Jaldert O. Rombouts

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A key function of brains is undoubtedly the abstraction and maintenance of information from the environment for later use. Neurons in association cortex play an important role in this process: by learning these neurons become tuned to relevant features and represent the information that is required later as a persistent elevation of their activity [1]. It(More)
Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we(More)
Spontaneous and drug-induced (haloperidol, apomorphine, and amphetamine) motor activity of rats was measured simultaneously via two distinct and independent methods: the classical optical scanning technique and a new procedure based on the piezo-electric principle. The latter procedure measured animal-induced mechanical vibrations of a flexible cage floor(More)
Working memory is a key component of intelligence that the brain implements as persistent neural activations. How do persistent neurons learn to store information, and how can they be made to forget this information once it is no longer relevant? When animals learn episodic tasks, neurons in prefrontal cortex learn to represent task ends. We show that a(More)
Many theories propose that top-down attentional signals control processing in sensory cortices by modulating neural activity. But who controls the controller? Here we investigate how a biologically plausible neural reinforcement learning scheme can create higher order representations and top-down attentional signals. The learning scheme trains neural(More)
How does the brain learn to map multi-dimensional sensory inputs to multi-dimensional motor outputs when it can only observe single rewards for the coordinated outputs of the whole network of neurons that make up the brain? We introduce Multi-AGREL, a novel, biologically plausible multi-layer neural network model for multi-dimensional reinforcement(More)
Humans and animals have the ability to perform very precise movements to obtain rewards. For instance, it is no problem at all to pick up a mug of coffee from your desk while you are working. Unfortunately, it is unknown how exactly the non-linear mapping between sensory inputs (e.g. your mug on the retina) and the correct motor actions (e.g. a set of joint(More)
We formulate and analyze a simple dynamical systems model for climate–vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in(More)