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Aleksic S, Fleysher R, Weiss EF, Tal N, Darby T, Blumen HM, Vazquez J, Ye KQ, Gao T, Siegel SM, Barzilai N, Lipton ML, Milman S. Hypothalamic MRI-derived microstructure is associated with neurocognitive aging in humans. Neurobiol Aging 2024; 141:102-112. [PMID: 38850591 DOI: 10.1016/j.neurobiolaging.2024.05.018] [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: 08/08/2023] [Revised: 05/17/2024] [Accepted: 05/31/2024] [Indexed: 06/10/2024]
Abstract
The hypothalamus regulates homeostasis across the lifespan and is emerging as a regulator of aging. In murine models, aging-related changes in the hypothalamus, including microinflammation and gliosis, promote accelerated neurocognitive decline. We investigated relationships between hypothalamic microstructure and features of neurocognitive aging, including cortical thickness and cognition, in a cohort of community-dwelling older adults (age range 65-97 years, n=124). Hypothalamic microstructure was evaluated with two magnetic resonance imaging diffusion metrics: mean diffusivity (MD) and fractional anisotropy (FA), using a novel image processing pipeline. Hypothalamic MD was cross-sectionally positively associated with age and it was negatively associated with cortical thickness. Hypothalamic FA, independent of cortical thickness, was cross-sectionally positively associated with neurocognitive scores. An exploratory analysis of longitudinal neurocognitive performance suggested that lower hypothalamic FA may predict cognitive decline. No associations between hypothalamic MD, age, and cortical thickness were identified in a younger control cohort (age range 18-63 years, n=99). To our knowledge, this is the first study to demonstrate that hypothalamic microstructure is associated with features of neurocognitive aging in humans.
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Affiliation(s)
- Sandra Aleksic
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States.
| | - Roman Fleysher
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States; Department of Radiology, Albert Einstein College of Medicine, Gruss Magnetic Resonance Research Center, Bronx, NY, United States
| | - Erica F Weiss
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Noa Tal
- Department of Medicine, Cedars-Sinai, Los Angeles, CA, United States
| | - Timothy Darby
- Albert Einstein College of Medicine, Bronx, NY, United States
| | - Helena M Blumen
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Medicine, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Juan Vazquez
- Department of Internal Medicine, John Hopkins University, Baltimore, MD, United States
| | - Kenny Q Ye
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Tina Gao
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Shira M Siegel
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States
| | - Nir Barzilai
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Michael L Lipton
- Department of Radiology, Columbia University Irving Medical Center, New York, NY, United States; Department of Biomedical Engineering, Columbia University, New York, NY, United States
| | - Sofiya Milman
- Department of Medicine, Institute for Aging Research, Albert Einstein College of Medicine, Bronx, NY, United States; Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, United States
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Carson RG, Berdondini D, Crosbie M, McConville C, Forbes S, Stewart M, Chiu RZX. Deficits in force production during multifinger tasks demarcate cognitive dysfunction. Aging Clin Exp Res 2024; 36:87. [PMID: 38578525 PMCID: PMC10997684 DOI: 10.1007/s40520-024-02723-9] [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: 07/20/2023] [Accepted: 02/08/2024] [Indexed: 04/06/2024]
Abstract
BACKGROUND The multifinger force deficit (MFFD) is the decline in force generated by each finger as the number of fingers contributing to an action is increased. It has been shown to associate with cognitive status. AIMS The aim was to establish whether a particularly challenging form of multifinger grip dynamometry, that provides minimal tactile feedback via cutaneous receptors and requires active compensation for reaction forces, will yield an MFFD that is more sensitive to cognitive status. METHODS Associations between measures of motor function, and cognitive status (Montreal Cognitive Assessment [MoCA]) and latent components of cognitive function (derived from 11 tests using principal component analysis), were estimated cross-sectionally using generalized partial rank correlations. The participants (n = 62) were community dwelling, aged 65-87. RESULTS Approximately half the participants were unable to complete the dynamometry task successfully. Cognitive status demarcated individuals who could perform the task from those who could not. Among those who complied with the task requirements, the MFFD was negatively correlated with MoCA scores-those with the highest MoCA scores tended to exhibit the smallest deficits, and vice versa. There were corresponding associations with latent components of cognitive function. DISCUSSION The results support the view that neurodegenerative processes that are a feature of normal and pathological aging exert corresponding effects on expressions of motor coordination-in multifinger tasks, and cognitive sufficiency, due to their dependence on shared neural systems. CONCLUSIONS The outcomes add weight to the assertion that deficits in force production during multifinger tasks are sensitive to cognitive dysfunction.
