontal cortex associated with deficits in working memory performance. Front Behav Neurosci 2023; 17:1213435. [PMID: 37915531 PMCID: PMC10616307 DOI: 10.3389/fnbeh.2023.1213435] [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: 04/27/2023] [Accepted: 08/31/2023] [Indexed: 11/03/2023] Open
Abstract
Working memory (WM), a core cognitive function, enables the temporary holding and manipulation of information in mind to support ongoing behavior. Neurophysiological recordings conducted in nonhuman primates have revealed neural correlates of this process in a network of higher-order cortical regions, particularly the prefrontal cortex (PFC). Here, we review the circuit mechanisms and functional importance of WM-related activity in these areas. Recent neurophysiological data indicates that the absence of these neural correlates at different stages of WM is accompanied by distinct behavioral deficits, which are characteristic of various disease states/normal aging and which we review here. Finally, we discuss emerging evidence of electrical stimulation ameliorating these WM deficits in both humans and non-human primates. These results are important for a basic understanding of the neural mechanisms supporting WM, as well as for translational efforts to developing therapies capable of enhancing healthy WM ability or restoring WM from dysfunction.
Collapse
Affiliation(s)
- Sihai Li
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - Matthew C. Rosen
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - Suha Chang
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - Samuel David
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - David J. Freedman
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
- Neuroscience Institute, The University of Chicago, Chicago, IL, United States
| |
Collapse
|
2
|
Hinkley LBN, Thompson M, Miller ZA, Borghesani V, Mizuiri D, Shwe W, Licata A, Ninomiya S, Lauricella M, Mandelli ML, Miller BL, Houde J, Gorno‐Tempini ML, Nagarajan SS. Distinct neurophysiology during nonword repetition in logopenic and non-fluent variants of primary progressive aphasia. Hum Brain Mapp 2023; 44:4833-4847. [PMID: 37516916 PMCID: PMC10472914 DOI: 10.1002/hbm.26408] [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: 12/20/2022] [Revised: 04/25/2023] [Accepted: 06/11/2023] [Indexed: 07/31/2023] Open
Abstract
Overlapping clinical presentations in primary progressive aphasia (PPA) variants present challenges for diagnosis and understanding pathophysiology, particularly in the early stages of the disease when behavioral (speech) symptoms are not clearly evident. Divergent atrophy patterns (temporoparietal degeneration in logopenic variant lvPPA, frontal degeneration in nonfluent variant nfvPPA) can partially account for differential speech production errors in the two groups in the later stages of the disease. While the existing dogma states that neurodegeneration is the root cause of compromised behavior and cortical activity in PPA, the extent to which neurophysiological signatures of speech dysfunction manifest independent of their divergent atrophy patterns remain unknown. We test the hypothesis that nonword deficits in lvPPA and nfvPPA arise from distinct patterns of neural oscillations that are unrelated to atrophy. We use a novel structure-function imaging approach integrating magnetoencephalographic imaging of neural oscillations during a non-word repetition task with voxel-based morphometry-derived measures of gray matter volume to isolate neural oscillation abnormalities independent of atrophy. We find reduced beta band neural activity in left temporal regions associated with the late stages of auditory encoding unique to patients with lvPPA and reduced high-gamma neural activity over left frontal regions associated with the early stages of motor preparation in patients with nfvPPA. Neither of these patterns of reduced cortical oscillations was explained by cortical atrophy in our statistical model. These findings highlight the importance of structure-function imaging in revealing neurophysiological sequelae in early stages of dementia when neither structural atrophy nor behavioral deficits are clinically distinct.
Collapse
Affiliation(s)
- Leighton B. N. Hinkley
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Megan Thompson
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Zachary A. Miller
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | - Danielle Mizuiri
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Wendy Shwe
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Abigail Licata
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Seigo Ninomiya
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Michael Lauricella
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | - Bruce L. Miller
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - John Houde
- Department of Otolaryngology – Head and Neck SurgeryUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | | - Srikantan S. Nagarajan
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
| |
Collapse
|
3
|
Kim SE, Shin C, Yim J, Seo K, Ryu H, Choi H, Park J, Min BK. Resting-state electroencephalographic characteristics related to mild cognitive impairments. Front Psychiatry 2023; 14:1231861. [PMID: 37779609 PMCID: PMC10539934 DOI: 10.3389/fpsyt.2023.1231861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 08/28/2023] [Indexed: 10/03/2023] Open
Abstract
Alzheimer's disease (AD) causes a rapid deterioration in cognitive and physical functions, including problem-solving, memory, language, and daily activities. Mild cognitive impairment (MCI) is considered a risk factor for AD, and early diagnosis and treatment of MCI may help slow the progression of AD. Electroencephalography (EEG) analysis has become an increasingly popular tool for developing biomarkers for MCI and AD diagnosis. Compared with healthy elderly, patients with AD showed very clear differences in EEG patterns, but it is inconclusive for MCI. This study aimed to investigate the resting-state EEG features of individuals with MCI (n = 12) and cognitively healthy controls (HC) (n = 13) with their eyes closed. EEG data were analyzed using spectral power, complexity, functional connectivity, and graph analysis. The results revealed no significant difference in EEG spectral power between the HC and MCI groups. However, we observed significant changes in brain complexity and networks in individuals with MCI compared with HC. Patients with MCI exhibited lower complexity in the middle temporal lobe, lower global efficiency in theta and alpha bands, higher local efficiency in the beta band, lower nodal efficiency in the frontal theta band, and less small-world network topology compared to the HC group. These observed differences may be related to underlying neuropathological alterations associated with MCI progression. The findings highlight the potential of network analysis as a promising tool for the diagnosis of MCI.
Collapse
Affiliation(s)
- Seong-Eun Kim
- Department of Applied Artificial Intelligence, Seoul National University of Science and Technology, Seoul, Republic of Korea
| | - Chanwoo Shin
- Department of Applied Artificial Intelligence, Seoul National University of Science and Technology, Seoul, Republic of Korea
| | - Junyeop Yim
- Department of Applied Mathematics, Kongju National University, Gongju-si, Republic of Korea
| | - Kyoungwon Seo
- Department of Applied Artificial Intelligence, Seoul National University of Science and Technology, Seoul, Republic of Korea
| | - Hokyoung Ryu
- Graduate School of Technology and Innovation Management, Hanyang University, Seoul, Republic of Korea
| | - Hojin Choi
- Department of Neurology, College of Medicine, Hanyang University, Seoul, Republic of Korea
| | - Jinseok Park
- Department of Neurology, College of Medicine, Hanyang University, Seoul, Republic of Korea
| | - Byoung-Kyong Min
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| |
Collapse
|
4
|
Sergiou CS, Tatti E, Romanella SM, Santarnecchi E, Weidema AD, Rassin EG, Franken IH, van Dongen JD. The effect of HD-tDCS on brain oscillations and frontal synchronicity during resting-state EEG in violent offenders with a substance dependence. Int J Clin Health Psychol 2023; 23:100374. [PMID: 36875007 PMCID: PMC9982047 DOI: 10.1016/j.ijchp.2023.100374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 01/25/2023] [Indexed: 02/24/2023] Open
Abstract
Violence is a major problem in our society and therefore research into the neural underpinnings of aggression has grown exponentially. Although in the past decade the biological underpinnings of aggressive behavior have been examined, research on neural oscillations in violent offenders during resting-state electroencephalography (rsEEG) remains scarce. In this study we aimed to investigate the effect of high-definition transcranial direct current stimulation (HD-tDCS) on frontal theta, alpha and beta frequency power, asymmetrical frontal activity, and frontal synchronicity in violent offenders. Fifty male violent forensic patients diagnosed with a substance dependence were included in a double-blind sham-controlled randomized study. The patients received 20 minutes of HD-tDCS two times a day on five consecutive days. Before and after the intervention, the patients underwent a rsEEG task. Results showed no effect of HD-tDCS on the power in the different frequency bands. Also, no increase in asymmetrical activity was found. However, we found increased synchronicity in frontal regions in the alpha and beta frequency bands indicating enhanced connectivity in frontal brain regions as a result of the HD-tDCS-intervention. This study has enhanced our understanding of the neural underpinnings of aggression and violence, pointing to the importance of alpha and beta frequency bands and their connectivity in frontal brain regions. Although future studies should further investigate the complex neural underpinnings of aggression in different populations and using whole-brain connectivity, it can be suggested with caution, that HD-tDCS could be an innovative method to regain frontal synchronicity in neurorehabilitation.
Collapse
Affiliation(s)
- Carmen S. Sergiou
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Elisa Tatti
- City College of New York (CUNY) School of Medicine, New York, NY, USA
| | - Sara M. Romanella
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Medical Center, Harvard Medical School, Boston, MA, USA
| | - Emiliano Santarnecchi
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Medical Center, Harvard Medical School, Boston, MA, USA
| | - Alix D. Weidema
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Eric G.C Rassin
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Ingmar H.A. Franken
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Josanne D.M. van Dongen
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, the Netherlands
| |
Collapse
|
5
|
Liu M, Liu B, Ye Z, Wu D. Bibliometric analysis of electroencephalogram research in mild cognitive impairment from 2005 to 2022. Front Neurosci 2023; 17:1128851. [PMID: 37021134 PMCID: PMC10067679 DOI: 10.3389/fnins.2023.1128851] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 03/06/2023] [Indexed: 03/22/2023] Open
Abstract
BackgroundElectroencephalogram (EEG), one of the most commonly used non-invasive neurophysiological examination techniques, advanced rapidly between 2005 and 2022, particularly when it was used for the diagnosis and prognosis of mild cognitive impairment (MCI). This study used a bibliometric approach to synthesize the knowledge structure and cutting-edge hotspots of EEG application in the MCI.MethodsRelated publications in the Web of Science Core Collection (WosCC) were retrieved from inception to 30 September 2022. CiteSpace, VOSviewer, and HistCite software were employed to perform bibliographic and visualization analyses.ResultsBetween 2005 and 2022, 2,905 studies related to the application of EEG in MCI were investigated. The United States had the highest number of publications and was at the top of the list of international collaborations. In terms of total number of articles, IRCCS San Raffaele Pisana ranked first among institutions. The Clinical Neurophysiology published the greatest number of articles. The author with the highest citations was Babiloni C. In descending order of frequency, keywords with the highest frequency were “EEG,” “mild cognitive impairment,” and “Alzheimer’s disease”.ConclusionThe application of EEG in MCI was investigated using bibliographic analysis. The research emphasis has shifted from examining local brain lesions with EEG to neural network mechanisms. The paradigm of big data and intelligent analysis is becoming more relevant in EEG analytical methods. The use of EEG to link MCI to other related neurological disorders, and to evaluate new targets for diagnosis and treatment, has become a new research trend. The above-mentioned findings have implications in the future research on the application of EEG in MCI.
Collapse
Affiliation(s)
- Mingrui Liu
- Department of Rehabilitation, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Baohu Liu
- Department of Rehabilitation, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zelin Ye
- Department of Cardiovascular, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Dongyu Wu
- Department of Rehabilitation, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- *Correspondence: Dongyu Wu,
| |
Collapse
|
6
|
Wang C, Xu T, Yu W, Li T, Han H, Zhang M, Tao M. Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography: From the perspective of event related potentials and deep learning. Int J Psychophysiol 2022; 182:182-189. [DOI: 10.1016/j.ijpsycho.2022.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/21/2022] [Accepted: 10/24/2022] [Indexed: 11/06/2022]
|
7
|
Cao J, Zhao Y, Shan X, Blackburn D, Wei J, Erkoyuncu JA, Chen L, Sarrigiannis PG. Ultra-high-resolution time-frequency analysis of EEG to characterise brain functional connectivity with the application in Alzheimer's disease. J Neural Eng 2022; 19. [PMID: 35896105 DOI: 10.1088/1741-2552/ac84ac] [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: 12/28/2021] [Accepted: 07/27/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE This study aims to explore the potential of high-resolution brain functional connectivity based on electroencephalogram (EEG), a non-invasive low-cost technique, to be translated into a long-overdue biomarker and a diagnostic method for Alzheimer's disease (AD). APPROACH The paper proposes a novel ultra-high-resolution time-frequency nonlinear cross-spectrum method to construct a promising biomarker of AD pathophysiology. Specifically, using the peak frequency estimated from a Revised Hilbert-Huang Transformation cross-spectrum as a biomarker, the Support Vector Machine classifier is used to distinguish AD from healthy controls (HC). MAIN RESULTS With the combinations of the proposed biomarker and machine learning, we achieved a promising accuracy of 89%. The proposed method performs better than the wavelet cross-spectrum and other functional connectivity measures in the temporal or frequency domain, particularly in the Full, Delta and Alpha bands. Besides, a novel visualisation approach developed from topography is introduced to represent the brain functional connectivity, with which the difference between AD and HCs can be clearly displayed. The interconnections between posterior and other brain regions are obviously affected in AD. SIGNIFICANCE Those findings imply that the proposed RHHT approach could better track dynamic and nonlinear functional connectivity information, paving the way for the development of a novel diagnostic approach.
