## 4 Discussion
The main challenge of the ongoing debate about the role of diffusion fMRI is that both vascular and neuronal factors influence DW-fMRI signals, and it can be difficult to separate them. In this work, we propose to use a new contrast parameter, the \(\gamma\) parameter, that could better highlight the vascular and/or neuronal dependence of the DW-fMRI signal. In recent years, a study by [PERSON] et al. [63] showed that DW-fMRI could detect activity-related changes in both gray and white matter during working memory tasks, suggesting a neuronal basis for the observed signal changes. Moreover, another study by [PERSON] et al. [64] provided models and experimental data that are relevant to understanding vascular effects in DW-fMRI, while in a study by [PERSON] et al. [65], DW-fMRI has been proposed as an alternative functional imaging method to detect brain activity without confounding hemodynamic effects in a neuropsychiatric disease mouse model. The current consensus acknowledges that DW-fMRI signals at high b-values likely encompass both neuronal and vascular components. The challenge lies in accurately quantifying the relative contributions of each. Factors such as the choice of b-values, diffusion time, type of magnetic field gradients, and the specific brain region under investigation play critical roles in this determination. Overall, to clarify the biophysical basis of DW-fMRI, the implementation of DW acquisition sequences in spectroscopic modality to check the behavior of specific metabolites during activation [66] may be useful. In particular, sophisticated DW sequences with high-strength diffusion gradients (of short duration) and high-performing gradient units and using bipolar gradients and double spin-echo modality are needed to clearly attenuate the effects of \(\rm G\) on \(\gamma\)-values (see Figure 4 of reference [43]). Currently, it would be only possible to perform this kind of optimization in pre-clinical scanners or state-of-the-art human scanners, such as the Siemens Connectom [67; 68; 69]. However, the emergence of new  
Figure 4: Schematic representation highlighting the main dependencies of the \(\rm T_{2}\)*, ADC, and \(\gamma\) parameters on the main physiological (\(\Delta\chi\)) and microstructural (\(\phi\)) variations that occur during neuronal activation. The size of the arrows is proportional to the degree of variation, and the upward or downward direction indicates an increase or decrease. commercial systems with ultra-strong ultra-performing gradients promises exciting new perspectives for further studies and validation in humans with larger cohorts. In these conditions, we suggest performing experiments using DW-fMRI with high-performance mono- and bipolar magnetic field gradients using both ADC and \(\gamma\), as they seem, to our current knowledge, to be independent and complementary parameters to investigate DW-fMRI's properties. Using monopolar magnetic field gradients maximizes \(\gamma\)'s dependence on magnetic susceptibility differences, while this is minimized using efficient bipolar magnetic field gradients. Future studies could focus on the quantification of \(\gamma\)'s dependence on vascular effects, for example in murine models using intravascular paramagnetic contrast agents at rest and under stimulation. The obtained information can be utilized in experiments using pharmacological challenges to modify or disrupt the neurovascular coupling. For instance, nitroprusside infusion is expected to inhibit neurovascular coupling, with no effects on the diffusion response or local field potentials [26]. In these conditions, a decrease in ADC, together with an increase in \(\gamma\), evaluated by subtracting any contribution that was quantified in the first experiment, would allow one to quantify the relative weight of the two vascular and extravascular effects, contributing to the observed transient changes in water diffusion during brain activation.