AI Medical Compendium Topic:
Models, Neurological

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Atoms of recognition in human and computer vision.

Proceedings of the National Academy of Sciences of the United States of America
Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have s...

Cortical Transformation of Spatial Processing for Solving the Cocktail Party Problem: A Computational Model(1,2,3).

eNeuro
In multisource, "cocktail party" sound environments, human and animal auditory systems can use spatial cues to effectively separate and follow one source of sound over competing sources. While mechanisms to extract spatial cues such as interaural tim...

A Simple fMRI Compatible Robotic Stimulator to Study the Neural Mechanisms of Touch and Pain.

Annals of biomedical engineering
This paper presents a simple device for the investigation of the human somatosensory system with functional magnetic imaging (fMRI). PC-controlled pneumatic actuation is employed to produce innocuous or noxious mechanical stimulation of the skin. Sti...

Multivariate pattern classification of pediatric Tourette syndrome using functional connectivity MRI.

Developmental science
Tourette syndrome (TS) is a developmental neuropsychiatric disorder characterized by motor and vocal tics. Individuals with TS would benefit greatly from advances in prediction of symptom timecourse and treatment effectiveness. As a first step, we ap...

Machine Learning Capabilities of a Simulated Cerebellum.

IEEE transactions on neural networks and learning systems
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...

Learning to Produce Syllabic Speech Sounds via Reward-Modulated Neural Plasticity.

PloS one
At around 7 months of age, human infants begin to reliably produce well-formed syllables containing both consonants and vowels, a behavior called canonical babbling. Over subsequent months, the frequency of canonical babbling continues to increase. H...

State-space model with deep learning for functional dynamics estimation in resting-state fMRI.

NeuroImage
Studies on resting-state functional Magnetic Resonance Imaging (rs-fMRI) have shown that different brain regions still actively interact with each other while a subject is at rest, and such functional interaction is not stationary but changes over ti...

Closed-Loop Modulation of the Pathological Disorders of the Basal Ganglia Network.

IEEE transactions on neural networks and learning systems
A generalized predictive closed-loop control strategy to improve the basal ganglia activity patterns in Parkinson's disease (PD) is explored in this paper. Based on system identification, an input-output model is established to reveal the relationshi...

A patient-specific EMG-driven neuromuscular model for the potential use of human-inspired gait rehabilitation robots.

Computers in biology and medicine
A patient-specific electromyography (EMG)-driven neuromuscular model (PENm) is developed for the potential use of human-inspired gait rehabilitation robots. The PENm is modified based on the current EMG-driven models by decreasing the calculation tim...

FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.

Computational intelligence and neuroscience
Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC...