Neural Activity Detection Using Extraneural Non-Zero-Lag Correlation
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Solution Overview
Problem
Conventional recording apparatuses are unable to detect ongoing spontaneous or natural neural activity due to excessive noise, which masks the neural signals, and require invasive methods to achieve a high signal-to-noise ratio.
Innovation Solution
A method involving correlation analysis of electrical signals received from pairs of electrodes located outside the perineurium of a nerve, utilizing non-zero lag times to enhance signal detection and distinguish neural activity from noise, allowing for minimally invasive chronic implantation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional recording apparatus is used to detect neural activity, then the device can record evoked neural activity in response to artificial stimulation, but it cannot record ongoing spontaneous or natural neural activity due to excessive noise in the signal
Solution Approach 1:
The patent introduces correlation analysis as an intermediary processing step between the raw electrical signals and the final neural activity detection. By computing correlation coefficients between signals from multiple electrode pairs, the system extracts neural activity information that is buried in noise, effectively separating the harmful noise from the useful signal without requiring direct penetration of the perineurium.
Solution Approach 2:
The patent replaces direct mechanical penetration of the perineurium (invasive approach) with a non-invasive correlation analysis method. Instead of physically penetrating the nerve sheath to achieve high signal-to-noise ratio, the system uses signal processing to extract neural activity from extraneural recordings, substituting mechanical invasion with computational analysis.
2Measurement precision
If electrodes are placed inside the perineurium to achieve high signal-to-noise ratio, then neural activity can be detected accurately, but the implantation becomes invasive and reduces device longevity
Solution Approach 1:
The patent uses correlation analysis as an intermediary that enables accurate neural activity detection without direct electrode-nerve contact. The correlation processing step extracts neural signals from extraneural recordings, eliminating the need for perineural electrode placement and its associated invasiveness and longevity issues.
Solution Approach 2:
The patent substitutes the mechanical approach of penetrating the perineurium with a computational approach using correlation analysis. This replacement maintains measurement precision while eliminating the harmful mechanical invasion, thereby improving device reliability and longevity.
3Ease of operation
If correlation analysis is applied to electrical signals from electrode pairs outside the perineurium, then spontaneous neural activity can be detected without invasive penetration, but the signal-to-noise ratio is initially low
Solution Approach 1:
The patent introduces correlation analysis as an intermediary processing step that operates on extraneural signals from electrode pairs outside the perineurium. This intermediary computation enhances the signal-to-noise ratio by extracting correlated neural activity patterns, enabling detection without invasive penetration while achieving sufficient measurement precision.
Solution Approach 2:
The patent replaces mechanical penetration of the perineurium with computational correlation analysis. This substitution maintains minimal invasiveness while achieving the necessary signal-to-noise ratio through signal processing, allowing neural activity detection without physical invasion of the nerve sheath.
Data Source
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AI summary
A method of detecting neural activity in a nerve is disclosed. A first electrical signal is received from a first pair of electrodes. A second electrical signal is received from a second pair of electrodes, the second pair of electrodes being spaced from the first pair of electrodes along the nerve. A correlation analysis is applied between the first and second electrical signals, including for at least one non-zero lag time, to obtain correlation data. From the correlation data, at least one neural signal is detected, indicative of neural activity in the nerve. The neural signal corresponds to increased correlation between the first and second signals at the at least one non-zero lag time.