Variational inference: A review for statisticians
One of the core problems of modern statistics is to approximate difficult-to-compute
probability densities. This problem is especially important in Bayesian statistics, which …
probability densities. This problem is especially important in Bayesian statistics, which …
TAPAS: an open-source software package for translational neuromodeling and computational psychiatry
Psychiatry faces fundamental challenges with regard to mechanistically guided differential
diagnosis, as well as prediction of clinical trajectories and treatment response of individual …
diagnosis, as well as prediction of clinical trajectories and treatment response of individual …
Glioblastoma remodelling of human neural circuits decreases survival
Gliomas synaptically integrate into neural circuits,. Previous research has demonstrated
bidirectional interactions between neurons and glioma cells, with neuronal activity driving …
bidirectional interactions between neurons and glioma cells, with neuronal activity driving …
Sparse Bayesian learning for end-to-end EEG decoding
Decoding brain activity from non-invasive electroencephalography (EEG) is crucial for brain-
computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG …
computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG …
MEG and EEG data analysis with MNE-Python
Magnetoencephalography and electroencephalography (M/EEG) measure the weak
electromagnetic signals generated by neuronal activity in the brain. Using these signals to …
electromagnetic signals generated by neuronal activity in the brain. Using these signals to …
MNE software for processing MEG and EEG data
Magnetoencephalography and electroencephalography (M/EEG) measure the weak
electromagnetic signals originating from neural currents in the brain. Using these signals to …
electromagnetic signals originating from neural currents in the brain. Using these signals to …
[HTML][HTML] Good practice for conducting and reporting MEG research
Magnetoencephalographic (MEG) recordings are a rich source of information about the
neural dynamics underlying cognitive processes in the brain, with excellent temporal and …
neural dynamics underlying cognitive processes in the brain, with excellent temporal and …
Informatics and data mining tools and strategies for the human connectome project
DS Marcus, J Harwell, T Olsen, M Hodge… - Frontiers in …, 2011 - frontiersin.org
The Human Connectome Project (HCP) is a major endeavor that will acquire and analyze
connectivity data plus other neuroimaging, behavioral, and genetic data from 1,200 healthy …
connectivity data plus other neuroimaging, behavioral, and genetic data from 1,200 healthy …
Deep neural networks constrained by neural mass models improve electrophysiological source imaging of spatiotemporal brain dynamics
Many efforts have been made to image the spatiotemporal electrical activity of the brain with
the purpose of mapping its function and dysfunction as well as aiding the management of …
the purpose of mapping its function and dysfunction as well as aiding the management of …
Modalities, modes, and models in functional neuroimaging
KJ Friston - Science, 2009 - science.org
In this, the 21st century, human-brain mapping celebrates 21 years of cognitive activation
studies. This review looks at imaging neuroscience and key ideas it has pursued; some …
studies. This review looks at imaging neuroscience and key ideas it has pursued; some …