ANNarchy (Artificial Neural Networks architect) is a general-purpose parallel neuro-simulator for rate-coded or spiking neural networks.
The Basal Ganglia (BG) are the main nuclei involved in reinforcement learning processes in the brain and allow a variety of cognitive functions such as working memory, decision making and action selection.
Deep neural networks and their applications to emotion recognition, attention, sensor fusion...
Modeling the dopaminergic system (VTA, SNc), its afferent system and its influence on the basal ganglia, prefrontal cortex and hippocampus.
The hippocampus is a key structure for mnemonic processes (episodic memory) and spatial navigation. Its importance in model-based behavior is increasingly recognized.
Reinforcement Learning (RL) is a machine learning framework studying how to derive optimal policies from reward signals. Coupled with deep neural networks, it became the most promising approach to artificial intelligence.
Reservoir computing studies the dynamical properties of recurrently connected populations of neurons. Their rich dynamics allow to represent and learn complex tasks currently out of reach of the classical machine learning methods, but also allow to better understand brain activities.