AIMC Topic: Cerebellum
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Machine learning identifies "rsfMRI epilepsy networks" in temporal lobe epilepsy.
European radiology
Feb 8, 2019
OBJECTIVES: Experimental models have provided compelling evidence for the existence of neural networks in temporal lobe epilepsy (TLE). To identify and validate the possible existence of resting-state "epilepsy networks," we used machine learning met...
Clinical applications of control systems models: The neural integrators for eye movements.
Progress in brain research
Feb 8, 2019
The first models that were proposed to account for the neural control of eye movements applied a classic control systems approach, including feedback, and measured system responses to sinusoidal and transient stimuli. Although such models provided ma...
Control of a Humanoid NAO Robot by an Adaptive Bioinspired Cerebellar Module in 3D Motion Tasks.
Computational intelligence and neuroscience
Jan 27, 2019
A bioinspired adaptive model, developed by means of a spiking neural network made of thousands of artificial neurons, has been leveraged to control a humanoid NAO robot in real time. The learning properties of the system have been challenged in a cla...
Proprioceptive Recognition with Artificial Neural Networks Based on Organizations of Spinocerebellar Tract and Cerebellum.
International journal of neural systems
Dec 9, 2018
Muscle kinematics and kinetics are nonlinearly encoded by proprioceptors, and the changes in muscle length and velocity are integrated into Ia afferent. Besides, proprioceptive signals from multiple muscles are probably mixed in afferent pathways, wh...
Control of a muscle-like soft actuator via a bioinspired approach.
Bioinspiration & biomimetics
Oct 9, 2018
Soft actuators have played an indispensable role in generating compliant motions of soft robots. Among the various soft actuators explored for soft robotic applications, dielectric elastomer actuators (DEAs) have caught the eye with their intriguing ...
Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.
NeuroImage
Aug 9, 2018
The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is importan...
A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks.
NeuroImage
May 21, 2018
Deep neural networks are increasingly being used in both supervised learning for classification tasks and unsupervised learning to derive complex patterns from the input data. However, the successful implementation of deep neural networks using neuro...
Dynamic functional network connectivity discriminates mild traumatic brain injury through machine learning.
NeuroImage. Clinical
Mar 15, 2018
Mild traumatic brain injury (mTBI) can result in symptoms that affect a person's cognitive and social abilities. Improvements in diagnostic methodologies are necessary given that current clinical techniques have limited accuracy and are solely based ...
Artificial intelligence in neurodegenerative disease research: use of IBM Watson to identify additional RNA-binding proteins altered in amyotrophic lateral sclerosis.
Acta neuropathologica
Nov 13, 2017
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease with no effective treatments. Numerous RNA-binding proteins (RBPs) have been shown to be altered in ALS, with mutations in 11 RBPs causing familial forms of the disease, a...
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
Oct 9, 2017
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...
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