Publications

Considerations and recommendations from the <scp>ISMRM</scp> diffusion study group for preclinical diffusion <scp>MRI</scp>: Part 1: In vivo small‐animal imaging

Ileana O. Jelescu

Francesco Grussu

Andrada Ianus

Brian Hansen

Rachel L. C. Barrett

Manisha Aggarwal

Stijn Michielse

Fatima Nasrallah

Warda Syeda

Nian Wang

Jelle Veraart

Alard Roebroeck

Andrew F. Bagdasarian

Cornelius Eichner

Farshid Sepehrband

Jan Zimmermann

Lucas Soustelle

Christien Bowman

Benjamin C. Tendler

Andreea Hertanu … (voir 37 de plus)

Ben Jeurissen

Marleen Verhoye

Lucio Frydman

Yohan van de Looij

David Hike

Jeff F. Dunn

Karla Miller

Bennett Landman

Noam Shemesh

Arthur Anderson

Emilie McKinnon

Shawna Farquharson

Flavio Dell’Acqua

Carlo Pierpaoli

Ivana Drobnjak

Alexander Leemans

Kevin D. Harkins

Maxime Descoteaux

Duan Xu

Hao Huang

Mathieu D. Santin

Samuel C. Grant

Andre Obenaus

Gene S. Kim

Dan Wu

Denis Le Bihan

Stephen J. Blackband

Luisa Ciobanu

Els Fieremans

Ruiliang Bai

Trygve B. Leergaard

Jiangyang Zhang

Tim B. Dyrby

G. Allan Johnson

Julien Cohen-Adad

Matthew D. Budde

Kurt G Schilling

2025-02-25

Magnetic Resonance in Medicine (publié)

doi.org

Deep multimodal representations and classification of first-episode psychosis via live face processing

Rahul Singh

Yanlei Zhang

Dhananjay Bhaskar

Vinod Srihari

Cenk Tek

Xian Zhang

J. Adam Noah

Smita Krishnaswamy

Joy Hirsch

Schizophrenia is a severe psychiatric disorder associated with a wide range of cognitive and neurophysiological dysfunctions and long-term s… (voir plus)ocial difficulties. In this paper, we test the hypothesis that integration of multiple simultaneous acquisitions of neuroimaging, behavioral, and clinical information will be better for prediction of early psychosis than unimodal recordings. We propose a novel framework to investigate the neural underpinnings of the early psychosis symptoms (that can develop into Schizophrenia with age) using multimodal acquisitions of neural and behavioral recordings including functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), and facial features. Our data acquisition paradigm is based on live face-to-face interaction in order to study the neural correlates of social cognition in first-episode psychosis (FEP). We propose a novel deep representation learning framework, Neural-PRISM, for learning joint multimodal compressed representations combining neural as well as behavioral recordings. These learned representations are subsequently used to describe, classify, and predict the severity of early psychosis in patients, as measured by the Positive and Negative Syndrome Scale (PANSS) and Global Assessment of Functioning (GAF) scores. We found that incorporating joint multimodal representations from fNIRS and EEG along with behavioral recordings enhances classification between typical controls and FEP individuals. Additionally, our results suggest that geometric and topological features such as curvatures and path signatures of the embedded trajectories of brain activity enable detection of discriminatory neural characteristics in early psychosis.

2025-02-25

Frontiers in Psychiatry (publié)

doi.org

Determinants of pleiotropy and monotonic gene dosage responses across human traits

Sayeh Kazem

Kuldeep Kumar

Martineau Jean‐Louis

Guillaume Huguet

Thomas Renne

Zohra Saci

Worrawat Engchuan

Omar Shanta

Bhooma Thiruvahindrapuram

Jeffrey R. MacDonald

Celia M. T. Greenwood

Stephen W. Scherer

Laura Almasy

Jonathan Sebat

David C. Glahn

Guillaume Dumas

Sébastien Jacquemont

Pleiotropic effects of gene dosage are central to understanding comorbidities in developmental pediatric and psychiatric disorders, yet the … (voir plus)underlying biological processes are unknown. We developed Functional Burden analysis (FunBurd) to investigate the association of all protein-coding copy-number-variants (CNVs), genome-wide, with 43 complex traits in ∼500,000 UK-Biobank participants. We tested CNV associations disrupting 172 tissue or cell-type gene-sets, observing associations across all traits. Pleiotropy was correlated with genetic constraint and was higher in the brain compared to non-brain functions, even after normalizing for genetic constraint. Cognition and mental health traits showed specific gene-dosage effects across cortical/sub-cortical and neuronal/glial functional categories. The levels of pleiotropy, measured by burden correlation, were similar in deletions and loss-of-function SNVs, and higher compared to common variants and duplications. Gene sets under high genetic constraint showed less monotonic gene dosage responses across traits. Across most traits, we observed a negative deletion-duplication effect size correlation, indicating that functional gene sets are preferentially sensitive to either deletion or duplication, but rarely both. Our results highlight the key role of genetic constraint and brain-specific mechanisms in shaping CNV-driven pleiotropy, providing a mechanistic basis for the whole-body multimorbidity observed in neurodevelopmental and psychiatric conditions.

