In search of the neural circuits of intrinsic motivation
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Whether we prepare a coffee or navigate to a shop: in many tasks we make multiple decisions before reaching a goal. Learning such state-action sequences from sparse reward raises the problem of credit-assignment: which actions out of a long sequence should ...
Our brain continuously self-organizes to construct and maintain an internal representation of the world based on the information arriving through sensory stimuli. Remarkably, cortical areas related to different sensory modalities appear to share the same f ...
Dopamine released from midbrain neurons is an important neuromodulatory signal during associative learning in many forebrain circuits. One model of associative learning is auditory cued fear learning, during which an innocuous sensory percept like a tone ( ...
Neuromorphic systems provide brain-inspired methods of computing. In a neuromorphic architecture, inputs are processed by a network of neurons receiving operands through synaptic interconnections, tuned in the process of learning. Neurons act simultaneousl ...
Everybody knows what it feels to be surprised. Surprise raises our attention and is crucial for learning. It is a ubiquitous concept whose traces have been found in both neuroscience and machine learning. However, a comprehensive theory has not yet been de ...
Imaging systems can be designed using examples and methods similar to the techniques used in deep learning. We describe experimental results demonstrating optical tomography based on the learning approach. ...
After decades of public or private vertically integrated monopolies, the organisation of the European railway sector was re-structured. The European Commission has been seeking to improve the efficiency of the railways to strengthen the position of railway ...
Reinforcement learning is a type of supervised learning, where reward is sparse and delayed. For example in chess, a series of moves is made until a sparse reward (win, loss) is issued, which makes it impossible to evaluate the value of a single move. Stil ...
Purpose of review Mild cognitive impairment (MCI) is a comorbid factor in Parkinson's disease. The aim of this review is to examine the recent neuroimaging findings in the search for Parkinson's disease MCI (PD-MCI) biomarkers to gain insight on whether MC ...
How do animals learn to repeat behaviors that lead to the obtention of food or other “rewarding” objects? As a biologically plausible paradigm for learning in spiking neural networks, spike-timing dependent plasticity (STDP) has been shown to perform well ...