tat2

hurst

This repository contains the code and data for the analyses in the eLife 2020 paper 'Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women'. It implements a method to compute the Hurst exponent (H) from fMRI data as a proxy for the excitation-inhibition (E:I) balance in neural circuits. ## Key Features - **E:I Ratio Modeling** — Simulates local field potentials (LFP) by manipulating excitation-inhibition ratios using the Gao et al. (2017) model. - **Hurst Exponent Computation** — Calculates the Hurst exponent (H) from fMRI time series as a measure of long-range temporal correlations and E:I balance. - **Multi-modal Analysis Pipeline** — Integrates in-silico neural modeling, in-vivo DREADD mouse experiments, and human resting-state fMRI analyses. - **Preprocessing & Denoising** — Includes scripts for fMRI preprocessing using AFNI, FSL, and wavelet denoising via the Brain Wavelet Toolbox. - **Statistical & Genomic Integration** — Performs univariate statistics, partial least squares (PLS) analysis, and gene expression enrichment tests. ## Philosophy The project adopts a multi-scale, cross-species approach to validate H as a biomarker for E:I imbalance, linking computational models with experimental and clinical neuroimaging data.