Recent studies have shown that biologically inspired Spiking Neural Networks (SNNs) has
potentials for the mobile robot controls. Based on SNNs, an autonomous learning paradigm …

Asynchrony, overlaps, and delays in sensory–motor signals introduce ambiguity as to which
stimuli, actions, and rewards are causally related. Only the repetition of reward episodes …

Reward-modulated spike timing dependent plasticity (STDP) combines unsupervised STDP
with a reinforcement signal that modulates synaptic changes. It was proposed as a learning …

Neural networks with a single plastic layer employing reward modulated spike time
dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we …

Elucidating the relative involvement of individual dopamine receptor subtypes in the
regulation of behavior has been made difficult by anomalies at the psychopharmacology …

The integration of modulatory neurons into evolutionary artificial neural networks is
proposed here. A model of modulatory neurons was devised to describe a plasticity …

Dopamine exerts its action through membrane receptors that belong to the seven
transmembrane domains (7TM) G protein-coupled receptor family. The dopamine receptor …

Humans and other animals share choice preference for smaller-but-sooner over later-but-
larger rewards, indicating that the subjective value of a reward is discounted as a function of …

Through The NTNU Cyborg initiative, a cybernetic (bio-robotic) organism is currently under
development. Using neural tissue, cultured on a microelectrode array (MEA), the goal is to …

Activation of midbrain dopamine systems is thought to be critically involved in the addictive
properties of abused substances. Drugs of abuse increase dopamine release in the nucleus …