A Wavelet-Based Framework for Mapping Long Memory in Resting-State fMRI: Age-Related Changes in the Hippocampus from the ADHD-200 Dataset

TL;DR

This paper introduces a wavelet-based computational pipeline to map long-range temporal dependencies in resting-state fMRI, revealing age-related changes in hippocampal dynamics in children from the ADHD-200 dataset.

Contribution

The study presents a novel wavelet-based Bayesian method for voxelwise estimation of long-memory parameters in rs-fMRI, linking temporal dependencies to brain development.

Findings

Positive association between age and long-memory parameter in hippocampus

Method enables detailed mapping of intrinsic temporal dynamics in rs-fMRI

Provides insights into developmental changes in brain memory regions

Abstract

Functional magnetic resonance imaging (fMRI) time series are known to exhibit long-range temporal dependencies that challenge traditional modeling approaches. In this study, we propose a novel computational pipeline to characterize and interpret these dependencies using a long-memory (LM) framework, which captures the slow, power-law decay of autocorrelation in resting-state fMRI (rs-fMRI) signals. The pipeline involves voxelwise estimation of LM parameters via a wavelet-based Bayesian method, yielding spatial maps that reflect temporal dependence across the brain. These maps are then projected onto a lower-dimensional space via a composite basis and are then related to individual-level covariates through group-level regression. We applied this approach to the ADHD-200 dataset and found significant positive associations between age in children and the LM parameter in the hippocampus, after adjusting for ADHD symptom severity and medication status. These findings complement prior neuroimaging work by linking long-range temporal dependence to developmental changes in memory-related brain regions. Overall, the proposed methodology enables detailed mapping of intrinsic temporal dynamics in rs-fMRI and offers new insights into the relationship between functional signal memory and brain development.