Our study is the first to combine evidence from ¹H MRS and rs-fMRI to predict individual differences in impulsive decision making in healthy volunteers. We found evidence that individual differences in impulsive decision making are associated with dACC function under task-free conditions in terms of glutamate concentrations and resting state functional connectivity. In line with previous research (Hoerst et al. 2010
), we found that higher impulsivity was associated with higher glutamate concentrations in the dACC. Dorsal ACC glutamate concentrations were also found to be increased in untreated children with ADHD, a disorder characterized by impaired impulse control (Hammerness et al. 2012
). In addition, increased functional coupling between the left dACC and a midbrain region including VTA and SN was associated with steeper discounting of delayed rewards, whereas a negative functional coupling was associated with less discounting and therefore lower impulsive decision making. Our findings of an association between resting state functional connectivity between dACC and the midbrain and impulsivity are consistent with a previous study of Tian et al. (2006
) who showed increased resting state connectivity between dACC and the midbrain in adolescents with ADHD, a disorder characterized by high levels of impulsivity. In addition, a task-related fMRI study of Diekhof and Gruber (2010
) found that preference for immediate rewards was associated with increased functional coupling between the PFC and the midbrain. The stronger interaction between brain regions involved in decision strategy (dACC) and subjective valuation of rewards (midbrain) under rest in high impulsive subjects as observed in the current and above mentioned studies might indicate a potential trait marker for impulsive decision making, especially because low impulsive decision making was associated with no or even a negative coupling between the left dACC and the midbrain. In addition, the current study suggests that this increased functional coupling between the dACC and the midbrain might be driven by glutamate neurotransmission. We established a functional pathway, showing that molecular properties (glutamate concentrations) of the dACC, via functional connectivity of the dACC with the midbrain including VTA and SN, translate into behavioral manifestations of delay discounting. This finding indicates that the relationship between dACC glutamate concentrations and impulsive decision making can, at least partly, be attributed to connectivity of the left dACC with the midbrain.
Preclinical literature has indicated a role for glutamate in impulsivity (for a review see Pattij and Vanderschuren 2008
). For instance, selective and nonselective NMDA receptor antagonists have been shown to increase impulsive behavior in animal models (Higgins et al. 2003
; Mirjana et al. 2004
). Systemic pretreatment with an mGlu2/3 receptor agonist attenuates impulsive behavior seen after serotonin receptor stimulation (Wischhof et al. 2011
). In humans, a recent study of Hoerst et al. (2010
) examined glutamate levels in the dACC in patients with borderline personality disorder and healthy controls. Irrespective of diagnosis, higher Glu/Cr was associated with higher self-reported (trait) impulsivity (Hoerst et al. 2010
). Anterior cingulate Glu/Cr was also found to be increased in untreated children with ADHD, a disorder characterized by impaired impulse control (Hammerness et al. 2012
). In keeping with these findings, the current study revealed that glutamate concentrations in the dACC were associated with impulsive decision making.
Interestingly, the current study revealed associations between dACC glutamate concentrations and resting state connectivity of the dACC with other brain regions (the midbrain and the left and right PCC). This is consistent with a previously described correlation between ¹H MRS glutamate concentrations and resting state functional connectivity (Horn et al. 2010
), suggesting that the amount of glutamate, which is present in neuronal and glial metabolic and neurotransmitter pools as measured by ¹H MRS, underlies the observed synchronization among these brain regions as assessed with resting state functional connectivity measures. This is not very surprising, as it is thought that the intrinsic energy demands of neuron populations in different brain regions with a common functional purpose have wired together through synaptic plasticity, and thereby form so-called resting state networks (e.g., Lewis et al. 2009
). It is well known that glutamate plays a critical role in synaptic plasticity. Unfortunately, ¹H MRS does not allow distinguishing the specific contribution of different components of the glutamatergic system to spontaneous coherence of BOLD signal fluctuations between brain regions. ¹H MRS glutamate measurements reflect primarily intracellular glutamate and does not directly measure synaptic glutamate transmission (Gruetter et al. 1998
). Furthermore, quantification and separation of glutamate by use of ¹H MRS is technically difficult because glutamate overlaps in its chemical shift range with glutamine and γ-amino butyric acid (GABA). Although in this study acceptable reliable peaks, as defined by LCModel quality control criteria, were recorded consistently for Glu separate from Glx (total glutamate plus glutamine), undetected (although probably small) contributions from glutamine (Gln) and GABA cannot be ruled out. Future studies are using more advanced spectral editing techniques, such as a spectrally selective refocusing method (Choi et al. 2006
) or 2D J-resolved spectroscopy (Jensen et al. 2009
