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Korte JA, Weakley A, Donjuan Fernandez K, Joiner WM, Fan AP. Neural Underpinnings of Learning in Dementia Populations: A Review of Motor Learning Studies Combined with Neuroimaging. J Cogn Neurosci 2024; 36:734-755. [PMID: 38285732 DOI: 10.1162/jocn_a_02116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
The intent of this review article is to serve as an overview of current research regarding the neural characteristics of motor learning in Alzheimer disease (AD) as well as prodromal phases of AD: at-risk populations, and mild cognitive impairment. This review seeks to provide a cognitive framework to compare various motor tasks. We will highlight the neural characteristics related to cognitive domains that, through imaging, display functional or structural changes because of AD progression. In turn, this motivates the use of motor learning paradigms as possible screening techniques for AD and will build upon our current understanding of learning abilities in AD populations.
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Williamson J, James SA, Mukli P, Yabluchanskiy A, Wu DH, Sonntag W, Yang Y. Sex difference in brain functional connectivity of hippocampus in Alzheimer's disease. GeroScience 2024; 46:563-572. [PMID: 37743414 PMCID: PMC10828268 DOI: 10.1007/s11357-023-00943-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 09/11/2023] [Indexed: 09/26/2023] Open
Abstract
Alzheimer's disease (AD), affecting nearly 6.5 million people, is the fifth leading cause of death in individuals 65 years or older in the USA. Prior research has shown that AD disproportionality affects females; females have a greater incidence rate, perform worse on a variety of neuropsychological tasks, and have greater total brain atrophy. Recent research has linked these sex differences to neuroimaging markers of brain pathology, such as hippocampal volumes. Specifically, research from our lab found that functional connectivity from the hippocampus to the precuneus cortex and brain stem was significantly stronger in males than in females with mild cognitive impairment. The aim of this study was to extend our understanding to individuals with AD and to determine if these potential sex-specific functional connectivity biomarkers extend through different disease stages. The resting state fMRI and T2 MRI of cognitively normal individuals (n = 32, female = 16) and individuals with AD (n = 32, female = 16) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed using the Functional Connectivity Toolbox (CONN). Our results demonstrate that males had a significantly stronger interhemispheric functional connectivity between the left and right hippocampus compared to females. These results improve our current understanding of the role of the hippocampus in sex differences in AD. Understanding the contribution of impaired functional connectivity sex differences may aid in the development of sex-specific precision medicine for improved AD treatment.
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Affiliation(s)
- Jordan Williamson
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Shirley A James
- Department of Public Health, Health Science Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Peter Mukli
- Vascular Cognitive Impairment and Neurodegeneration Program, Oklahoma Center for Geroscience and Healthy Brain Aging, Department of Neurosurgery, Health Sciences Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Andriy Yabluchanskiy
- Vascular Cognitive Impairment and Neurodegeneration Program, Oklahoma Center for Geroscience and Healthy Brain Aging, Department of Neurosurgery, Health Sciences Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Dee H Wu
- Department of Radiological Science and Medical Physics, Health Science Center, University of Oklahoma, Oklahoma City, OK, USA
- Data Institute for Societal Challenges, University of Oklahoma, Norman, OK, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - William Sonntag
- Vascular Cognitive Impairment and Neurodegeneration Program, Oklahoma Center for Geroscience and Healthy Brain Aging, Department of Neurosurgery, Health Sciences Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Yuan Yang
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Department of Rehabilitation Sciences, Health Science Center, University of Oklahoma, Oklahoma City, OK, USA.
- Data Institute for Societal Challenges, University of Oklahoma, Norman, OK, USA.
- Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- SFCRI Clinical Imaging Research Center, Carle Foundation Hospital, Urbana, IL, USA.
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, USA.
