P412: A mouse model for EEG resting state using high-density recordings in the awake animal

AbstractAlzheimer’s disease (AD) is the most common form of dementia in the elderly. According to the amyloid hypothesis, the accumulation and deposition of amyloid-beta (Aβ) peptides play a key role in AD. Soluble Aβ (sAβ) oligomers were shown to be involved in pathological hypersynchronisation of brain resting-state networks in different transgenic developmental-onset mouse models of amyloidosis. However, the impact of protein overexpression during brain postnatal development may cause additional phenotypes unrelated to AD. To address this concern, we investigated sAβ effects on functional resting-state networks in transgenic mature-onset amyloidosis Tet-Off APP (TG) mice. TG mice and control littermates were raised on doxycycline (DOX) diet from 3d up to 3 m of age to suppress transgenic Aβ production. Thereafter, longitudinal resting-state functional MRI was performed on a 9.4 T MR-system starting from week 0 (3 m old mice) up to 28w post DOX treatment. Ex-vivo immunohistochemistry and ELISA analysis was performed to assess the development of amyloid pathology. Functional Connectivity (FC) analysis demonstrated early abnormal hypersynchronisation in the TG mice compared to the controls at 8w post DOX treatment, particularly across regions of the default mode-like network, known to be affected in AD. Ex-vivo analyses performed at this time point confirmed a 20-fold increase in total sAβ levels preceding the apparition of Aβ plaques and inflammatory responses in the TG mice compared to the controls. On the contrary at week 28, TG mice showed an overall hypoconnectivity, coinciding with a widespread deposition of Aβ plaques in the brain. By preventing developmental influence of APP and/or sAβ during brain postnatal development, we demonstrated FC abnormalities potentially driven by sAβ neurotoxicity on resting-state neuronal networks in mature-induced TG mice. Thus, the Tet-Off APP mouse model could be a powerful tool while used as a mature-onset model to shed light into amyloidosis mechanisms in AD.

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Rice Endosperm Protein Improves the Anti-Inflammatory Effects of High-Density Lipoprotein and Produces Lower Atherosclerotic Lesion Accelerated by the Renal Mass Reduction than Casein in a Mouse Model

Journal of the American College of Nutrition ◽

10.1080/07315724.2021.1950584 ◽

2021 ◽

pp. 1-11

Author(s):

Ryohei Kaseda ◽

Michihiro Hosojima ◽

Shoji Kuwahara ◽

Hideyuki Kabasawa ◽

Hiroyuki Aoki ◽

...

Keyword(s):

Mouse Model ◽

High Density Lipoprotein ◽

Renal Mass ◽

Atherosclerotic Lesion ◽

Density Lipoprotein ◽

High Density ◽

Mass Reduction ◽

Rice Endosperm ◽

Endosperm Protein ◽

Anti Inflammatory

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CMR2009: 10.07: Multimodality investigation of lipoprotein metabolism in a mouse model of atherosclerosis using iron oxide core high-density lipoprotein nano-particles

Contrast Media & Molecular Imaging ◽

10.1002/cmmi.353 ◽

2009 ◽

Vol 4 (6) ◽

pp. 293-294

Author(s):

T. Skajaa ◽

D. P. Cormode ◽

P. Jarzyna ◽

A. Barazza ◽

E. A. Fisher ◽

...

Keyword(s):

Iron Oxide ◽

Mouse Model ◽

High Density Lipoprotein ◽

Lipoprotein Metabolism ◽

Density Lipoprotein ◽

High Density ◽

Nano Particles ◽

Iron Oxide Core

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Fenofibrate Increases High-Density Lipoprotein and Sphingosine 1 Phosphate Concentrations Limiting Abdominal Aortic Aneurysm Progression in a Mouse Model

American Journal Of Pathology ◽

10.1016/j.ajpath.2012.04.015 ◽

2012 ◽

Vol 181 (2) ◽

pp. 706-718 ◽

Cited By ~ 49

Author(s):

Smriti M. Krishna ◽

Sai Wang Seto ◽

Joseph V. Moxon ◽

Catherine Rush ◽

Philip J. Walker ◽

...

