Visual search, a vital task for humans and animals, has also become a common and
important tool for studying many topics central to active vision and cognition ranging from …

Deep neural networks (DNNs) have become powerful and increasingly ubiquitous tools to
model human cognition, and often produce similar behaviors. For example, with their …

We begin by reviewing the statistical framework of information theory as applicable to
neuroimaging data analysis. A major factor hindering wider adoption of this framework in …

According to signal detection theoretical analyses, visual signals occurring at a cued
location are detected more accurately, whereas frequently occurring ones are reported more …

Many of the commonly used methods for modeling and fitting psychophysical data are
special cases of statistical procedures of great power and generality, notably the …

The notion of 'interpretability'of artificial neural networks (ANNs) is of growing importance in
neuroscience and artificial intelligence (AI). But interpretability means different things to …

In any given perceptual task, the visual system selectively weighs or filters incoming
information. The particular set of weights or filters form a kind of template, which reveals the …

The success of human cooperation crucially depends on mechanisms enabling individuals
to detect unreliability in their conspecifics. Yet, how such epistemic vigilance is achieved …

Human listeners excel at forming high-level social representations about each other, even
from the briefest of utterances. In particular, pitch is widely recognized as the auditory …

Due to the inhomogenous visual representation across the visual field, humans use
peripheral vision to select objects of interest and foveate them by saccadic eye movements …