Brain Effective Connectome based on fMRI and DTI Data: Bayesian Causal Learning and Assessment

Autor: Bagheri, Abdolmahdi, Dehshiri, Mahdi, Bagheri, Yamin, Akhondi-Asl, Alireza, Araabi, Babak Nadjar

Neuroscientific studies aim to find an accurate and reliable brain Effective Connectome (EC). Although current EC discovery methods have contributed to our understanding of brain organization, their performances are severely constrained by the short

Externí odkaz: http://arxiv.org/abs/2302.05451

Brain effective connectome based on fMRI and DTI data: Bayesian causal learning and assessment.

Autor: Bagheri A; School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran., Dehshiri M; School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran., Bagheri Y; Department of Psychology, Faculty of Psychology and Education, University of Tehran, Tehran, Iran., Akhondi-Asl A; Department of Anaesthesia, Harvard Medical School, Boston, Massachusetts, United States of America., Nadjar Araabi B; School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Publikováno v: PloS one [PLoS One] 2023 Aug 18; Vol. 18 (8), pp. e0289406. Date of Electronic Publication: 2023 Aug 18 (Print Publication: 2023).