2024

• Camacho, M., Wilms, M., Almgren, H., Amador, K., Camicioli, R., Ismail, Z., Monchi, O., Forkert, N. (2024). Exploiting macro- and micro-structural brain changes for improved Parkinson’s disease classification from MRI data. NPJ Parkinson's Disease, 10(1). [More Information]
• Monchi, O., Pinilla-Monsalve, G., Almgren, H., Ghahremani, M., Kibreab, M., Maarouf, N., Kathol, I., Bore, A., Rheault, F., Descoteaux, M., et al (2024). White Matter Microstructural Underpinnings of Mild Behavioral Impairment in Parkinson's Disease. Movement Disorders, 39(6), 1026-1036. [More Information]

2023

• Camacho, M., Wilms, M., Mouches, P., Almgren, H., Souza, R., Camicioli, R., Ismail, Z., Monchi, O., Forkert, N. (2023). Explainable classification of Parkinson's disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets. NeuroImage: Clinical, 38. [More Information]
• Almgren, H., Camacho, M., Hanganu, A., Kibreab, M., Camicioli, R., Ismail, Z., Forkert, N., Monchi, O. (2023). Machine learning-based prediction of longitudinal cognitive decline in early Parkinson’s disease using multimodal features. Scientific Reports, 13(1). [More Information]
• Almgren, H., Hanganu, A., Camacho, M., Kibreab, M., Camicioli, R., Ismail, Z., Forkert, N., Monchi, O. (2023). Motor symptoms in Parkinson's disease are related to the interplay between cortical curvature and thickness. NeuroImage: Clinical, 37. [More Information]
• Tullo, M., Almgren, H., Van de Steen, F., Boccia, M., Bencivenga, F., Galati, G. (2023). Preferential signal pathways during the perception and imagery of familiar scenes: An effective connectivity study. Human Brain Mapping, 44(10), 3954-3971. [More Information]

2022

• Parsons, N., Steward, T., Clohesy, R., Almgren, H., Duehlmeyer, L. (2022). A systematic review of resting-state functional connectivity in obesity: Refining current neurobiological frameworks and methodological considerations moving forward. Reviews in Endocrine & Metabolic Disorders, 23(4), 861-879. [More Information]
• Tullo, M., Almgren, H., Van de Steen, F., Sulpizio, V., Marinazzo, D., Galati, G. (2022). Individual differences in mental imagery modulate effective connectivity of scene-selective regions during resting state. Brain Structure and Function, 227(5), 1831-1842. [More Information]
• Aerts, H., Colenbier, N., Almgren, H., Dhollander, T., Daparte, J., Clauw, K., Johri, A., Meier, J., Palmer, J., Schirner, M., et al (2022). Pre- and post-surgery brain tumor multimodal magnetic resonance imaging data optimized for large scale computational modelling. Scientific Data, 9(1). [More Information]

2020

• Van de Steen, F., Krebs, R., Colenbier, N., Almgren, H., Marinazzo, D. (2020). Effective connectivity modulations related to win and loss outcomes. NeuroImage, 207, 116369. [More Information]
• Almgren, H., Van de Steen, F., Razi, A., Friston, K., Marinazzo, D. (2020). The effect of global signal regression on DCM estimates of noise and effective connectivity from resting state fMRI. NeuroImage, 208. [More Information]

2019

• Van de Steen, F., Almgren, H., Razi, A., Friston, K., Marinazzo, D. (2019). Dynamic causal modelling of fluctuating connectivity in resting-state EEG. NeuroImage, 189, 476-484. [More Information]

2018

• Almgren, H., Van de Steen, F., Kühn, S., Razi, A., Friston, K., Marinazzo, D. (2018). Variability and reliability of effective connectivity within the core default mode network: A multi-site longitudinal spectral DCM study. NeuroImage, 183, 757-768. [More Information]