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Affiliation(s)
- Richard G Carson
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland.
- School of Psychology, Queen's University Belfast, Belfast, Northern Ireland, UK.
| | - Debora Berdondini
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland
| | - Maebh Crosbie
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin 2, Ireland
| | - Caoilan McConville
- School of Psychology, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Shannon Forbes
- School of Psychology, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Marla Stewart
- School of Psychology, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Ruth Zhi Xian Chiu
- School of Psychology, Queen's University Belfast, Belfast, Northern Ireland, UK
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Hall MG, Wollman SC, Haines ME, Katschke JL, Boyle MA, Richardson HK, Hammers DB. Clinical validation of an aggregate learning ratio from the neuropsychological assessment battery. APPLIED NEUROPSYCHOLOGY. ADULT 2024:1-10. [PMID: 38527375 DOI: 10.1080/23279095.2024.2329974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Quantifying learning deficits provides valuable information in identifying and diagnosing mild cognitive impairment and dementia. Previous research has found that a learning ratio (LR) metric, derived from the list learning test from the Neuropsychological Assessment Battery (NAB), was able to distinguish between those with normal cognition versus memory impairment. The current study furthers the NAB LR research by validating a NAB story LR, as well as an aggregate LR. The aggregate LR was created by combining the individual list and story LRs. Participants were classified as those with normal cognition (n = 51), those with MCI (n = 39) and those with dementia (n = 35). Results revealed the story LR was able to accurately distinguish normal controls from those with mild cognitive impairment and those with dementia and offers enhanced discriminability beyond the story immediate recall score (sum of trial 1 and trial 2). Further, the aggregate LR provided superior discriminability beyond the individual list and story LRs and accounted for additional variance in diagnostic group classification. The NAB aggregate LR provides improved sensitivity in detecting declines in impaired learning, which may assist clinicians in making diagnoses earlier in a disease process, benefiting the individual through earlier interventions.
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Affiliation(s)
- Matthew G Hall
- PM&R, The University of Toledo - Health Science Campus, Toledo, OH, USA
| | | | - Mary E Haines
- PM&R, The University of Toledo - Health Science Campus, Toledo, OH, USA
| | | | - Mellisa A Boyle
- PM&R, The University of Toledo - Health Science Campus, Toledo, OH, USA
| | | | - Dustin B Hammers
- Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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Chang M, Brainerd CJ. Predicting conversion from mild cognitive impairment to Alzheimer's disease with multimodal latent factors. J Clin Exp Neuropsychol 2022; 44:316-335. [PMID: 36036715 DOI: 10.1080/13803395.2022.2115015] [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: 10/15/2022]
Abstract
INTRODUCTION We studied the ability of latent factor scores to predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and investigated whether multimodal factor scores improve predictive power, relative to single-modal factor scores. METHOD We conducted exploratory factor analyses (EFAs) and confirmatory factor analyses (CFAs) of the baseline data of MCI subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) to generate factor scores for three data modalities: neuropsychological (NP), magnetic resonance imaging (MRI), and cerebrospinal fluid (CSF). Factor scores from single or multiple modalities were entered in logistic regression models to predict MCI to AD conversion for 160 ADNI subjects over a 2-year interval. RESULTS NP factors attained an area under the curve (AUC) of .80, with a sensitivity of .66 and a specificity of .77. MRI factors reached a comparable level of performance (AUC = .80, sensitivity = .66, specificity = .78), whereas CSF factors produced weaker prediction (AUC = .70, sensitivity = .56, specificity = .79). Combining NP factors with MRI or CSF factors produced better prediction than either MRI or CSF factors alone. Similarly, adding MRI factors to NP or CSF factors produced improvements in prediction relative to NP or CSF factors alone. However, adding CSF factors to either NP or MRI factors produced no improvement in prediction. CONCLUSIONS Latent factor scores provided good accuracy for predicting MCI to AD conversion. Adding NP or MRI factors to factors from other modalities enhanced predictive power but adding CSF factors did not.
