Publications

General anaesthesia decreases the uniqueness of brain functional connectivity across individuals and species
Andrea I. Luppi
Daniel Golkowski
Andreas Ranft
Rudiger Ilg
Denis Jordan
Danilo Bzdok
Adrian M. Owen
Lorina Naci
Emmanuel A. Stamatakis
Enrico Amico
Bratislav Misic
The human brain is characterized by idiosyncratic patterns of spontaneous thought, rendering each brain uniquely identifiable from its neura… (voir plus)l activity. However, deep general anaesthesia suppresses subjective experience. Does it also suppress what makes each brain unique? Here we used functional MRI scans acquired under the effects of the general anaesthetics sevoflurane and propofol to determine whether anaesthetic-induced unconsciousness diminishes the uniqueness of the human brain, both with respect to the brains of other individuals and the brains of another species. Using functional connectivity, we report that under anaesthesia individual brains become less self-similar and less distinguishable from each other. Loss of distinctiveness is highly organized: it co-localizes with the archetypal sensory–association axis, correlating with genetic and morphometric markers of phylogenetic differences between humans and other primates. This effect is more evident at greater anaesthetic depths, reproducible across sevoflurane and propofol and reversed upon recovery. Providing convergent evidence, we show that anaesthesia shifts the functional connectivity of the human brain closer to the functional connectivity of the macaque brain in a low-dimensional space. Finally, anaesthesia diminishes the match between spontaneous brain activity and cognitive brain patterns aggregated from the Neurosynth meta-analytic engine. Collectively, the present results reveal that anaesthetized human brains are not only less distinguishable from each other, but also less distinguishable from the brains of other primates, with specifically human-expanded regions being the most affected by anaesthesia.
2025-03-23
Nature Human Behaviour (publié)
doi.org
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 (publié)
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
Hitting the right pitch: Cortical tracking of speech fundamental frequency in auditory and somatomotor regions
Yorguin-Jose Mantilla-Ramos
Ana-Sofía Hincapié-Casas
Annalisa Pascarella
Tarek Lajnef
Richard M. Leahy
Emily B.J. Coffey
Karim Jerbi CoCo Lab
Véronique Boulenger
Low-frequency neural oscillations contribute to the parsing of continuous speech into linguistic units. Little is known however on the coupl… (voir plus)ing of brain rhythms to higher-frequencies in speech such as fundamental frequency (F0) or pitch. Using magnetoencephalography, we investigated whole-brain cortical tracking of F0 while participants listened to sentences produced at normal rate or fast rate, where pitch naturally increases, and to artificially accelerated sentences, where F0 remains unchanged. Our results revealed significant brain-to-F0 coupling across all speech rates not only in right auditory but also in right parietal, insular, and pre- and postcentral regions, likely including the ventral larynx area. Importantly, the cortico-acoustic coupling peak frequency was higher for natural fast speech to reflect the corresponding F0 increase compared to normal rate and time-compressed speech. These findings demonstrate the engagement of an auditory-somato-motor network in F0 tracking, supporting its role in facilitating phonemic processing during the perception of naturally-produced speech.
2025-03-17
bioRxiv (prépublication)
doi.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
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
Tanya Simuni
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 (publié)
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
Understanding the impact of IoT security patterns on CPU usage and energy consumption: a dynamic approach for selecting patterns with deep reinforcement learning
Saeid Jamshidi
Amin Nikanjam
Kawser Wazed Nafi
Foutse Khomh
2025-03-09
International Journal of Information Security (publié)
doi.org