Description:
Background
Electrical stimulation has been used to study neurons and neural activity for decades, and it has led to numerous practical inventions. A frequent problem is removing electrical stimulation-induced neural signals, which can be easily mistaken for neural signals. This uncertainty has limited the impact of the technology. Numerous groups have developed different models and algorithms previously, often called "artifact rejection" or "spike detection" algorithms. However, none of these algorithms possess the unique feature of capturing ionic movement.
 
Technology Overview
Northeastern researchers have created a mathematical model that describes the movement of ions in response to an electrical pulse and then showed that this model can be used to extract electrical stimulation-induced neural activity from in vivo settings. It does this by removing electrical stimulation artifact signals, which are primarily a product of the movement of ions in a liquid.
This physical model developed to mimic the recorded curve shapes consists of three significant parts: 
- A Gaussian to fit the depolarization and repolarization 
- A Damped harmonic oscillator to fit the refractory period 
- A screening function to account for the movement of charge throughout individual neurons and CNTs 
Matlab’s Non-Linear Regression fitting packages were implemented to adjust coefficients in each portion of the equation for fitting.
 
Benefits
- Improved artifact rejection algorithm
- Electrical stimulation offers significant cost and time improvement over optogenetics or patch clamp
- It allows in vivo systems to be probed
 
Applications
Extracting electrical stimulation-induced neural signals from in vivo systems, enabling:
- Study and analysis of neural signals
- Advancing efforts for two-way communications with neurons and neural networks
- Advancing efforts to passively listen to neural networks
The method and experimental setup allow for the discovery of new materials that form strong couplings with neurons and nerves in vivo.
 
Opportunity
- License
- Partnering
- Research collaboration
Patent Information:
Category(s):
1. Life Science
For Information, Contact:
Mark Saulich
Associate Director of Commercialization
Northeastern University
m.saulich@northeastern.edu
Inventors:
Zachariah Hennighausen
Vineet Mathur
Swastik Kar
Keywords:
Artifact Rejection Algorithm
Carbon nanotubes
electrophysiology
Medical Device
neural communication
Spinal Cord Injury