All network dynamics emerge from the complex interaction between the intrinsic membrane properties of network neurons and their synaptic connections. Nervous systems contain numer...
This article throws new light on the possible role of synapses in information transmission through theoretical analysis and computer simulations. We show that the internal dynamic...
Self-organizing maps (SOMs) are widely used in several fields of application, from neurobiology to multivariate data analysis. In that context, this paper presents variants of the...
It has recently been suggested that the nervous system employs forward models for the purpose of motor control. The evidence for this hypothetical computational structure comes fr...
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
In the temporal difference model of primate dopamine neurons, their phasic activity reports a prediction error for future reward. This model is supported by a wealth of experiment...
We propose a new scheme for enlarging generalized learning vector quantization (GLVQ) with weighting factors for the input dimensions. The factors allow an appropriate scaling of ...
The prefrontal cortex (PFC) is essential for working memory, which is the ability to transiently hold and manipulate information necessary for generating forthcoming action. PFC n...