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Characterization of the hemodynamic response function in default mode network subregions for task-evoked negative BOLD responses

Hengda He, B. G. Yazdi, Amir Sedaghat, S. H. Hojjati, S. Ozoria, Peter Chernek, Jenseric Calimag, F. Feiz, Q. Razlighi

bioRxiv September 19, 2025 preprint DOI: 10.1101/2025.09.19.677202 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Observational fMRI study
Topics Default mode network
Key findings The authors report that the negative BOLD response is linear with respect to stimulus duration, and that each default mode network sub-region has a unique hemodynamic response function distinct from the positive BOLD HRF and from other DMN regions. Inter-regional variability exceeded inter-task variability, and HRFs were not biased by task performance. They suggest each DMN node may have different neural or vascular mechanisms.

Abstract

While the hemodynamic response function (HRF) of the positive blood oxygenated level dependent (BOLD) signal is well characterized in the functional magnetic resonance imaging (fMRI) field, studies investigating the shape and properties of the negative BOLD HRF, often observed in the default mode network (DMN) regions, are rare. In this study, we first investigated the linearity of the task-evoked negative BOLD response (NBR) with respect to stimulus duration. Then, we obtained the shape of the HRF from each region of the DMN, using an in-house developed unbiased and robust iterative deconvolution technique. Our results demonstrated that each region of the DMN represented a unique HRF, which was not only substantially different from the HRF of the positive BOLD signal, but also different from the HRF extracted from the other DMN regions. We replicated these findings using different fMRI datasets with distinct task paradigms. When comparing the HRF across DMN sub-regions and across tasks, our results demonstrated a significantly higher inter-regional variability compared to inter-task variability. Furthermore, our performance correlation analysis illustrated that the HRFs in the DMN sub-regions extracted by our iterative FIR method were not biased by the task performance level. Altogether, we demonstrated the linearity of the NBR, introduced a robust HRF extraction approach to obtain a distinct HRF for each DMN sub-regions, which were different from the HRF of the positive BOLD signal. The results suggest there is possibility that each node of the DMN might have different underlying neural and/or vascular mechanisms.

Comparable studies

Other experimental studies on default mode network, most cited first.

Study Year Design Participants
Functional connectivity of default mode network components: Correlation, anticorrelation, and causality Healthy subjects 2008 Observational study using resting-state fMRI and seed correlation analysis
Patterns of Brain Activity Supporting Autobiographical Memory, Prospection, and Theory of Mind, and Their Relationship to the Default Mode Network Healthy subjects 2009 Experimental study using fMRI
Dynamic reconfiguration of the default mode network during narrative comprehension Human subjects 2016 Experimental study
Broadband Cortical Desynchronization Underlies the Human Psychedelic State Healthy human participants 2013 Experimental study
The brain on art: intense aesthetic experience activates the default mode network Human observers 2012 Observational study with fMRI and behavioral analysis

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