Publications

A transient neural code for feedback-driven motor corrections during reaching
Nina Kudryashova
Cole Hurwitz
Matthew G. Perich
Matthias H. Hennig
Movement is the result of complex, dynamic interaction between cortical and subcortical circuits. These dynamic interactions implement both … (voir plus)feedforward motor control, arising from preparatory states, and feedback control, triggered by unexpected sensory events during movement. We show that the neural responses for feedback-driven control can be transient and small in variance, posing difficulties for unsupervised inference methods. We thus propose the Behavior-Aligned Neural Dynamics (BAND) model, which exploits semi-supervised learning to extract latent dynamics that predict both feedforward planned movement and unplanned feedback corrections. Our analysis suggests that motor corrections during movement 1) are encoded on the population level in small neural variability in primary motor (M1), but not dorsal premotor (PMd) cortex; 2) are transient; and 3) are driven by sensory feedback. Our work highlights the importance of targeted closed-loop aware methods to extract and study neural dynamics underlying complex behavioral phenomena.
2025-03-23
bioRxiv (prépublication)
doi.org
Offline Model-Based Optimization: Comprehensive Review
Minsu Kim
Jiayao Gu
Ye Yuan
Taeyoung YUN
Zixuan Liu
Yoshua Bengio
Can Chen
2025-03-20
ArXiv (prépublication)
doi.org
arxiv.org
Quantifying associations between socio-spatial factors and cognitive development in the ABCD cohort
Nicole Osayande
Justin Marotta
Shambhavi Aggarwal
Jakub Kopal
Avram Holmes
Sarah W. Yip
Danilo Bzdok
2025-03-19
Nature Computational Science (publié)
doi.org
Quantifying associations between socio-spatial factors and cognitive development in the ABCD cohort.
Nicole Osayande
Justin Marotta
Shambhavi Aggarwal
Jakub Kopal
Avram J. Holmes
Sarah W. Yip
Danilo Bzdok
2025-03-19
Nature Computational Science (inconnu)
doi.org
RL4Med-DDPO: Reinforcement Learning for Controlled Guidance Towards Diverse Medical Image Generation using Vision-Language Foundation Models
Parham Saremi
Amar Kumar
Mohammed Mohammed
Zahra Tehrani Nasab
Tal Arbel
2025-03-19
ArXiv (prépublication)
doi.org
arxiv.org
Fusion for Visual-Infrared Person ReID in Real-World Surveillance Using Corrupted Multimodal Data
Arthur Josi
Mahdi Alehdaghi
Rafael M. O. Cruz
Eric Granger
2025-03-17
International Journal of Computer Vision (publié)
doi.org
arxiv.org
Tapered Off-Policy REINFORCE: Stable and efficient reinforcement learning for LLMs
Nicolas Roux
Bellemare Marc-Emmanuel
Jonathan Lebensold
Arnaud Bergeron
Joshua Greaves
Alex Fr'echette
Carolyne Pelletier
Éric Thibodeau-Laufer
S'andor Toth
Sam Work
2025-03-17
ArXiv (prépublication)
doi.org
arxiv.org
Sparse Decomposition of Graph Neural Networks
Yaochen Hu
Mai Zeng
Ge Zhang
Pavel Rumiantsev
Liheng Ma
Yingxue Zhang
Mark J. Coates
2025-03-16
TMLR (accepté)
doi.org
openreview.net
Negotiative Alignment: Embracing Disagreement to Achieve Fairer Outcomes -- Insights from Urban Studies
Rashid A. Mushkani
Hugo Berard
Shin Koseki
2025-03-15
ArXiv (prépublication)
doi.org
arxiv.org
Sample Compression for Continual Learning
Jacob Comeau
Mathieu Bazinet
Pascal Germain
Yusuf Cem Sübakan
2025-03-12
ArXiv (prépublication)
doi.org
arxiv.org
Carriers of
<i>LRRK2</i>
pathogenic variants show a milder, anatomically distinct brain signature of Parkinson’s disease
Jakub Kopal
Andrew Vo
Qin Tao
Tanya Simuni
Lana M. Chahine
Danilo Bzdok
Alain Dagher
LRRK2 gene variants are a major genetic risk factor for both familial and sporadic Parkinson’s disease (PD), opening an … (voir plus)unattended window on the disease’s mechanisms and potential therapies. Investigating the influence of pathogenic variants in LRRK2 gene on brain structure is a crucial step toward enabling early diagnosis and personalized treatment. Yet, despite its significance, the ways in which LRRK2 genotype affects brain structure remain largely unexplored. Work in this domain is plagued by small sample sizes and differences in cohort composition, which can obscure genuine distinctions among clinical subgroups. In this study, we overcome such important limitations by combining explicit modeling of population background variation and pattern matching. Specifically, we leveraged a large cohort of 641 participants (including 364 with a PD diagnosis) to examine MRI-detectable cortical atrophy patterns associated with the LRRK2 pathogenic variants in people with PD and non-manifesting individuals. LRRK2 PD patients exhibited milder cortical thinning compared to sporadic PD, with notable preservation in temporal and occipital regions, suggesting a distinct pattern of neurodegeneration. Non-manifesting LRRK2 carriers showed no significant cortical atrophy, indicating no structural signs of subclinical PD. We further analyzed the relationship between aggregated alpha-synuclein in cerebrospinal fluid and atrophy. We found that those with evidence of aggregated alpha-synuclein experienced pronounced neurodegeneration and increased cortical thinning, possibly defining another aggressive PD subtype. Our findings highlight avenues for distinguishing PD subtypes, which could lead to more targeted treatment approaches and a more complete understanding of Parkinson’s disease progression.
2025-03-09
medRxiv (prépublication)
doi.org
Relative biological effectiveness of 31 meV thermal neutrons in peripheral blood lymphocytes
Laura C Paterson
Fawaz Ali
Mohsen Naseri
David Perez Loureiro
Amy Festarini
Marilyne Stuart
Chad Boyer
Ronald Rogge
Christie Costello
Norma Ybarra
J. Kildea
Richard B Richardson
2025-03-09
Radiation Protection Dosimetry (publié)
doi.org