AIMC Topic: Cerebellum
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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...
New insights into olivo-cerebellar circuits for learning from a small training sample.
Current opinion in neurobiology
Aug 19, 2017
Artificial intelligence such as deep neural networks exhibited remarkable performance in simulated video games and 'Go'. In contrast, most humanoid robots in the DARPA Robotics Challenge fell down to ground. The dramatic contrast in performance is ma...
Using short-range and long-range functional connectivity to identify schizophrenia with a family-based case-control design.
Psychiatry research. Neuroimaging
Apr 24, 2017
Abnormal short-range and long-range functional connectivities (FCs) have been implicated in the neurophysiology of schizophrenia. This study was conducted to examine the potential of short-range and long-range FCs for differentiating the patients fro...
Detection of Mild Traumatic Brain Injury by Machine Learning Classification Using Resting State Functional Network Connectivity and Fractional Anisotropy.
Journal of neurotrauma
Nov 21, 2016
Traumatic brain injury (TBI) may adversely affect a person's thinking, memory, personality, and behavior. While mild TBI (mTBI) diagnosis is challenging, there is a risk for long-term psychiatric, neurologic, and psychosocial problems in some patient...
Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.
PloS one
May 23, 2016
Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate w...
A General Fuzzy Cerebellar Model Neural Network Multidimensional Classifier Using Intuitionistic Fuzzy Sets for Medical Identification.
Computational intelligence and neuroscience
May 19, 2016
The diversity of medical factors makes the analysis and judgment of uncertainty one of the challenges of medical diagnosis. A well-designed classification and judgment system for medical uncertainty can increase the rate of correct medical diagnosis....
Machine Learning Capabilities of a Simulated Cerebellum.
IEEE transactions on neural networks and learning systems
Jan 26, 2016
This paper describes the learning and control capabilities of a biologically constrained bottom-up model of the mammalian cerebellum. Results are presented from six tasks: 1) eyelid conditioning; 2) pendulum balancing; 3) proportional-integral-deriva...
Real-Time Simulation of Passage-of-Time Encoding in Cerebellum Using a Scalable FPGA-Based System.
IEEE transactions on biomedical circuits and systems
Oct 6, 2015
The cerebellum plays a critical role for sensorimotor control and learning. However, dysmetria or delays in movements' onsets consequent to damages in cerebellum cannot be cured completely at the moment. Neuroprosthesis is an emerging technology that...
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