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Updated: Jul 25, 2025
Whole-Brain 3D Activation and Functional Connectivity Mapping in Mice using Transcranial Functional Ultrasound Imaging
Published on: February 24, 2021
Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the
Mohit H Adhikari1,2, Tamara Vasilkovska3,4, Roger Cachope5
1Bio-Imaging Lab, University of Antwerp, Antwerp, Belgium. mohit.adhikari@uantwerpen.be.
Insights
Huntington's disease (HD) brain function changes were studied in a mouse model. Resting-state fMRI revealed altered brain activity patterns, with spatial properties accurately predicting disease presence.
Area of Science:
- Neuroscience
- Genetics
- Medical Imaging
Background:
- Huntington's disease (HD) is a neurodegenerative disorder caused by CAG repeat expansion in the huntingtin gene.
- While genetic and clinical aspects are known, pre-symptomatic functional brain changes remain poorly understood.
- The zQ175 delta-neo (DN) mouse model exhibits age-dependent molecular, cellular, and circuitry alterations.
Purpose of the Study:
- To investigate longitudinal functional brain changes in the zQ175 DN mouse model of HD using resting-state functional magnetic resonance imaging (RS-fMRI).
- To characterize alterations in co-activation patterns (CAPs) and their temporal and spatial properties.
- To assess the predictive power of CAP metrics for distinguishing HD model mice from wild-type controls.
Main Methods:
- Longitudinal RS-fMRI was performed on heterozygous (HET) zQ175 DN mice and wild-type littermates at 3, 6, and 10 months of age.
- Analysis focused on temporal and spatial properties of co-activation patterns (CAPs), which represent transient brain activity states within resting-state networks (RSNs).
- Cross-validation was used to determine the accuracy of CAP metrics in classifying HET animals.
Main Results:
- Most significant temporal changes in CAP durations were observed at 10 months, with reduced durations of specific anti-correlated CAPs in HET mice.
- Spatial properties of CAPs showed changes at all ages, becoming more pronounced at 6 and 10 months.
- CAP spatial metrics achieved 80% classification accuracy in distinguishing HET from wild-type mice at 6 and 10 months.
Conclusions:
- Functional brain architecture, specifically CAPs, undergoes significant alterations in the zQ175 DN HD mouse model prior to overt motor deficits.
- Spatial properties of CAPs are sensitive indicators of HD-related brain changes and possess strong predictive power.
- These findings highlight the potential of RS-fMRI and CAP analysis for early detection and monitoring of HD progression.
Abstract:
Huntington's disease (HD) is a neurodegenerative disorder caused by expanded (≥ 40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and clinical signs and symptoms of the disease are better known, changes in the functional architecture of the brain, especially before the clinical expression becomes apparent, are not fully and consistently characterized. In this study, we sought to uncover functional changes in the brain in the heterozygous (HET) zQ175 delta-neo (DN) mouse model at 3, 6, and 10 months of age, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that worsen through age. Motor function disturbances are manifested in this model at 6 and 10 months of age. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the 10-months time point; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three ages and became progressively more pronounced at 6-, and 10 months of age. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three ages with 80% classification accuracy at 6 and 10 months of age.
