Towards data-driven group inferences of resting-state fMRI data in rodents: Comparison of group ICA, GIG-ICA, and IVA-GL

Scanning ultrasound-mediated memory and functional improvements do not require amyloid-β reduction

A prevalent view in treating age-dependent disorders including Alzheimer's disease (AD) is that the underlying amyloid plaque pathology must be targeted for cognitive improvements. In contrast, we report here that repeated scanning ultrasound (SUS) treatment at 1 MHz frequency can ameliorate memory deficits in the APP23 mouse model of AD without reducing amyloid-β (Aβ) burden. Different from previous studies that had shown Aβ clearance as a consequence of blood-brain barrier (BBB) opening, here, the BBB was not opened as no microbubbles were used. Quantitative SWATH proteomics and functional magnetic resonance imaging revealed that ultrasound induced long-lasting functional changes that correlate with the improvement in memory. Intriguingly, the treatment was more effective at a higher frequency (1 MHz) than at a frequency within the range currently explored in clinical trials in AD patients (286 kHz). Together, our data suggest frequency-dependent bio-effects of ultrasound and a dissociation of cognitive improvement and Aβ clearance, with important implications for the design of trials for AD therapies.

Identification of Alzheimer’s Disease Progression Stages Using Topological Measures of Resting-State Functional Connectivity Networks: A Comparative Study

Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely employed to examine brain functional connectivity (FC) alterations in various neurological disorders. At present, various computational methods have been proposed to estimate connectivity strength between different brain regions, as the edge weight of FC networks. However, little is known about which model is more sensitive to Alzheimer's disease (AD) progression. This study comparatively characterized topological properties of rs-FC networks constructed with Pearson correlation (PC), dynamic time warping (DTW), and group information guided independent component analysis (GIG-ICA), aimed at investigating the sensitivity and effectivity of these methods in differentiating AD stages. A total of 54 subjects from Alzheimer's Disease Neuroimaging Initiative (ANDI) database, divided into healthy control (HC), mild cognition impairment (MCI), and AD groups, were included in this study. Network-level (global efficiency and characteristic path length) and nodal (clustering coefficient) metrics were used to capture groupwise difference across HC, MCI, and AD groups. The results showed that almost no significant differences were found according to global efficiency and characteristic path length. However, in terms of clustering coefficient, 52 brain parcels sensitive to AD progression were identified in rs-FC networks built with GIG-ICA, much more than PC (6 parcels) and DTW (3 parcels). This indicates that GIG-ICA is more sensitive to AD progression than PC and DTW. The findings also confirmed that the AD-linked FC alterations mostly appeared in temporal, cingulate, and angular areas, which might contribute to clinical diagnosis of AD. Overall, this study provides insights into the topological properties of rs-FC networks over AD progression, suggesting that FC strength estimation of FC networks cannot be neglected in AD-related graph analysis.

Chemogenetic stimulation of tonic locus coeruleus activity strengthens the default mode network

The default mode network (DMN) of the brain is functionally associated with a wide range of behaviors. In this study, we used functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and spectral fiber photometry to investigate the selective neuromodulatory effect of norepinephrine (NE)-releasing noradrenergic neurons in the locus coeruleus (LC) on the mouse DMN. Chemogenetic-induced tonic LC activity decreased cerebral blood volume (CBV) and glucose uptake and increased synchronous low-frequency fMRI activity within the frontal cortices of the DMN. Fiber photometry results corroborated these findings, showing that LC-NE activation induced NE release, enhanced calcium-weighted neuronal spiking, and reduced CBV in the anterior cingulate cortex. These data suggest that LC-NE alters conventional coupling between neuronal activity and CBV in the frontal DMN. We also demonstrated that chemogenetic activation of LC-NE neurons strengthened functional connectivity within the frontal DMN, and this effect was causally mediated by reduced modulatory inputs from retrosplenial and hippocampal regions to the association cortices of the DMN.