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RWTH Aachen University
Algorithms to understand default brain function

Abstract: One of the least expected findings from systems neuroscience is the "Default Mode Network". This macroscopical brain network has the highest metabolic consumption and the perhaps highest neuronal baseline activity. Functional processing in this network is associated with diverse human-defining psychological processes: complex social cognition, such as perspective-taking, language and moral judgment, as well as the imagination of events and places in future and past. At the same time, the default-mode network has been linked to a range of psychiatric disorders, including schizophrenia, autism and depression. Despite its anthropological significance, the (patho-)physiological function of this network remains essentially unknown. The alternative quantitative approaches into investigating the biology of the DMN will include semisupervised factored logistic regression, extended autoencoder architectures including L1 penalization, hierarchical tree sparsity for regularized high-dimensional prediction, transfer learning in multi-output deep models, and canonical correlation analysis with bootstrapped sensitivity analysis

Galen Ballentine
Drexel Medical School
Primer: Ways of Seeing the Brain's Default Mode Network

Abstract: What happens in the brain when the mind wanders? The surprising discovery of the default mode network came hand-in-hand with a trend toward analyzing intrinsic brain activity. Several imaging modalities have been used to isolate and analyze this network, its normal metabolism, development, and functional anatomy. Activations of the default mode network are associated with self-referential thinking, theories of mind, moral reasoning, and mental time travel, while perturbations of it are associated with psychiatric conditions such as PTSD, depression, autism, and Alzheimer's disease. A new language is emerging which describes both normal and pathological brain functions in terms of distributed networks of connectivity rather than discrete and specialized regions.