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Impact of referencing scheme on decoding performance of LFP-based brain-machine interface.

Nur Ahmadi1,2, Timothy G Constandinou1,2,3, Christos-Savvas Bouganis1

  • 1Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2BT, United Kingdom.

Journal of Neural Engineering
|November 26, 2020
PubMed
Summary
This summary is machine-generated.

Local motor potential (LMP) combined with common average reference (CAR) significantly improves brain-machine interface (BMI) performance. This approach enhances hand kinematic decoding using local field potentials (LFPs).

Keywords:
brain-machine interfacecommon average referencedeep learninglocal field potentiallocal motor potentialneural decodingreferencing scheme

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Local field potential (LFP) is increasingly used in brain-machine interfaces (BMIs) for its stable, low-bandwidth signals.
  • Unipolar referencing of LFPs is prone to common noise, prompting research into alternative schemes like bipolar, CSD, and CAR.
  • The impact of different LFP referencing schemes on BMI decoding performance remains understudied.

Purpose of the Study:

  • To investigate the influence of various referencing schemes and LFP features on hand kinematic decoding performance in LFP-based BMIs.
  • To identify optimal feature extraction and referencing strategies for robust BMI applications.

Main Methods:

  • Chronic LFP recordings from a monkey's motor cortex during reaching tasks.
  • Application of a deep learning model for hand kinematic decoding.
  • Comparative analysis of different referencing schemes (bipolar, CSD, CAR) and LFP features.

Main Results:

  • Local motor potential (LMP) was identified as the most informative LFP feature across all referencing methods.
  • The common average reference (CAR) scheme consistently outperformed other methods when using LMP for decoding.
  • CAR demonstrated superior decoding performance over extended recording periods.

Conclusions:

  • Local motor potential (LMP) is a highly effective feature for LFP-based BMI decoding.
  • Common average reference (CAR) is a promising referencing strategy for enhancing BMI performance.
  • The combination of LMP and CAR offers a potential pathway for improved LFP-based BMI systems.