Journal Article FZJ-2022-00874

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Test–retest stability of spontaneous brain activity and functional connectivity in the core resting‐state networks assessed with ultrahigh field 7‐Tesla resting‐state functional magnetic resonance imaging

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2022
Wiley-Liss New York, NY

Human brain mapping 43(6), 2026-2040 () [10.1002/hbm.25771]

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Abstract: The growing demand for precise and reliable biomarkers in psychiatry is fueling research interest in the hope that identifying quantifiable indicators will improve diagnoses and treatment planning across a range of mental health conditions. The individual properties of brain networks at rest have been highlighted as a possible source for such biomarkers, with the added advantage that they are relatively straightforward to obtain. However, an important prerequisite for their consideration is their reproducibility. While the reliability of resting-state (RS) measurements has often been studied at standard field strengths, they have rarely been investigated using ultrahigh-field (UHF) magnetic resonance imaging (MRI) systems. We investigated the intersession stability of four functional MRI RS parameters—amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF; representing the spontaneous brain activity), regional homogeneity (ReHo; measure of local connectivity), and degree centrality (DC; measure of long-range connectivity)—in three RS networks, previously shown to play an important role in several psychiatric diseases—the default mode network (DMN), the central executive network (CEN), and the salience network (SN). Our investigation at individual subject space revealed a strong stability for ALFF, ReHo, and DC in all three networks, and a moderate level of stability in fALFF. Furthermore, the internetwork connectivity between each network pair was strongly stable between CEN/SN and moderately stable between DMN/SN and DMN/SN. The high degree of reliability and reproducibility in capturing the properties of the three major RS networks by means of UHF-MRI points to its applicability as a potentially useful tool in the search for disease-relevant biomarkers.

Classification:

Contributing Institute(s):
  1. Physik der Medizinischen Bildgebung (INM-4)
  2. Jara-Institut Quantum Information (INM-11)
  3. Jülich-Aachen Research Alliance - Translational Brain Medicine (JARA-BRAIN)
Research Program(s):
  1. 5253 - Neuroimaging (POF4-525) (POF4-525)

Appears in the scientific report 2022
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 Record created 2022-01-20, last modified 2023-02-23