Neural Interface Activity Simulator for Motor Intent Decoding
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Solution Overview
Problem
Current spinal cord simulators require significant computational resources and time, focusing on specific aspects of spinal cord physiology, and do not effectively simulate neural activity for decoding motor intent or controlling neural prostheses, particularly for human electrophysiology.
Innovation Solution
The development of systems and methods that simulate neural activity recorded from nerve fibers, including motor intent signals, using a computer-readable medium to generate and translate signals into motor neuron firing patterns, enabling realistic neural recordings for evaluating decoding algorithms and developing neural interface devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex computational models are used to simulate spinal cord physiology, then simulation accuracy is improved, but computational resources and simulation time increase significantly
Solution Approach 1:
The patent extracts and simulates only the essential neural components relevant to motor intent decoding (motor cortex neurons, spinal motor neurons, muscle activation) while omitting less critical physiological details. This selective extraction maintains simulation accuracy for the intended application while significantly reducing computational resource requirements.
Solution Approach 2:
The neural system is segmented into distinct functional modules: motor intent generation, neural signal transmission, motor neuron firing, and muscle activation. Each module is simulated independently with appropriate level of detail, allowing accurate representation of key processes while reducing overall computational complexity through modular processing.
2Measurement precision
If detailed spinal cord physiology is simulated, then physiological accuracy is improved, but simulation time increases
Solution Approach 1:
The simulation implements partial physiological detail by focusing computational effort only on the neural pathways and mechanisms directly relevant to motor intent decoding. Less critical physiological processes are simplified or omitted, achieving sufficient physiological accuracy for the application while reducing simulation time through selective detail representation.
3Measurement precision
If complex computational models are used, then simulation detail is improved, but ease of operation deteriorates
Solution Approach 1:
The patent creates simplified computational models that copy only the essential characteristics of neural physiology required for motor intent decoding. These simplified models maintain sufficient biological realism for accurate simulation while being computationally efficient and easier to operate, effectively copying only the necessary physiological features rather than implementing complete biological complexity.
Data Source
AI summary
Systems and methods to simulate activity that would be recorded using an interface to nerve fibers are provided. Signals, such as motor intent signals, can be converted to neural recordings, such as neural recordings by longitudinal intrafascicular electrodes (LIFEs). Spinal cord motor pools and neural interfaces can be jointly simulated. Realistic simulated neural recordings, such as from electrodes such as LIFEs, can be provided and can be used for the evaluation of decoding algorithms. Systems and methods described herein provide a framework for developing neural interface devices.