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Caravaglios G, Muscoso EG, Blandino V, Di Maria G, Gangitano M, Graziano F, Guajana F, Piccoli T. EEG Resting-State Functional Networks in Amnestic Mild Cognitive Impairment. Clin EEG Neurosci 2023; 54:36-50. [PMID: 35758261 DOI: 10.1177/15500594221110036] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background. Alzheimer's cognitive-behavioral syndrome is the result of impaired connectivity between nerve cells, due to misfolded proteins, which accumulate and disrupt specific brain networks. Electroencephalography, because of its excellent temporal resolution, is an optimal approach for assessing the communication between functionally related brain regions. Objective. To detect and compare EEG resting-state networks (RSNs) in patients with amnesic mild cognitive impairment (aMCI), and healthy elderly (HE). Methods. We recruited 125 aMCI patients and 70 healthy elderly subjects. One hundred and twenty seconds of artifact-free EEG data were selected and compared between patients with aMCI and HE. We applied standard low-resolution brain electromagnetic tomography (sLORETA)-independent component analysis (ICA) to assess resting-state networks. Each network consisted of a set of images, one for each frequency (delta, theta, alpha1/2, beta1/2). Results. The functional ICA analysis revealed 17 networks common to groups. The statistical procedure demonstrated that aMCI used some networks differently than HE. The most relevant findings were as follows. Amnesic-MCI had: i) increased delta/beta activity in the superior frontal gyrus and decreased alpha1 activity in the paracentral lobule (ie, default mode network); ii) greater delta/theta/alpha/beta in the superior frontal gyrus (i.e, attention network); iii) lower alpha in the left superior parietal lobe, as well as a lower delta/theta and beta, respectively in post-central, and in superior frontal gyrus(ie, attention network). Conclusions. Our study confirms sLORETA-ICA method is effective in detecting functional resting-state networks, as well as between-groups connectivity differences. The findings provide support to the Alzheimer's network disconnection hypothesis.
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Affiliation(s)
- G Caravaglios
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - E G Muscoso
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - V Blandino
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - G Di Maria
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - M Gangitano
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - F Graziano
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - F Guajana
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - T Piccoli
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
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Bagattini C, Esposito M, Ferrari C, Mazza V, Brignani D. Connectivity alterations underlying the breakdown of pseudoneglect: New insights from healthy and pathological aging. Front Aging Neurosci 2022; 14:930877. [PMID: 36118681 PMCID: PMC9475001 DOI: 10.3389/fnagi.2022.930877] [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: 04/28/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
A right-hemisphere dominance for visuospatial attention has been invoked as the most prominent neural feature of pseudoneglect (i.e., the leftward visuospatial bias exhibited in neurologically healthy individuals) but the neurophysiological underpinnings of such advantage are still controversial. Previous studies investigating visuospatial bias in multiple-objects visual enumeration reported that pseudoneglect is maintained in healthy elderly and amnesic mild cognitive impairment (aMCI), but not in Alzheimer’s disease (AD). In this study, we aimed at investigating the neurophysiological correlates sustaining the rearrangements of the visuospatial bias along the progression from normal to pathological aging. To this aim, we recorded EEG activity during an enumeration task and analyzed intra-hemispheric fronto-parietal and inter-hemispheric effective connectivity adopting indexes from graph theory in patients with mild AD, patients with aMCI, and healthy elderly controls (HC). Results revealed that HC showed the leftward bias and stronger fronto-parietal effective connectivity in the right as compared to the left hemisphere. A breakdown of pseudoneglect in patients with AD was associated with both the loss of the fronto-parietal asymmetry and the reduction of inter-hemispheric parietal interactions. In aMCI, initial alterations of the attentional bias were associated with a reduction of parietal inter-hemispheric communication, but not with modulations of the right fronto-parietal connectivity advantage, which remained intact. These data provide support to the involvement of fronto-parietal and inter-parietal pathways in the leftward spatial bias, extending these notions to the complex neurophysiological alterations characterizing pathological aging.
