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Models, Neurological

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Modeling the motor cortex: Optimality, recurrent neural networks, and spatial dynamics.

Neuroscience research
Specialization of motor function in the frontal lobe was first discovered in the seminal experiments by Fritsch and Hitzig and subsequently by Ferrier in the 19th century. It is, however, ironical that the functional and computational role of the mot...

Learning to Estimate Dynamical State with Probabilistic Population Codes.

PLoS computational biology
Tracking moving objects, including one's own body, is a fundamental ability of higher organisms, playing a central role in many perceptual and motor tasks. While it is unknown how the brain learns to follow and predict the dynamics of objects, it is ...

Novel plasticity rule can explain the development of sensorimotor intelligence.

Proceedings of the National Academy of Sciences of the United States of America
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, ...

Off-line simulation inspires insight: A neurodynamics approach to efficient robot task learning.

Neural networks : the official journal of the International Neural Network Society
There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in c...

Goal-oriented robot navigation learning using a multi-scale space representation.

Neural networks : the official journal of the International Neural Network Society
There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nat...

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications.

Neural networks : the official journal of the International Neural Network Society
The paper describes a new type of evolving connectionist systems (ECOS) called evolving spatio-temporal data machines based on neuromorphic, brain-like information processing principles (eSTDM). These are multi-modular computer systems designed to de...

Spatially regularized machine learning for task and resting-state fMRI.

Journal of neuroscience methods
BACKGROUND: Reliable mapping of brain function across sessions and/or subjects in task- and resting-state has been a critical challenge for quantitative fMRI studies although it has been intensively addressed in the past decades.

Expanding the role of striatal cholinergic interneurons and the midbrain dopamine system in appetitive instrumental conditioning.

Journal of neurophysiology
The basal ganglia are a collection of subcortical nuclei thought to underlie a wide variety of vertebrate behavior. Although a great deal is known about the functional and physiological properties of the basal ganglia, relatively few models have been...

Enhancement of Spike-Timing-Dependent Plasticity in Spiking Neural Systems with Noise.

International journal of neural systems
Synaptic plasticity is widely recognized to support adaptable information processing in the brain. Spike-timing-dependent plasticity, one subtype of plasticity, can lead to synchronous spike propagation with temporal spiking coding information. Recen...