204 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- King's College LondonGB8 papers
- Parc Sanitari Sant Joan de DéuES6 papers
- Universitat de BarcelonaES6 papers
- University College LondonGB6 papers
- KU LeuvenBE5 papers
- South London and Maudsley NHS Foundation TrustGB5 papers
- Amsterdam NeuroscienceNL4 papers
- Amsterdam University Medical CentersNL4 papers
- Janssen (United States)US4 papers
- LAB University of Applied SciencesFI4 papers
- Northwestern UniversityUS4 papers
- Vrije Universiteit AmsterdamNL4 papers
12 papers
Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning
Filippo Corponi, Bryan M. Li, Gerard Anmella +13
Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood di…
The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff +111
The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is mean…
Challenges in Using mHealth Data From Smartphones and Wearable Devices to Predict Depression Symptom Severity: Retrospective Analysis
Shaoxiong Sun, Amos A. Folarin, Yuezhou Zhang +28
A number of challenges exist for the analysis of mHealth data: maintaining participant engagement over extended time periods and therefore understanding what constitutes an accepta…
Associations between depression symptom severity and daily-life gait characteristics derived from long-term acceleration signals in real-world settings
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +27
Gait is an essential manifestation of depression. Laboratory gait characteristics have been found to be closely associated with depression. However, the gait characteristics of dai…
Predicting Depressive Symptom Severity through Individuals' Nearby Bluetooth Devices Count Data Collected by Mobile Phones: A Preliminary Longitudinal Study
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +21
The Bluetooth sensor embedded in mobile phones provides an unobtrusive, continuous, and cost-efficient means to capture individuals' proximity information, such as the nearby Bluet…
The Relationship between Major Depression Symptom Severity and Sleep Collected Using a Wristband Wearable Device: Multi-centre Longitudinal Observational Study
Yuezhou Zhang, Amos A Folarin, Shaoxiong Sun +19
Research in mental health has implicated sleep pathologies with depression. However, the gold standard for sleep assessment, polysomnography, is not suitable for long-term, continu…
Using smartphones and wearable devices to monitor behavioural changes during COVID-19
Shaoxiong Sun, Amos Folarin, Yatharth Ranjan +23
We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiti…
Deep Sequential Models for Suicidal Ideation from Multiple Source Data
Ignacio Peis, Pablo M. Olmos, Constanza Vera-Varela +4
This article presents a novel method for predicting suicidal ideation from Electronic Health Records (EHR) and Ecological Momentary Assessment (EMA) data using deep sequential mode…
Extraordinarily transparent compact metallic metamaterials
Samuel J. Palmer, Xiaofei Xiao, Nicolas Pazos-Perez +5
Metals are highly opaque, yet we show that densely packed arrays of metallic nanoparticles can be more transparent to infrared radiation than dielectrics such as germanium, even fo…
Deep Learning for Quality Control of Subcortical Brain 3D Shape Models
Dmitry Petrov, Boris A. Gutman Egor Kuznetsov, Theo G. M. van Erp +70
We present several deep learning models for assessing the morphometric fidelity of deep grey matter region models extracted from brain MRI. We test three different convolutional ne…
Multiplicative and additive modulation of neuronal tuning with population activity affects encoded information
Iñigo Arandia-Romero, Seiji Tanabe, Jan Drugowitsch +2
Numerous studies have shown that neuronal responses are modulated by stimulus properties, and also by the state of the local network. However, little is known about how activity fl…
Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and spatial regularization
Erick J. Canales-Rodríguez, Alessandro Daducci, Stamatios N. Sotiropoulos +11
Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assum…