AI Medical Compendium Topic:
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Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatiotemporal Scales RNN Model.

Neural computation
This letter proposes a novel predictive coding type neural network model, the predictive multiple spatiotemporal scales recurrent neural network (P-MSTRNN). The P-MSTRNN learns to predict visually perceived human whole-body cyclic movement patterns b...

Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks.

International journal of neural systems
One of the greatest challenges in data mining is related to processing and analysis of massive data streams. Contrary to traditional static data mining problems, data streams require that each element is processed only once, the amount of allocated m...

Fuzzy neuronal model of motor control inspired by cerebellar pathways to online and gradually learn inverse biomechanical functions in the presence of delay.

Biological cybernetics
Contrary to forward biomechanical functions, which are deterministic, inverse biomechanical functions are generally not. Calculating an inverse biomechanical function is an ill-posed problem, which has no unique solution for a manipulator with severa...

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear "mixed...

Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability.

Nature communications
If a three-dimensional physical electronic system emulating synapse networks could be built, that would be a significant step toward neuromorphic computing. However, the fabrication complexity of complementary metal-oxide-semiconductor architectures ...

The Ugly Truth About Ourselves and Our Robot Creations: The Problem of Bias and Social Inequity.

Science and engineering ethics
Recently, there has been an upsurge of attention focused on bias and its impact on specialized artificial intelligence (AI) applications. Allegations of racism and sexism have permeated the conversation as stories surface about search engines deliver...

ASD+M: Automatic parameter tuning in stochastic optimization and on-line learning.

Neural networks : the official journal of the International Neural Network Society
In this paper the classic momentum algorithm for stochastic optimization is considered. A method is introduced that adjusts coefficients for this algorithm during its operation. The method does not depend on any preliminary knowledge of the optimizat...

Parsing learning in networks using brain-machine interfaces.

Current opinion in neurobiology
Brain-machine interfaces (BMIs) define new ways to interact with our environment and hold great promise for clinical therapies. Motor BMIs, for instance, re-route neural activity to control movements of a new effector and could restore movement to pe...

Leg-local neural mechanisms for searching and learning enhance robotic locomotion.

Biological cybernetics
Adapting motor output based on environmental forces is critical for successful locomotion in the real world. Arthropods use at least two neural mechanisms to adjust muscle activation while walking based on detected forces. Mechanism 1 uses negative f...

Developmental Approach for Behavior Learning Using Primitive Motion Skills.

International journal of neural systems
Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet t...