Collapse
Affiliation(s)
- Jun Cao
- Cranfield University, Building 30, Cranfield, Bedford, Cranfield, Bedfordshire, MK43 0AL, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Yifan Zhao
- Cranfield University, Building 30, Cranfield, Bedford, Cranfield, Bedfordshire, MK43 0AL, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Xiaocai Shan
- Cranfield University, Building 30, Cranfield, Bedford, Bedfordshire, MK43 0AL, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Daniel Blackburn
- Department of Neuroscience, University of Sheffield, 385a Glossop Road, Sheffield, S10 7HQ, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Jize Wei
- Hong Kong Polytechnic University University Learning Hub, Department of Applied Mathematics, Kowloon, HONG KONG
| | - John Ahmet Erkoyuncu
- Cranfield University, Building 30, Cranfield, Bedford, Cranfield, Bedfordshire, MK43 0AL, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| | - Liangyu Chen
- Department of Neurosurgery, Shengjing Hospital of China Medical University, Sanhao street, Shenyang, 110004, CHINA
| | - Ptolemaios G Sarrigiannis
- Royal Devon and Exeter NHS Foundation Trust, 1, Exeter, EX2 5DW, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
| |
Collapse
|
8
|
Adeoye T, Shah SI, Demuro A, Rabson DA, Ullah G. Upregulated Ca 2+ Release from the Endoplasmic Reticulum Leads to Impaired Presynaptic Function in Familial Alzheimer's Disease. Cells 2022; 11:2167. [PMID: 35883609 PMCID: PMC9315668 DOI: 10.3390/cells11142167] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/28/2022] [Accepted: 07/02/2022] [Indexed: 12/10/2022] Open
Abstract
Neurotransmitter release from presynaptic terminals is primarily regulated by rapid Ca2+ influx through membrane-resident voltage-gated Ca2+ channels (VGCCs). Moreover, accumulating evidence indicates that the endoplasmic reticulum (ER) is extensively present in axonal terminals of neurons and plays a modulatory role in synaptic transmission by regulating Ca2+ levels. Familial Alzheimer's disease (FAD) is marked by enhanced Ca2+ release from the ER and downregulation of Ca2+ buffering proteins. However, the precise consequence of impaired Ca2+ signaling within the vicinity of VGCCs (active zone (AZ)) on exocytosis is poorly understood. Here, we perform in silico experiments of intracellular Ca2+ signaling and exocytosis in a detailed biophysical model of hippocampal synapses to investigate the effect of aberrant Ca2+ signaling on neurotransmitter release in FAD. Our model predicts that enhanced Ca2+ release from the ER increases the probability of neurotransmitter release in FAD. Moreover, over very short timescales (30-60 ms), the model exhibits activity-dependent and enhanced short-term plasticity in FAD, indicating neuronal hyperactivity-a hallmark of the disease. Similar to previous observations in AD animal models, our model reveals that during prolonged stimulation (~450 ms), pathological Ca2+ signaling increases depression and desynchronization with stimulus, causing affected synapses to operate unreliably. Overall, our work provides direct evidence in support of a crucial role played by altered Ca2+ homeostasis mediated by intracellular stores in FAD.
Collapse
Affiliation(s)
- Temitope Adeoye
- Department of Physics, University of South Florida, Tampa, FL 33620, USA; (T.A.); (S.I.S.); (D.A.R.)
| | - Syed I. Shah
- Department of Physics, University of South Florida, Tampa, FL 33620, USA; (T.A.); (S.I.S.); (D.A.R.)
| | - Angelo Demuro
- Department of Neurobiology and Behavior, University of California, Irvine, CA 92697, USA;
| | - David A. Rabson
- Department of Physics, University of South Florida, Tampa, FL 33620, USA; (T.A.); (S.I.S.); (D.A.R.)
| | - Ghanim Ullah
- Department of Physics, University of South Florida, Tampa, FL 33620, USA; (T.A.); (S.I.S.); (D.A.R.)
| |
Collapse
|
9
|
Clark RA, Smith K, Escudero J, Ibáñez A, Parra MA. Robust Assessment of EEG Connectivity Patterns in Mild Cognitive Impairment and Alzheimer's Disease. FRONTIERS IN NEUROIMAGING 2022; 1:924811. [PMID: 37555186 PMCID: PMC10406240 DOI: 10.3389/fnimg.2022.924811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/21/2022] [Indexed: 08/10/2023]
Abstract
The prevalence of dementia, including Alzheimer's disease (AD), is on the rise globally with screening and intervention of particular importance and benefit to those with limited access to healthcare. Electroencephalogram (EEG) is an inexpensive, scalable, and portable brain imaging technology that could deliver AD screening to those without local tertiary healthcare infrastructure. We study EEG recordings of subjects with sporadic mild cognitive impairment (MCI) and prodromal familial, early-onset, AD for the same working memory tasks using high- and low-density EEG, respectively. A challenge in detecting electrophysiological changes from EEG recordings is that noise and volume conduction effects are common and disruptive. It is known that the imaginary part of coherency (iCOH) can generate functional connectivity networks that mitigate against volume conduction, while also erasing true instantaneous activity (zero or π-phase). We aim to expose topological differences in these iCOH connectivity networks using a global network measure, eigenvector alignment (EA), shown to be robust to network alterations that emulate the erasure of connectivities by iCOH. Alignments assessed by EA capture the relationship between a pair of EEG channels from the similarity of their connectivity patterns. Significant alignments-from comparison with random null models-are seen to be consistent across frequency ranges (delta, theta, alpha, and beta) for the working memory tasks, where consistency of iCOH connectivities is also noted. For high-density EEG recordings, stark differences in the control and sporadic MCI results are observed with the control group demonstrating far more consistent alignments. Differences between the control and pre-dementia groupings are detected for significant correlation and iCOH connectivities, but only EA suggests a notable difference in network topology when comparing between subjects with sporadic MCI and prodromal familial AD. The consistency of alignments, across frequency ranges, provides a measure of confidence in EA's detection of topological structure, an important aspect that marks this approach as a promising direction for developing a reliable test for early onset AD.
Collapse
Affiliation(s)
- Ruaridh A. Clark
- Centre for Signal and Image Processing, University of Strathclyde, Glasgow, United Kingdom
| | - Keith Smith
- Department of Physics and Mathematics, Nottingham Trent University, Nottingham, United Kingdom
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh, United Kingdom
| | - Agustín Ibáñez
- Latin American Brain Health Institute, Universidad Adolfo Ibáñez, Santiago, Chile
- Cognitive Neuroscience Center, Universidad de San Andrés & Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
- Global Brain Health Institute (GBHI), University of California, San Francisco, CA, United States
- Global Brain Health Institute (GBHI), Trinity College, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Mario A. Parra
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, United Kingdom
| |
Collapse
|
10
|
Smith KM, Starr JM, Escudero J, Ibañez A, Parra MA. Abnormal Functional Hierarchies of EEG Networks in Familial and Sporadic Prodromal Alzheimer's Disease During Visual Short-Term Memory Binding. FRONTIERS IN NEUROIMAGING 2022; 1:883968. [PMID: 37555153 PMCID: PMC10406202 DOI: 10.3389/fnimg.2022.883968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 05/16/2022] [Indexed: 08/10/2023]
Abstract
Alzheimer's Disease (AD) shows both complex alterations of functional dependencies between brain regions and a decreased ability to perform Visual Short-Term Memory Binding (VSTMB) tasks. Recent advances in network neuroscience toward understanding the complexity of hierarchical brain function here enables us to establish a link between these two phenomena. Here, we study data on two types of dementia at Mild Cognitive Impairment (MCI) stage-familial AD patients (E280A mutation of the presenilin-1 gene) and elderly MCI patients at high risk of sporadic AD, both with age-matched controls. We analyzed Electroencephalogram (EEG) signals recorded during the performance of Visual Short-Term Memory (VSTM) tasks by these participants. Functional connectivity was computed using the phase-lag index in Alpha and Beta; and network analysis was employed using network indices of hierarchical spread (degree variance) and complexity. Hierarchical characteristics of EEG functional connectivity networks revealed abnormal patterns in familial MCI VSTMB function and sporadic MCI VSTMB function. The middle-aged familial MCI binding network displayed a larger degree variance in lower Beta compared to healthy controls (p = 0.0051, Cohen's d = 1.0124), while the elderly sporadic MCI binding network displayed greater hierarchical complexity in Alpha (p = 0.0140, Cohen's d = 1.1627). Characteristics in healthy aging were not shown to differ. These results indicate that activity in MCI exhibits cross-frequency network reorganization characterized by increased heterogeneity of node roles in the functional hierarchy. Aging itself is not found to cause VSTM functional hierarchy differences.
Collapse
Affiliation(s)
- Keith M. Smith
- Department of Physics and Mathematics, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom
| | - John M. Starr
- Alzheimer Scotland Dementia Research Centre, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, University of Edinburgh, Edinburgh, United Kingdom
| | - Agustin Ibañez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibañez, Santiago, Chile
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Center for Social and Cognitive Neuroscience, School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile
- Global Brain Health Institute, UCSF, San Francisco, CA, United States
- Trinity College Institute of Neuroscience, Trintity College Dublin, Dublin, Ireland
| | - Mario A. Parra
- Trinity College Institute of Neuroscience, Trintity College Dublin, Dublin, Ireland
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, United Kingdom
- Neuroprogressive and Dementia Network, NHS Scotland, Glasgow, United Kingdom
| |
Collapse
|
11
|
Salimi M, Tabasi F, Abdolsamadi M, Dehghan S, Dehdar K, Nazari M, Javan M, Mirnajafi-Zadeh J, Raoufy MR. Disrupted connectivity in the olfactory bulb-entorhinal cortex-dorsal hippocampus circuit is associated with recognition memory deficit in Alzheimer's disease model. Sci Rep 2022; 12:4394. [PMID: 35292712 PMCID: PMC8924156 DOI: 10.1038/s41598-022-08528-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/02/2022] [Indexed: 12/18/2022] Open
Abstract
Neural synchrony in brain circuits is the mainstay of cognition, including memory processes. Alzheimer's disease (AD) is a progressive neurodegenerative disorder that disrupts neural synchrony in specific circuits, associated with memory dysfunction before a substantial neural loss. Recognition memory impairment is a prominent cognitive symptom in the early stages of AD. The entorhinal-hippocampal circuit is critically engaged in recognition memory and is known as one of the earliest circuits involved due to AD pathology. Notably, the olfactory bulb is closely connected with the entorhinal-hippocampal circuit and is suggested as one of the earliest regions affected by AD. Therefore, we recorded simultaneous local field potential from the olfactory bulb (OB), entorhinal cortex (EC), and dorsal hippocampus (dHPC) to explore the functional connectivity in the OB-EC-dHPC circuit during novel object recognition (NOR) task performance in a rat model of AD. Animals that received amyloid-beta (Aβ) showed a significant impairment in task performance and a marked reduction in OB survived cells. We revealed that Aβ reduced coherence and synchrony in the OB-EC-dHPC circuit at theta and gamma bands during NOR performance. Importantly, our results exhibit that disrupted functional connectivity in the OB-EC-dHPC circuit was correlated with impaired recognition memory induced by Aβ. These findings can elucidate dynamic changes in neural activities underlying AD, helping to find novel diagnostic and therapeutic targets.