2025-02-25

medRxiv (publié)

doi.org

Origin of Nonlinear Circular Photocurrent in 2D Semiconductor
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi>MoS</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:math>

Yanchong Zhao

Fengyu Chen

Jing Liang

Mohammad Saeed Bahramy

Mingwei Yang

Yao Guang

Xiaomei Li

Zheng Wei

Jian Tang

Jiaojiao Zhao

Mengzhou Liao

Cheng Shen

Qinqin Wang

Rong Yang

Kenji Watanabe

Takashi Taniguchi

Zhiheng Huang

Dongxia Shi

Kaihui Liu

Zhipei Sun … (voir 3 de plus)

Ji Feng

Luojun Du

Guangyu Zhang

2025-02-25

Physical Review Letters (publié)

doi.org

Origin of Nonlinear Circular Photocurrent in 2D Semiconductor MoS_{2}.

Yanchong Zhao

Fengyu Chen

Jing Liang

Mohammad Saeed Bahramy

Mingwei Yang

Yao Guang

Xiaomei Li

Zheng Wei

Jian Tang

Jiaojiao Zhao

Mengzhou Liao

Cheng Shen

Qinqin Wang

Rong Yang

Kenji Watanabe

Takashi Taniguchi

Zhiheng Huang

Dongxia Shi

Kaihui Liu

Zhipei Sun … (voir 3 de plus)

Ji Feng

Luojun Du

Guangyu Zhang

2025-02-25

Physical Review Letters (publié)

doi.org

Recommendations and guidelines from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 1 -- In vivo small-animal imaging

Ileana O. Jelescu

Francesco Grussu

Andrada Ianus

Brian Hansen

Rachel L. C. Barrett

Manisha Aggarwal

Stijn Michielse

Fatima Nasrallah

Warda Syeda

Nian Wang

Jelle Veraart

Alard Roebroeck

Andrew F. Bagdasarian

Cornelius Eichner

Farshid Sepehrband

Jan Zimmermann

Ben Jeurissen

Lucio Frydman

Lucas Soustelle

Christien Bowman … (voir 37 de plus)

Yohan van de Looij

Benjamin C. Tendler

David Hike

Jeff F. Dunn

Andrada Ianus

Karla Miller

Bennett Landman

Marleen Verhoye

Noam Shemesh

Arthur Anderson

Emilie McKinnon

Shawna Farquharson

Flavio Dell’Acqua

Carlo Pierpaoli

Ivana Drobnjak

Alexander Leemans

Kevin D. Harkins

Maxime Descoteaux

Duan Xu

Mathieu D. Santin

Samuel C. Grant

Andre Obenaus

Gene S. Kim

Dan Wu

Denis Le Bihan

Stephen J. Blackband

Nian Wang

Luisa Ciobanu

Els Fieremans

Ruiliang Bai

Trygve B. Leergaard

Jiangyang Zhang

Tim B. Dyrby

G. Allan Johnson

Julien Cohen-Adad

Matthew D. Budde

Kurt G Schilling

The value of in vivo preclinical diffusion MRI (dMRI) is substantial. Small-animal dMRI has been used for methodological development and val… (voir plus)idation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. Many of the influential works in this field were first performed in small animals or ex vivo samples. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the data. This work aims to serve as a reference, presenting selected recommendations and guidelines from the diffusion community, on best practices for preclinical dMRI of in vivo animals. In each section, we also highlight areas for which no guidelines exist (and why), and where future work should focus. We first describe the value that small animal imaging adds to the field of dMRI, followed by general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss how they are appropriate for different studies. We then give guidelines for in vivo acquisition protocols, including decisions on hardware, animal preparation, imaging sequences and data processing, including pre-processing, model-fitting, and tractography. Finally, we provide an online resource which lists publicly available preclinical dMRI datasets and software packages, to promote responsible and reproducible research. An overarching goal herein is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.

2025-02-25

Magnetic Resonance in Medicine (publié)

doi.org

arxiv.org

The use of extended reality in anesthesiology education: a scoping review

Gianluca Bertolizio

Yu Tong Huang

Marta Garbin

Elena Guadagno

Dan Poenaru

2025-02-25

Canadian Journal of Anaesthesia-journal Canadien D Anesthesie (publié)

doi.org

Learning Multi-agent Multi-machine Tending by Mobile Robots

Abdalwhab Abdalwhab

Giovanni Beltrame

S Ebrahimi Kahou

David St-Onge

Robotics can help address the growing worker shortage challenge of the manufacturing industry. As such, machine tending is a task collaborat… (voir plus)ive robots can tackle that can also highly boost productivity. Nevertheless, existing robotics systems deployed in that sector rely on a fixed single-arm setup, whereas mobile robots can provide more flexibility and scalability. In this work, we introduce a multi-agent multi-machine tending learning framework by mobile robots based on Multi-agent Reinforcement Learning (MARL) techniques with the design of a suitable observation and reward. Moreover, an attention-based encoding mechanism is developed and integrated into Multi-agent Proximal Policy Optimization (MAPPO) algorithm to boost its performance for machine tending scenarios. Our model (AB-MAPPO) outperformed MAPPO in this new challenging scenario in terms of task success, safety, and resources utilization. Furthermore, we provided an extensive ablation study to support our various design decisions.

2025-02-24

AAAI.org/2025/Workshop/MARW (publié)

doi.org

openreview.net

The In-Situ Effect of Offensive Ads on Search Engine Users

Elad Yom-Tov

Liat Levontin

A.R. Olteanu

2025-02-24

ACM Transactions on Information Systems (publié)

doi.org

On the Dichotomy Between Privacy and Traceability in $\ell_p$ Stochastic Convex Optimization