Keyword(s):

Abdominal Aortic Aneurysm ◽

Aortic Aneurysm ◽

Mouse Model ◽

High Density Lipoprotein ◽

Density Lipoprotein ◽

High Density ◽

Abdominal Aortic ◽

Sphingosine 1 Phosphate

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Detection of Resting-State Functional Connectivity from High-Density Electroencephalography Data: Impact of Head Modeling Strategies

Brain Sciences ◽

10.3390/brainsci11060741 ◽

2021 ◽

Vol 11 (6) ◽

pp. 741

Author(s):

Gaia Amaranta Taberna ◽

Jessica Samogin ◽

Marco Marino ◽

Dante Mantini

Keyword(s):

Functional Connectivity ◽

Resting State ◽

High Density ◽

Reliable Estimate ◽

Head Model ◽

Resting State Functional Connectivity ◽

Tissue Segmentation ◽

Technological Advances ◽

Electrode Positioning ◽

Band Limited

Recent technological advances have been permitted to use high-density electroencephalography (hdEEG) for the estimation of functional connectivity and the mapping of resting-state networks (RSNs). The reliable estimate of activity and connectivity from hdEEG data relies on the creation of an accurate head model, defining how neural currents propagate from the cortex to the sensors placed over the scalp. To the best of our knowledge, no study has been conducted yet to systematically test to what extent head modeling accuracy impacts on EEG-RSN reconstruction. To address this question, we used 256-channel hdEEG data collected in a group of young healthy participants at rest. We first estimated functional connectivity in EEG-RSNs by means of band-limited power envelope correlations, using neural activity estimated with an optimized analysis workflow. Then, we defined a series of head models with different levels of complexity, specifically testing the effect of different electrode positioning techniques and head tissue segmentation methods. We observed that robust EEG-RSNs can be obtained using a realistic head model, and that inaccuracies due to head tissue segmentation impact on RSN reconstruction more than those due to electrode positioning. Additionally, we found that EEG-RSN robustness to head model variations had space and frequency specificity. Overall, our results may contribute to defining a benchmark for assessing the reliability of hdEEG functional connectivity measures.

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High-Density EEG in a Charles Bonnet Syndrome Patient during and without Visual Hallucinations: A Case-Report Study

Cells ◽

10.3390/cells10081991 ◽

2021 ◽

Vol 10 (8) ◽

pp. 1991

Author(s):

Andrea Piarulli ◽

Jitka Annen ◽

Ron Kupers ◽

Steven Laureys ◽

Charlotte Martial

Keyword(s):

Case Report ◽

Resting State ◽

High Density ◽

Alpha Power ◽

Visual Hallucinations ◽

Charles Bonnet Syndrome ◽

Eeg Data ◽

Signal Diversity ◽

Signal Complexity ◽

Cortical Regions

Charles Bonnet syndrome (CBS) is a rare clinical condition characterized by complex visual hallucinations in people with loss of vision. So far, the neurobiological mechanisms underlying the hallucinations remain elusive. This case-report study aims at investigating electrical activity changes in a CBS patient during visual hallucinations, as compared to a resting-state period (without hallucinations). Prior to the EEG, the patient underwent neuropsychological, ophthalmologic, and neurological examinations. Spectral and connectivity, graph analyses and signal diversity were applied to high-density EEG data. Visual hallucinations (as compared to resting-state) were characterized by a significant reduction of power in the frontal areas, paralleled by an increase in the midline posterior regions in delta and theta bands and by an increase of alpha power in the occipital and midline posterior regions. We next observed a reduction of theta connectivity in the frontal and right posterior areas, which at a network level was complemented by a disruption of small-worldness (lower local and global efficiency) and by an increase of network modularity. Finally, we found a higher signal complexity especially when considering the frontal areas in the alpha band. The emergence of hallucinations may stem from these changes in the visual cortex and in core cortical regions encompassing both the default mode and the fronto-parietal attentional networks.

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