ORCID Profile
0000-0003-1604-9143
Current Organisation
Radboud University Nijmegen Medical Centre
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Publisher: Center for Open Science
Date: 24-12-2018
Abstract: The brain is a complex dynamical system composed of many interacting sub-regions. Knowledge of how these interactions reconfigure over time is critical to a full understanding of the brain’s functional architecture, the neural basis of flexible cognition and behavior, and how neural systems are disrupted in psychiatric and neurological illness. The idea that we might be able to study neural and cognitive dynamics through analysis of neuroimaging data has catalyzed substantial interest in methods which seek to estimate moment-to-moment fluctuations in functional connectivity (often referred to as “dynamic” or time-varying connectivity TVC). At the same time, debates have emerged regarding the application of TVC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive relevance of resting TVC. These and other unresolved issues complicate the interpretation of resting TVC findings and limit the insights which can be gained from this otherwise promising research area. This article reviews the current resting TVC literature in light of these issues. We introduce core concepts, define key terms, summarize current controversies and open questions, and present a forward-looking perspective on how resting TVC analyses can be rigorously applied to investigate a wide range of questions in cognitive and systems neuroscience.
Publisher: MIT Press - Journals
Date: 2020
DOI: 10.1162/NETN_A_00116
Abstract: The brain is a complex, multiscale dynamical system composed of many interacting regions. Knowledge of the spatiotemporal organization of these interactions is critical for establishing a solid understanding of the brain’s functional architecture and the relationship between neural dynamics and cognition in health and disease. The possibility of studying these dynamics through careful analysis of neuroimaging data has catalyzed substantial interest in methods that estimate time-resolved fluctuations in functional connectivity (often referred to as “dynamic” or time-varying functional connectivity TVFC). At the same time, debates have emerged regarding the application of TVFC analyses to resting fMRI data, and about the statistical validity, physiological origins, and cognitive and behavioral relevance of resting TVFC. These and other unresolved issues complicate interpretation of resting TVFC findings and limit the insights that can be gained from this promising new research area. This article brings together scientists with a variety of perspectives on resting TVFC to review the current literature in light of these issues. We introduce core concepts, define key terms, summarize controversies and open questions, and present a forward-looking perspective on how resting TVFC analyses can be rigorously and productively applied to investigate a wide range of questions in cognitive and systems neuroscience.
Publisher: Wiley
Date: 05-03-2022
DOI: 10.1111/FEBS.15757
Abstract: Writing recommendation letters on behalf of students and other early‐career researchers is an important mentoring task within academia. An effective recommendation letter describes key candidate qualities such as academic achievements, extracurricular activities, outstanding personality traits, participation in and dedication to a particular discipline, and the mentor’s confidence in the candidate's abilities. In this Words of Advice, we provide guidance to researchers on composing constructive and supportive recommendation letters, including tips for structuring and providing specific and effective ex les, while maintaining a balance in language and avoiding potential biases.
Publisher: Wiley
Date: 05-04-2022
DOI: 10.1111/FEBS.15823
Abstract: Mentorship is experience and/or knowledge‐based guidance. Mentors support, sponsor and advocate for mentees. Having one or more mentors when you seek advice can significantly influence and improve your research endeavours, well‐being and career development. Positive mentee–mentor relationships are vital for maintaining work–life balance and success in careers. Early‐career researchers (ECRs), in particular, can benefit from mentorship to navigate challenges in academic and nonacademic life and careers. Yet, strategies for selecting mentors and maintaining interactions with them are often underdiscussed within research environments. In this Words of Advice, we provide recommendations for ECRs to seek and manage mentorship interactions. Our article draws from our experiences as ECRs and published work, to provide suggestions for mentees to proactively promote beneficial mentorship interactions. The recommended practices highlight the importance of identifying mentorship needs, planning and selecting multiple and erse mentors, setting goals, and maintaining constructive, and mutually beneficial working relationships with mentors.
Publisher: Wiley
Date: 20-01-2019
DOI: 10.1111/EJN.14320
Abstract: Mentorship facilitates personal growth through pairing trainees with mentors who can share their expertise. In times of global integration, geographical proximity between mentors and mentees is relevant to a lesser degree. This has led to popularization of online mentoring programs. In this editorial, we introduce the history and architecture of the International Online Mentoring Programme organized by the Student and Postdoc Special Interest Group of the Organization for Human Brain Mapping.
Publisher: MIT Press - Journals
Date: 2019
DOI: 10.1162/NETN_A_00062
Abstract: In the past two decades, functional Magnetic Resonance Imaging (fMRI) has been used to relate neuronal network activity to cognitive processing and behavior. Recently this approach has been augmented by algorithms that allow us to infer causal links between component populations of neuronal networks. Multiple inference procedures have been proposed to approach this research question but so far, each method has limitations when it comes to establishing whole-brain connectivity patterns. In this paper, we discuss eight ways to infer causality in fMRI research: Bayesian Nets, Dynamical Causal Modelling, Granger Causality, Likelihood Ratios, Linear Non-Gaussian Acyclic Models, Patel’s Tau, Structural Equation Modelling, and Transfer Entropy. We finish with formulating some recommendations for the future directions in this area.
No related grants have been discovered for Natalia Bielczyk.