Lateralised Readiness Potential

This demo shows how to calculate the Lateralised Readiness Potential (LRP) from ERP data.

What is the LRP?

The LRP is an ERP measure of lateralised motor preparation. It is computed from the difference in activity between hemispheres contralateral and ipsilateral to the responding hand, and is widely used in cognitive and motor neuroscience to study response preparation timing.

How is it Calculated?

For each channel pair (e.g., C3/C4), the LRP is:

LRP_C3 = 0.5 × ((C3_right − C4_right) + (C4_left − C3_left))

Where "left" and "right" refer to the hand used for the response.

Key Functions

Function	Purpose
lrp(erp_left, erp_right)	Single-participant LRP
lrp(file_pattern, pairs)	Batch LRP across participants

Channel Pairing

• By default, all odd/even channel pairs are detected automatically (e.g., C3/C4, CP1/CP2)

• Use channel_selection to restrict to specific pairs

Workflow Summary

Single-Participant LRP

• Calculate LRP from left and right response conditions

Batch Processing

• Process all participants with specified condition pairs

Visualisation

• Plot LRP waveforms with plot_erp

Code Examples

Show Code

# Demo: Lateralised Readiness Potential (LRP)
# Shows how to calculate the LRP from left-hand and right-hand ERP conditions
# and perform batch processing across participants.

# Note: EegFun.example_path() resolves bundled example data paths.
# When using your own data, simply pass the file path directly, e.g.:
# dat = EegFun.read_raw_data("/path/to/your/data.bdf")

using EegFun
using GLMakie

const DEMO_OUTPUT = "./tutorials/output/"
mkpath(DEMO_OUTPUT)

#######################################################################
# LOAD ERP DATA
#######################################################################

# Load a participant's ERPs
erps = EegFun.read_data(EegFun.example_path("data/julia/erps/example1_erps_final.jld2"))

#######################################################################
# LATERALISED READINESS POTENTIAL (IN-MEMORY)
#######################################################################

# Calculate LRP from two conditions (e.g., Left response vs Right response)
# Assuming condition 1 is Left Hand and condition 2 is Right Hand
# The default channel_selection = EegFun.channels() auto-detects all 
# odd/even lateral pairs (e.g., C3/C4, C1/C2).
lrp_data = EegFun.lrp(erps[1], erps[2])

# Plot the LRP (e.g., at C3/C4)
EegFun.plot_erp(lrp_data, channel_selection = EegFun.channels([:C3, :C4]))

# Calculate LRP for multiple condition pairs simultaneously from an array of ERPs
# e.g., Left vs Right (1 vs 2) and Left vs Right under a different condition (3 vs 4)
pairs = [(1, 2), (3, 4)]
lrp_results = EegFun.lrp(erps, pairs)


#######################################################################
# BATCH LRP (FROM DISK)
#######################################################################

# Batch calculate LRPs for a list of condition pairs across all participant files
EegFun.lrp(
    "erps_final",
    [(1, 2)],
    input_dir = EegFun.example_path("data/julia/erps/"),
    output_dir = DEMO_OUTPUT
)

See Also

• API Reference