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Create a Feature-Based RSA Model

feature_rsa_model.Rd

Creates a model for feature-based Representational Similarity Analysis (RSA) that relates neural patterns (X) to a predefined feature space (F).

Usage

feature_rsa_model(
  dataset,
  design,
  method = c("scca", "pls", "pca"),
  crossval = NULL,
  cache_pca = FALSE
)

Arguments

dataset

An mvpa_dataset object containing the neural data (X).

design

A feature_rsa_design object specifying the feature space (F).

method

Character string specifying the analysis method. One of:

scca

Sparse Canonical Correlation Analysis

pls

Partial Least Squares

pca

Principal Component Analysis on feature space

crossval

Optional cross-validation specification.

Value

A feature_rsa_model object (S3 class).

Details

Feature RSA models analyze how well a feature matrix F can predict neural data X. For example: - pca: PCA on F, then regress X on those principal components. - pls: partial least squares regression of X on F. - scca: sparse CCA of X and F.