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Affiliation(s)
- Minyu Chang
- Department of Psychology and Human Neuroscience Institute, Cornell University, Ithaca, New York, USA
| | - C J Brainerd
- Department of Psychology and Human Neuroscience Institute, Cornell University, Ithaca, New York, USA
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Duran T, Woo E, Otero D, Risacher SL, Stage E, Sanjay AB, Nho K, West JD, Phillips ML, Goukasian N, Hwang KS, Apostolova LG. Associations between Cortical Thickness and Metamemory in Alzheimer’s Disease. Brain Imaging Behav 2022; 16:1495-1503. [PMID: 35064438 PMCID: PMC9450553 DOI: 10.1007/s11682-021-00627-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/21/2021] [Indexed: 12/27/2022]
Abstract
Metacognitive deficits affect Alzheimer's disease (AD) patient safety and increase caregiver burden. The brain areas that support metacognition are not well understood. 112 participants from the Imaging and Genetic Biomarkers for AD (ImaGene) study underwent comprehensive cognitive testing and brain magnetic resonance imaging. A performance-prediction paradigm was used to evaluate metacognitive abilities for California Verbal Learning Test-II learning (CVLT-II 1-5) and delayed recall (CVLT-II DR); Visual Reproduction-I immediate recall (VR-I Copy) and Visual Reproduction-II delayed recall (VR-II DR); Rey-Osterrieth Complex Figure Copy (Rey-O Copy) and delayed recall (Rey-O DR). Vertex-wise multivariable regression of cortical thickness was performed using metacognitive scores as predictors while controlling for age, sex, education, and intracranial volume. Subjects who overestimated CVLT-II DR in prediction showed cortical atrophy, most pronounced in the bilateral temporal and left greater than right (L > R) frontal cortices. Overestimation of CVLT-II 1-5 prediction and DR performance in postdiction showed L > R associations with medial, inferior and lateral temporal and left posterior cingulate cortical atrophy. Overconfident prediction of VR-I Copy performance was associated with right greater than left medial, inferior and lateral temporal, lateral parietal, anterior and posterior cingulate and lateral frontal cortical atrophy. Underestimation of Rey-O Copy performance in prediction was associated with atrophy localizing to the temporal and cingulate areas, and in postdiction, with diffuse cortical atrophy. Impaired metacognition was associated to cortical atrophy. Our results indicate that poor insight into one's cognitive abilities is a pervasive neurodegenerative feature associated with AD across the cognitive spectrum.
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Affiliation(s)
- Tugce Duran
- Department of Internal Medicine-Section of Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, 525 Vine Street, Suite 150, Winston-Salem, NC, 27101, USA.