), are warranted to separate Glu from Gln. Gln could be of particular interest, as synaptic glutamate taken up by glial cells is converted into glutamine before returning to the presynaptic neuron for conversion back into Glu (Magistretti and Pellerin 1999
) and therefore Gln may be a more accurate index of overall glutamatergic neurotransmission than Glu (Rothman et al. 2003
The ACC is part of a control network, and activity in the ACC correlates with the degree of decision conflict experienced when choosing between an immediate smaller and delayed larger reward (Pochon et al. 2008
). Midbrain areas, such as the VTA and SN are involved in the subjective valuation of rewards presented during a DDT (Luo et al. 2009
). Recently, it has been shown that the midbrain, through its dopaminergic projection to the striatum, predicts individual differences in impulsivity in humans (Buckholtz et al. 2010
). Midbrain dopaminergic neurons project to various brain areas, such as the striatum and PFC, signaling the availability of a reward. The dACC is important in integrating these reward signals in the decision making process, as dACC activation reflects decision conflict and decision strategy (Pochon et al. 2008
; Marco-Pallares et al. 2010
). Therefore, the current results of associations between functional connectivity between the midbrain and dACC, dACC glutamate concentrations and delay discounting could suggest a projection from the midbrain to the dACC related to signaling reward, thereby increasing activity in the dACC reflected by increased glutamate concentrations, leading to steeper discounting of delayed rewards. However, this should have been reflected by a mediation model with dACC glutamate concentrations as a mediator of the relationship between resting state functional connectivity of the dACC with the midbrain and delay discounting, but this proposed pathway was not significant. Instead, we established a functional pathway from glutamate concentrations in the dACC to delay discounting, through functional coupling between dACC and the midbrain. Rodent studies have indicated the presence of glutamatergic projections from the PFC to the midbrain and it has been suggested that firing of VTA dopamine neurons depends largely on glutamatergic inputs (Kalivas 1993
). Evidence of (limited) glutamatergic projections from the ACC to the VTA and SN has also been found in primates (Frankle et al. 2006
). The current findings of glutamatergic modulation of resting state functional connectivity of the dACC with the midbrain is suggestive of glutamatergic control of the dACC over midbrain regions, which in turn could modulate midbrain dopamine firing and subsequent dopaminergic projections to the striatum, leading to individual differences in impulsive decision making. However, as ¹H MRS does not directly measure synaptic glutamate transmission, but rather reflects metabolic and neurotransmitter pools of glutamate within a ROI (Gruetter et al. 1998
), and resting state functional connectivity does not represent glutamatergic projections from one brain region to another, animal research is needed to further investigate this interpretation of the current findings.
It is important to stress that our results should be viewed in light of some methodological limitations. First, the sample size was modest, which might limit the generalizability of the current results. Second, because of the exploratory nature of our study, we applied a statistical threshold for significance that did not fully account for the issue of multiple comparisons. However, the observed correlation between delay discounting (AUC values) and glutamate concentrations and between delay discounting and functional connectivity of the dACC with the midbrain remained significant when correcting for multiple comparisons. Instead, there was a trend toward a significant correlation between glutamate concentrations and dACC functional connectivity with the midbrain when fully correcting for multiple comparisons. Although the current study was set up as a pilot study and gives a first indication of the interaction between glutamate concentrations and functional connectivity between brain regions under rest in predicting impulsive behavior, future studies are required using larger sample sizes (and thereby increasing statistical power) to replicate the current findings.
In conclusion, the current findings suggest that individual differences in impulsive decision making depend on intrinsic properties of the dACC and not merely on task-related cognitive processes, supporting the idea that altered basic conditions of brain functioning lead to abnormal functional responses. This is important to acknowledge, because spontaneous intrinsic brain processes have been proposed to be a potential promising biomarker of disease (Greicius 2008
) and impulsive decision making is a common feature in several psychiatric disorders. Recent findings have indicated that there is a genetic influence on individual differences in delay discounting (Boettiger et al. 2007
; Eisenberg et al. 2007
; Anokhin et al. 2011
). Assuming there is a long road between genes and higher-order cognitive functions, intrinsic properties of brain functioning in the form of resting state glutamate concentrations or functional connectivity, may provide an intermediate step between genes and abnormalities in higher-order cognitive functions, such as excessive delay discounting. In addition, the current study indicates that in addition to previously found involvement of dopaminergic and serotonergic neurotransmission, glutamate signaling plays an important role in human impulsive decision making. Although these findings need to be replicated in larger samples, the current results suggest that glutamate concentrations obtained by ¹H MRS and resting state fMRI are candidate biomarkers for impulsivity and impulsivity related diseases.