Aberrant brain functional and structural developments in MECP2 duplication rats

Xu, Ming; Qi, Shile; Calhoun, Vince D.; Dai, Jiankun; Yu, Bin; Zhang, Kaiwei; Pei, Mengchao; Li, Chenjian; Wei, Yusheng; Jiang, Rongtao; Zhi, Dongmei; Huang, Zhimin; Qiu, Zilong; Liang, Zhifeng; Sui, Jing

doi:10.1016/j.nbd.2022.105838

Cited by 3 publications

(1 citation statement)

References 70 publications

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“…jICA is further applied on the concatenated components to keep the modality linkage of the potential target components and maximize the spatial independence, generating the final independent components as well as their corresponding mixing matrices. By incorporating prior information, the mCCAR + jICA enables the identification of joint multimodal components that have robust correlations within referred measures and among themselves (inter-modality correlations) (Qi, Yang, et al ., 2018 ; Zhi et al ., 2020 ; Qi et al ., 2021 ; Xu et al ., 2022 ), which may not be detected by a blind N -way multimodal fusion approach.…”

Section: Review Of Multivariate Multimodal Fusion Modelsmentioning

confidence: 99%

Data-driven multimodal fusion: approaches and applications in psychiatric research

Sui,

Zhi,

Calhoun

2023

Psychoradiology

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In the era of big data, where vast amounts of information are being generated and collected at an unprecedented rate, there is a pressing demand for innovative data-driven multi-modal fusion methods. These methods aim to integrate diverse neuroimaging perspectives to extract meaningful insights and attain a more comprehensive understanding of complex psychiatric disorders. However, analyzing each modality separately may only reveal partial insights or miss out on important correlations between different types of data. This is where data-driven multi-modal fusion techniques come into play. By combining information from multiple modalities in a synergistic manner, these methods enable us to uncover hidden patterns and relationships that would otherwise remain unnoticed. In this paper, we present an extensive overview of data-driven multimodal fusion approaches with or without prior information, with specific emphasis on canonical correlation analysis and independent component analysis. The applications of such fusion methods are wide-ranging and allow us to incorporate multiple factors such as genetics, environment, cognition, and treatment outcomes across various brain disorders. After summarizing the diverse neuropsychiatric magnetic resonance imaging fusion applications, we further discuss the emerging neuroimaging analyzing trends in big data, such as N-way multimodal fusion, deep learning approaches, and clinical translation. Overall, multimodal fusion emerges as an imperative approach providing valuable insights into the underlying neural basis of mental disorders, which can uncover subtle abnormalities or potential biomarkers that may benefit targeted treatments and personalized medical interventions.

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Section: Review Of Multivariate Multimodal Fusion Modelsmentioning

confidence: 99%

Data-driven multimodal fusion: approaches and applications in psychiatric research

Sui,

Zhi,

Calhoun

2023

Psychoradiology

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Gut microbiome and metabolic profiles of mouse model for MeCP2 duplication syndrome

Wu,

Hu,

Rao

et al. 2024

Brain Research Bulletin

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R-Baclofen Treatment Corrects Autistic-like Behavioral Deficits in the RjIbm(m):FH Fawn-Hooded Rat Strain

Varga,

Kedves,

Sághy

et al. 2024

Pharmaceuticals

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The Fawn-hooded rat has long been used as a model for various peripheral and central disorders and the data available indicate that the social behavior of this strain may be compromised. However, a thorough description of the Fawn-hooded rat is unavailable in this regard. The objective of the present study was to investigate various aspects of the Fawn-hooded rat’s social behavior in depth. Our results show that several facets of socio-communicational behavior are impaired in the RjIbm(m):FH strain, including defective ultrasonic vocalizations in pups upon maternal deprivation, reduced social play in adolescence and impaired social novelty discrimination in adulthood. In addition, Fawn-hooded rats exhibited heightened tactile sensitivity and hyperactivity. The defects observed were comparable to those induced by prenatal valproate exposure, a widely utilized model of autism spectrum disorder. Further on, the pro-social drug R-baclofen (0.25–1 mg/kg) reversed the autistic-like defects observed in Fawn-hooded rats, specifically the deficiency in ultrasonic vocalization, tactile sensitivity and social novelty discrimination endpoints. In conclusion, the asocial, hypersensitive and hyperactive phenotype as well as the responsivity to R-baclofen indicate this variant of the Fawn-hooded rat strain may serve as a model of autism spectrum disorder and could be useful in the identification of novel drug candidates.

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Aberrant brain functional and structural developments in MECP2 duplication rats

Cited by 3 publications

References 70 publications

Data-driven multimodal fusion: approaches and applications in psychiatric research

Data-driven multimodal fusion: approaches and applications in psychiatric research

Gut microbiome and metabolic profiles of mouse model for MeCP2 duplication syndrome

R-Baclofen Treatment Corrects Autistic-like Behavioral Deficits in the RjIbm(m):FH Fawn-Hooded Rat Strain

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