Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivity
BackgroundDisruption of N-methyl-D-aspartate receptor (NMDAR) activity within the septohippocampal network - a critical circuit that includes the hippocampus, medial prefrontal cortex (mPFC) and other nuclei - is believed to contribute to learning and memory impairments. Although animal models using...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Pharmacology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2025.1562102/full |
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| author | Erik Hakopian Argishti E. Stepanian Shan Zhong Shan Zhong Kofi A. Agyeman Kofi A. Agyeman Nancy Zepeda Kevin Wu Charles Liu Charles Liu Charles Liu Charles Liu Darrin J. Lee Darrin J. Lee Darrin J. Lee Darrin J. Lee Vassilios Christopoulos Vassilios Christopoulos Vassilios Christopoulos Vassilios Christopoulos |
| author_facet | Erik Hakopian Argishti E. Stepanian Shan Zhong Shan Zhong Kofi A. Agyeman Kofi A. Agyeman Nancy Zepeda Kevin Wu Charles Liu Charles Liu Charles Liu Charles Liu Darrin J. Lee Darrin J. Lee Darrin J. Lee Darrin J. Lee Vassilios Christopoulos Vassilios Christopoulos Vassilios Christopoulos Vassilios Christopoulos |
| author_sort | Erik Hakopian |
| collection | DOAJ |
| description | BackgroundDisruption of N-methyl-D-aspartate receptor (NMDAR) activity within the septohippocampal network - a critical circuit that includes the hippocampus, medial prefrontal cortex (mPFC) and other nuclei - is believed to contribute to learning and memory impairments. Although animal models using the NMDAR antagonist Dizocilpine (MK-801) replicate cognitive deficits associated with memory and learning disorders, the direct effects of MK-801 on brain network connectivity have not been well characterized.ObjectiveThis study aims to explore the effects of MK-801 on brain network connectivity using functional ultrasound imaging (fUSI) and apply time series analysis methods to mitigate potential statistical confounds in functional connectivity assessments.MethodsfUSI was employed to assess changes in cerebral blood volume (CBV) and network connectivity in MK-801-treated mice. To account for the nonstationarity and autocorrelation inherent in fUSI time series, an AutoRegressive Integrated Moving Average (ARIMA) model was applied to stabilize the mean and remove autocorrelation, ensuring more reliable signal analysis.ResultsOur analysis revealed that MK-801 significantly disrupts functional connectivity (FC) across key brain regions, including the hippocampus, mPFC, and striatum. We also demonstrated that removing autocorrelation from the fUSI time series mitigates the risk of spurious associations, enhancing the reliability of network analysis.ConclusionThis study demonstrates the importance of accounting for nonstationarity in fUSI time series to improve the accuracy of brain network connectivity analysis. Our findings indicate that MK-801-induced NMDAR inhibition disrupts connectivity both within and outside the septohippocampal circuit, offering new insights into the neural mechanisms underlying cognitive deficits in disorders affecting memory and learning. |
| format | Article |
| id | doaj-art-103d3d1c93dd4151a55ed50e759fdbcb |
| institution | DOAJ |
| issn | 1663-9812 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pharmacology |
| spelling | doaj-art-103d3d1c93dd4151a55ed50e759fdbcb2025-08-20T03:07:17ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122025-06-011610.3389/fphar.2025.15621021562102Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivityErik Hakopian0Argishti E. Stepanian1Shan Zhong2Shan Zhong3Kofi A. Agyeman4Kofi A. Agyeman5Nancy Zepeda6Kevin Wu7Charles Liu8Charles Liu9Charles Liu10Charles Liu11Darrin J. Lee12Darrin J. Lee13Darrin J. Lee14Darrin J. Lee15Vassilios Christopoulos16Vassilios Christopoulos17Vassilios Christopoulos18Vassilios Christopoulos19Department of Neuroscience, University of California Riverside, Riverside, CA, United StatesDepartment of Neuroscience, University of California Riverside, Riverside, CA, United StatesDepartment of Neuroscience, University of California Riverside, Riverside, CA, United StatesDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United StatesDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United StatesDepartment of Bioengineering, University of California Riverside, Riverside, CA, United StatesDepartment of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesDepartment of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United StatesDepartment of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesNeurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesRancho Los Amigos National Rehabilitation Center, Downey, CA, United StatesDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United StatesDepartment of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesNeurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesRancho Los Amigos National Rehabilitation Center, Downey, CA, United StatesDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United StatesDepartment of Bioengineering, University of California Riverside, Riverside, CA, United StatesDepartment of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesNeurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, United StatesBackgroundDisruption of N-methyl-D-aspartate receptor (NMDAR) activity within the septohippocampal network - a critical circuit that includes the hippocampus, medial prefrontal cortex (mPFC) and other nuclei - is believed to contribute to learning and memory impairments. Although animal models using the NMDAR antagonist Dizocilpine (MK-801) replicate cognitive deficits associated with memory and learning disorders, the direct effects of MK-801 on brain network connectivity have not been well characterized.ObjectiveThis study aims to explore the effects of MK-801 on brain network connectivity using functional ultrasound imaging (fUSI) and apply time series analysis methods to mitigate potential statistical confounds in functional connectivity assessments.MethodsfUSI was employed to assess changes in cerebral blood volume (CBV) and network connectivity in MK-801-treated mice. To account for the nonstationarity and autocorrelation inherent in fUSI time series, an AutoRegressive Integrated Moving Average (ARIMA) model was applied to stabilize the mean and remove autocorrelation, ensuring more reliable signal analysis.ResultsOur analysis revealed that MK-801 significantly disrupts functional connectivity (FC) across key brain regions, including the hippocampus, mPFC, and striatum. We also demonstrated that removing autocorrelation from the fUSI time series mitigates the risk of spurious associations, enhancing the reliability of network analysis.ConclusionThis study demonstrates the importance of accounting for nonstationarity in fUSI time series to improve the accuracy of brain network connectivity analysis. Our findings indicate that MK-801-induced NMDAR inhibition disrupts connectivity both within and outside the septohippocampal circuit, offering new insights into the neural mechanisms underlying cognitive deficits in disorders affecting memory and learning.https://www.frontiersin.org/articles/10.3389/fphar.2025.1562102/fullfunctional ultrasound imaging (fUSI)brain network connectivityprewhitening analysisMK-801NMDAR inhibitionmemory |
| spellingShingle | Erik Hakopian Argishti E. Stepanian Shan Zhong Shan Zhong Kofi A. Agyeman Kofi A. Agyeman Nancy Zepeda Kevin Wu Charles Liu Charles Liu Charles Liu Charles Liu Darrin J. Lee Darrin J. Lee Darrin J. Lee Darrin J. Lee Vassilios Christopoulos Vassilios Christopoulos Vassilios Christopoulos Vassilios Christopoulos Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivity Frontiers in Pharmacology functional ultrasound imaging (fUSI) brain network connectivity prewhitening analysis MK-801 NMDAR inhibition memory |
| title | Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivity |
| title_full | Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivity |
| title_fullStr | Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivity |
| title_full_unstemmed | Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivity |
| title_short | Functional ultrasound imaging and prewhitening analysis reveal MK-801-induced disruption of brain network connectivity |
| title_sort | functional ultrasound imaging and prewhitening analysis reveal mk 801 induced disruption of brain network connectivity |
| topic | functional ultrasound imaging (fUSI) brain network connectivity prewhitening analysis MK-801 NMDAR inhibition memory |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2025.1562102/full |
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