Collapse
Affiliation(s)
- Morteza Salimi
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, 1411713116, Iran
| | - Farhad Tabasi
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, 1411713116, Iran
- Faculty of Medical Sciences, Institute for Brain Sciences and Cognition, Tarbiat Modares University, Tehran, Iran
| | - Maryam Abdolsamadi
- Department of Mathematics, Faculty of Science, Islamic Azad University, North Tehran Branch, Tehran, Iran
| | - Samaneh Dehghan
- Stem Cell and Regenerative Medicine Research Center, Iran University of Medical Sciences, Tehran, Iran
- Eye Research Center, The Five Senses Institute, Rassoul Akram Hospital, Iran University of Medical Sciences, Tehran, Iran
| | - Kolsoum Dehdar
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, 1411713116, Iran
- Faculty of Medical Sciences, Institute for Brain Sciences and Cognition, Tarbiat Modares University, Tehran, Iran
| | - Milad Nazari
- Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
- DANDRITE, The Danish Research Institute of Translational Neuroscience, Aarhus University, Aarhus, Denmark
| | - Mohammad Javan
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, 1411713116, Iran
- Faculty of Medical Sciences, Institute for Brain Sciences and Cognition, Tarbiat Modares University, Tehran, Iran
| | - Javad Mirnajafi-Zadeh
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, 1411713116, Iran
- Faculty of Medical Sciences, Institute for Brain Sciences and Cognition, Tarbiat Modares University, Tehran, Iran
| | - Mohammad Reza Raoufy
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, 1411713116, Iran.
- Faculty of Medical Sciences, Institute for Brain Sciences and Cognition, Tarbiat Modares University, Tehran, Iran.
| |
Collapse
|
12
|
Karimi H, Marefat H, Khanbagi M, Kalafatis C, Modarres MH, Vahabi Z, Khaligh-Razavi SM. Temporal dynamics of animacy categorization in the brain of patients with mild cognitive impairment. PLoS One 2022; 17:e0264058. [PMID: 35196356 PMCID: PMC8865635 DOI: 10.1371/journal.pone.0264058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 02/02/2022] [Indexed: 11/18/2022] Open
Abstract
Electroencephalography (EEG) has been commonly used to measure brain alterations in Alzheimer’s Disease (AD). However, reported changes are limited to those obtained from using univariate measures, including activation level and frequency bands. To look beyond the activation level, we used multivariate pattern analysis (MVPA) to extract patterns of information from EEG responses to images in an animacy categorization task. Comparing healthy controls (HC) with patients with mild cognitive impairment (MCI), we found that the neural speed of animacy information processing is decreased in MCI patients. Moreover, we found critical time-points during which the representational pattern of animacy for MCI patients was significantly discriminable from that of HC, while the activation level remained unchanged. Together, these results suggest that the speed and pattern of animacy information processing provide clinically useful information as a potential biomarker for detecting early changes in MCI and AD patients.
Collapse
Affiliation(s)
- Hamed Karimi
- Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
- Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
- * E-mail: (HK); (SMKR)
| | - Haniyeh Marefat
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mahdiyeh Khanbagi
- Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
| | - Chris Kalafatis
- South London & Maudsley NHS Foundation Trust, London, United Kingdom
- Department of Old Age Psychiatry, King’s College London, London, United Kingdom
- Cognetivity Ltd, London, United Kingdom
| | | | - Zahra Vahabi
- Department of Geriatric Medicine, Ziaeian Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Memory and Behavioral Neurology Division, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed-Mahdi Khaligh-Razavi
- Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran
- Cognetivity Ltd, London, United Kingdom
- * E-mail: (HK); (SMKR)
| |
Collapse
|
13
|
Behavior of olfactory-related frontal lobe oscillations in Alzheimer's disease and MCI: A pilot study. Int J Psychophysiol 2022; 175:43-53. [PMID: 35217110 DOI: 10.1016/j.ijpsycho.2022.02.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 12/19/2021] [Accepted: 02/17/2022] [Indexed: 11/20/2022]
Abstract
Slow-gamma (35-45 Hz) phase synchronization and the coupling between slow-gamma and low-frequency theta oscillations (4-8 Hz) are closely related to memory retrieval and cognitive functions. In this pilot study, we assess the Phase Amplitude Coupling (PAC) between theta and slow-gamma oscillatory bands and the quality of synchronization in slow-gamma oscillations using Phase Locking Value (PLV) on EEG data from healthy individuals and patients diagnosed with amnestic Mild Cognitive Impairment (aMCI) and Alzheimer's Disease (AD) during an oddball olfactory task. Our study indicates noticeable differences between the PLV and PAC values corresponding to olfactory stimulation in the three groups of participants. These differences can help explain the underlying processes involved in these cognitive disorders and the differences between aMCI and AD patients in performing cognitive tasks. Our study also proposes a diagnosis method for aMCI through comparing the brain's response characteristics during olfactory stimulation and rest. Early diagnosis of aMCI can potentially lead to its timely treatment and prevention from progression to AD.
Collapse
|
14
|
Weighted Brain Network Analysis on Different Stages of Clinical Cognitive Decline. Bioengineering (Basel) 2022; 9:bioengineering9020062. [PMID: 35200415 PMCID: PMC8869328 DOI: 10.3390/bioengineering9020062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/26/2022] [Accepted: 01/29/2022] [Indexed: 11/25/2022] Open
Abstract
This study addresses brain network analysis over different clinical severity stages of cognitive dysfunction using electroencephalography (EEG). We exploit EEG data of subjective cognitive impairment (SCI) patients, mild cognitive impairment (MCI) patients and Alzheimer’s disease (AD) patients. We propose a new framework to study the topological networks with a spatiotemporal entropy measure for estimating the connectivity. Our results show that functional connectivity and graph analysis are frequency-band dependent, and alterations start at the MCI stage. In delta, the SCI group exhibited a decrease of clustering coefficient and an increase of path length compared to MCI and AD. In alpha, the opposite behavior appeared, suggesting a rapid and high efficiency in information transmission across the SCI network. Modularity analysis showed that electrodes of the same brain region were distributed over several modules, and some obtained modules in SCI were extended from anterior to posterior regions. These results demonstrate that the SCI network was more resilient to neuronal damage compared to that of MCI and even more compared to that of AD. Finally, we confirm that MCI is a transitional stage between SCI and AD, with a predominance of high-strength intrinsic connectivity, which may reflect the compensatory response to the neuronal damage occurring early in the disease process.
Collapse
|
15
|
Cao J, Zhao Y, Shan X, Wei H, Guo Y, Chen L, Erkoyuncu JA, Sarrigiannis PG. Brain functional and effective connectivity based on electroencephalography recordings: A review. Hum Brain Mapp 2022; 43:860-879. [PMID: 34668603 PMCID: PMC8720201 DOI: 10.1002/hbm.25683] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 09/10/2021] [Accepted: 09/27/2021] [Indexed: 12/02/2022] Open
Abstract
Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the study of the intrinsic brain network and its functional mechanism. Many recent studies on electroencephalography (EEG) have been focusing on modeling and estimating brain connectivity due to increasing evidence that it can help better understand various brain neurological conditions. However, there is a lack of a comprehensive updated review on studies of EEG-based brain connectivity, particularly on visualization options and associated machine learning applications, aiming to translate those techniques into useful clinical tools. This article reviews EEG-based functional and effective connectivity studies undertaken over the last few years, in terms of estimation, visualization, and applications associated with machine learning classifiers. Methods are explored and discussed from various dimensions, such as either linear or nonlinear, parametric or nonparametric, time-based, and frequency-based or time-frequency-based. Then it is followed by a novel review of brain connectivity visualization methods, grouped by Heat Map, data statistics, and Head Map, aiming to explore the variation of connectivity across different brain regions. Finally, the current challenges of related research and a roadmap for future related research are presented.
Collapse
Affiliation(s)
- Jun Cao
- School of Aerospace, Transport and ManufacturingCranfield UniversityCranfield
| | - Yifan Zhao
- School of Aerospace, Transport and ManufacturingCranfield UniversityCranfield
| | - Xiaocai Shan
- School of Aerospace, Transport and ManufacturingCranfield UniversityCranfield
- Institute of Geology and Geophysics, Chinese Academy of SciencesBeijingChina
| | - Hua‐liang Wei
- Department of Automatic Control and Systems EngineeringUniversity of SheffieldSheffieldUK
| | - Yuzhu Guo
- School of Automation Science and Electrical EngineeringBeihang UniversityBeijingChina
| | - Liangyu Chen
- Department of NeurosurgeryShengjing Hospital of China Medical UniversityShenyangChina
| | | | | |
Collapse
|
16
|
Decision Tree in Working Memory Task Effectively Characterizes EEG Signals in Healthy Aging Adults. Ing Rech Biomed 2021. [DOI: 10.1016/j.irbm.2021.12.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
|
17
|
Fatima Shad K, Soubra W, Cordato DJ. The Auditory Afferent Pathway as a Clinical Marker of Alzheimer's Disease. J Alzheimers Dis 2021; 85:47-53. [PMID: 34776450 DOI: 10.3233/jad-215206] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Brain stem neural tracts and nuclei may be disturbed prior to observable neuronal atrophy in AD. In this perspective, we discuss the notion of functional deficits presenting prior to structural abnormalities in Alzheimer's disease (AD). Imaging of inferior colliculi using magnetic resonance spectroscopy (MRS) shows significant decrease in the neuronal markers, N acetyl aspartate/creatine ratio and increase in the glial marker myo-Inositol, in subjects with Mini-Mental State Examination scores greater than 24 and with no signs of atrophy in their MRI of the medial temporal lobe. Abnormalities in components of the auditory event-related potentials (ERPs) are described in cognitive impairment including AD. We observed a significant decrease in amplitude and increase in latency during the first 10 ms of auditory evoked potentials measured on electroencephalography (EEG) indicating slow auditory response of the brainstem. EEG spectral power recorded at the cortex is also associated with neural activity at the level of the inferior colliculi. We postulate that a functional examination of auditory afferent pathways, using non-invasive techniques, such as MRS, brain stem auditory evoked potentials (BAEPs) and ERPs may improve diagnostic accuracy of AD. Functional changes precede structural changes and it is important to further understand the relationship between biochemical and electrophysiological measures such as MRS, BAEPs and EEG.
Collapse
Affiliation(s)
- Kaneez Fatima Shad
- School of Life Sciences, University of Technology Sydney, NSW, Australia.,Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Wissam Soubra
- A Healthy Step Clinic, NSW, Australia.,Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| | - Dennis John Cordato
- Department of Neurophysiology, Liverpool Hospital, NSW, Australia.,Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia
| |
Collapse
|
18
|
Mosbacher JA, Waser M, Garn H, Seiler S, Coronel C, Dal-Bianco P, Benke T, Deistler M, Ransmayr G, Mayer F, Sanin G, Lechner A, Lackner HK, Schwingenschuh P, Grossegger D, Schmidt R. Functional (un-)Coupling: Impairment, Compensation, and Future Progression in Alzheimer's Disease. Clin EEG Neurosci 2021; 54:316-326. [PMID: 34658289 DOI: 10.1177/15500594211052208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Functional (un-)coupling (task-related change of functional connectivity) between different sites of the brain is a mechanism of general importance for cognitive processes. In Alzheimer's disease (AD), prior research identified diminished cortical connectivity as a hallmark of the disease. However, little is known about the relation between the amount of functional (un-)coupling and cognitive performance and decline in AD. Method: Cognitive performance (based on CERAD-Plus scores) and electroencephalogram (EEG)-based functional (un-)coupling measures (connectivity changes from rest to a Face-Name-Encoding task) were assessed in 135 AD patients (age: M = 73.8 years; SD = 9.0). Of these, 68 patients (M = 73.9 years; SD = 8.9) participated in a follow-up assessment of their cognitive performance 1.5 years later. Results: The amounts of functional (un-)coupling in left anterior-posterior and homotopic interhemispheric connections in beta1-band were related to cognitive performance at baseline (β = .340; p < .001; β = .274; P = .001, respectively). For both markers, a higher amount of functional coupling was associated with better cognitive performance. Both markers also were significant predictors for cognitive decline. However, while patients with greater functional coupling in left anterior-posterior connections declined less in cognitive performance (β = .329; P = .035) those with greater functional coupling in interhemispheric connections declined more (β = -.402; P = .010). Conclusion: These findings suggest an important role of functional coupling mechanisms in left anterior-posterior and interhemispheric connections in AD. Especially the complex relationship with cognitive decline in AD patients might be an interesting aspect for future studies.