| | - Ellen Woo
- Department of Psychology, California State University, Fresno, Fresno, CA, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA
| | - Diana Otero
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Department of Radiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Eddie Stage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Apoorva B Sanjay
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik Nho
- Department of Radiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - John D West
- Department of Radiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Meredith L Phillips
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
| | - Naira Goukasian
- Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Kristy S Hwang
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology, Indiana University School of Medicine, Indianapolis, IN, USA
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Nayar K, Ventura LM, DeDios-Stern S, Oh A, Soble JR. The Impact of Learning and Memory on Performance Validity Tests in a Mixed Clinical Pediatric Population. Arch Clin Neuropsychol 2021; 37:50-62. [PMID: 34050354 DOI: 10.1093/arclin/acab040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2021] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE This study examined the degree to which verbal and visuospatial memory abilities influence performance validity test (PVT) performance in a mixed clinical pediatric sample. METHOD Data from 252 consecutive clinical pediatric cases (Mage=11.23 years, SD=4.02; 61.9% male) seen for outpatient neuropsychological assessment were collected. Measures of learning and memory (e.g., The California Verbal Learning Test-Children's Version; Child and Adolescent Memory Profile [ChAMP]), performance validity (Test of Memory Malingering Trial 1 [TOMM T1]; Wechsler Intelligence Scale for Children-Fifth Edition [WISC-V] or Wechsler Adult Intelligence Scale-Fourth Edition Digit Span indices; ChAMP Overall Validity Index), and intellectual abilities (e.g., WISC-V) were included. RESULTS Learning/memory abilities were not significantly correlated with TOMM T1 and accounted for relatively little variance in overall TOMM T1 performance (i.e., ≤6%). Conversely, ChAMP Validity Index scores were significantly correlated with verbal and visual learning/memory abilities, and learning/memory accounted for significant variance in PVT performance (12%-26%). Verbal learning/memory performance accounted for 5%-16% of the variance across the Digit Span PVTs. No significant differences in TOMM T1 and Digit Span PVT scores emerged between verbal/visual learning/memory impairment groups. ChAMP validity scores were lower for the visual learning/memory impairment group relative to the nonimpaired group. CONCLUSIONS Findings highlight the utility of including PVTs as standard practice for pediatric populations, particularly when memory is a concern. Consistent with the adult literature, TOMM T1 outperformed other PVTs in its utility even among the diverse clinical sample with/without learning/memory impairment. In contrast, use of Digit Span indices appear to be best suited in the presence of visuospatial (but not verbal) learning/memory concerns. Finally, the ChAMP's embedded validity measure was most strongly impacted by learning/memory performance.
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Affiliation(s)
- Kritika Nayar
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Lea M Ventura
- Department of Psychiatry, University of Illinois College of Medicine, Chicago, IL, USA.,Department of Pediatrics, University of Illinois College of Medicine, Chicago, IL, USA
| | - Samantha DeDios-Stern
- Department of Psychiatry, University of Illinois College of Medicine, Chicago, IL, USA
| | - Alison Oh
- Department of Psychiatry, University of Illinois College of Medicine, Chicago, IL, USA
| | - Jason R Soble
- Department of Psychiatry, University of Illinois College of Medicine, Chicago, IL, USA.,Department of Neurology, University of Illinois College of Medicine, Chicago, IL, USA
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Lee JY, Lee YA, Yoo MS. Development of the child's ego strength scale: an observation-based assessment of the board game behaviors in play therapy in Korea. Child Adolesc Psychiatry Ment Health 2021; 15:20. [PMID: 33865431 PMCID: PMC8053275 DOI: 10.1186/s13034-021-00369-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 03/23/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The purpose of this study was to develop a scale for assessing children's ego strength through the observation of children playing board games in a therapeutic setting. Because ego strength is an index of psychosocial health, it is important to assess ego strength in childhood. In particular, children aged 7 to 9 exhibit their ego-strength characteristics in a situation challenged by self-competence due to their latency period. Therapists can identify such ego strength through game behaviors of children aged 7 to 9 in the play therapy setting. Thus, it is needed to develop a scale by selecting game play behaviors that grasp ego-strength. METHOD Data were collected from 127 play therapists and play therapist-supervisors, who observed 468 play therapy sessions and 55 children aged 7-9 who received play therapy in Korea. The scale was created through content validity verification, factor analysis and verification of criterion-related validity. RESULTS We generated a Child's Ego Strength Scale (CESS) consisting of five sub-factors (Coping Strategy, Cognitive Strategy, Ego Restriction, Interpersonal Functioning, Frustration Tolerance) through exploratory factor analysis. The scale met the goodness of fit criteria in a confirmatory factor analysis. The analysis of therapy sessions of children with strong and weak ego strength, as identified by play therapists, showed a significant difference between the two groups in all five sub-variables. There was a significant correlation between the CESS scores and scores of ego strength-related variables of the Rorschach scale, indicating good criterion-related validity. CONCLUSION The CESS appears to be a practical method for the assessment of ego strength in the field of child counseling.
