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This paper explores an alternative way for analyzing static Functional Connectivity (FC) in functional Magnetic Resonance Imaging (fMRI) data across multiple timescales using a class of adaptive frequency-based methods referred to as Multivariate Mode Decomposition (MMD). The proposed method decomposes fMRI into their intrinsic multivariate oscillatory components through a fully data-driven approach, and enables the isolation of intrinsic neurophysiological activation patterns across multiple frequency bands from other interfering components. Unlike other methods, this approach is inherently equipped to handle the multivariate nature of fMRI data by aligning frequency information across multiple regions of interest. The proposed method was validated using three fMRI experiments: resting-state, motor and gambling experiments. Results demonstrate the capability of the methodology to extract reliable and reproducible FC patterns across individuals while uncovering unique connectivity features at different times scales. In addition, the results evidence the effect of the different task on the spectral organization of FC patterns, highlighting the importance of multiscale analysis for understanding functional interactions.

Human brains exhibit highly organized multiscale neurophysiological dynamics. Understanding those dynamic changes and the neuronal networks involved is critical for understanding how the brain functions in health and disease. Functional Magnetic Resonance Imaging (fMRI) is a prevalent neuroimaging technique for studying these complex interactions. However, analyzing fMRI data poses several challenges. Furthermore, most approaches for analyzing Functional Connectivity (FC) still rely on preprocessing or conventional methods, often built upon oversimplified assumptions. On top of that, those approaches often ignore frequency-related information despite evidence showing that fMRI data contain rich information that spans multiple timescales. This study introduces a novel methodology, Multiscale Functional Connectivity (MFC), to analyze fMRI data by decomposing the fMRI into their intrinsic modes, allowing us to separate the neurophysiological activation patterns at multiple timescales while separating them from other interfering components. Additionally, the proposed approach accounts for the natural nonlinear and nonstationary nature of fMRI and the particularities of each individual in a data-driven way. We evaluated the performance of our proposed methodology using three fMRI experiments. Our results demonstrate that our novel approach effectively separates the fMRI data into different timescales while identifying highly reliable functional connectivity patterns across individuals. In addition, we further extended our knowledge of how the FC for these three experiments spans among different timescales.

Introduction Anti-amyloid antibodies for the treatment of Alzheimer´s disease (AD) are currently being evaluated for approval and reimbursement in Europe. An approval brings opportunities, but also challenges to health care systems across Europe. The objective of this position paper is to provide guidance from experts in the field in terms of navigating implementation. Methods Members of the European Alzheimer's Disease Consortium and a representative of Alzheimer Europe convened to formulate recommendations covering key areas related to the possible implementation of anti-amyloid antibodies in AD through online discussions and 2 rounds of online voting with an 80% threshold for a position to be accepted. Results In total, 24 recommendations were developed covering the research landscape and priorities within research in AD following a possible approval, potential impact on health care systems and diagnostic pathways, and communication to patients about anti-amyloid antibodies. Anti-amyloid antibodies are regarded as a substantial innovation with an important clinical impact. In addition, however, new compounds with other mechanisms of action and/or route of administration are also needed. Approval of new treatments will require changes to existing patient pathways and real-world data needs to be generated. Conclusion Comprehensive guidance is provided on the potential implementation of anti-amyloid antibody therapies in Europe following possible approval. Emphasis is placed on the necessity of regularly updating recommendations as new evidence emerges in the coming years.