The present study demonstrates that acute dAMPH administration reduced connectivity within the CST network and that striatal DA release, but not baseline striatal DA D 2/3 receptor availability, was associated with changes in striatal resting-state connectivity in this network. In addition to the CST, large effects of acute dAMPH administration were observed in the salience executive networks and default mode networks. Contrary to our hypothesis, we did not observe a group difference in dAMPH-induced changes in RSNs.

The cortex, striatum and thalamus are connected by means of large-scale parallel loops with direct monosynaptic connections from the cortex to the striatum and indirect, polysynaptic connections from the striatum, through the thalamus and back to the cortex (Shepherd 2013). This wiring is thought to be crucial for its role in cognition and motor function and DA has been shown to modulate these connections (Cole et al. 2013; Honey et al. 2003). Indeed, we found a small cluster in the ACC that showed reduced connectivity with the CST network following dAMPH administration. This is in accordance with other studies, showing that drugs that increase DA release or elevate DA levels (such as MPH and L-DOPA respectively) decrease FC within regions of the CST network. For instance, L-DOPA administration has also been found to reduce connectivity of the ACC with a CST network (Cole et al. 2013). Honey et al. (2003), demonstrated that MPH, a DAT and noradrenaline transporter blocker, reduced connectivity between the caudate nucleus and the midbrain, without showing an effect on the connectivity between the caudate nucleus and the thalamus. Similarly, Mueller et al. (2014) reported a decrease in cortical and subcortical components of the CST network following MPH. In addition, Ramaekers et al. (2013) found reduced connectivity following MPH administration between the ventral and dorsal striatum, as well as between the ventral striatum and the medial prefrontal cortex (mPFC). Konova et al. (2013) also focused on the CST network but found opposite effects, with MPH decreasing intra-striatal connectivity, but increasing cortico-striatal connectivity. However, this was in a sample of cocaine dependent subjects, which has been shown to have altered connectivity patterns (Konova et al. 2013).

We also demonstrated that dAMPH-induced striatal DA release was associated with changes in CST resting-state FC in the striatum following dAMPH administration. This is in line with animal studies in which microdialysis measurements of striatal DA release are associated with BOLD and CBF changes following dAMPH administration (Chen et al. 1997). Our correlational analysis was performed for the striatum, because this is the brain region where we also measured DA release, whereas differences in RS FC following dAMPH administration were measured for the whole brain. The neuronal effects of dAMPH are thought to originate mainly from the basal ganglia, as dAMPH increases extracellular DA primarily in these regions (Chen et al. 1997). Yet, in our study, we did not find any subcortical areas that showed altered connectivity following dAMPH administration. However, dopaminergic and noradrenergic (NA) terminals are also widely distributed in cortical areas (Lewis et al. 1987). Indeed, a recent microdialysis study showed that administration of dAMPH increases both DA and NA in the prefrontal cortex, but only DA in the striatum (Rowley et al. 2014). As such, modulation of RSNs in the striatum may be mainly determined by DA release, whereas cortical RS FC is both dependent on changes of DA and NA. This could also explain why we find a decrease in ACC connectivity, despite increases in striatal DA release. This is further supported by the inverted-U hypothesis of DAergic modulation, suggesting that there is an optimal level of DAergic stimulation, with both too little and too much DA negatively impacting behavior. Indeed, previous studies have already shown that DA modulations can induce inverted-U relationships in cortical FC patterns (Cole et al. 2013). Therefore, it is conceivable that FC decreases in the cortex when DA release is acutely increased to a large extent in subcortical areas. In this context, it would be very interesting to study dose–response relationships of DA modulation on RS FC.

Contrary to what we expected, no significant group differences nor any interaction effects on RS FC patterns were found, even though the groups under study differed markedly on baseline striatal DA D 2/3 receptor availability and dAMPH-induced DA release, as we reported elsewhere (Schrantee et al. 2014). This is possibly due to the sensitivity of rs-fMRI measurements to pick up regional DA alterations. SPECT is a direct method to investigate DAergic receptor binding, whereas rs-fMRI is an indirect tool to assess temporal coherent activity between brain regions and could therefore be less sensitive to small DA alterations in part of a network. This is in contrast with studies reporting alterations in CST connectivity in subjects with other drugs of abuse acting on the DA system, such as cocaine and METH (Gu et al. 2010; Kohno et al. 2014; Konova et al. 2013). The largest difference between those studies and the present one is that those subjects suffered from substance dependence, whereas our subjects were typically recreational users. It is extremely difficult to disentangle the effects of addiction per se and neurotoxicity of the drug that subjects are addicted to. Yet, it is possible that addiction in itself induces changes in resting state connectivity that are not evident in recreational users of a drug. For example, neurobiological correlates of intoxication differ from those of craving and compulsory drug administration (Goldstein and Volkow 2002; Koob and Volkow 2010). A related explanation might be that although our users displayed alterations in DA release, compensatory changes in the CST loops may have ‘buffered’ alterations in resting state connectivity. Such compensatory measures may be sufficient to maintain normal CST connectivity in case of recreational use, but might fail when subjects become addicted to a drug. Although no studies have directly compared RS FC between recreational use and addiction, the transition phase from abuse to addiction has been associated with compensatory mechanisms (Kalivas and Volkow 2005).

