Digital embryos: a novel technical approach to investigate perceptual categorization in pigeons (Columba livia) using machine learning.

Pigeons are classic model animals to study perceptual category learning. To achieve a deeper understanding of the cognitive mechanisms of categorization, a careful consideration of the employed stimulus material and a thorough analysis of the choice behavior is mandatory. In the present study, we combined the use of "virtual phylogenesis", an evolutionary algorithm to generate artificial yet naturalistic stimuli termed digital embryos and a machine learning approach on the pigeons' pecking responses to gain insight into the underlying categorization strategies of the animals.

Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia).

Recognizing and categorizing visual stimuli are cognitive functions vital for survival, and an important feature of visual systems in primates as well as in birds. Visual stimuli are processed along the ventral visual pathway. At every stage in the hierarchy, neurons respond selectively to more complex features, transforming the population representation of the stimuli.

The neuroscience of perceptual categorization in pigeons: A mechanistic hypothesis.

We are surrounded by an endless variation of objects. The ability to categorize these objects represents a core cognitive competence of humans and possibly all vertebrates. Research on category learning in nonhuman animals started with the seminal studies of Richard Herrnstein on the category "human" in pigeons.

Specific barriers to the conduct of randomised clinical trials on medical devices.

Background: Medical devices play an important role in the diagnosis, prevention, treatment and care of diseases. However, compared to pharmaceuticals, there is no rigorous formal regulation for demonstration of benefits and exclusion of harms to patients. The medical device industry argues that the classical evidence hierarchy cannot be applied for medical devices, as randomised clinical trials are impossible to perform.

Categories in the pigeon brain: A reverse engineering approach.

Pigeons are well known for their visual capabilities as well as their ability to categorize visual stimuli at both the basic and superordinate level. We adopt a reverse engineering approach to study categorization learning: Instead of training pigeons on predefined categories, we simply present stimuli and analyze neural output in search of categorical clustering on a solely neural level. We presented artificial stimuli, pictorial and grating stimuli, to pigeons without the need of any differential behavioral responding while recording from the nidopallium frontolaterale (NFL), a higher visual area in the avian brain.