AI Medical Compendium Topic:
Models, Neurological

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Large-scale neuromorphic computing systems.

Journal of neural engineering
Neuromorphic computing covers a diverse range of approaches to information processing all of which demonstrate some degree of neurobiological inspiration that differentiates them from mainstream conventional computing systems. The philosophy behind n...

Neural correlates of motor recovery after robot-assisted stroke rehabilitation: a case series study.

Neurocase
Robot-assisted bilateral arm therapy (RBAT) has shown promising results in stroke rehabilitation; however, connectivity mapping of the sensorimotor networks after RBAT remains unclear. We used fMRI before and after RBAT and a dose-matched control int...

Detecting epileptic seizures with electroencephalogram via a context-learning model.

BMC medical informatics and decision making
BACKGROUND: Epileptic seizure is a serious health problem in the world and there is a huge population suffering from it every year. If an algorithm could automatically detect seizures and deliver the patient therapy or notify the hospital, that would...

Audiovisual integration in hemianopia: A neurocomputational account based on cortico-collicular interaction.

Neuropsychologia
Hemianopic patients retain some abilities to integrate audiovisual stimuli in the blind hemifield, showing both modulation of visual perception by auditory stimuli and modulation of auditory perception by visual stimuli. Indeed, conscious detection o...

Linear readout of object manifolds.

Physical review. E
Objects are represented in sensory systems by continuous manifolds due to sensitivity of neuronal responses to changes in physical features such as location, orientation, and intensity. What makes certain sensory representations better suited for inv...

Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation.

Computational intelligence and neuroscience
A bioinspired locomotion system for a quadruped robot is presented. Locomotion is achieved by a spiking neural network (SNN) that acts as a Central Pattern Generator (CPG) producing different locomotion patterns represented by their raster plots. To ...

Methodology of Recurrent Laguerre-Volterra Network for Modeling Nonlinear Dynamic Systems.

IEEE transactions on neural networks and learning systems
In this paper, we have introduced a general modeling approach for dynamic nonlinear systems that utilizes a variant of the simulated annealing algorithm for training the Laguerre-Volterra network (LVN) to overcome the local minima and convergence pro...

Decoder Design Based on Spiking Neural P Systems.

IEEE transactions on nanobioscience
The spiking neural P systems (SN P systems, for short) refer to the parallel-distributed biocomputing models, which have currently become research hotspots in the biocomputing field. In computing systems, logical operations and arithmetic operations ...