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Affiliation(s)
- Ji Yoen Lee
- grid.412670.60000 0001 0729 3748Graduate School of Psychotherapy, Play Therapy, Sookmyung Women’s University, 100 Cheongpa-ro 47-gil, Youngsan-gu, Seoul, 04310 Korea
| | - Young-ae Lee
- grid.412670.60000 0001 0729 3748Graduate School of Psychotherapy, Play Therapy, Sookmyung Women’s University, 100 Cheongpa-ro 47-gil, Youngsan-gu, Seoul, 04310 Korea
| | - Mee Sook Yoo
- grid.412670.60000 0001 0729 3748Department of Child Welfare and Studies, Sookmyung Women’s University, 100 Cheongpa-ro 47-gil, Youngsan-gu, Seoul, 04310 Korea
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Abstract
Males and females are subject to differences in cognitive processing strategies, i.e. the way males and females solve cognitive tasks. So far primarily reported for younger adults, this seems to be especially important in older adults, who also show sex differences in cognitive impairments. Therefore, the aim of the current study was to examine the older adult population with respect to cognitive profiles derived from a large variety of cognitive functions. Using an exploratory component analysis with consecutive confirmatory factor analysis in a sample of 676 older adults, neuropsychological performance data in a variety of cognitive domains was decomposed into cognitive components. A general cognitive profile based on the whole group fits unequally well on the two sexes. Importantly, cognitive profiles based on either males or females differ in terms of their composition of cognitive components, i.e. three components in males versus four components in females, with a generally better model fit in females. Thus, related to the established differences in processing styles between males and females the current study found a rather decomposed (or local) cognitive profile in females while males seem to show a holistic (or global) cognitive profile, with more interrelations between different cognitive functions.
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Choi S, Mukherjee S, Gibbons LE, Sanders RE, Jones RN, Tommet D, Mez J, Trittschuh EH, Saykin A, Lamar M, Rabin L, Foldi NS, Sikkes S, Jutten RJ, Grandoit E, Mac Donald C, Risacher S, Groot C, Ossenkoppele R, Crane PK. Development and validation of language and visuospatial composite scores in ADNI. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2020; 6:e12072. [PMID: 33313380 PMCID: PMC7718716 DOI: 10.1002/trc2.12072] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 07/28/2020] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Composite scores may be useful to summarize overall language or visuospatial functioning in studies of older adults. METHODS We used item response theory to derive composite measures for language (ADNI-Lan) and visuospatial functioning (ADNI-VS) from the cognitive battery administered in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We evaluated the scores among groups of people with normal cognition, mild cognitive impairment (MCI), and Alzheimer's disease (AD) in terms of responsiveness to change, association with imaging findings, and ability to differentiate between MCI participants who progressed to AD dementia and those who did not progress. RESULTS ADNI-Lan and ADNI-VS were able to detect change over time and predict conversion from MCI to AD. They were associated with most of the pre-specified magnetic resonance imaging measures. ADNI-Lan had strong associations with a cerebrospinal fluid biomarker pattern. DISCUSSION ADNI-Lan and ADNI-VS may be useful composites for language and visuospatial functioning in ADNI.
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Affiliation(s)
- Seo‐Eun Choi
- Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | | | - Laura E. Gibbons
- Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | | | - Richard N. Jones
- Department of NeurologyBrown UniversityProvidenceRhode IslandUSA
| | - Douglas Tommet
- Department of NeurologyBrown UniversityProvidenceRhode IslandUSA
| | - Jesse Mez
- Department of NeurologyBoston UniversityBostonMassachusettsUSA
| | - Emily H. Trittschuh
- Department of PsychiatryUniversity of WashingtonSeattleWashingtonUSA
- Puget Sound Veterans AdministrationGeriatric Research Education and Clinical CenterVA Puget Sound Health Care SystemSeattleWashingtonUSA
| | - Andrew Saykin
- Department of Radiology and Alzheimer's Research CenterIndiana UniversityIndianapolisIndianaUSA
| | - Melissa Lamar
- Rush Alzheimer's Disease Center and Department of Behavioral Sciences and PsychiatryRush University Medical CenterChicagoIllinoisUSA
| | - Laura Rabin
- Department of PsychologyCity University of New York–BrooklynNew YorkUSA
| | - Nancy S. Foldi
- Department of PsychologyCity University of New York–Queens CollegeNew YorkUSA
