Functional Disintegration of the Default Mode Network in Prodromal Alzheimer's Disease.

Neurodegenerative brain changes can affect the functional connectivity strength between nodes of the default-mode network (DMN), which may underlie changes in cognitive performance. It remains unclear how the functional connectivity strength of DMN nodes differs from healthy to pathological aging and whether these changes are cognitively relevant. We used resting-state functional magnetic resonance imaging to investigate the functional connectivity strength across five DMN nodes in 25 healthy controls (HC), 28 subjective cognitive decline (SCD) participants, and 25 prodromal Alzheimer's disease (AD) patients. After identifying the ventral medial prefrontal cortex (vmPFC), posterior cingulate cortex (PCC), retrosplenial cortex (RSC), inferior parietal lobule, and the hippocampus we investigated the functional strength between DMN nodes using temporal network modeling. Functional coupling of the vmPFC and PCC in prodromal AD patients was disrupted. This vmPFC-PCC coupling correlated positively with memory performance in prodromal AD. Furthermore, the hippocampus de-coupled from posterior DMN nodes in SCD and prodromal AD patients. There was no coupling between the hippocampus and the anterior DMN. Additional mediation analyses indicated that the RSC enables communication between the hippocampus and DMN regions in HC but none of the other two groups. These results suggest an anterior-posterior disconnection and a hippocampal de-coupling from posterior DMN nodes with disease progression. Hippocampal de-coupling already occurring in SCD may provide valuable information for the development of a functional biomarker.

[1]  B. Miller,et al.  Neurodegenerative Diseases Target Large-Scale Human Brain Networks , 2009, Neuron.

[2]  R. Petersen Mild cognitive impairment as a diagnostic entity , 2004, Journal of internal medicine.

[3]  V. Calhoun,et al.  Interrater and intermethod reliability of default mode network selection , 2009, Human brain mapping.

[4]  K-J Langen,et al.  High resolution BrainPET combined with simultaneous MRI , 2011, Nuklearmedizin.

[5]  B. Fischl,et al.  White matter pathology isolates the hippocampal formation in Alzheimer's disease , 2010, Neurobiology of Aging.

[6]  Naruhiko Sahara,et al.  Propagation of Tau Pathology in a Model of Early Alzheimer's Disease , 2012, Neuron.

[7]  Nick C Fox,et al.  Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria , 2014, The Lancet Neurology.

[8]  F. Collette,et al.  Alzheimer' Disease as a Disconnection Syndrome? , 2003, Neuropsychology Review.

[9]  G. V. Van Hoesen,et al.  Alzheimer's disease: cell-specific pathology isolates the hippocampal formation. , 1984, Science.

[10]  Keith A. Johnson,et al.  Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease , 2009, The Journal of Neuroscience.

[11]  Koene R. A. Van Dijk,et al.  The parahippocampal gyrus links the default‐mode cortical network with the medial temporal lobe memory system , 2014, Human brain mapping.

[12]  H. Braak,et al.  Neuropathological stageing of Alzheimer-related changes , 2004, Acta Neuropathologica.

[13]  E. Maguire,et al.  The Human Hippocampus and Spatial and Episodic Memory , 2002, Neuron.

[14]  E. Tangalos,et al.  Mild Cognitive Impairment Clinical Characterization and Outcome , 1999 .

[15]  Nick C Fox,et al.  Revising the definition of Alzheimer's disease: a new lexicon , 2010, The Lancet Neurology.

[16]  Li Yao,et al.  Altered Connectivity Pattern of Hubs in Default-Mode Network with Alzheimer's Disease: An Granger Causality Modeling Approach , 2011, PloS one.

[17]  Ludovica Griffanti,et al.  Automatic denoising of functional MRI data: Combining independent component analysis and hierarchical fusion of classifiers , 2014, NeuroImage.

[18]  J. Jolles,et al.  Visuospatial processing in early Alzheimer’s disease: A multimodal neuroimaging study , 2015, Cortex.

[19]  M. Greicius,et al.  Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI , 2004, Proc. Natl. Acad. Sci. USA.

[20]  J. Brandt,et al.  Development and psychometric properties of the brief test of attention , 1996 .

[21]  E. Bullmore,et al.  A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs , 2006, The Journal of Neuroscience.

[22]  Habib Benali,et al.  Characteristics of the default mode functional connectivity in normal ageing and Alzheimer's disease using resting state fMRI with a combined approach of entropy-based and graph theoretical measurements , 2014, NeuroImage.