Collapse
Affiliation(s)
| | - Markus Waser
- Center for Digital Safety and Security, AIT Austrian Institute of Technology, Vienna, Austria
| | - Heinrich Garn
- Center for Digital Safety and Security, AIT Austrian Institute of Technology, Vienna, Austria
| | - Stephan Seiler
- Department of Neurology, 31475Medical University of Graz, Graz, Austria
| | - Carmina Coronel
- Center for Digital Safety and Security, AIT Austrian Institute of Technology, Vienna, Austria
| | - Peter Dal-Bianco
- Department of Neurology, 27271Medical University of Vienna, Vienna, Austria
| | - Thomas Benke
- Department of Neurology, 27280Medical University of Innsbruck, Innsbruck, Austria
| | - Manfred Deistler
- Institute of Statistics and Mathematical Methods in Economics, 27259Vienna University of Technology, Vienna, Austria
| | - Gerhard Ransmayr
- Department of Neurology 2, 31197Kepler University Hospital Linz, Med Campus III, Linz, Austria
| | - Florian Mayer
- Department of Neurology, 27271Medical University of Vienna, Vienna, Austria
| | - Guenter Sanin
- Department of Neurology, 27280Medical University of Innsbruck, Innsbruck, Austria
| | - Anita Lechner
- Department of Neurology, 31475Medical University of Graz, Graz, Austria
| | - Helmut K Lackner
- Division of Physiology, Otto Loewi Research Center, Medical University of Graz, Graz, Austria
| | | | | | - Reinhold Schmidt
- Department of Neurology, 31475Medical University of Graz, Graz, Austria
| |
Collapse
|
19
|
Monllor P, Cervera-Ferri A, Lloret MA, Esteve D, Lopez B, Leon JL, Lloret A. Electroencephalography as a Non-Invasive Biomarker of Alzheimer's Disease: A Forgotten Candidate to Substitute CSF Molecules? Int J Mol Sci 2021; 22:10889. [PMID: 34639229 PMCID: PMC8509134 DOI: 10.3390/ijms221910889] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/26/2021] [Accepted: 10/05/2021] [Indexed: 12/12/2022] Open
Abstract
Biomarkers for disease diagnosis and prognosis are crucial in clinical practice. They should be objective and quantifiable and respond to specific therapeutic interventions. Optimal biomarkers should reflect the underlying process (pathological or not), be reproducible, widely available, and allow measurements repeatedly over time. Ideally, biomarkers should also be non-invasive and cost-effective. This review aims to focus on the usefulness and limitations of electroencephalography (EEG) in the search for Alzheimer's disease (AD) biomarkers. The main aim of this article is to review the evolution of the most used biomarkers in AD and the need for new peripheral and, ideally, non-invasive biomarkers. The characteristics of the EEG as a possible source for biomarkers will be revised, highlighting its advantages compared to the molecular markers available so far.
Collapse
Affiliation(s)
- Paloma Monllor
- CIBERFES, Department of Physiology, Institute INCLIVA, Faculty of Medicine, Health Research University of Valencia, Avda. Blasco Ibanez 17, 46010 Valencia, Spain; (P.M.); (D.E.)
| | - Ana Cervera-Ferri
- Department of Human Anatomy and Embryology, Faculty of Medicine, University of Valencia, 46010 Valencia, Spain;
| | - Maria-Angeles Lloret
- Department of Clinical Neurophysiology, University Clinic Hospital of Valencia, Avda. Blasco Ibanez, 19, 46010 Valencia, Spain;
| | - Daniel Esteve
- CIBERFES, Department of Physiology, Institute INCLIVA, Faculty of Medicine, Health Research University of Valencia, Avda. Blasco Ibanez 17, 46010 Valencia, Spain; (P.M.); (D.E.)
| | - Begoña Lopez
- Department of Neurology, University Clinic Hospital of Valencia, Avda. Blasco Ibanez, 19, 46010 Valencia, Spain;
| | - Jose-Luis Leon
- Ascires Biomedical Group, Department of Neuroradiology, Hospital Clinico Universitario, 46010 Valencia, Spain;
| | - Ana Lloret
- CIBERFES, Department of Physiology, Institute INCLIVA, Faculty of Medicine, Health Research University of Valencia, Avda. Blasco Ibanez 17, 46010 Valencia, Spain; (P.M.); (D.E.)
| |
Collapse
|
20
|
Fodor Z, Horváth A, Hidasi Z, Gouw AA, Stam CJ, Csukly G. EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance. Front Aging Neurosci 2021; 13:680200. [PMID: 34690735 PMCID: PMC8529331 DOI: 10.3389/fnagi.2021.680200] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 09/20/2021] [Indexed: 12/18/2022] Open
Abstract
Background: While decreased alpha and beta-band functional connectivity (FC) and changes in network topology have been reported in Alzheimer's disease, it is not yet entirely known whether these differences can mark cognitive decline in the early stages of the disease. Our study aimed to analyze electroencephalography (EEG) FC and network differences in the alpha and beta frequency band during visuospatial memory maintenance between Mild Cognitive Impairment (MCI) patients and healthy elderly with subjective memory complaints. Methods: Functional connectivity and network structure of 17 MCI patients and 20 control participants were studied with 128-channel EEG during a visuospatial memory task with varying memory load. FC between EEG channels was measured by amplitude envelope correlation with leakage correction (AEC-c), while network analysis was performed by applying the Minimum Spanning Tree (MST) approach, which reconstructs the critical backbone of the original network. Results: Memory load (increasing number of to-be-learned items) enhanced the mean AEC-c in the control group in both frequency bands. In contrast to that, after an initial increase, the MCI group showed significantly (p < 0.05) diminished FC in the alpha band in the highest memory load condition, while in the beta band this modulation was absent. Moreover, mean alpha and beta AEC-c correlated significantly with the size of medial temporal lobe structures in the entire sample. The network analysis revealed increased maximum degree, betweenness centrality, and degree divergence, and decreased diameter and eccentricity in the MCI group compared to the control group in both frequency bands independently of the memory load. This suggests a rerouted network in the MCI group with a more centralized topology and a more unequal traffic load distribution. Conclusion: Alpha- and beta-band FC measured by AEC-c correlates with cognitive load-related modulation, with subtle medial temporal lobe atrophy, and with the disruption of hippocampal fiber integrity in the earliest stages of cognitive decline. The more integrated network topology of the MCI group is in line with the "hub overload and failure" framework and might be part of a compensatory mechanism or a consequence of neural disinhibition.
Collapse
Affiliation(s)
- Zsuzsanna Fodor
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - András Horváth
- Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Zoltán Hidasi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Alida A. Gouw
- Department of Clinical Neurophysiology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Cornelis J. Stam
- Department of Clinical Neurophysiology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Gábor Csukly
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| |
Collapse
|
21
|
Járdánházy A, Járdánházy T. The effect of photic stimulation alone and in combination with sleep deprivation after a seizure-like event - reappraisal by using linear and nonlinear EEG methods. Neurol Res 2021; 44:104-111. [PMID: 34334110 DOI: 10.1080/01616412.2021.1961186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
ObjectivesThe present study aimed to compare the effectiveness of different provocation tests used for the study of the 'susceptibility to seizure' by quantitative electroencephalography (EEG) analysis.MethodsEight subjects with a history of a seizure-like disturbed consciousness participated in this preliminary study. A routine EEG was carried out with photic stimulation (eyes closed and after eyes open) at the beginning of the investigation. Some days later, a sleep-deprived EEG was recorded with the same protocol. Selected epochs (in eyes closed condition) after the stimulations were analysed with Point(wise) Correlation Dimension (PD2i) and Synchronization Likelihood (SL) methods. The results were compared to those obtained by similar analysis of the resting state (control) epochs with Wilcoxon Signed Rank Test (p ≤ 0.05).ResultsIn our study, significantly lower grand mean PD2i and higher delta SL values were found in sleep-deprived state after stimulation with eyes closed compared to the control. Our results indicated a lower-dimensional, hypersynchronous state of the brain as a consequence of these combined provocations.DiscussionThis may correspond to a possible 'preictal' state of the brain. Accordingly, it is suggested that photic stimulation together with sleep deprivation seems to be more effective in provocation - especially when the stimulation was made with eyes closed.
Collapse
|
22
|
Watanabe A, Yamazaki T. Representation of the brain network by electroencephalograms during facial expressions. J Neurosci Methods 2021; 357:109158. [PMID: 33819556 DOI: 10.1016/j.jneumeth.2021.109158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/19/2021] [Accepted: 03/22/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Facial expressions, such as smiling and anger, cause many physical and psychological effects in the body, known as 'embodied emotions' or 'facial feedback theory.' In the clinical application of this theory in certain diseases, such as autism and depression, treatments such as forcing patients to smile have been used. However, the neural mechanisms underlying the representation of facial expressions remain unclear. NEW METHOD We proposed a method to construct brain networks based on the time course of the synchronization likelihood and determine the effects of various facial expressions on the situation using visual stimulus of faces. This method was applied to analyze electroencephalographic (EEG) data recorded during the recognition and representation of various positive and negative facial expressions. The brain networks were constructed based on the EEG data recorded in 11 healthy participants. RESULTS Channel sets from brain networks during unsymmetrical smiling expressions (i.e., only the right or left side) were highly linearly symmetrical. Channel sets from brain networks during negative facial expressions (i.e., anger and sadness) and symmetrical smiling expressions (i.e., smiling with an opened or closed mouth) were similar. COMPARISON WITH EXISTING METHODS While we obtained brain networks based on time course EEG correlations throughout the experiment, existing methods can analyze EEG data only at a certain time point. CONCLUSIONS The comparisons of different facial expressions could be used to identify the side of the facial muscles used while smiling and to determine how similar brain networks are induced by positive and negative facial expressions.
Collapse
Affiliation(s)
- Asako Watanabe
- Department of Bioscience and Bioinformatics, Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Kawazu 680-4, Iizuka City, Fukuoka, 820-8502, Japan.
| | - Toshimasa Yamazaki
- Department of Bioscience and Bioinformatics, Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Kawazu 680-4, Iizuka City, Fukuoka, 820-8502, Japan
| |
Collapse
|
23
|
Jeong E, Park J, Kim Y, Woo M. Aerobic Exercise Mediates Neural Inefficiency Among Adolescents At Risk for Suicide. Percept Mot Skills 2021; 128:1130-1149. [PMID: 33641504 DOI: 10.1177/0031512521998281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This study examined the electroencephalograpy (EEG) coherence and working memory performance effects of a 9-week exercise program on a small group of adolescents at high suicide risk. We randomly assigned 26 adolescents at high suicide risk (based on their scores on the Adolescents Mental Health Inventory- AMHI) into equal sized exercise and no-exercise groups. Before and after the 9-week exercise program, all participants performed the Sternberg working memory task, during which we recorded their EEGs, with electrodes placed at F3, F4, C3, C4, P3, P4, T3, T4, O1, and O2 regions (using the International 10-20 system of EEG electrode placement). We measured working memory performance and inter-hemispheric (F3-F4, C3-C4, T3-T4, P3-P4, O1-O2) and intra-hemispheric (F3-C3, F3-T3, F3-P3, F3-O1, F4-C4, F4-T4, F4-P4, F4-O2) EEG coherence as an index of the participants' underlying neural efficiency. While we found no significant group differences in working memory performances, the exercise group, relative to the no-exercise group, exhibited lower inter- and intra-hemispheric EEG coherence while performing the working memory task. These EEG differences may reflect a mediating effect of aerobic exercise on these participants' neural efficiency.
