Disruptions to functional connectivity in subsystems of the default mode network are evident in Alzheimer's disease (AD). Functional connectivity estimates correlations in the time course of low-frequency activity. Much less is known about other potential perturbations to this activity, such as changes in the amplitude of oscillations and how this relates to cognition. We examined the amplitude of low-frequency fluctuations in 44 AD patients and 128 cognitively normal participants and related this to episodic memory, the core deficit in AD. We show higher amplitudes of low-frequency oscillations in AD patients. Rather than being compensatory, this appears to be maladaptive, with greater amplitude in the ventral default mode subnetwork associated with poorer episodic memory. Perturbations to default mode subnetworks in AD are evident in the amplitude of low-frequency oscillations in the resting brain. These disruptions are associated with episodic memory demonstrating their behavioral and clinical relevance in AD.
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http://dx.doi.org/10.1016/j.neurobiolaging.2017.07.011 | DOI Listing |
Am J Geriatr Psychiatry
December 2024
Department of Clinical and Experimental Sciences (DA, BB), University of Brescia, Brescia, Italy; Molecular Markers Laboratory (BB), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy. Electronic address:
Objectives: The present study aims to assess the prevalence, associated clinical symptoms, longitudinal changes, and imaging correlates of Loss of Insight (LOI), which is still unexplored in syndromes associated with Frontotemporal Lobar Degeneration (FTLD).
Design: Retrospective longitudinal cohort study, from Oct 2009 to Feb 2023.
Setting: Tertiary Frontotemporal Dementia research clinic.
Biol Psychiatry Cogn Neurosci Neuroimaging
January 2025
Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Brain and Cognitive Science at the McGovern Institute for Brain Research at Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Psychology, Northeastern University. Electronic address:
The default mode network (DMN) is intricately linked with processes such as self-referential thinking, episodic memory recall, goal-directed cognition, self-projection, and theory of mind. Over recent years, there has been a surge in examining its functional connectivity, particularly its relationship with frontoparietal networks (FPN) involved in top-down attention, executive function, and cognitive control. The fluidity in switching between these internal and external modes of processing-highlighted by anti-correlated functional connectivity-has been proposed as an indicator of cognitive health.
View Article and Find Full Text PDFCommun Biol
January 2025
FrontLab, Institut du Cerveau - Paris Brain Institute - ICM, INSERM, CNRS, Hôpital de la Pitié Salpêtrière, AP-HP, Sorbonne University, Paris, France.
Creative thinking involves the evaluation of one's ideas in order to select the best one, but the cognitive and neural mechanisms underlying this evaluation remain unclear. Using a combination of creativity and rating tasks, this study demonstrates that individuals attribute subjective values to their ideas, as a relative balance of their originality and adequacy. This relative balance depends on individual preferences and predicts individuals' creative abilities.
View Article and Find Full Text PDFBiol Psychol
January 2025
De(p)artment of Educational Psychology and Counseling, National Taiwan Normal University, Taipei 10610, Taiwan; Institute for Research Excellence in Learning Sciences, National Taiwan Normal University, Taipei 10610, Taiwan; Chinese Language and Technology Center, National Taiwan Normal University, Taipei 10610, Taiwan; Social Emotional Education and Development Center, National Taiwan Normal University, Taipei 10610, Taiwan. Electronic address:
Research on how functional connectivity (FC) during resting-state relates to humor styles and sex is limited. This study aimed to address this knowledge gap by analyzing resting-state fMRI data from 56 healthy participants and measuring FC. In addition, participants completed the Humor Styles Questionnaire.
View Article and Find Full Text PDFJ Headache Pain
January 2025
Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagnostic model for migraine. In this study, we aimed to integrate different types of magnetic resonance imaging (MRI), providing structural and functional information, and develop a robust machine learning model that classifies migraine patients from healthy controls by testing multiple combinations of hyperparameters to ensure stability across different migraine phases and longitudinally repeated data. Specifically, we constructed a diagnostic model to classify patients with episodic migraine from healthy controls, and validated its performance across ictal and interictal phases, as well as in a longitudinal setting.
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