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Pubmed for Handhelds

PUBMED FOR HANDHELDS

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  • Title: Interpreting spatial and temporal neural activity through a recurrent neural network brain-machine interface.
    Author: Sanchez JC, Erdogmus D, Nicolelis MA, Wessberg J, Principe JC.
    Journal: IEEE Trans Neural Syst Rehabil Eng; 2005 Jun; 13(2):213-9. PubMed ID: 16003902.
    Abstract:
    We propose the use of optimized brain-machine interface (BMI) models for interpreting the spatial and temporal neural activity generated in motor tasks. In this study, a nonlinear dynamical neural network is trained to predict the hand position of primates from neural recordings in a reaching task paradigm. We first develop a method to reveal the role attributed by the model to the sampled motor, premotor, and parietal cortices in generating hand movements. Next, using the trained model weights, we derive a temporal sensitivity measure to asses how the model utilized the sampled cortices and neurons in real-time during BMI testing.
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