Abstract
In general, the Hurst exponent. is used as a measure of long-term memory of time series. In previous neuroimaging studies, H has been introduced as one important parameter to define resting-state networks, reflecting upon global scale-free properties emerging from a network. H has been examined in the waiting impulsivity (WI) network in an earlier study. We found that alterations of H in the anterior cingulate cortex (HACC) and the nucleus accumbens (HNAcc) were lower in high impulsive (highIMP) compared to low impulsive (lowIMP) participants. Following up on those findings, we addressed the relation between altered fractality in HACC and HNAcc and brain activation and neural network connectivity. To do so, brain activation maps were calculated, and network connectivity was determined using the Dynamic Causal Modeling (DCM) approach. Finally, 1–H scores were determined to quantify the alterations of H. This way, the focus of the analyses was placed on the potential effects of alterations of H on neural network activation and connectivity. Correlation analyses between the alterations of HACC/HNAcc and activation maps and DCM estimates were performed. We found that the alterations of H predominantly correlated with fronto-hippocampal pathways and correlations were significant only in highIMP subjects. For example, alterations of HACC was associated with a decrease in neural activation in the right HC in combination with increased ACC-hippocampal connectivity. Alteration inHNAcc, in return, was related to an increase in bilateral prefrontal activation in combination with increased fronto-hippocampal connectivity. The findings, that the WI network was related to H alteration in highIMP subjects indicated that impulse control was not reduced per se but lacked consistency. Additionally, H has been used to describe long-term memory processes before, e.g., in capital markets, energy future prices, and human memory. Thus, current findings supported the relation of H toward memory processing even when further prominent cognitive functions were involved.
Highlights
The Hurst exponent H is used as a measure of long-term memory of time series (Eke et al, 2000)
We found that, H in the anterior cingulate cortex (ACC) and nucleus accumbens (NAcc) was reduced in high impulsive compared to low impulsive participants (Akhrif et al, 2018)
That functional connectivity between the ACC and NAcc in the waiting impulsivity (WI) network varied in function of monetary reward and that especially H in the ACC was associated with impulsivity (Gentili et al, 2020)
Summary
The Hurst exponent H is used as a measure of long-term memory of time series (Eke et al, 2000). Long-range dependence and self-similarity have been shown to be strongly interrelated (e.g., Pipiras and Taqqu, 2017), the application of fractal approaches on time series showing long-range dependence has been encouraged (Abry et al, 2013). (multi)fractal analysis of fMRI has been used to “disentangle functional components from artifactual ones, in a robust and significant manner.” (Ciuciu et al, 2012) and to differentiate between healthy neural network from impaired ones at the example of the waiting impulsivity (WI) network in an earlier publication (Akhrif et al, 2018). That functional connectivity between the ACC and NAcc in the WI network varied in function of monetary reward (high reward, strong connectivity, and vice versa, Mechelmans et al, 2017) and that especially H in the ACC was associated with impulsivity (Gentili et al, 2020)
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