The connectomics of brain disorders
By Alex Fornito, Andrew Zalesky, Michael Breakspear. Nature Reviews Neuroscience, 2015
1,620 citations recorded by the source corpus.
Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/614092867fac6212818f9feb2183eeab19b3522e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
- Olaf Sporns
- Michael Breakspear
- Richard F. Betzel
- Andrew Zalesky
- D. Bassett
- Waldemar Karwowski
- Farzad Vasheghani Farahani
- Nichole R. Lighthall
In Radiology, Nuclear Medicine and Imaging
- Olaf Sporns
- Richard F. Betzel
- Andrew Zalesky
- Michael Breakspear
- Waldemar Karwowski
- Farzad Vasheghani Farahani
- Nichole R. Lighthall
- Daniel Rueckert
Citations in the corpus
- Criticality in the brain: A synthesis of neurobiology, models and cognition. (2017, background): “There is a growing focus in the imaging community on spontaneous (resting-state) fMRI data and the reproducible structures these reveal in health (Damoiseaux et al., 2006; Zalesky et al., 2014) and disease (Fornito et al., 2015).”
- Modular Brain Networks (2015, background): “The importance of modular brain networks for shaping brain dynamics is a strong motivation for ongoing empirical work examining changes in modularity associated with disturbances of brain function in clinical disorders (Fornito et al. 2015).”
- Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review (2019, background): “Recent advances in neuroimaging have enabled mapping of the human connectome in different applications (Van Essen et al., 2012; Fornito et al., 2015).”
- Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex (2017, background): “It has been common525 practice in recent neuroscience studies to explore several neurological (Tijms et al., 2013; Fornito et al., 2015) and neuro-developmental disorders (Jafri et al., 2008; Liu et al., 2008; Dennis et al., 2011; Fornito et al., 2012) from a network perspective.”
- Metric learning with spectral graph convolutions on brain connectivity networks (2018, background): “This is primarily due to the fact that associations between the topological organisation of these networks and brain development (Hagmann et al., 2010), function (Smith et al., 2015) as well as disease (Catani and ffytche, 2005; Fornito et al., 2015) have been established.”
- Graph Neural Networks in Network Neuroscience (2021, background): “However, this was demonstrated to be a computationally expensive task as it requires an intensive data acquisition and processing steps [14].”
- Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data (2018, background): “Functional connectivity and network measures derived from fMRI data have facilitated the study of the brain’s function during development, in aging (Bressler & Menon, 2010; Fox & Raichle, 2007; Raichle 2015), and in the context of various neurological disorders (Bullmore & Sporns, 2009, 2012; Fornit”