motoRneuron

motoRneuron performs time-domain analysis of motor unit synchronization in R to quantify temporal synchrony and common input between motor neuron discharge trains.

Key Features:

• R implementation: Implemented in R for analysis of motor unit discharge and action potential train data.
• Cross-correlation histogram analysis: Generates cross-correlation histograms with configurable bin width (e.g., 1 ms) and analyzes first-order recurrence intervals.
• Peak detection methods: Implements cumulative sum method, z-score method, and a subjective visual method for detecting peaks in cross-correlation histograms.
• Synchronization indices: The mu_synch function computes six indices: Common Input Strength (CIS), k', k' - 1, E, S, and Synch Index.
• Data input: Processes motor unit action potential trains recorded with fine-wire electromyography during tasks such as isometric finger flexion.

Scientific Applications:

• Motor control research: Quantifies temporal relationships between motor neurons and muscle fibers to investigate neural control mechanisms of force generation.
• Neuromuscular disorder studies: Assesses alterations in motor unit synchronization associated with neuromuscular conditions.
• Rehabilitation and intervention evaluation: Evaluates effects of interventions on motor unit synchrony.
• Method comparison and reproducibility: Enables comparison of peak detection and index computation methods, with reported variability between methods (e.g., a 45% difference in CIS between visual and z-score methods).

Methodology:

Processes motor unit action potential trains (fine-wire electromyography, e.g., isometric finger flexion), computes cross-correlation histograms with specified bin width (e.g., 1 ms) focusing on first-order recurrence intervals, detects peaks using cumulative sum, z-score, or subjective visual methods, and computes synchronization indices (CIS, k', k' - 1, E, S, Synch Index) via the mu_synch function.