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Affiliation(s)
- Chiara Bagattini
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- *Correspondence: Chiara Bagattini,
| | - Marco Esposito
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Clarissa Ferrari
- Unit of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Veronica Mazza
- Center for Mind/Brain Sciences CIMeC, University of Trento, Rovereto, Italy
| | - Debora Brignani
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
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5
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Scally B, Burke MR, Bunce D, Delvenne JF. Visual and visuomotor interhemispheric transfer time in older adults. Neurobiol Aging 2018; 65:69-76. [DOI: 10.1016/j.neurobiolaging.2018.01.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2017] [Revised: 11/07/2017] [Accepted: 01/09/2018] [Indexed: 12/01/2022]
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Babiloni C, Del Percio C, Lizio R, Noce G, Lopez S, Soricelli A, Ferri R, Nobili F, Arnaldi D, Famà F, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Garn H, Fraioli L, Pievani M, Frisoni GB, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, Taylor JP, Vacca L, De Pandis MF, Bonanni L. Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study. Neurobiol Aging 2017; 65:18-40. [PMID: 29407464 DOI: 10.1016/j.neurobiolaging.2017.12.023] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Revised: 12/21/2017] [Accepted: 12/21/2017] [Indexed: 11/30/2022]
Abstract
Previous evidence showed abnormal posterior sources of resting-state delta (<4 Hz) and alpha (8-12 Hz) rhythms in patients with Alzheimer's disease with dementia (ADD), Parkinson's disease with dementia (PDD), and Lewy body dementia (DLB), as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis of additional abnormalities in functional cortical connectivity computed in those sources, in ADD, considered as a "disconnection cortical syndrome", in comparison with PDD and DLB. Resting-state eyes-closed electroencephalographic (rsEEG) rhythms had been collected in 42 ADD, 42 PDD, 34 DLB, and 40 normal healthy older (Nold) participants. Exact low-resolution brain electromagnetic tomography (eLORETA) freeware estimated the functional lagged linear connectivity (LLC) from rsEEG cortical sources in delta, theta, alpha, beta, and gamma bands. The area under receiver operating characteristic (AUROC) curve indexed the classification accuracy between Nold and diseased individuals (only values >0.7 were considered). Interhemispheric and intrahemispheric LLCs in widespread delta sources were abnormally higher in the ADD group and, unexpectedly, normal in DLB and PDD groups. Intrahemispheric LLC was reduced in widespread alpha sources dramatically in ADD, markedly in DLB, and moderately in PDD group. Furthermore, the interhemispheric LLC in widespread alpha sources showed lower values in ADD and DLB than PDD groups. At the individual level, AUROC curves of LLC in alpha sources exhibited better classification accuracies for the discrimination of ADD versus Nold individuals (0.84) than for DLB versus Nold participants (0.78) and PDD versus Nold participants (0.75). Functional cortical connectivity markers in delta and alpha sources suggest a more compromised neurophysiological reserve in ADD than DLB, at both group and individual levels.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy.
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy; Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy; Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Flavio Nobili
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology and Psychiatry and Faculty of Medicine, Johannes Kepler University Linz, General Hospital of the City of Linz, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Görsev Yener
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy; Casa di Cura Privata del Policlinico (CCPP) Milano SpA, Milan, Italy
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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Guzzetti S, Daini R. Inter-hemispheric recruitment as a function of task complexity, age and cognitive reserve. AGING NEUROPSYCHOLOGY AND COGNITION 2014; 21:722-45. [DOI: 10.1080/13825585.2013.874522] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Huang S, Li J, Ye J, Fleisher A, Chen K, Wu T, Reiman E. A sparse structure learning algorithm for Gaussian Bayesian Network identification from high-dimensional data. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2013; 35:1328-42. [PMID: 22665720 PMCID: PMC3924722 DOI: 10.1109/tpami.2012.129] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Structure learning of Bayesian Networks (BNs) is an important topic in machine learning. Driven by modern applications in genetics and brain sciences, accurate and efficient learning of large-scale BN structures from high-dimensional data becomes a challenging problem. To tackle this challenge, we propose a Sparse Bayesian Network (SBN) structure learning algorithm that employs a novel formulation involving one L1-norm penalty term to impose sparsity and another penalty term to ensure that the learned BN is a Directed Acyclic Graph--a required property of BNs. Through both theoretical analysis and extensive experiments on 11 moderate and large benchmark networks with various sample sizes, we show that SBN leads to improved learning accuracy, scalability, and efficiency as compared with 10 existing popular BN learning algorithms. We apply SBN to a real-world application of brain connectivity modeling for Alzheimer's disease (AD) and reveal findings that could lead to advancements in AD research.