In addition to acute changes in the CST network, we found reduced connectivity in DMNs and SENs following dAMPH administration. This is concordance with other studies that also found changes in connectivity after DA drug administration in networks outside the CST loops. In our study, the most prominent effect of acute dAMPH on FC was in the DMN, a network in which connectivity is suppressed during task performance. We found reductions of connectivity primarily in posterior parietal regions. Failure to inhibit DMN activity during task performance is associated with worse behavioral performance (Weissman et al. 2006). Our findings are in concordance with a study by Kelly et al. (2009) that showed that L-DOPA, a DA precursor, decreased DMN activity, and Nagano-Saito et al. (2008) that demonstrated that DA depletion increased DMN activity in healthy controls. In addition to changes in DMN connectivity we also found reductions in connectivity within salience-executive networks (dSEN and iSEN), including mostly frontal areas. Salience-executive networks are thought to play a role in reward and cognitive processing (Seeley et al. 2007). These findings are in line with task fMRI literature showing that administration of oral dAMPH reduces activation in a monetary incentive delay task (Knutson et al. 2004). However, Cole et al. (2013) reported no changes in SEN networks following L-DOPA administration, whereas Mueller et al. (2014) found increased connectivity of SENs with the visual cortex, but decreased connectivity with the cerebellum and thalamus. Although we found large reductions of RS FC in DMN and SEN’s, these analyses were exploratory in nature and therefore we cannot draw strong conclusions from them. Still, the large effects observed in these networks, highlight the importance of whole brain analyses for rs-fMRI data. Networks in the brain are not single entities, but can influence other networks and work in close concordance. It would be interesting for further research to assess the effects of DA drugs on between-network connectivity (Smith et al. 2013).

This study investigated the effects of dAMPH administration on resting-state BOLD signal fluctuations. The BOLD signal is influenced by a large number of factors including CBF, cerebral blood volume, and oxygenation. dAMPH has been shown to be a vasoconstrictive agent systemically and in the brain by DA receptors on microvessels (Choi et al. 2006). Therefore, we cannot exclude vascular contributions (unrelated to neuronal effects) to the acute dAMPH-induced changes in RS FC as reported here. In addition, in this study we administered the drug intravenously rather than orally, as most studies so far have done. Intravenous administration induces a large strain on the cardiovascular system which may influence the BOLD response (Heal et al. 2013). However, we observed that the large physiological effects are primarily present directly following administration and have largely subsided at the time of our rs-fMRI sequence 30 min later (Heal et al. 2013). In addition, adding HR as a covariate in our statistical analysis did not affect our results. Therefore, it is unlikely that cardiovascular changes contributed to the acute dAMPH-induced RSN modulations. In addition, we used FIX to remove residual physiological variation and motion (Griffanti et al. 2014). So, the potential confounding cardiovascular effects were reduced to a minimum in this study. In addition, in between resting-state scans subjects underwent a resting-state ASL scan, which means that there were no confounding effects of cognitive tasks that could influence subsequent resting-state FC (Gordon et al. 2014).

In this study, the participants received a dAMPH challenge twice, which could potentially impose an order effect. To account for this, we counterbalanced the visits within groups, with half of the subjects first undergoing the SPECT scans and the other half first undergoing the MRI scan. One more limitation of this study is that subjects always underwent the dAMPH scan after the baseline scan, which could induce expectancy effects (Gundersen et al. 2008). However, subjects were aware that they would not yet receive the dAMPH challenge until the ASL scan 15 min later. In addition, if the anticipation differed between AMPH users and controls, one would expect AMPH users to have more anticipation of reward and therefore more [123I]IBZM displacement than the controls. Yet, we observed a blunted response in the AMPH users compared to controls. Nevertheless, future studies could assess the expectancy effects by including a placebo condition. In addition, an inherent limitation to studies investigating recreational drug use is polydrug use. Indeed, in our sample, AMPH users also used significantly more other drugs and we can therefore not exclude that our results are due to other drug use. However, the subjects underwent a drug screening prior to the scans, which excludes acute effects of other drugs of abuse on our results. In addition, the effect of acute administration on the CST network is consistent with studies investigating the effect of MPH and L-DOPA on CST FC. However, polydrug use could have increased variation within the dAMPH user group and this could have resulted in a lower power to detect group differences. In addition, many different analysis techniques are employed, but comparisons between for example ICA and seed-based approaches have not found significant differences in reproducibility and ability to detect resting-state networks (Franco et al. 2013; Hale et al. 2015). In fact, for inter-individual differences ICA-based approaches may be more sensitive than seed-based approaches (Smith et al. 2014), which is reflected in the association we observed between striatal DA release and RS FC. Yet, it is possible that other techniques are more sensitive than ICA-based techniques to detect group differences in specific subcortical DA-ergic regions, but this postulate remains to be tested. Another potential limitation is that our resting-state scan contained 130 volumes, which is a relatively short scan. However, studies have shown that resting state scans of 5 up to 13 min provide reliable estimates of resting state connectivity networks (Birn et al. 2013). Although our scan of 5 min falls within that time window, it is possible that longer resting-state scans (up to 12 min) provide more information and could thus be more sensitive to detect the difference between our recreational dAMPH users and controls. This would be an interesting topic for further research.