It is suggested that edge based controllability captures circuit level properties relevant to treatment response and may inform personalized neuromodulation strategies.
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD), yet variability in treatment response remains a significant challenge. Network control theory provides a framework to quantify how brain networks facilitate state transitions, but prior work has focused primarily on node level metrics. Here, I investigate whether edge based controllability of the structural connectome is associated with rTMS outcomes. Twenty five patients with treatment-resistant depression underwent diffusion MRI prior to a five week course of high frequency rTMS targeting the dorsolateral prefrontal cortex. Structural connectomes were constructed using MRtrix3 and the Destrieux atlas, and edge based controllability metrics were computed at baseline. Controllability of specific middle frontal gyrus centered edges showed significant associations with changes in HAMD-24 scores, including connections to the superior frontal gyrus, hippocampus, angular gyrus, and orbital gyrus (r = -(0.470–0.597), p < 0.05). These findings suggest that edge based controllability captures circuit level properties relevant to treatment response and may inform personalized neuromodulation strategies.
This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 727 citations· ⚡54
The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.
M. Pikkarainen, Jukka Haikara, O. Salo et al.· Empirical Software Engineeri...· 401 citations· ⚡48
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
The perception of the impact of agile methods is predominantly positive, and several challenge areas were discovered, but based on this study, agile methods are here to stay.
M. Laanti, O. Salo, P. Abrahamsson· Information and Software Tec...· 260 citations· ⚡20
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.