The second edition of this comprehensive textbook for students of Neuropsychology gives a
thorough overview of the complex relationship between brain and behaviour. With an …

Connectionist models can be characterized within the more general framework of
probabilistic graphical models, which allow to efficiently describe complex statistical …

In this review, we describe our recent attempts to model the neural correlates of visual
perception with biologically inspired networks of spiking neurons, emphasizing the …

A quintessential challenge for any perceptual system is the need to focus on task-relevant
information without being blindsided by unexpected, yet important information. The human …

Here we examine the plausibility of deep convolutional neural networks (CNNs) as a
theoretical framework for understanding biological vision in the context of image …

We tested the hypothesis that modulation of neurocomputational inputs to value-based
decision-making affects the rationality of economic choices. The brain's right temporoparietal …

For 50 years or so, visual search experiments have been used to examine how humans find
behaviourally relevant objects in complex visual scenes. For the same length of time, there …

Spontaneous trait inference (STI) and trait transference (STT) refer to the inference of
personality traits from behaviors. in STI the inferred trait is attached to the actor, and in STT it …

We present an extension of a neurobiologically inspired robotics model, termed CoRLEGO
(Choice reaching with a LEGO arm robot). CoRLEGO models experimental evidence from …

The selective attention for identification model (SAIM) is an established model of selective
visual attention. SAIM implements translation-invariant object recognition, in scenes with …