[23]  Mark Jenkinson,et al.  Optimizing parameter choice for FSL-Brain Extraction Tool (BET) on 3D T1 images in multiple sclerosis , 2012, NeuroImage.

[24]  P. Shrout,et al.  Mediation in experimental and nonexperimental studies: new procedures and recommendations. , 2002, Psychological methods.

[25]  Christiane,et al.  WORLD MEDICAL ASSOCIATION DECLARATION OF HELSINKI: Ethical Principles for Medical Research Involving Human Subjects , 2001, Journal of postgraduate medicine.

[26]  H. Lehfeld,et al.  The Bayer Activities of Daily Living Scale (B-ADL) , 1998, Dementia and Geriatric Cognitive Disorders.

[27]  Daniel Rueckert,et al.  Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment , 2013, Neurobiology of Aging.

[28]  Stephen M. Smith,et al.  Probabilistic independent component analysis for functional magnetic resonance imaging , 2004, IEEE Transactions on Medical Imaging.

[29]  Benjamin J. Shannon,et al.  Molecular, Structural, and Functional Characterization of Alzheimer's Disease: Evidence for a Relationship between Default Activity, Amyloid, and Memory , 2005, The Journal of Neuroscience.

[30]  J. Baron,et al.  In Vivo Mapping of Gray Matter Loss with Voxel-Based Morphometry in Mild Alzheimer's Disease , 2001, NeuroImage.

[31]  Stephen M. Smith,et al.  fMRI resting state networks define distinct modes of long-distance interactions in the human brain , 2006, NeuroImage.

[32]  M. Mattson Pathways towards and away from Alzheimer's disease , 2004, Nature.

[33]  C. Helmstaedter,et al.  VLMT: Verbaler Lern- und Merkfähigkeitstest: Ein praktikables und differenziertes Instrumentarium zur Prüfung der verbalen Gedächtnisleistungen , 1990 .

[34]  Mark W. Woolrich,et al.  Resting-state fMRI in the Human Connectome Project , 2013, NeuroImage.

[35]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.

[36]  Yong He,et al.  Identifying and Mapping Connectivity Patterns of Brain Network Hubs in Alzheimer's Disease. , 2015, Cerebral cortex.

[37]  Nick C Fox,et al.  The Diagnosis of Mild Cognitive Impairment due to Alzheimer’s Disease: Recommendations from the National Institute on Aging-Alzheimer’s Association Workgroups on Diagnostic Guidelines for Alzheimer’s Disease , 2011 .

[38]  A. Mitchell,et al.  Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: meta‐analysis , 2014, Acta psychiatrica Scandinavica.

[39]  Gereon R. Fink,et al.  Ageing-related changes of neural activity associated with spatial contextual memory , 2009, Neurobiology of Aging.

[40]  Keith A. Johnson,et al.  Neuronal dysfunction and disconnection of cortical hubs in non-demented subjects with elevated amyloid burden , 2011, Alzheimer's & Dementia.

[41]  J. Stroop Studies of interference in serial verbal reactions. , 1992 .

[42]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[43]  K. Blennow,et al.  The cerebrospinal fluid “Alzheimer profile”: Easily said, but what does it mean? , 2014, Alzheimer's & Dementia.

[44]  M. Lowe,et al.  Functional Connectivity in Single and Multislice Echoplanar Imaging Using Resting-State Fluctuations , 1998, NeuroImage.

[45]  William J Jagust,et al.  Brain function and cognition in a community sample of elderly Latinos , 2002, Neurology.

[46]  Vince D. Calhoun,et al.  Alterations in Memory Networks in Mild Cognitive Impairment and Alzheimer's Disease: An Independent Component Analysis , 2006, The Journal of Neuroscience.

[47]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[48]  Stephen M. Smith,et al.  Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference , 2009, NeuroImage.

[49]  Özgür A. Onur,et al.  Aberrant functional connectivity differentiates retrosplenial cortex from posterior cingulate cortex in prodromal Alzheimer's disease , 2016, Neurobiology of Aging.

[50]  M. Zimmerman,et al.  Severity classification on the Hamilton Depression Rating Scale. , 2013, Journal of affective disorders.

[51]  Mark W. Woolrich,et al.  Bayesian analysis of neuroimaging data in FSL , 2009, NeuroImage.

[52]  C. Jack,et al.  Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade , 2010, The Lancet Neurology.

