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Background: Amnestic mild cognitive impairment (aMCI) is a transitional state between normal aging and dementia, and identifying early biomarkers is crucial for disease detection and intervention. Functional magnetic resonance imaging (fMRI) has the potential to identify changes in neural activity in MCI.
Methods: We investigated neural activity changes in the visual network of the aMCI patients (n:20) and healthy persons (n:17) using resting-state fMRI and visual oddball task fMRI. We used independent component analysis to identify regions of interest and compared the activity between groups using a false discovery rate correction.
Results: Resting-state fMRI revealed increased activity in the areas that have functional connectivity with the visual network, including the right superior and inferior lateral occipital cortex, the right angular gyrus and the temporo-occipital part of the right middle temporal gyrus (p-FDR = 0.008) and decreased activity in the bilateral thalamus and caudate nuclei, which are part of the frontoparietal network in the aMCI group (p-FDR = 0.002). In the visual oddball task fMRI, decreased activity was found in the right frontal pole, the right frontal orbital cortex, the left superior parietal lobule, the right postcentral gyrus, the right posterior part of the supramarginal gyrus, the right superior part of the lateral occipital cortex, and the right angular gyrus in the aMCI group.
Conclusion: Our results suggest the alterations in the visual network are present in aMCI patients, both during resting-state and task-based fMRI. These changes may represent early biomarkers of aMCI and highlight the importance of assessing visual processing in cognitive impairment. However, future studies with larger sample sizes and longitudinal designs are needed to confirm these findings.
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http://dx.doi.org/10.1111/cns.14371 | DOI Listing |
PLoS Comput Biol
September 2025
Faculty of Science, Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.
Predictive coding (PC) proposes that our brains work as an inference machine, generating an internal model of the world and minimizing predictions errors (i.e., differences between external sensory evidence and internal prediction signals).
View Article and Find Full Text PDFFront Psychol
August 2025
Department of Psychology, University of South Florida, Tampa, Fl, United States.
Background: Attention regulation is crucial for mindfulness practice; however, the influence of baseline attention ability on mindfulness training outcomes remains underexplored. This study examined the effects of a brief mindfulness intervention on attention and investigated whether baseline inattention symptoms moderated these effects in meditation-naïve university students.
Methods: This study employed a pretest-posttest, between-groups experimental design.
Cureus
July 2025
Paediatrics, All India Institute of Medical Sciences, Patna, IND.
Background P300 event-related potential (ERP) has been used to assess differences in modes of information processing and cognitive skill from childhood through adulthood. However, research on the development of the visual P300 is relatively sparse, with several discrepant findings. In this study, we aimed to evaluate the conventional parameters of visual ERPs and their relationship with mean response time in children and adolescents.
View Article and Find Full Text PDFCommun Biol
August 2025
Department of Neurosciences, KU Leuven, Leuven, Belgium.
Nonpharmaceutical approaches based on gamma entrainment using sensory stimuli (GENUS) have shown promise in reducing Alzheimer's disease pathology in mouse models. While human studies remain limited, GENUS has been shown to alleviate aspects of neurodegeneration in patients with Alzheimer's disease. In this study, we analyze intracranial EEG data from 490 contacts across eleven patients with refractory epilepsy in response to three visual stimulation conditions.
View Article and Find Full Text PDFJ Geriatr Psychiatry Neurol
August 2025
Department of Neurosciences, Institute of Health Sciences, Dokuz Eylül University, Izmir, Turkey.
BackgroundLate-life depression often co-occurs with neurological disorders such as dementia, significantly impacting cognitive function and overall well-being. Mild cognitive impairment represents a critical stage between normal aging and dementia, often accompanied by depressive symptoms. Electroencephalography (EEG) offers a non-invasive method to investigate underlying neural mechanisms associated with depressive symptoms and cognitive dysfunction.
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