| | - Sietske Sikkes
- Alzheimer CenterAmsterdam UMC ‐ VU University Medical CenterAmsterdamthe Netherlands
| | - Roos J. Jutten
- Alzheimer CenterAmsterdam UMC ‐ VU University Medical CenterAmsterdamthe Netherlands
| | - Evan Grandoit
- Department of PsychologyNorthwestern UniversityEvanstonIllinoisUSA
| | | | - Shannon Risacher
- Department of Radiology and Alzheimer's Research CenterIndiana UniversityIndianapolisIndianaUSA
| | - Colin Groot
- Alzheimer CenterAmsterdam UMC ‐ VU University Medical CenterAmsterdamthe Netherlands
| | - Rik Ossenkoppele
- Alzheimer CenterAmsterdam UMC ‐ VU University Medical CenterAmsterdamthe Netherlands
- Clinical Memory Research UnitLund UniversityLundSweden
| | | | - Paul K. Crane
- Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
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Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2020; 2020:8915961. [PMID: 32549888 PMCID: PMC7256687 DOI: 10.1155/2020/8915961] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 05/06/2020] [Indexed: 12/20/2022]
Abstract
Cognitive decline is a severe concern of patients with mild cognitive impairment. Also, in patients with temporal lobe epilepsy, memory problems are a frequently encountered problem with potential progression. On the background of a unifying hypothesis for cognitive decline, we merged knowledge from dementia and epilepsy research in order to identify biomarkers with a high predictive value for cognitive decline across and beyond these groups that can be fed into intelligent systems. We prospectively assessed patients with temporal lobe epilepsy (N = 9), mild cognitive impairment (N = 19), and subjective cognitive complaints (N = 4) and healthy controls (N = 18). All had structural cerebral MRI, EEG at rest and during declarative verbal memory performance, and a neuropsychological assessment which was repeated after 18 months. Cognitive decline was defined as significant change on neuropsychological subscales. We extracted volumetric and shape features from MRI and brain network measures from EEG and fed these features alongside a baseline testing in neuropsychology into a machine learning framework with feature subset selection and 5-fold cross validation. Out of 50 patients, 27 had a decline over time in executive functions, 23 in visual-verbal memory, 23 in divided attention, and 7 patients had an increase in depression scores. The best sensitivity/specificity for decline was 72%/82% for executive functions based on a feature combination from MRI volumetry and EEG partial coherence during recall of memories; 95%/74% for visual-verbal memory by combination of MRI-wavelet features and neuropsychology; 84%/76% for divided attention by combination of MRI-wavelet features and neuropsychology; and 81%/90% for increase of depression by combination of EEG partial directed coherence factor at rest and neuropsychology. Combining information from EEG, MRI, and neuropsychology in order to predict neuropsychological changes in a heterogeneous population could create a more general model of cognitive performance decline.
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Goukasian N, Porat S, Blanken A, Avila D, Zlatev D, Hurtz S, Hwang KS, Pierce J, Joshi SH, Woo E, Apostolova LG. Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment. Dement Geriatr Cogn Dis Extra 2019; 9:281-293. [PMID: 31572424 PMCID: PMC6751474 DOI: 10.1159/000490044] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Accepted: 05/15/2018] [Indexed: 12/25/2022] Open
Abstract
We analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors.
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Affiliation(s)
- Naira Goukasian
- University of Vermont, Larner College of Medicine, Burlington, Vermont, USA
| | - Shai Porat
- Department of Psychology, University of Southern California, Los Angeles, California, USA
| | - Anna Blanken
- Department of Psychology, University of Southern California, Los Angeles, California, USA
| | - David Avila
- Irvine School of Medicine, University of California, Irvine, California, USA
| | - Dimitar Zlatev
- Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sona Hurtz
- Drexel University College of Medicine, Philadelphia, Pennsylvania, USA
| | - Kristy S Hwang
- Emory University School of Medicine, Atlanta, Georgia, USA
| | - Jonathan Pierce
- Department of Neurology, University of California, Los Angeles, California, USA
| | - Shantanu H Joshi
- Department of Neurology, University of California, Los Angeles, California, USA
| | - Ellen Woo
- Department of Neurology, University of California, Los Angeles, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.,Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
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