Aug 2026· Progress in Neuro-psychopharmacology and Biological Psychiatry· pp.
111883
· 0 citations· 66 references
Medicine
TL;DR
This study provides a dimensional framework for understanding the neurobiological organization of behavioral dysregulation in addiction by demonstrating that distinct dimensions of disinhibition in CUD are associated with partially overlapping but largely separable structural connectome architectures.
Abstract
The transdiagnostic dimensional framework implicates disinhibition as a core dimension associated with cocaine use disorder (CUD) and broader externalizing psychopathology. However, accumulating evidence suggests that disinhibition comprises multiple partially dissociable dimensions. It remains unclear how these dimensions manifest in CUD and whether they are supported by distinct neural architectures. Here, we combined self-report measures, structured clinical assessments, and behavioral tasks to characterize multidimensional disinhibition in individuals with CUD. Connectome-based predictive modeling and graph-theoretical analyses were subsequently employed to identify structural connectome patterns associated with distinct disinhibition dimensions. Exploratory factor analysis revealed two partially dissociable dimensions of disinhibition associated with CUD: trait and cognitive disinhibition. These dimensions showed largely distinct structural connectivity signatures, with only a single overlapping positive predictive connection linking the left amygdala and the right medial prefrontal cortex. Cognitive disinhibition was associated with a distributed positive predictive connectivity pattern spanning multiple large-scale systems, with prominent contributions from visual, somatomotor, default mode, and subcortical networks. In contrast, trait disinhibition was characterized by a negative predictive network involving reduced structural connectivity between somatomotor and control systems, as well as increased nodal clustering coefficients across multiple large-scale networks. Together, these findings demonstrate that distinct dimensions of disinhibition in CUD are associated with partially overlapping but largely separable structural connectome architectures. By moving beyond a unitary conceptualization of disinhibition, this study provides a dimensional framework for understanding the neurobiological organization of behavioral dysregulation in addiction.
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoption of Agile methods in general, and Scrum in particular. Little, if anything, is empirically known about the application and adoption of Scrum in a multi-team and multi-project situation. The authors carried out an ethnographically informed longitudinal case study in industrial settings and closely followed how the Scrum method was adopted in a 20-person department, working in a simultaneous multi-project R&D environment. Altogether 10 challenges pertinent to the case of multi-team multi-project Scrum adoption were identified in the study. The authors contend that these results carry great relevance for other industrial teams. Future research avenues arising from the study are indicated.
A. Marchenko, P. Abrahamsson· Agile Conference· 59 citations· ⚡11
A comprehensive taxonomy of the challenges faced when a medium-scale organization decided to adopt software platforms is provided, namely: business challenges, organizational challenges, technical challenges, and people challenges.
Yaser Ghanam, F. Maurer, P. Abrahamsson· Information and Software Tec...· 41 citations· ⚡3
It is shown that high article processing charges are not sufficiently justified by the publishers, which often lack transparency and may prevent authors from adopting OA.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· Scientometrics· 21 citations· ⚡1
MCGLPPI, a novel geometric representation learning framework that combines graph neural networks (GNNs) with the MARTINI molecular coarse-grained (CG) model to predict overall PPI properties accurately and efficiently, offers an effective and efficient solution for PPI overall property predictions.
Yang Yue, Shu Li, Yihua Cheng et al.· bioRxiv· 15 citations
PepPCBench enables a robust evaluation of PFNN-based methods and supports their continued development for peptide-protein structure prediction, and highlights the influence of peptide length, conformational flexibility, and training set similarity on prediction accuracy.
Si-Long Zhai, Huifeng Zhao, Ji-Ke Wang et al.· Journal of Chemical Informat...· 13 citations· ⚡1
OmniMol is presented, a framework using hypergraphs to improve predictions of molecular properties, addressing challenges of imperfect data annotation and enhancing model explainability, and achieves state-of-the-art performance in properties prediction.
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.