Collapse
Affiliation(s)
- Eunbi Jeong
- School of Exercise and Sports Science, University of Ulsan, Ulsan, South Korea
| | - Jinhan Park
- School of Exercise and Sports Science, University of Ulsan, Ulsan, South Korea
| | - Yujin Kim
- Department of Physical Education, Sejong University, Sejong, South Korea
| | - Minjung Woo
- School of Exercise and Sports Science, University of Ulsan, Ulsan, South Korea
| |
Collapse
|
24
|
Kim JA, Davis KD. Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences. J Neurophysiol 2021; 125:938-956. [PMID: 33567968 DOI: 10.1152/jn.00530.2020] [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: 11/22/2022] Open
Abstract
Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.
Collapse
Affiliation(s)
- Junseok A Kim
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Karen D Davis
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
25
|
Kim BM, Kim MS, Kim JS. Alterations of Functional Connectivity During the Resting State and Their Associations With Visual Memory in College Students Who Binge Drink. Front Hum Neurosci 2021; 14:600437. [PMID: 33424567 PMCID: PMC7793784 DOI: 10.3389/fnhum.2020.600437] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 11/06/2020] [Indexed: 12/15/2022] Open
Abstract
This study investigated the characteristics of neural oscillation and functional connectivity (FC) in college students engaging in binge drinking (BD) using resting-state electroencephalography (EEG). Also, the associations of visual memory, evaluated by the Rey-Osterrieth Complex Figure Test (RCFT), and neural oscillation with FC during the resting state were investigated. The BD (n = 35) and non-BD (n = 35) groups were selected based on scores of the Korean version of the Alcohol use disorders (AUDs) Identification Test and the Alcohol Use Questionnaire. EEG was performed for 6 min while the participants rested with eyes closed. The theta, lower-alpha, and upper alpha powers did not differ between the BD and non-BD groups. Concerning FC, the BD group exhibited stronger theta coherence than that of the non-BD group, and in the lower and upper alpha bands, the BD group showed stronger coherence in some areas but weaker coherence in others compared with the non-BD group. However, these significant results were not observed after Bonferroni correction. The BD group showed significantly lower delayed recall scores on the RCFT than did the non-BD group. A positive correlation between the left prefrontal-parietal-occipital midline connection and performance on the delayed recall of the RCFT was observed in the BD group. The present results could suggest that binge drinkers have alterations in brain FC, which may be related to their visual memory deficits.
Collapse
Affiliation(s)
- Bo-Mi Kim
- Department of Psychology, Sungshin Women's University, Seoul, South Korea
| | - Myung-Sun Kim
- Department of Psychology, Sungshin Women's University, Seoul, South Korea
| | - June Sic Kim
- Research Institute of Basic Sciences, Seoul National University, Seoul, South Korea
| |
Collapse
|
26
|
Sedghizadeh MJ, Hojjati H, Ezzatdoost K, Aghajan H, Vahabi Z, Tarighatnia H. Olfactory response as a marker for Alzheimer's disease: Evidence from perceptual and frontal lobe oscillation coherence deficit. PLoS One 2020; 15:e0243535. [PMID: 33320870 PMCID: PMC7737889 DOI: 10.1371/journal.pone.0243535] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Accepted: 11/24/2020] [Indexed: 11/19/2022] Open
Abstract
High-frequency oscillations of the frontal cortex are involved in functions of the brain that fuse processed data from different sensory modules or bind them with elements stored in the memory. These oscillations also provide inhibitory connections to neural circuits that perform lower-level processes. Deficit in the performance of these oscillations has been examined as a marker for Alzheimer's disease (AD). Additionally, the neurodegenerative processes associated with AD, such as the deposition of amyloid-beta plaques, do not occur in a spatially homogeneous fashion and progress more prominently in the medial temporal lobe in the early stages of the disease. This region of the brain contains neural circuitry involved in olfactory perception. Several studies have suggested that olfactory deficit can be used as a marker for early diagnosis of AD. A quantitative assessment of the performance of the olfactory system can hence serve as a potential biomarker for Alzheimer's disease, offering a relatively convenient and inexpensive diagnosis method. This study examines the decline in the perception of olfactory stimuli and the deficit in the performance of high-frequency frontal oscillations in response to olfactory stimulation as markers for AD. Two measurement modalities are employed for assessing the olfactory performance: 1) An interactive smell identification test is used to sample the response to a sizable variety of odorants, and 2) Electroencephalography data are collected in an olfactory perception task with a pair of selected odorants in order to assess the connectivity of frontal cortex regions. Statistical analysis methods are used to assess the significance of selected features extracted from the recorded modalities as Alzheimer's biomarkers. Olfactory decline regressed to age in both healthy and mild AD groups are evaluated, and single- and multi-modal classifiers are also developed. The novel aspects of this study include: 1) Combining EEG response to olfactory stimulation with behavioral assessment of olfactory perception as a marker of AD, 2) Identification of odorants most significantly affected in mild AD patients, 3) Identification of odorants which are still adequately perceived by mild AD patients, 4) Analysis of the decline in the spatial coherence of different oscillatory bands in response to olfactory stimulation, and 5) Being the first study to quantitatively assess the performance of olfactory decline due to aging and AD in the Iranian population.
Collapse
Affiliation(s)
| | - Hadi Hojjati
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | - Kiana Ezzatdoost
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | - Hamid Aghajan
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | - Zahra Vahabi
- Department of Geriatric Medicine, Ziaeian Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Memory and Behavioral Neurology Division, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Heliya Tarighatnia
- Department of Geriatric Medicine, Ziaeian Hospital, Tehran University of Medical Sciences, Tehran, Iran
| |
Collapse
|
27
|
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: 33] [Impact Index Per Article: 8.3] [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.
Collapse
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
| |
Collapse
|
28
|
Cheng S, Li M, Yu H, Zhao K, Liu S, Wan H. Decoding Pigeon Behavior Outcomes during Goal-directed Decision Task by WSR Functional Network Analysis .. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:38-41. [PMID: 33017925 DOI: 10.1109/embc44109.2020.9175413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
It is a hot research direction to reveal the working mechanism of brain by measuring the connection characteristics of brain function network. In this paper, to decode pigeon behavior outcomes in goal-directed decision task, an experiment based on plus maze was designed and the nidopallium caudolaterale (NCL) of the pigeon was selected as the target brain region. The local field potential (LFP) signals in the waiting area (WA) and turning area (TA) were recorded when the pigeons performed the goal-directed tasks. Then, the brain functional connection networks of the LFPs were constructed and the extracted features were applied to decode pigeon behavior outcomes. Firstly, continuous wavelet transform (CWT) was used to carried out time-frequency analysis and the task-related frequency band (40-60 Hz) was extracted. Then, weighted sparse representation (WSR) method was used to construct the functional connectivity network and the related network features were selected. Finally, k-nearest neighbor (kNN) algorithm was used to decode behavior outcomes. The results show that the energy difference between TA and WA in 40-60 Hz band is significantly higher than those in other bands. The selected features have good discriminability for the representation of the differences between WA and TA. The decoding results also suggest the classification performance of the different behavior outcomes. These results show the effectiveness of the WSR to construct the function network to decode behavior outcomes.
Collapse
|
29
|
Lees T, Maharaj S, Kalatzis G, Nassif NT, Newton PJ, Lal S. Electroencephalographic prediction of global and domain specific cognitive performance of clinically active Australian Nurses. Physiol Meas 2020; 41:095001. [PMID: 33021231 DOI: 10.1088/1361-6579/abb12a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE To investigate the relationship between EEG activity and the global and domain specific cognitive performance of healthy nurses, and determine the predictive capabilities of these relationships. APPROACH Sixty-four nurses were recruited for the present study, and data from 61 were utilised in the present analysis. Global and domain specific cognitive performance of each participant was assessed psychometrically using the Mini-mental state exam and the Cognistat, and a 32-lead monopolar EEG was recorded during a resting baseline phase and an active phase in which participants completed the Stroop test. MAIN RESULTS Global cognitive performance was successfully predicted (81%-85% of variance) by a combination of fast wave activity variables in the alpha, beta and theta frequency bands. Interestingly, predicting domain specific performance had varying degrees of success (42%-99% of the variance predicted) and relied on combinations of both slow and fast wave activity, with delta and gamma activity predicting attention performance; delta, theta, and gamma activity predicting memory performance; and delta and beta variables predicting judgement performance. SIGNIFICANCE Global and domain specific cognitive performance of Australian nurses may be predicted with varying degrees of success by a unique combination of EEG variables. These proposed models image transitory cognitive declines and as such may prove useful in the prediction of early cognitive impairment, and may enable better diagnosis, and management of cognitive impairment.
Collapse
Affiliation(s)
- Ty Lees
- Edna Bennett Pierce Prevention Research Center, Pennsylvania State University, 115 Health & Human Development Building, University Park, PA 16802, United States of America
| | | | | | | | | | | |
Collapse
|
30
|
Jafari Z, Kolb BE, Mohajerani MH. Neural oscillations and brain stimulation in Alzheimer's disease. Prog Neurobiol 2020; 194:101878. [PMID: 32615147 DOI: 10.1016/j.pneurobio.2020.101878] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 12/20/2019] [Accepted: 06/25/2020] [Indexed: 12/30/2022]
Abstract
Aging is associated with alterations in cognitive processing and brain neurophysiology. Whereas the primary symptom of amnestic mild cognitive impairment (aMCI) is memory problems greater than normal for age and education, patients with Alzheimer's disease (AD) show impairments in other cognitive domains in addition to memory dysfunction. Resting-state electroencephalography (rsEEG) studies in physiological aging indicate a global increase in low-frequency oscillations' power and the reduction and slowing of alpha activity. The enhancement of slow and the reduction of fast oscillations, and the disruption of brain functional connectivity, however, are characterized as major rsEEG changes in AD. Recent rodent studies also support human evidence of age- and AD-related changes in resting-state brain oscillations, and the neuroprotective effect of brain stimulation techniques through gamma-band stimulations. Cumulatively, current evidence moves toward optimizing rsEEG features as reliable predictors of people with aMCI at risk for conversion to AD and mapping neural alterations subsequent to brain stimulation therapies. The present paper reviews the latest evidence of changes in rsEEG oscillations in physiological aging, aMCI, and AD, as well as findings of various brain stimulation therapies from both human and non-human studies.
Collapse
Affiliation(s)
- Zahra Jafari
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4, Canada
| | - Bryan E Kolb
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4, Canada.
| | - Majid H Mohajerani
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, T1K 3M4, Canada.
| |
Collapse
|
31
|
Li X, Zhang J, Li XD, Cui W, Su R. Neurofeedback Training for Brain Functional Connectivity Improvement in Mild Cognitive Impairment. J Med Biol Eng 2020. [DOI: 10.1007/s40846-020-00531-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
|
32
|
Abstract
Currently established and employed biomarkers of Alzheimer's disease (AD) predominantly mirror AD-associated molecular and structural brain changes. While they are necessary for identifying disease-specific neuropathology, they lack a clear and robust relationship with the clinical presentation of dementia; they can be altered in healthy individuals, while they often inadequately mirror the degree of cognitive and functional deficits in affected subjects. There is growing evidence that synaptic loss and dysfunction are early events during the trajectory of AD pathogenesis that best correlate with the clinical symptoms, suggesting measures of brain functional deficits as candidate early markers of AD. Resting-state electroencephalography (EEG) is a widely available and noninvasive diagnostic method that provides direct insight into brain synaptic activity in real time. Quantitative EEG (qEEG) analysis additionally provides information on physiologically meaningful frequency components, dynamic alterations and topography of EEG signal generators, i.e. neuronal signaling. Numerous studies have shown that qEEG measures can detect disruptions in activity, topographical distribution and synchronization of neuronal (synaptic) activity such as generalized EEG slowing, reduced global synchronization and anteriorization of neuronal generators of fast-frequency resting-state EEG activity in patients along the AD continuum. Moreover, qEEG measures appear to correlate well with surrogate markers of AD neuropathology and discriminate between different types of dementia, making them promising low-cost and noninvasive markers of AD. Future large-scale longitudinal clinical studies are needed to elucidate the diagnostic and prognostic potential of qEEG measures as early functional markers of AD on an individual subject level.
