Objective: Cognitive deficits are prominent in schizophrenia. Patients have an average score one standard deviation below normal on a broad spectrum of cognitive tests. It has been repeatedly noted, however, that 20%-25% of patients differ from this general pattern and score close to normal on neuropsychological testing. This study used brain morphometry to 1) identify brain abnormalities associated with more severe cognitive deficits and 2) help determine whether cognitively relatively intact patients perform better because they have less severe illness or because they have a different illness.
Method: Patients were assigned to a neuropsychologically near normal (N=21) subgroup if they scored within 0.5 standard deviation of healthy comparison subjects (N=30) on four tests of attention and verbal and nonverbal working memory, and to a neuropsychologically impaired (N=54) group if they scored at least 1.0 standard deviation below that of comparison subjects. Subgroup assignments were confirmed with the California Verbal Learning Test and degraded-stimulus Continuous Performance Test. Volumes of ventricular compartments, hippocampus, amygdala, thalamus, cerebellum, and regional cortical gray and white matter were dependent variables. Differences among groups were evaluated by using linear mixed-model multivariate analyses with gender, age, and height as covariates.
Results: Both neuropsychologically near normal and neuropsychologically impaired patients had markedly smaller gray matter and larger third ventricle volumes than healthy comparison subjects. Only neuropsychologically impaired patients, however, had significantly smaller white matter and larger lateral ventricle volumes than healthy comparison subjects.
Conclusions: Although both neuropsychologically impaired and neuropsychologically near normal patients have marked neuropathology in their gray matter, the relative absence of white matter pathology in the neuropsychologically near normal group suggests the possibility of differences in the disease process.
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http://dx.doi.org/10.1176/appi.ajp.2008.08020258 | DOI Listing |
Alzheimer Dis Assoc Disord
January 2025
Department of Cognition, Brain & Behavior Lab of Neuropsychology and Behavioral Neuroscience, School of Psychology, Aristotle University of Thessaloniki, Thessaloniki.
Objective: Sleep disturbance is considered a risk factor for cognitive decline in elderly individuals. Our aim in the current study was to investigate whether baseline sleep parameters can predict the conversion from normal cognition to mild cognitive impairment or dementia at follow-up. The Hellenic Longitudinal Investigation of Aging and Diet is a longitudinal population-based study designed to estimate the prevalence and incidence of cognitive decline and dementia in the older Greek population.
View Article and Find Full Text PDFFront Public Health
January 2025
Engineering Research Center of Photoelectric Detection and Perception Technology, Yunnan Normal University, Kunming, China.
The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs. The advent of deep learning in medical diagnosis opens new possibilities for early AD detection. In this study, we introduce retinal vessel segmentation methods based on U-Net ad iterative registration Learning (ReIU), which extract retinal vessel maps from OCT angiography (OCT-A) facilities.
View Article and Find Full Text PDFEur J Neurol
January 2025
AIMS Lab, Center for Neurosciences, Vrije Universiteit Brussel, Elsene, Brussels, Belgium.
Background And Purpose: Cognitive impairment in multiple sclerosis (MS) is common and is associated with problems in employment, driving ability, and quality of life. Since cognitive impairment at time of diagnosis is predictive of disability progression, early assessment and annual monitoring is recommended. The Brief International Cognitive Assessment in Multiple Sclerosis (BICAMS) was introduced as a time-efficient screening tool that can easily be applied in standard clinical care.
View Article and Find Full Text PDFZhonghua Yi Xue Za Zhi
January 2025
Mild cognitive impairment (MCI) is a state of objective cognitive decline that falls between normal aging and dementia, with a high prevalence among the elderly in China. Cognitive impairments in MCI patients involve multiple cognitive domains such as memory, language, attention, executive, visuospatial functions, and social cognition, as well as non-cognitive domains such as neuropsychiatric, mood, sleep, daily living activities, and frailty. The assessment and clinical diagnosis of MCI highly rely on neuropsychological testing.
View Article and Find Full Text PDFAlzheimers Res Ther
January 2025
Department of Neurosciences, University of California, San Diego, La Jolla, CA, 92093-0948, USA.
Background: Effective detection of cognitive impairment in the primary care setting is limited by lack of time and specialized expertise to conduct detailed objective cognitive testing and few well-validated cognitive screening instruments that can be administered and evaluated quickly without expert supervision. We therefore developed a model cognitive screening program to provide relatively brief, objective assessment of a geriatric patient's memory and other cognitive abilities in cases where the primary care physician suspects but is unsure of the presence of a deficit.
Methods: Referred patients were tested during a 40-min session by a psychometrist or trained nurse in the clinic on a brief battery of neuropsychological tests that assessed multiple cognitive domains.
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