Neurorehabilitation and neural repair
Aug 1, 2017
BACKGROUND: Robots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning.
Neuron
Jul 19, 2017
The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better ...
IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Jul 1, 2017
Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder characterized by a persistence of social and communication impairment, and restricted and repetitive behaviors. However, motor disorders have also been described, but not ob...
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Jun 28, 2017
In recent years, an increasing number of studies have demonstrated that networks in the brain can self-organize into a critical state where dynamics exhibit a mixture of ordered and disordered patterns. This critical branching phenomenon is termed ne...
Journal of vision
Apr 1, 2017
What are the roles of central and peripheral vision in human scene recognition? Larson and Loschky (2009) showed that peripheral vision contributes more than central vision in obtaining maximum scene recognition accuracy. However, central vision is m...
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Jan 5, 2017
Even newborn infants are able to extract structure from a stream of sensory inputs; yet how this is achieved remains largely a mystery. We present a connectionist autoencoder model, TRACX2, that learns to extract sequence structure by gradually const...
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Jan 5, 2017
A growing literature suggests that the hippocampus is critical for the rapid extraction of regularities from the environment. Although this fits with the known role of the hippocampus in rapid learning, it seems at odds with the idea that the hippoca...
The Behavioral and brain sciences
Jan 1, 2017
We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of ...
The Behavioral and brain sciences
Jan 1, 2017
Machines that learn and think like people should simulate how people really think in their everyday lives. The field of artificial intelligence originally traveled down two roads, one of which emphasized abstract, idealized, rational thinking and the...
The Behavioral and brain sciences
Jan 1, 2017
Lake et al. suggest that current AI systems lack the inductive biases that enable human learning. However, Lake et al.'s proposed biases may not directly map onto mechanisms in the developing brain. A convergence of fields may soon create a correspon...