[53]  Moo K. Chung,et al.  Integrating VBM into the General Linear Model with voxelwise anatomical covariates , 2007, NeuroImage.

[54]  V. Calhoun,et al.  Selective changes of resting-state networks in individuals at risk for Alzheimer's disease , 2007, Proceedings of the National Academy of Sciences.

[55]  S. Rombouts,et al.  Reduced resting-state brain activity in the "default network" in normal aging. , 2008, Cerebral cortex.

[56]  D. Wechsler Wechsler Adult Intelligence Scale , 2021, Encyclopedia of Evolutionary Psychological Science.

[57]  P. Shrout,et al.  Mediation in experimental and nonexperimental studies: new procedures and recommendations. , 2002, Psychological methods.

[58]  Alan C. Evans,et al.  Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease , 2008, The Journal of Neuroscience.

[59]  A. Hayes PROCESS : A Versatile Computational Tool for Observed Variable Mediation , Moderation , and Conditional Process Modeling 1 , 2012 .

[60]  N. Schuff,et al.  Headache and cerebral venous air embolism , 2007, Neurology.

[61]  Peter Fransson,et al.  The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis , 2008, NeuroImage.

[62]  N. Foster,et al.  Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease , 1997, Annals of neurology.

[63]  Denise C. Park,et al.  Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[64]  Mark Mühlau,et al.  Grey-matter atrophy in Alzheimer's disease is asymmetric but not lateralized. , 2011, Journal of Alzheimer's disease : JAD.

[65]  O Sporns,et al.  Predicting human resting-state functional connectivity from structural connectivity , 2009, Proceedings of the National Academy of Sciences.

[66]  Paul J. Laurienti,et al.  An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets , 2003, NeuroImage.

[67]  M H Buonocore,et al.  Brain structure and cognition in a community sample of elderly Latinos , 2002, Neurology.

[68]  Zhishun Wang,et al.  Visual inspection of independent components: Defining a procedure for artifact removal from fMRI data , 2010, Journal of Neuroscience Methods.

[69]  Lars Nyberg,et al.  Longitudinal Evidence for Dissociation of Anterior and Posterior MTL Resting-State Connectivity in Aging: Links to Perfusion and Memory , 2016, Cerebral cortex.

[70]  E. Tulving,et al.  Episodic and declarative memory: Role of the hippocampus , 1998, Hippocampus.

[71]  Andrew J. Saykin,et al.  A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease , 2014, Alzheimer's & Dementia.

[72]  Stephen M. Smith,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[73]  C. Stam,et al.  Small-world networks and functional connectivity in Alzheimer's disease. , 2006, Cerebral cortex.

[74]  Stephen M Smith,et al.  Fast robust automated brain extraction , 2002, Human brain mapping.

[75]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[76]  J. Baron,et al.  Relationships between Hippocampal Atrophy, White Matter Disruption, and Gray Matter Hypometabolism in Alzheimer's Disease , 2008, The Journal of Neuroscience.

[77]  O. Sporns,et al.  Network hubs in the human brain , 2013, Trends in Cognitive Sciences.

[78]  Wolzt,et al.  World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. , 2003, The Journal of the American College of Dentists.

[79]  Steven Mennerick,et al.  Synaptic Activity Regulates Interstitial Fluid Amyloid-β Levels In Vivo , 2005, Neuron.

[80]  Katherine E. Prater,et al.  Functional connectivity tracks clinical deterioration in Alzheimer's disease , 2012, Neurobiology of Aging.

[81]  Zhang Ji-qiang Default-mode network and Alzheimer’s disease , 2012 .

[82]  Abraham Z. Snyder,et al.  Resting-state functional connectivity in the human brain revealed with diffuse optical tomography , 2009, NeuroImage.

[83]  Zhi-jun Zhang,et al.  Detection of PCC functional connectivity characteristics in resting-state fMRI in mild Alzheimer’s disease , 2009, Behavioural Brain Research.

[84]  T. Crook,et al.  Assessment of Memory Complaint in Age-Associated Memory Impairment: The MAC-Q , 1992, International Psychogeriatrics.

[85]  Olaf Sporns,et al.  Small worlds inside big brains , 2006, Proceedings of the National Academy of Sciences.

[86]  R. Reitan Validity of the Trail Making Test as an Indicator of Organic Brain Damage , 1958 .

[87]  D. Schacter,et al.  The Brain's Default Network , 2008, Annals of the New York Academy of Sciences.

