Sensory cortices display a suite of ubiquitous dynamical features, such as ongoing noise
variability, transient overshoots and oscillations, that have so far escaped a common, principled …

In real-life applications, machine learning models often face scenarios where there is a
change in data distribution between training and test domains. When the aim is to make …

A plethora of work has shown that AI systems can systematically and unfairly be biased against
certain populations in multiple scenarios. The field of medical imaging, where AI systems …

Generating functionals may guide the evolution of a dynamical system and constitute a
possible route for handling the complexity of neural networks as relevant for computational …

Neural networks are required to meet significant metabolic demands associated with performing
sophisticated computational tasks in the brain. The necessity for efficient transmission of …

In recent years the development of artificial intelligence (AI) for medical image analysis has
gained enormous momentum. At the same time, a large body of work has shown that AI …

In 2006, Ma et al. presented an elegant theory for how populations of neurons might
represent uncertainty to perform Bayesian inference. Critically, according to this theory, neural …

Spontaneous brain activity is characterized in part by a balanced asynchronous chaotic
state. Cortical recordings show that excitatory (E) and inhibitory (I) drivings in the EI balanced …

We present an effective model for timing-dependent synaptic plasticity (STDP) in terms of
two interacting traces, corresponding to the fraction of activated NMDA receptors and the …

Theories for autism spectrum disorder (ASD) have been formulated at different levels, ranging
from physiological observations to perceptual and behavioral descriptions. Understanding …