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Affiliation(s)
- Shuai Huang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, PO Box 878809, Tempe, AZ 85287-8809
| | - Jing Li
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, PO Box 878809, Tempe, AZ 85287-8809.
| | - Jieping Ye
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, PO Box 878809, Tempe, AZ 85287-8809
| | - Adam Fleisher
- Banner Alzheimer’s Institute, 1111 E. McDowell Road, Phoenix AZ 85006
| | - Kewei Chen
- Banner Alzheimer’s Institute, 1111 E. McDowell Road, Phoenix AZ 85006
| | - Teresa Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, PO Box 878809, Tempe, AZ 85287-8809
| | - Eric Reiman
- Banner Alzheimer’s Institute, 1111 E. McDowell Road, Phoenix AZ 85006
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Pieramico V, Esposito R, Sensi F, Cilli F, Mantini D, Mattei PA, Frazzini V, Ciavardelli D, Gatta V, Ferretti A, Romani GL, Sensi SL. Combination training in aging individuals modifies functional connectivity and cognition, and is potentially affected by dopamine-related genes. PLoS One 2012; 7:e43901. [PMID: 22937122 PMCID: PMC3429431 DOI: 10.1371/journal.pone.0043901] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2011] [Accepted: 07/27/2012] [Indexed: 01/12/2023] Open
Abstract
Background Aging is a major co-risk factor in many neurodegenerative diseases. Cognitive enrichment positively affects the structural plasticity of the aging brain. In this study, we evaluated effects of a set of structured multimodal activities (Combination Training; CT) on cognitive performances, functional connectivity, and cortical thickness of a group of healthy elderly individuals. CT lasted six months. Methodology Neuropsychological and occupational performances were evaluated before and at the end of the training period. fMRI was used to assess effects of training on resting state network (RSN) functional connectivity using Independent Component Analysis (ICA). Effects on cortical thickness were also studied. Finally, we evaluated whether specific dopamine-related genes can affect the response to training. Principal Findings Results of the study indicate that CT improves cognitive/occupational performances and reorganizes functional connectivity. Intriguingly, individuals responding to CT showed specific dopamine-related genotypes. Indeed, analysis of dopamine-related genes revealed that carriers of DRD3 ser9gly and COMT Val158Met polymorphisms had the greatest benefits from exposure to CT. Conclusions and Significance Overall, our findings support the idea that exposure to a set of structured multimodal activities can be an effective strategy to counteract aging-related cognitive decline and also indicate that significant capability of functional and structural changes are maintained in the elderly.