Collapse
Affiliation(s)
- Una Smailovic
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden.
| | - Vesna Jelic
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Huddinge, Sweden
| |
Collapse
|
33
|
Menardi A, Pascual-Leone A, Fried PJ, Santarnecchi E. The Role of Cognitive Reserve in Alzheimer's Disease and Aging: A Multi-Modal Imaging Review. J Alzheimers Dis 2019; 66:1341-1362. [PMID: 30507572 DOI: 10.3233/jad-180549] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Comforts in modern society have generally been associated with longer survival rates, enabling individuals to reach advanced age as never before in history. With the increase in longevity, however, the incidence of neurodegenerative diseases, especially Alzheimer's disease, has also doubled. Nevertheless, most of the observed variance, in terms of time of clinical diagnosis and progression, often remains striking. Only recently, differences in the social, educational and occupational background of the individual, as proxies of cognitive reserve (CR), have been hypothesized to play a role in accounting for such discrepancies. CR is a well-established concept in literature; lots of studies have been conducted in trying to better understand its underlying neural substrates and associated biomarkers, resulting in an incredible amount of data being produced. Here, we aimed to summarize recent relevant published work addressing the issue, gathering evidence for the existence of a common path across research efforts that might ease future investigations by providing a general perspective on the actual state of the arts. An innovative model is hereby proposed, addressing the role of CR across structural and functional evidences, as well as the potential implementation of non-invasive brain stimulation techniques in the causal validation of such theoretical frame.
Collapse
Affiliation(s)
- Arianna Menardi
- Brain Investigation and Neuromodulation Lab, Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy.,Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Emiliano Santarnecchi
- Brain Investigation and Neuromodulation Lab, Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Section, University of Siena, Italy.,Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
34
|
Maharaj S, Lees T, Lal S. Negative Mental States and Their Association to the Cognitive Function of Nurses. J PSYCHOPHYSIOL 2019. [DOI: 10.1027/0269-8803/a000223] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Abstract. Nurses’ inherently stressful occupation leaves them at a higher risk of developing negative mental states (stress, anxiety, and depression). However, research examining the effect of negative mental states on these health professionals’ cognitive performance is sparse. Thus, the present study aimed to assess the link between negative mental states and cognitive performance in nurses ( n = 53). Negative mental state data was obtained using the Depression Anxiety Stress Scale, brain activity was measured using electroencephalography, and finally, cognitive performance was assessed using the Cognistat and the Mini-Mental State Examination. Significant negative correlations ( p < .05) were observed between anxiety and attention, and all three negative mental states and memory performance. Electroencephalographic changes indicated that increases in anxiety were significantly associated ( p < .05) with decreases in gamma reactivity at fronto-central sites. The current study suggests that higher levels of negative mental states are associated with domain-specific cognitive impairments, and variations in gamma reactivity; possibly reflecting less optimal cortical functioning.
Collapse
Affiliation(s)
- Shamona Maharaj
- Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, New South Wales, Australia
| | - Ty Lees
- Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, New South Wales, Australia
| | - Sara Lal
- Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, New South Wales, Australia
| |
Collapse
|
35
|
Goodman MS, Zomorrodi R, Kumar S, Barr MS, Daskalakis ZJ, Blumberger DM, Fischer CE, Flint A, Mah L, Herrmann N, Pollock BG, Bowie CR, Mulsant BH, Rajji TK. Changes in Theta but not Alpha Modulation Are Associated with Impairment in Working Memory in Alzheimer's Disease and Mild Cognitive Impairment. J Alzheimers Dis 2019; 68:1085-1094. [PMID: 30909240 DOI: 10.3233/jad-181195] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
While several studies have found that neural oscillations play a key role in the functioning of working memory, the nature of aberrant oscillatory activity underlying working memory impairments in Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains largely unexplored. These individuals often display structural alterations in brain regions and pathways involved in working memory processes and therefore may also display altered oscillatory activity during memory activation. Electroencephalographic (EEG) activity was recorded during the N-back working memory task in three groups: AD (n = 29), MCI (n = 100), and healthy controls (HCs; n = 40). Theta (4-7 Hz) and alpha (7.5-12 Hz) modulation was measured in response to the stimulus presentation during correct and incorrect responses. This modulation represents the change in EEG activity associated with the stimulus onset and was measured as a ratio of post stimulus power to pre stimulus power. We also assessed the relationship between change in oscillatory power and working memory performance. Compared to HCs, the AD group demonstrated the lowest working memory accuracy and a smaller theta ratio for correct responses on the 2-back condition; the MCI group demonstrated a smaller theta ratio for correct responses on the 3-back condition. Finally, we observed that the theta ratio, but not the alpha ratio, was a significant predictor of working memory performance in the three groups for all conditions. Taken together, these behavioral and electrophysiological results suggest that in addition to impairments in working memory performance, modulation of theta, but not alpha power, may be impaired in MCI and AD.
Collapse
Affiliation(s)
- Michelle S Goodman
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada
| | - Reza Zomorrodi
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada
| | - Sanjeev Kumar
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Mera S Barr
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Zafiris J Daskalakis
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Daniel M Blumberger
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Corinne E Fischer
- Department of Psychiatry, University of Toronto, Toronto, Canada.,Keenan Research Centre for Biomedical Research, St. Michael's Hospital, Toronto, Canada
| | - Alastair Flint
- Department of Psychiatry, University of Toronto, Toronto, Canada.,Centre for Mental Health, University Health Network, Toronto, Canada
| | - Linda Mah
- Department of Psychiatry, University of Toronto, Toronto, Canada.,Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, Canada
| | - Nathan Herrmann
- Department of Psychiatry, University of Toronto, Toronto, Canada.,Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Bruce G Pollock
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Christopher R Bowie
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Canada
| | - Benoit H Mulsant
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Tarek K Rajji
- Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health, Toronto, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Canada.,Department of Psychiatry, University of Toronto, Toronto, Canada
| | | |
Collapse
|
36
|
Tan B, Liu Q, Wan C, Jin Z, Yang Y, Li L. Altered Functional Connectivity of Alpha Rhythm in Obsessive-Compulsive Disorder During Rest. Clin EEG Neurosci 2019; 50:88-99. [PMID: 30280595 DOI: 10.1177/1550059418804378] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Obsessive-compulsive disorder (OCD) is a common inheritable psychiatric disorder characteristic of repetitive thinking, imagination (obsession), and stereotyped behaviors (compulsive). To explore whether there is an alteration of brain functional connectivity (BFC) in patients with OCD during rest, electroencephalogram (EEG) data of healthy controls (HCs) and patients with OCD were collected during rest in both eyes-closed and eyes-open states. Synchronization likelihood and graph theory were applied to construct and analyze brain functional networks of patients with OCD and HCs. Patients with OCD showed abnormal graph-theoretic parameters and impaired small world features in the alpha and beta bands. In addition, the topological analysis consistently showed that the long-range BFC of alpha rhythm was significantly reduced in the bilateral posterior areas in patients with OCD in comparison with HCs, while the BFC in the beta rhythm was significantly increased only in the eyes-open state. The findings suggest that the BFC of patients with OCD show abnormal small-world features and altered topological structure during rest, mainly in alpha and beta bands, which may provide a new insight for the diagnosis and treatment of OCD.
Collapse
Affiliation(s)
- Bo Tan
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Qingxiao Liu
- Hospital of Chengdu University of TCM, Chengdu, China
| | - Chaoyang Wan
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhenlan Jin
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yanchun Yang
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Ling Li
- Key Laboratory for NeuroInformation of Ministry of Education, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China
| |
Collapse
|
37
|
Electrophysiological assessment methodology of sensory processing dysfunction in schizophrenia and dementia of the Alzheimer type. Neurosci Biobehav Rev 2019; 97:70-84. [DOI: 10.1016/j.neubiorev.2018.09.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 09/04/2018] [Accepted: 09/05/2018] [Indexed: 12/26/2022]
|
38
|
Waser M, Benke T, Dal‐Bianco P, Garn H, Mosbacher JA, Ransmayr G, Schmidt R, Seiler S, Sorensen HBD, Jennum PJ. Neuroimaging markers of global cognition in early Alzheimer's disease: A magnetic resonance imaging-electroencephalography study. Brain Behav 2019; 9:e01197. [PMID: 30592179 PMCID: PMC6346656 DOI: 10.1002/brb3.1197] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Revised: 11/26/2018] [Accepted: 12/05/2018] [Indexed: 12/16/2022] Open
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) and electroencephalography (EEG) are a promising means to an objectified assessment of cognitive impairment in Alzheimer's disease (AD). Individually, however, these modalities tend to lack precision in both AD diagnosis and AD staging. A joint MRI-EEG approach that combines structural with functional information has the potential to overcome these limitations. MATERIALS AND METHODS This cross-sectional study systematically investigated the link between MRI and EEG markers and the global cognitive status in early AD. We hypothesized that the joint modalities would identify cognitive deficits with higher accuracy than the individual modalities. In a cohort of 111 AD patients, we combined MRI measures of cortical thickness and regional brain volume with EEG measures of rhythmic activity, information processing and functional coupling in a generalized multiple regression model. Machine learning classification was used to evaluate the markers' utility in accurately separating the subjects according to their cognitive score. RESULTS We found that joint measures of temporal volume, cortical thickness, and EEG slowing were well associated with the cognitive status and explained 38.2% of ifs variation. The inclusion of the covariates age, sex, and education considerably improved the model. The joint markers separated the subjects with an accuracy of 84.7%, which was considerably higher than by using individual modalities. CONCLUSIONS These results suggest that including joint MRI-EEG markers may be beneficial in the diagnostic workup, thus allowing for adequate treatment. Further studies in larger populations, with a longitudinal design and validated against functional-metabolic imaging are warranted to confirm the results.
Collapse
Affiliation(s)
- Markus Waser
- Biomedical EngineeringDepartment of Electrical EngineeringTechnical University of DenmarkLyngbyDenmark
- Danish Center for Sleep MedicineDepartment of Clinical NeurophysiologyRigshospitalet GlostrupGlostrupDenmark
- AIT Austrian Institute of Technology GmbHCenter for Digital Safety & SecuritySensing and Vision SolutionsViennaAustria
| | - Thomas Benke
- Department of NeurologyMedical University of InnsbruckInnsbruckAustria
| | - Peter Dal‐Bianco
- Department of NeurologyMedical University of ViennaViennaAustria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbHCenter for Digital Safety & SecuritySensing and Vision SolutionsViennaAustria
| | | | - Gerhard Ransmayr
- Clinic for Neurology IIKepler University HospitalMed Campus IIILinzAustria
| | | | - Stephan Seiler
- Department of NeurologyMedical University of GrazGrazAustria
| | - Helge B. D. Sorensen
- Biomedical EngineeringDepartment of Electrical EngineeringTechnical University of DenmarkLyngbyDenmark
| | - Poul J. Jennum
- Danish Center for Sleep MedicineDepartment of Clinical NeurophysiologyRigshospitalet GlostrupGlostrupDenmark
| |
Collapse
|
39
|
Perpetuini D, Chiarelli AM, Cardone D, Filippini C, Bucco R, Zito M, Merla A. Complexity of Frontal Cortex fNIRS Can Support Alzheimer Disease Diagnosis in Memory and Visuo-Spatial Tests. ENTROPY 2019; 21:e21010026. [PMID: 33266742 PMCID: PMC7514130 DOI: 10.3390/e21010026] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Revised: 12/20/2018] [Accepted: 12/27/2018] [Indexed: 01/26/2023]
Abstract
Decline in visuo-spatial skills and memory failures are considered symptoms of Alzheimer's Disease (AD) and they can be assessed at early stages employing clinical tests. However, performance in a single test is generally not indicative of AD. Functional neuroimaging, such as functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests in an ecological setting to support diagnosis. Indeed, neuroimaging should not alter clinical practice allowing free doctor-patient interaction. However, block-designed paradigms, necessary for standard functional neuroimaging analysis, require tests adaptation. Novel signal analysis procedures (e.g., signal complexity evaluation) may be useful to establish brain signals differences without altering experimental conditions. In this study, we estimated fNIRS complexity (through Sample Entropy metric) in frontal cortex of early AD and controls during three tests that assess visuo-spatial and short-term-memory abilities (Clock Drawing Test, Digit Span Test, Corsi Block Tapping Test). A channel-based analysis of fNIRS complexity during the tests revealed AD-induced changes. Importantly, a multivariate analysis of fNIRS complexity provided good specificity and sensitivity to AD. This outcome was compared to cognitive tests performances that were predictive of AD in only one test. Our results demonstrated the capabilities of fNIRS and complexity metric to support early AD diagnosis.
