Introduction: During the past decades there has been an increasing interest in tracking brain network fluctuations in health and disease by means of resting state functional magnetic resonance imaging (rs-fMRI). Rs-fMRI however does not provide the ideal environmental setting, as participants are continuously exposed to noise generated by MRI coils during acquisition of Echo Planar Imaging (EPI). We investigated the effect of EPI noise on resting state activity and connectivity using magnetoencephalography (MEG), by reproducing the acoustic characteristics of rs-fMRI environment during the recordings. As compared to fMRI, MEG has little sensitivity to brain activity generated in deep brain structures, but has the advantage to capture both the dynamic of cortical magnetic oscillations with high temporal resolution and the slow magnetic fluctuations highly correlated with BOLD signal.
Methods: Thirty healthy subjects were enrolled in a counterbalanced design study including three conditions: a) silent resting state (Silence), b) resting state upon EPI noise (fMRI), and c) resting state upon white noise (White). White noise was employed to test the specificity of fMRI noise effect. The amplitude envelope correlation (AEC) in alpha band measured the connectivity of seven Resting State Networks (RSN) of interest (default mode network, dorsal attention network, language, left and right auditory and left and right sensory-motor). Vigilance dynamic was estimated from power spectral activity.
Results: fMRI and White acoustic noise consistently reduced connectivity of cortical networks. The effects were widespread, but noise and network specificities were also present. For fMRI noise, decreased connectivity was found in the right auditory and sensory-motor networks. Progressive increase of slow theta-delta activity related to drowsiness was found in all conditions, but was significantly higher for fMRI . Theta-delta significantly and positively correlated with variations of cortical connectivity.
Discussion: rs-fMRI connectivity is biased by unavoidable environmental factors during scanning, which warrant more careful control and improved experimental designs. MEG is free from acoustic noise and allows a sensitive estimation of resting state connectivity in cortical areas. Although underutilized, MEG could overcome issues related to noise during fMRI, in particular when investigation of motor and auditory networks is needed.
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http://dx.doi.org/10.1016/j.neuroimage.2021.118791 | DOI Listing |
Int J Geriatr Psychiatry
January 2025
Precision Neuroscience & Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Background: Alzheimer's disease (AD) is characterized by impaired inhibitory circuitry and GABAergic dysfunction, which is associated with reduced fast brain oscillations in the gamma band (γ, 30-90 Hz) in several animal models. Investigating such activity in human patients could lead to the identification of novel biomarkers of diagnostic and prognostic value. The current study aimed to test a multimodal "Perturbation-based" transcranial Alternating Current Stimulation-Electroencephalography (tACS)-EEG protocol to detect how responses to tACS in AD patients correlate with patients' clinical phenotype.
View Article and Find Full Text PDFSchizophrenia (Heidelb)
January 2025
Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA.
Psychogenic erectile dysfunction (pED) is often accompanied by abnormal brain activities. This study aimed to develop an automaticclassifier to distinguish pED from healthy controls (HCs) by identified brain-basedcharacteristics. Resting-state functional magnetic resonance imaging data were acquired from 45 pED patients and 43 HCs.
View Article and Find Full Text PDFBiol 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 PDFBiol Psychiatry
January 2025
Department of Neuroscience, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA; Department of Behavioral Medicine and Psychiatry, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA. Electronic address:
Background: Opioid use disorder remains a critical healthcare challenge as current therapeutic strategies have limitations resulting in high recurrence and deaths. We evaluated safety and feasibility of focused ultrasound (FUS) neuromodulation to reduce substance cravings and use in severe opioid- and co-occurring substance use disorders.
Methods: This prospective, open-label, single-arm study enrolled 8 participants with severe, primary opioid use disorder with co-occurring substance use.
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