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Affiliation(s)
- Valentina Pieramico
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
- Molecular Neurology Unit, Center of Excellence on Aging, University “G. d’Annunzio”, Chieti-Pescara, Chieti, Italy
| | - Roberto Esposito
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
| | - Francesca Sensi
- Molecular Neurology Unit, Center of Excellence on Aging, University “G. d’Annunzio”, Chieti-Pescara, Chieti, Italy
| | - Franco Cilli
- Molecular Neurology Unit, Center of Excellence on Aging, University “G. d’Annunzio”, Chieti-Pescara, Chieti, Italy
| | - Dante Mantini
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
- Department of Neurosciences, Laboratory for Neuro- and Psychophysiology, Catholic University of Leuven, Leuven, Belgium
| | - Peter A. Mattei
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
| | - Valerio Frazzini
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
- Molecular Neurology Unit, Center of Excellence on Aging, University “G. d’Annunzio”, Chieti-Pescara, Chieti, Italy
| | - Domenico Ciavardelli
- Molecular Neurology Unit, Center of Excellence on Aging, University “G. d’Annunzio”, Chieti-Pescara, Chieti, Italy
- Department of Biochemistry, School of Motor Sciences, Kore University of Enna, Enna, Italy
| | - Valentina Gatta
- Department of Psychological sciences, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
- Functional Genomics Unit, Center of Excellence on Aging, University “G. d’Annunzio”, Chieti-Pescara, Chieti, Italy
| | - Antonio Ferretti
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
| | - Gian Luca Romani
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
| | - Stefano L. Sensi
- Department of Neuroscience and Imaging, University “G. d’Annunzio” Chieti-Pescara, Chieti, Italy
- Molecular Neurology Unit, Center of Excellence on Aging, University “G. d’Annunzio”, Chieti-Pescara, Chieti, Italy
- Departments of Neurology and Pharmacology, University of California Irvine, Irvine, California, United States of America
- * E-mail:
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Huang S, Li J, Ye J, Fleisher A, Chen K, Wu T, Reiman E. Brain Effective Connectivity Modeling for Alzheimer's Disease by Sparse Gaussian Bayesian Network. KDD : PROCEEDINGS. INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY & DATA MINING 2011:931-939. [PMID: 26952033 PMCID: PMC4779440 DOI: 10.1145/2020408.2020562] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
Recent studies have shown that Alzheimer's disease (AD) is related to alteration in brain connectivity networks. One type of connectivity, called effective connectivity, defined as the directional relationship between brain regions, is essential to brain function. However, there have been few studies on modeling the effective connectivity of AD and characterizing its difference from normal controls (NC). In this paper, we investigate the sparse Bayesian Network (BN) for effective connectivity modeling. Specifically, we propose a novel formulation for the structure learning of BNs, which involves one L1-norm penalty term to impose sparsity and another penalty to ensure the learned BN to be a directed acyclic graph - a required property of BNs. We show, through both theoretical analysis and extensive experiments on eleven moderate and large benchmark networks with various sample sizes, that the proposed method has much improved learning accuracy and scalability compared with ten competing algorithms. We apply the proposed method to FDG-PET images of 42 AD and 67 NC subjects, and identify the effective connectivity models for AD and NC, respectively. Our study reveals that the effective connectivity of AD is different from that of NC in many ways, including the global-scale effective connectivity, intra-lobe, interlobe, and inter-hemispheric effective connectivity distributions, as well as the effective connectivity associated with specific brain regions. These findings are consistent with known pathology and clinical progression of AD, and will contribute to AD knowledge discovery.