Collapse
Affiliation(s)
- David Perpetuini
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy
- Correspondence: ; Tel.: +39-0871-3556954
| | - Antonio M. Chiarelli
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy
| | - Daniela Cardone
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy
| | - Chiara Filippini
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy
| | - Roberta Bucco
- Department of Medicine and Science of Ageing, University G. d’Annunzio of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy
| | - Michele Zito
- Department of Medicine and Science of Ageing, University G. d’Annunzio of Chieti-Pescara, Via dei Vestini 31, 66100 Chieti, Italy
| | - Arcangelo Merla
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy
| |
Collapse
|
40
|
Lees T, Chalmers T, Burton D, Zilberg E, Penzel T, Lal S, Lal S. Electroencephalography as a predictor of self-report fatigue/sleepiness during monotonous driving in train drivers. Physiol Meas 2018; 39:105012. [PMID: 30251970 DOI: 10.1088/1361-6579/aae42e] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE In this study, electroencephalography activity recorded during monotonous driving was investigated to examine the predictive capability of monopolar EEG analysis for fatigue/sleepiness in a cohort of train drivers. APPROACH Sixty-three train drivers participated in the study, where 32- lead monopolar EEG data was recorded during a monotonous driving task. Participant sleepiness was assessed using the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the Karolinksa sleepiness scale (KSS) and the checklist of individual strength 20 (CIS20). MAIN RESULTS Self-reported fatigue/sleepiness scores of the train driver cohort were primarily associated with EEG delta, theta, and alpha variables; however, some beta and gamma associations were also implicated. Furthermore, general linear models informed by these EEG variables were able to predict self-reported scores with varying degrees of success, representing between 48% and 54% of variance in fatigue scores. SIGNIFICANCE Self-reported fatigue/sleepiness scores of train drivers were predicted with varying degrees of success (dependent upon the self-reported fatigue/sleepiness measure) by alterations to monopolar delta, theta, and alpha band activity variables, indicating EEG as a potential indicator for fatigue/sleepiness in train drivers.
Collapse
Affiliation(s)
- Ty Lees
- Neuroscience Research Unit, School of Life Sciences, University of Technology Sydney, PO Box 123, Broadway NSW 2007, Australia. Indicates an equal joint first author contribution
| | | | | | | | | | | | | |
Collapse
|
41
|
Tan J, Iyer KK, Tang AD, Jamil A, Martins RN, Sohrabi HR, Nitsche MA, Hinder MR, Fujiyama H. Modulating functional connectivity with non-invasive brain stimulation for the investigation and alleviation of age-associated declines in response inhibition: A narrative review. Neuroimage 2018; 185:490-512. [PMID: 30342977 DOI: 10.1016/j.neuroimage.2018.10.044] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 10/12/2018] [Accepted: 10/17/2018] [Indexed: 12/25/2022] Open
Abstract
Response inhibition, the ability to withhold a dominant and prepotent response following a change in circumstance or sensory stimuli, declines with advancing age. While non-invasive brain stimulation (NiBS) has shown promise in alleviating some cognitive and motor functions in healthy older individuals, NiBS research focusing on response inhibition has mostly been conducted on younger adults. These extant studies have primarily focused on modulating the activity of distinct neural regions known to be critical for response inhibition, including the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA). However, given that changes in structural and functional connectivity have been associated with healthy aging, this review proposes that NiBS protocols aimed at modulating the functional connectivity between the rIFG and pre-SMA may be the most efficacious approach to investigate-and perhaps even alleviate-age-related deficits in inhibitory control.
Collapse
Affiliation(s)
- Jane Tan
- Action and Cognition Laboratory, School of Psychology and Exercise Science, Murdoch University, Perth, Australia
| | - Kartik K Iyer
- Centre for Clinical Research, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Alexander D Tang
- Experimental and Regenerative Neurosciences, School of Biological Sciences, University of Western Australia, Australia
| | - Asif Jamil
- Leibniz Research Centre for Working Environment and Human Factors, Department of Psychology and Neurosciences, Dortmund, Germany
| | - Ralph N Martins
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Western Australia, Australia; Department of Biomedical Sciences, Macquarie University, New South Wales, Australia; The School of Psychiatry and Clinical Neurosciences, University of Western Australia, Western Australia, Australia
| | - Hamid R Sohrabi
- Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Western Australia, Australia; Department of Biomedical Sciences, Macquarie University, New South Wales, Australia; The School of Psychiatry and Clinical Neurosciences, University of Western Australia, Western Australia, Australia
| | - Michael A Nitsche
- Leibniz Research Centre for Working Environment and Human Factors, Department of Psychology and Neurosciences, Dortmund, Germany; Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Mark R Hinder
- Sensorimotor Neuroscience and Ageing Research Laboratory, School of Medicine (Division of Psychology), University of Tasmania, Hobart, Australia
| | - Hakuei Fujiyama
- Action and Cognition Laboratory, School of Psychology and Exercise Science, Murdoch University, Perth, Australia.
| |
Collapse
|
42
|
Yang CY, Huang CK. Working-memory evaluation based on EEG signals during n-back tasks. J Integr Neurosci 2018; 17:695-707. [DOI: 10.3233/jin-180096] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Chia-Yen Yang
- Department of Biomedical Engineering, Ming Chuan University, No. 5 De Ming Rd., Gui Shan District, Taoyuan County 333, Taiwan
| | - Chong-Kai Huang
- Department of Electrical Engineering, Chang Gung University, No. 259, Wen hua 1st Rd., Gui shan District, Taoyuan County 333, Taiwan
| |
Collapse
|
43
|
Teng C, Cheng Y, Wang C, Ren Y, Xu W, Xu J. Aging-related changes of EEG synchronization during a visual working memory task. Cogn Neurodyn 2018; 12:561-568. [PMID: 30483364 DOI: 10.1007/s11571-018-9500-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 07/12/2018] [Accepted: 08/22/2018] [Indexed: 12/15/2022] Open
Abstract
Differences of EEG synchronization between normal old and young people during a working memory (WM) task were investigated. The synchronization likelihood (SL) is a novel method to assessed synchronization in multivariate time series for non-stationary systems. To evaluate this method to study the mechanisms of WM, we calculated the SL values in brain electrical activity for both resting state and task state. EEG signals were recorded from 14 young adults and 12 old adults during two different states, respectively. SL was used to measure EEG synchronization between 19 electrodes in delta, theta, alpha1, alpha2 and beta frequency bands. Bad task performance and significantly decreased EEG synchronization were found in old group compared to young group in alpha1, alpha2 and beta frequency bands during the WM task. Moreover, significantly decreased EEG synchronization in beta band in the elder was also detected during the resting state. The findings suggested that reduced EEG synchronization may be one of causes for WM capacity decline along with healthy aging.
Collapse
Affiliation(s)
- Chaolin Teng
- 1The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049 Shaanxi Province People's Republic of China
| | - Yao Cheng
- 1The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049 Shaanxi Province People's Republic of China
| | - Chao Wang
- 1The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049 Shaanxi Province People's Republic of China
| | - Yijing Ren
- 2Beijing University of Posts and Telecommunications, Beijing, China
| | - Weiyong Xu
- 1The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049 Shaanxi Province People's Republic of China.,3Department of Psychology, University of Jyväskylä, Jyväskylä, Finland
| | - Jin Xu
- 1The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049 Shaanxi Province People's Republic of China
| |
Collapse
|
44
|
Gao L, Chen J, Gu L, Shu H, Wang Z, Liu D, Yan Y, Zhang Z. Effects of Gender and Apolipoprotein E on Novelty MMN and P3a in Healthy Elderly and Amnestic Mild Cognitive Impairment. Front Aging Neurosci 2018; 10:256. [PMID: 30186155 PMCID: PMC6110901 DOI: 10.3389/fnagi.2018.00256] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2018] [Accepted: 08/03/2018] [Indexed: 01/27/2023] Open
Abstract
Background: The apolipoprotein E epsilon4 (ApoE ε4) allele and female gender may be important risk factors for the development of Alzheimer’s disease and amnestic mild cognitive impairment (aMCI). Novelty mismatch negativity (MMN) represents the pre-attentive index of deviance detection and P3a represents the attention orienting response. Furthermore, MMN and P3a components have been reported to be potential markers in aMCI. Therefore, this study will investigate the effects of gender and ApoE on auditory novelty MMN and P3a and their relationship to neuropsychological performance in aMCI. Methods: Thirty nine aMCI subjects and 44 controls underwent neuropsychological assessment and ApoE genotyping. Novelty MMN and P3a components were investigated during an auditory novelty oddball task. Results: Firstly, novelty MMN latency was significantly shorter in aMCI than in healthy control (HC) group. Secondly, novelty MMN latency was negatively correlated with episodic memory in aMCI, but not in HC. Novelty P3a latency was negatively correlated with information processing speed in all subjects. For gender effect, novelty MMN latency was shorter in aMCI females than in HC females. Moreover, novelty P3a amplitudes were lower in males than in females in both aMCI and HC. For the effect of ApoE status, novelty MMN latency was shorter in aMCI ApoE ε4- than HC ApoE ε4-. Conclusion: aMCI presents altered pre-attentive processing indexed by novelty MMN components. Furthermore, there may be a compensatory mechanism on the impaired processing in aMCI. It further suggests that aMCI female and ApoE ε4- recruited the compensatory mechanism.
Collapse
Affiliation(s)
- Lijuan Gao
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Jiu Chen
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Lihua Gu
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Hao Shu
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Duan Liu
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yanna Yan
- Department of Psychology, Xinxiang Medical University, Xinxiang, China
| | - Zhijun Zhang
- Department of Neurology, Affiliated Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.,Department of Psychology, Xinxiang Medical University, Xinxiang, China
| |
Collapse
|
45
|
A Pilot Study Investigating a Novel Non-Linear Measure of Eyes Open versus Eyes Closed EEG
Synchronization in People with Alzheimer’s Disease and Healthy Controls. Brain Sci 2018; 8:brainsci8070134. [PMID: 30018264 PMCID: PMC6070980 DOI: 10.3390/brainsci8070134] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 06/27/2018] [Accepted: 07/16/2018] [Indexed: 12/14/2022] Open
Abstract
Background: The incidence of Alzheimer disease (AD) is increasing with the ageing population. The development of low cost non-invasive diagnostic aids for AD is a research priority. This pilot study investigated whether an approach based on a novel dynamic quantitative parametric EEG method could detect abnormalities in people with AD. Methods: 20 patients with probable AD, 20 matched healthy controls (HC) and 4 patients with probable fronto temporal dementia (FTD) were included. All had detailed neuropsychology along with structural, resting state fMRI and EEG. EEG data were analyzed using the Error Reduction Ratio-causality (ERR-causality) test that can capture both linear and nonlinear interactions between different EEG recording areas. The 95% confidence intervals of EEG levels of bi-centroparietal synchronization were estimated for eyes open (EO) and eyes closed (EC) states. Results: In the EC state, AD patients and HC had very similar levels of bi-centro parietal synchronization; but in the EO resting state, patients with AD had significantly higher levels of synchronization (AD = 0.44; interquartile range (IQR) 0.41 vs. HC = 0.15; IQR 0.17, p < 0.0001). The EO/EC synchronization ratio, a measure of the dynamic changes between the two states, also showed significant differences between these two groups (AD ratio 0.78 versus HC ratio 0.37 p < 0.0001). EO synchronization was also significantly different between AD and FTD (FTD = 0.075; IQR 0.03, p < 0.0001). However, the EO/EC ratio was not informative in the FTD group due to very low levels of synchronization in both states (EO and EC). Conclusion: In this pilot work, resting state quantitative EEG shows significant differences between healthy controls and patients with AD. This approach has the potential to develop into a useful non-invasive and economical diagnostic aid in AD.