[88]  L. Nyberg,et al.  Elevated hippocampal resting-state connectivity underlies deficient neurocognitive function in aging , 2014, Proceedings of the National Academy of Sciences.

[89]  Paul M. Matthews,et al.  Brain Microstructure Reveals Early Abnormalities more than Two Years prior to Clinical Progression from Mild Cognitive Impairment to Alzheimer's Disease , 2013, The Journal of Neuroscience.

[90]  F. Jessen,et al.  Differential Risk of Incident Alzheimer's Disease Dementia in Stable Versus Unstable Patterns of Subjective Cognitive Decline. , 2016 .

[91]  Bill Seeley,et al.  Neurodegenerative diseases target large-scale human brain networks , 2010, Alzheimer's & Dementia.

[92]  Timothy O. Laumann,et al.  Methods to detect, characterize, and remove motion artifact in resting state fMRI , 2014, NeuroImage.

[93]  Joseph V. Hajnal,et al.  A robust method to estimate the intracranial volume across MRI field strengths (1.5T and 3T) , 2010, NeuroImage.

[94]  Steen Moeller,et al.  ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging , 2014, NeuroImage.

[95]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[96]  Sébastien Ourselin,et al.  Brain MAPS: An automated, accurate and robust brain extraction technique using a template library , 2011, NeuroImage.

[97]  A. Sack,et al.  The cross-functional role of frontoparietal regions in cognition: internal attention as the overarching mechanism , 2014, Progress in Neurobiology.

[98]  X. Delbeuck,et al.  Is Alzheimer's disease a disconnection syndrome? Evidence from a crossmodal audio-visual illusory experiment , 2007, Neuropsychologia.

[99]  J. Morris,et al.  The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[100]  E. Bullmore,et al.  Impaired long distance functional connectivity and weighted network architecture in Alzheimer's disease. , 2014, Cerebral cortex.

[101]  H. Uylings,et al.  Neuroscience and Biobehavioral Reviews Parietal Cortex Matters in Alzheimer's Disease: an Overview of Structural, Functional and Metabolic Findings , 2022 .

[102]  R. Petersen,et al.  Mild Cognitive Impairment: An Overview , 2008, CNS Spectrums.

[103]  M. Hamilton A RATING SCALE FOR DEPRESSION , 1960, Journal of neurology, neurosurgery, and psychiatry.

[104]  C. Grady,et al.  Intercorrelations of regional cerebral glucose metabolic rates in Alzheimer's disease , 1987, Brain Research.

[105]  R. Killiany,et al.  Subregions of the inferior parietal lobule are affected in the progression to Alzheimer's disease , 2010, Neurobiology of Aging.

[106]  N. Filippini,et al.  Group comparison of resting-state FMRI data using multi-subject ICA and dual regression , 2009, NeuroImage.

[107]  Francesca Baglio,et al.  High-Dimensional ICA Analysis Detects Within-Network Functional Connectivity Damage of Default-Mode and Sensory-Motor Networks in Alzheimer’s Disease , 2015, Front. Hum. Neurosci..

[108]  Yong He,et al.  Disrupted Functional Brain Connectome in Individuals at Risk for Alzheimer's Disease , 2013, Biological Psychiatry.

[109]  H. Soininen,et al.  MRI of the Hippocampus in Alzheimer’s Disease: Sensitivity, Specificity, and Analysis of the Incorrectly Classified Subjects , 1998, Neurobiology of Aging.

[110]  Koene R. A. Van Dijk,et al.  Accelerated decline in white matter integrity in clinically normal individuals at risk for Alzheimer's disease , 2016, Neurobiology of Aging.

[111]  Daniel L. Rubin,et al.  Network Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease , 2008, PLoS Comput. Biol..

[112]  S. Rombouts,et al.  Loss of ‘Small-World’ Networks in Alzheimer's Disease: Graph Analysis of fMRI Resting-State Functional Connectivity , 2010, PloS one.

[113]  George S Alexopoulos,et al.  Depression in the elderly , 2005, Lancet.

[114]  Lennart Verhagen,et al.  Causal manipulation of functional connectivity in a specific neural pathway during behaviour and at rest , 2015, eLife.

[115]  J. Schneider,et al.  Parahippocampal tau pathology in healthy aging, mild cognitive impairment, and early Alzheimer's disease , 2002, Annals of neurology.

[116]  D. Holtzman,et al.  Neuronal activity regulates extracellular tau in vivo , 2014, The Journal of experimental medicine.