# Deep linear matrix approximate reconstruction with integrated BOLD signal denoising reveals reproducible hierarchical brain connectivity networks from multiband multi-echo fMRI

## TL;DR

A new deep learning method combined with advanced fMRI techniques reveals more accurate brain connectivity networks, improving the study of neurological and psychiatric disorders.

## Contribution

A novel deep linear model (DELMAR) with integrated BOLD signal denoising improves hierarchical brain connectivity mapping using MBME fMRI.

## Key findings

- DELMAR/Denoising/Mapping outperforms traditional ME-ICA denoising in producing accurate and reproducible hierarchical BCNs.
- MBME fMRI provides better hierarchical BCN mapping accuracy and precision compared to multiband fMRI.
- Reproducible spatial hierarchies in BCNs can enhance diagnostic and prognostic biomarkers for neurological and psychiatric disorders.

## Abstract

The hierarchical modular functional structure in the human brain has not been adequately depicted by conventional functional magnetic resonance imaging (fMRI) acquisition techniques and traditional functional connectivity reconstruction methods. Fortunately, rapid advancements in fMRI scanning techniques and deep learning methods open a novel frontier to map the spatial hierarchy within Brain Connectivity Networks (BCNs). The novel multiband multi-echo (MBME) fMRI technique has increased spatiotemporal resolution and peak functional sensitivity, while the advanced deep linear model (multilayer-stacked) named DEep Linear Matrix Approximate Reconstruction (DELMAR) enables the identification of hierarchical features without extensive hyperparameter tuning. We incorporate a multi-echo blood oxygenation level-dependent (BOLD) signal and DELMAR for denoising in its first layer, thereby eliminating the need for a separate multi-echo independent component analysis (ME-ICA) denoising step. Our results demonstrate that the DELMAR/Denoising/Mapping strategy produces more accurate and reproducible hierarchical BCNs than traditional ME-ICA denoising followed by DELMAR. Additionally, we showcase that MBME fMRI outperforms multiband (MB) fMRI in terms of hierarchical BCN mapping accuracy and precision. These reproducible spatial hierarchies in BCNs have significant potential for developing improved fMRI diagnostic and prognostic biomarkers of functional connectivity across a wide range of neurological and psychiatric disorders.