Our incomplete understanding of the link between Alzheimer's Disease pathology and
symptomatology is a crucial obstacle for therapeutic success. Recently, translational studies …

Individual variability has clear effects upon the outcome of therapies and treatment
approaches. The customization of healthcare options to the individual patient should …

The human brain is arguably one of the most complex systems in nature. To understand how
it operates, it is essential to understand the link between neural activity and behavior …

Despite the importance and frequent use of Bayesian frameworks in brain network modeling
for parameter inference and model prediction, the advanced sampling algorithms …

Cortical network structure has been extensively characterized at the level of local circuits
and in terms of long-range connectivity, but seldom in a manner that integrates both of these …

Brain tumor patients scheduled for tumor resection often face significant uncertainty, as the
outcome of neurosurgery is difficult to predict at the individual patient level. Recently …

Auditory evoked fields (AEFs) are commonly studied, yet their underlying neural
mechanisms remain poorly understood. Here, we used the biophysical modelling software …

Variability of neural signaling is an important index of healthy brain functioning, as is signal
complexity, which relates to information processing capacity. Alterations in variability and …

A key challenge for neuroscience is to develop generative, causal models of the human
nervous system in an individualized, data-driven manner. Previous initiatives have either …

Connectomics data from animal models provide an invaluable opportunity to reveal the
complex interplay between structure and function in the mammalian brain. In this work, we …