Equilibrium propagation (EP) is an alternative to backpropagation (BP) that allows the
training of deep neural networks with local learning rules. It thus provides a compelling …

The experimental study of learning and plasticity has always been driven by an implicit
question: how can physiological changes be adaptive and improve performance? For …

Energy-based learning algorithms have recently gained a surge of interest due to their
compatibility with analog (post-digital) hardware. Existing algorithms include contrastive …

Neural coding has traditionally been examined through changes in firing rates and latencies
in response to different stimuli,,,–. However, populations of neurons can also exhibit …

Attentional priming has a dominating influence on vision, speeding visual search, releasing
items from crowding, reducing masking effects, and during free-choice, primed targets are …

Equilibrium propagation (EP) is a compelling alternative to the backpropagation of error
algorithm (BP) for computing gradients of neural networks on biological or analog …

The sub-regions of the hippocampal formation are essential for episodic learning and
memory formation, yet the spike dynamics of each region contributing to this function are …

Abstract Theory suggest that networks of neurons may predict their input. Prediction may
underlie most aspects of information processing and is believed to be involved in motor and …

The human brain is a prediction device, a view widely accepted in neuroscience. Prediction
is a rational and efficient response that relies on the brain's ability to create and employ …

This article presents an overview of a theory for performing temporal smoothing on temporal
signals in such a way that:(i) temporally smoothed signals at coarser temporal scales are …