Collapse
|
46
|
Complexity Changes in Brain Activity in Healthy Ageing: A Permutation Lempel-Ziv Complexity Study of Magnetoencephalograms. ENTROPY 2018; 20:e20070506. [PMID: 33265596 PMCID: PMC7513026 DOI: 10.3390/e20070506] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 06/26/2018] [Accepted: 06/28/2018] [Indexed: 12/17/2022]
Abstract
Maturation and ageing, which can be characterised by the dynamic changes in brain morphology, can have an impact on the physiology of the brain. As such, it is possible that these changes can have an impact on the magnetic activity of the brain recorded using magnetoencephalography. In this study changes in the resting state brain (magnetic) activity due to healthy ageing were investigated by estimating the complexity of magnetoencephalogram (MEG) signals. The main aim of this study was to identify if the complexity of background MEG signals changed significantly across the human lifespan for both males and females. A sample of 177 healthy participants (79 males and 98 females aged between 21 and 80 and grouped into 3 categories i.e., early-, mid- and late-adulthood) was used in this investigation. This investigation also extended to evaluating if complexity values remained relatively stable during the 5 min recording. Complexity was estimated using permutation Lempel-Ziv complexity, a recently introduced complexity metric, with a motif length of 5 and a lag of 1. Effects of age and gender were investigated in the MEG channels over 5 brain regions, i.e., anterior, central, left lateral, posterior, and, right lateral, with highest complexity values observed in the signals recorded by the channels over the anterior and central regions of the brain. Results showed that while changes due to age had a significant effect on the complexity of the MEG signals recorded over 5 brain regions, gender did not have a significant effect on complexity values in all age groups investigated. Moreover, although some changes in complexity were observed between the different minutes of recording, due to the small magnitude of the changes it was concluded that practical significance might outweigh statistical significance in this instance. The results from this study can contribute to form a fingerprint of the characteristics of healthy ageing in MEGs that could be useful when investigating changes to the resting state activity due to pathology.
Collapse
|
47
|
Dimitriadis SI, López ME, Bruña R, Cuesta P, Marcos A, Maestú F, Pereda E. How to Build a Functional Connectomic Biomarker for Mild Cognitive Impairment From Source Reconstructed MEG Resting-State Activity: The Combination of ROI Representation and Connectivity Estimator Matters. Front Neurosci 2018; 12:306. [PMID: 29910704 PMCID: PMC5992286 DOI: 10.3389/fnins.2018.00306] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Accepted: 04/20/2018] [Indexed: 11/24/2022] Open
Abstract
Our work aimed to demonstrate the combination of machine learning and graph theory for the designing of a connectomic biomarker for mild cognitive impairment (MCI) subjects using eyes-closed neuromagnetic recordings. The whole analysis based on source-reconstructed neuromagnetic activity. As ROI representation, we employed the principal component analysis (PCA) and centroid approaches. As representative bi-variate connectivity estimators for the estimation of intra and cross-frequency interactions, we adopted the phase locking value (PLV), the imaginary part (iPLV) and the correlation of the envelope (CorrEnv). Both intra and cross-frequency interactions (CFC) have been estimated with the three connectivity estimators within the seven frequency bands (intra-frequency) and in pairs (CFC), correspondingly. We demonstrated how different versions of functional connectivity graphs single-layer (SL-FCG) and multi-layer (ML-FCG) can give us a different view of the functional interactions across the brain areas. Finally, we applied machine learning techniques with main scope to build a reliable connectomic biomarker by analyzing both SL-FCG and ML-FCG in two different options: as a whole unit using a tensorial extraction algorithm and as single pair-wise coupling estimations. We concluded that edge-weighed feature selection strategy outperformed the tensorial treatment of SL-FCG and ML-FCG. The highest classification performance was obtained with the centroid ROI representation and edge-weighted analysis of the SL-FCG reaching the 98% for the CorrEnv in α1:α2 and 94% for the iPLV in α2. Classification performance based on the multi-layer participation coefficient, a multiplexity index reached 52% for iPLV and 52% for CorrEnv. Selected functional connections that build the multivariate connectomic biomarker in the edge-weighted scenario are located in default-mode, fronto-parietal, and cingulo-opercular network. Our analysis supports the notion of analyzing FCG simultaneously in intra and cross-frequency whole brain interactions with various connectivity estimators in beamformed recordings.
Collapse
Affiliation(s)
- Stavros I. Dimitriadis
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
- School of Psychology, Cardiff University, Cardiff, United Kingdom
- Neuroinformatics Group, Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
| | - María E. López
- Department of Basic Psychology II, Complutense University of Madrid, Madrid, Spain
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Ricardo Bruña
- Department of Basic Psychology II, Complutense University of Madrid, Madrid, Spain
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Pablo Cuesta
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Madrid, Spain
- Electrical Engineering and Bioengineering Group, Department of Industrial Engineering and IUNE, Universidad de La Laguna, Tenerife, Spain
| | - Alberto Marcos
- Department of Neurology, San Carlos University Hospital, Madrid, Spain
| | - Fernando Maestú
- Department of Basic Psychology II, Complutense University of Madrid, Madrid, Spain
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Madrid, Spain
- Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Ernesto Pereda
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Madrid, Spain
- Electrical Engineering and Bioengineering Group, Department of Industrial Engineering and IUNE, Universidad de La Laguna, Tenerife, Spain
| |
Collapse
|
48
|
Goodman MS, Kumar S, Zomorrodi R, Ghazala Z, Cheam ASM, Barr MS, Daskalakis ZJ, Blumberger DM, Fischer C, Flint A, Mah L, Herrmann N, Bowie CR, Mulsant BH, Rajji TK. Theta-Gamma Coupling and Working Memory in Alzheimer's Dementia and Mild Cognitive Impairment. Front Aging Neurosci 2018; 10:101. [PMID: 29713274 PMCID: PMC5911490 DOI: 10.3389/fnagi.2018.00101] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 03/26/2018] [Indexed: 01/09/2023] Open
Abstract
Working memory deficits are common among individuals with Alzheimer's dementia (AD) or mild cognitive impairment (MCI). Yet, little is known about the mechanisms underlying these deficits. Theta-gamma coupling-the modulation of high-frequency gamma oscillations by low-frequency theta oscillations-is a neurophysiologic process underlying working memory. We assessed the relationship between theta-gamma coupling and working memory deficits in AD and MCI. We hypothesized that: (1) individuals with AD would display the most significant working memory impairments followed by MCI and finally healthy control (HC) participants; and (2) there would be a significant association between working memory performance and theta-gamma coupling across all participants. Ninety-eight participants completed the N-back working memory task during an electroencephalography (EEG) recording: 33 with AD (mean ± SD age: 76.5 ± 6.2), 34 with MCI (mean ± SD age: 74.8 ± 5.9) and 31 HCs (mean ± SD age: 73.5 ± 5.2). AD participants performed significantly worse than control and MCI participants on the 1- and 2-back conditions. Regarding theta-gamma coupling, AD participants demonstrated the lowest level of coupling followed by the MCI and finally control participants on the 2-back condition. Finally, a linear regression analysis demonstrated that theta-gamma coupling (β = 0.69, p < 0.001) was the most significant predictor of 2-back performance. Our results provide evidence for a relationship between altered theta-gamma coupling and working memory deficits in individuals with AD and MCI. They also provide insight into a potential mechanism underlying working memory impairments in these individuals.
Collapse
Affiliation(s)
- Michelle S Goodman
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Sanjeev Kumar
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Reza Zomorrodi
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Zaid Ghazala
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Amay S M Cheam
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Mera S Barr
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Zafiris J Daskalakis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Daniel M Blumberger
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Corinne Fischer
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Alastair Flint
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Centre for Mental Health, University Health Network, Toronto, ON, Canada
| | - Linda Mah
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Rotman Research Institute, Baycrest Health Sciences Centre, Toronto, ON, Canada
| | - Nathan Herrmann
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Christopher R Bowie
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Benoit H Mulsant
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Tarek K Rajji
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
49
|
Fodor Z, Sirály E, Horváth A, Salacz P, Hidasi Z, Csibri É, Szabó Á, Csukly G. Decreased Event-Related Beta Synchronization During Memory Maintenance Marks Early Cognitive Decline in Mild Cognitive Impairment. J Alzheimers Dis 2018; 63:489-502. [PMID: 29630552 DOI: 10.3233/jad-171079] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Mild cognitive impairment (MCI) refers to a measurable deficit in cognition in the absence of dementia or impairment in activities of daily living. Working memory impairment is among the earliest signs of MCI. Oscillatory analysis of working memory might be a potential tool for identifying patients at increased risk of developing dementia. Our study aimed to assess the temporospatial pattern of spectral differences during working memory maintenance between MCI patients and healthy controls and to compare the sources of oscillatory activity between the two groups. Event-related spectral perturbation of 17 MCI patients and 21 healthy control participants was studied with 128-channel EEG during the Sternberg working memory task. Source localization was performed by using the eLORETA software. Among the participants, 13 MCI and 15 control participants underwent a structural brain MRI examination. Event-related synchronization (ERS) in the alpha and beta frequency band was significantly lower in MCI patients compared to healthy control participants during retention. Both study groups showed significant memory load-related enhancement in both frequency band. In the MCI group, source localization revealed significantly attenuated beta oscillatory activity in the inferior and middle temporal gyrus, in the fusiform gyrus, and in the cuneus. Beta ERS correlated significantly with the size of the hippocampus, entorhinal cortex, and parahippocampal gyrus. During the retention period, MCI is characterized by decreased alpha and beta ERS compared to controls indicating early impairment in neural networks serving working memory maintenance. The assessment of electrophysiological changes in the beta frequency range may provide a useful diagnostic tool for the early detection of cognitive impairment.
Collapse
Affiliation(s)
- Zsuzsanna Fodor
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Enikő Sirály
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - András Horváth
- Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Pál Salacz
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary.,Department of Neurology, Hospital at Péterfy Sándor Street, Budapest, Hungary
| | - Zoltán Hidasi
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Éva Csibri
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| | - Ádám Szabó
- MR Research Center, Semmelweis University, Budapest, Hungary
| | - Gábor Csukly
- Department of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary
| |
Collapse
|
50
|
Coherence and phase synchrony analyses of EEG signals in Mild Cognitive Impairment (MCI): A study of functional brain connectivity. POLISH JOURNAL OF MEDICAL PHYSICS AND ENGINEERING 2018. [DOI: 10.2478/pjmpe-2018-0001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Abstract
This paper presents an EEG study for coherence and phase synchrony in mild cognitive impairment (MCI) subjects. MCI is characterized by cognitive decline, which is an early stage of Alzheimer’s disease (AD). AD is a neurodegenerative disorder with symptoms such as memory loss and cognitive impairment. EEG coherence is a statistical measure of correlation between signals from electrodes spatially separated on the scalp. The magnitude of phase synchrony is expressed in the phase locking value (PLV), a statistical measure of neuronal connectivity in the human brain. Brain signals were recorded using an Emotiv Epoc 14-channel wireless EEG at a sampling frequency of 128 Hz. In this study, we used 22 elderly subjects consisted of 10 MCI subjects and 12 healthy subjects as control group. The coherence between each electrode pair was measured for all frequency bands (delta, theta, alpha and beta). In the MCI subjects, the value of coherence and phase synchrony was generally lower than in the healthy subjects especially in the beta frequency. A decline of intrahemisphere coherence in the MCI subjects occurred in the left temporo-parietal-occipital region. The pattern of decline in MCI coherence is associated with decreased cholinergic connectivity along the path that connects the temporal, occipital, and parietal areas of the brain to the frontal area of the brain. EEG coherence and phase synchrony are able to distinguish persons who suffer AD in the early stages from healthy elderly subjects.
Collapse
|