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Match Voxels to Library HRFs in Shared Basis (SBHM)

Source: R/sbhm_match.R
sbhm_match.Rd

Given per-voxel aggregate coefficients beta_bar in the shared basis B, and library coordinates A, perform shape-only matching in a whitened, L2-normalized coefficient space (cosine similarity). Optionally apply a simple shrinkage of beta_bar towards a reference coordinate before matching, and an orientation fix.

Usage

sbhm_match(
  beta_bar,
  S,
  A,
  shrink = list(tau = 0, ref = NULL, snr = NULL),
  topK = 1,
  whiten = TRUE,
  sv_floor_rel = 1e-06,
  whiten_power = 1,
  orient_ref = TRUE
)

Arguments

beta_bar

Numeric matrix (r×V): per-voxel coefficients from a prepass GLM in the SBHM basis. Columns correspond to voxels.

S

Numeric vector (length r): singular values of the library SVD.

A

Numeric matrix (r×K): coordinates of library HRFs in SBHM basis.

shrink

List with optional shrinkage options:

  • tau numeric >=0: global strength (default 0, i.e., no shrinkage).

  • ref numeric length-r vector (alpha_ref) or NULL. If NULL, uses the mean of A columns. Shrinkage is: beta_bar <- (1-lambda) beta_bar + lambda ref.

  • snr optional numeric length-V estimates; if provided, per-voxel lambda_v = tau/(snr_v + tau). Otherwise lambda = tau.

topK

Integer, return top-K scores/weights if >1 (default 1).

whiten

Logical, divide coefficients by S before normalization (default TRUE).

sv_floor_rel

Relative singular-value floor used when whiten=TRUE (default 1e-6).

whiten_power

Numeric in [0, 1] controlling whitening strength when whiten=TRUE. Uses division by S^whiten_power (1 = full whitening, 0.5 = partial whitening, 0 = no whitening). Default 1.

orient_ref

Logical, flip beta_bar columns when their dot with ref is negative before matching (default TRUE).

Value

A list with:

  • idx length-V integer indices of best-matching library HRF (1..K)

  • margin length-V numeric: score(top1) - score(top2)

  • alpha_hat r×V matrix: the selected library coordinates (unwhitened, unnormalized)

  • scores optional K×V cosine score matrix (returned when topK > 1)

  • weights optional top-K weights per voxel (when topK > 1)

Examples

if (FALSE) { # \dontrun{
  set.seed(42)
  r <- 4; K <- 12; V <- 3
  A <- matrix(rnorm(r*K), r, K)
  S <- seq(1, 0.2, length.out = r)
  alpha2 <- A[,2]
  beta_bar <- cbind(alpha2 + rnorm(r, sd = 0.1),
                    A[,7] + rnorm(r, sd = 0.1),
                    A[,10] + rnorm(r, sd = 0.1))
  m <- sbhm_match(beta_bar, S, A)
  m$idx
} # }