Multivariate pattern analysis (MVPA) or brain decoding methods have become standard
practice in analyzing fMRI data. Although decoding methods have been extensively applied …

Abstract Machine learning has enhanced the abilities of neuroscientists to interpret
information collected through EEG, fMRI, and MEG data. With these powerful techniques …

BACKGROUND The coronavirus disease 2019 (COVID-19) rapidly progressed to a global
pandemic. Although some patients totally recover from COVID-19 pneumonia, the disease's …

The most widely used task functional magnetic resonance imaging (fMRI) analyses use
parametric statistical methods that depend on a variety of assumptions. In this work, we use …

Abstract Analysis and interpretation of neuroimaging datasets has become a
multidisciplinary endeavor, relying not only on statistical methods, but increasingly on …

A critical issue in many neuroimaging studies is the comparison between brain maps.
Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or …

Microglia, the specialized innate immune cells of the CNS, play crucial roles in neural
development and function. Different phenotypes and functions have been ascribed to rodent …

Our capacity to jointly represent information about the world underpins our social
experience. By leveraging one individual's brain activity to model another's, we can measure …

Cognitive impairment is one of the most prevalent symptoms of post Severe Acute
Respiratory Syndrome COronaVirus 2 (SARS-CoV-2) state, which is known as Long COVID …

Despite a growing body of research suggesting that task-based functional magnetic
resonance imaging (fMRI) studies often suffer from a lack of statistical power due to too …