Making inferences from behaviour to cognition is problematic due to a many-to-one map**
problem, in which any one behaviour can be generated by multiple possible cognitive …

The advent of Vision Language Models (VLM) has allowed researchers to investigate the
visual understanding of a neural network using natural language. Beyond object …

Vision-Language Models (VLMs) are trained on vast amounts of data captured by humans
emulating our understanding of the world. However, known as visual illusions, human's …

Visual illusions provide valuable insights into the brain's interpretation of the world given
sensory inputs. However, the precise manner in which brain activity translates into illusory …

The contrast sensitivity function (CSF) is a fundamental signature of the visual system that
has been measured extensively in several species. It is defined by the visibility threshold for …

Three decades ago, Atick et al. suggested that human frequency sensitivity may emerge
from the enhancement required for a more efficient analysis of retinal images. Here we …

Bistable images, also known as ambiguous or reversible images, present visual stimuli that
can be seen in two distinct interpretations, though not simultaneously by the observer. In this …

It has been demonstrated many times that the behavior of the human visual system is
connected to the statistics of natural images. Since machine learning relies on the statistics …

Photoacoustic (PA) imaging is hybrid imaging modality with good optical contrast and spatial
resolution. Portable, cost‐effective, smaller footprint light emitting diodes (LEDs) are rapidly …

Deep neural networks (DNNs) have revolutionized computer science and are now widely
used for neuroscientific research. A hot debate has ensued about the usefulness of DNNs as …