prism

Welcome to Prism

Fast, modular, and extensible permutation-based statistical inference for neuroimaging.

Prism is a Python library for running fast, scalable, and fully nonparametric statistical analyses on brain imaging data. It replicates much of the core functionality of Anderson Winkler’s PALM, but without MATLAB dependencies.

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🚀 Features

• Mass univariate GLM analysis with flexible contrast modeling
• Permutation-based testing including sign flips and blockwise shuffling
• Support for TFCE, FDR, FWE (Westfall–Young), and GPD-based p-value tail estimation
• Voxelwise map comparison tools for assessing spatial similarity
• CLI interface modeled after PALM
• Works directly with NIfTI files or NumPy arrays

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Minimal Example

import numpy as np
from prism.datasets import Dataset

Y = np.random.randn(100, 50)        # Brain data (samples x voxels)
X = np.random.randn(100, 2)         # Design matrix
C = np.array([1, -1])               # Contrast

dataset = Dataset(
    data=Y,
    design=X,
    contrast=C,
    output_prefix="prism_example",
    n_permutations=1000
)

results = dataset.permutation_analysis()

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License

Prism is released under the MIT License.

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