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Affiliation(s)
- Shuai Huang
- School of Computing, Informatics, and Decisions Systems Engineering, Arizona State University, Tempe, AZ, 85287
| | - Jing Li
- School of Computing, Informatics, and Decisions Systems Engineering, Arizona State University, Tempe, AZ, 85287
| | - Jieping Ye
- School of Computing, Informatics, and Decisions Systems Engineering, Arizona State University, Tempe, AZ, 85287
| | - Adam Fleisher
- Banner Alzheimer's Institute, Banner Good Samaritan Medical Center, Phoenix, AZ, 85006
| | - Kewei Chen
- Banner Alzheimer's Institute, Banner Good Samaritan Medical Center, Phoenix, AZ, 85006
| | - Teresa Wu
- School of Computing, Informatics, and Decisions Systems Engineering, Arizona State University, Tempe, AZ, 85287
| | - Eric Reiman
- Banner Alzheimer's Institute, Banner Good Samaritan Medical Center, Phoenix, AZ, 85006
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11
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Exploring interhemispheric collaboration in older compared to younger adults. Brain Cogn 2010; 72:218-27. [DOI: 10.1016/j.bandc.2009.09.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2009] [Revised: 09/10/2009] [Accepted: 09/16/2009] [Indexed: 11/22/2022]
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Ansado J, Faure S, Joanette Y. Le cerveau adaptatif : rôle du couplage interhémisphérique dans le maintien des habiletés cognitives avec l'âge et découplage dans la maladie d'Alzheimer ? ACTA ACUST UNITED AC 2009. [DOI: 10.3917/rne.012.0159] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
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강동형, 김남균. Perception of Movement and Interhemispheric Interaction in Alzheimer's Disease. ACTA ACUST UNITED AC 2008. [DOI: 10.15842/kjcp.2008.27.4.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
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Delbeuck X, Collette F, Van der Linden M. Is Alzheimer's disease a disconnection syndrome? Neuropsychologia 2007; 45:3315-23. [PMID: 17765932 DOI: 10.1016/j.neuropsychologia.2007.05.001] [Citation(s) in RCA: 88] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2006] [Revised: 04/19/2007] [Accepted: 05/03/2007] [Indexed: 11/28/2022]
Abstract
In Alzheimer's disease (AD), loss of connectivity in the patient's brain has been evidenced by a range of electrophysiological and neuroimaging studies. However, few neuropsychological research projects have sought to interpret the cognitive modifications following the appearance of AD in terms of a disconnection syndrome. In this paper, we sought to investigate brain connectivity in AD via the study of a crossmodal effect. More precisely, we examined the integration of auditory and visual speech information (the McGurk effect) in AD patients and matched control subjects. Our results revealed impaired crossmodal integration during speech perception in AD, which was not associated with disturbances in the separate processing of auditory and visual speech stimuli. In conclusion, our data suggest the occurrence of a specific, audio-visual integration deficit in AD, which might be the consequence of a connectivity breakdown and corroborate the observation from other studies of crossmodal deficits between the auditory and visual modalities in this population.
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Affiliation(s)
- X Delbeuck
- Memory, Resources & Research Centre, EA 2691, Lille University Hospital, Lille, France.
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Murray C, Viehman A, Lippa CF. The corpus callosum in Pick's disease, Alzheimer's disease, and amyotrophic lateral sclerosis: gliosis implies possible clinical consequence. Am J Alzheimers Dis Other Demen 2006; 21:37-43. [PMID: 16526588 PMCID: PMC10833212 DOI: 10.1177/153331750602100111] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Lesions of the corpus callosum have the potential to interfere with a neurologically impaired individual's ability to function in day-to-day activities, since the corpus callosum is important for a number of higher-order activities that involve information transfer between the left and right hemispheres. Even in normal individuals, callosal lesions may lead to apraxia, agraphia, and even an alien hand syndrome whereby the person is unable to control the actions of a hand. It is easy to envisage that callosal damage could compound cognitive symptoms in individuals with dementia. However, despite the common presence of apraxia in dementia, physicians and other healthcare providers rarely focus on callosalfunction in dementia patients. The current manuscript compares pathological data from a variety of patients with dementia with age-matched control subjects showing callosal gliosis in neurodegenerative diseases including Alzheimer's disease (AD), frontotemporal dementia (FTD), and amyotrophic lateral sclerosis. We conclude that callosal gliosis is not uncommon, particularly in patients with AD and FTD. Given the severity of this pathology in some cases, we cannot exclude the possibility that it is clinically relevant. Clinical implications are discussed, and it is recommended that further studies be done to determine whether there is a relevant clinical correlate.
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Affiliation(s)
- Cynelle Murray
- Department of Neurology, Drexel University College of Medicine, Philadelphia, Pennsylvania, USA
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