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. 2017 Nov 22;39(2):1004–1014. doi: 10.1002/hbm.23899

Influence of ventral tegmental area input on cortico‐subcortical networks underlying action control and decision making

Anja Richter 1,2,✉, Oliver Gruber 1,2
PMCID: PMC6866482  PMID: 29165901

Abstract

It is argued that the mesolimbic system has a more general function in processing all salient events, including and extending beyond rewards. Saliency was defined as an event that is unexpected due to its frequency of occurrence and elicits an attentional‐behavioral switch. Using functional magnetic resonance imaging (fMRI), signals were measured in response to the modulation of salience of rewarding and nonrewarding events during a reward‐based decision making task, the so called desire‐reason dilemma paradigm (DRD). Replicating previous findings, both frequent and infrequent, and therefore salient, reward stimuli elicited reliable activation of the ventral tegmental area (VTA) and ventral striatum (vStr). When immediate reward desiring contradicted the superordinate task‐goal, we found an increased activation of the VTA and vStr when the salient reward stimuli were presented compared to the nonsalient reward stimuli, indicating a boosting of activation in these brain regions. Furthermore, we found a significantly increased functional connectivity between the VTA and vStr, confirming the boosting of vStr activation via VTA input. Moreover, saliency per se without a reward association led to an increased activation of brain regions in the mesolimbic reward system as well as the orbitofrontal cortex (OFC), inferior frontal gyrus (IFG), and anterior cingulate cortex (ACC). Finally, findings uncovered multiple increased functional interactions between cortical saliency‐processing brain areas and the VTA and vStr underlying detection and processing of salient events and adaptive decision making.

Keywords: desire‐reason dilemma, fMRI, functional connectivity, mesolimbic dopamine system, reward, saliency, ventral striatum, VTA

1. INTRODUCTION

Converging evidence suggests a specific role for the mesolimbic reward system and its major dopaminergic input in coding rewards and reward‐associated stimuli (Schultz, Tremblay, & Hollerman, 1998; Schultz, Tremblay, & Hollerman, 2000). However, it is argued that dopamine‐driven signaling may not be selective for rewards, but instead may code all salient events in general. It has been reported that dopamine neurons in the substantia nigra and VTA respond to many different salient environmental events. Human striatal activations have been observed following punishment (Knutson, Fong, Bennett, Adams, & Hommer, 2003; Knutson, Westdorp, Kaiser, & Hommer, 2000) and aversive stimuli (Becerra, Breiter, Wise, Gonzalez, & Borsook, 2001), neutral events when they are unexpected (Zink, Pagnoni, Martin, Dhamala, & Berns, 2003) as well as novel or infrequent events (Downar, Crawley, Mikulis, & Davis, 2002). Moreover, Zink, Pagnoni, Martin‐Skurski, Chappelow, and Berns (2004) provided evidence that the mesolimbic system's role in processing reward is dependent on the saliency modulated by the rewards receipt, rather than value or hedonic feelings. Furthermore, it is hypothesized that dopamine becomes a mediator of incentive salience (Berridge & Robinson, 1998; Berridge, 2007) in a way that dopamine signaling may promote attention towards important events in the environment leading to an adjustment of behavioral reactions and therewith influencing goal‐directed behavior (Horvitz, 2000).

In this study, the term salience is characterized as remarkable feature of an event that automatically captures the attention of an organism and involuntarily leads to a switch in attentional and behavioral resources (Redgrave, Prescott, & Gurney, 1999). The salience of a given stimulus can either be context‐dependent or stimulus‐inherent, depending on factors such as frequency of occurrence or novelty (Downar et al., 2002). Thereby, infrequent behaviorally relevant events are salient due to their rarity and automatically provoke a bottom‐up stimulus‐driven orienting reflex. Furthermore, these behaviorally relevant events require an adjustment of both attentional and behavioral resources to obtain a goal, involving higher order cognitive processes (Corbetta & Shulman, 2002).

The current experiment sought to differentiate human mesolimbic responses to various salient events. The vStr as key region within the reward circuitry, integrates widespread limbic and cortical inputs, which are in turn under modulatory influence of dopaminergic neurons in the VTA (Haber & Knutson, 2010; Sesack & Grace, 2010). We used fMRI to examine the influence of the modulation of salience on neural mechanisms and cortico‐subcortical functional interactions involved in action control of reward‐based decision making. For this purpose, we created a modified version of the “desire‐reason dilemma” (DRD) paradigm (Diekhof & Gruber, 2010). This task allowed us to systematically investigate reward‐related brain activations resulting from dopaminergic bottom‐up mechanisms when previously conditioned reward stimuli had to be collected as well as top‐down regulatory mechanisms when these reward stimuli had to be rejected in favor of a superordinate long‐term goal. In contrast to the paradigm introduced by Diekhof and Gruber (2010), the new feature of the current design was the manipulation of saliency by altering the frequency of occurrence of rewarding stimuli. Additionally, we also wanted to investigate human mesolimbic responses to saliency per se without a reward association by manipulating the frequency of occurrence of goal‐irrelevant nonrewarding stimuli. In this context, less frequent events are more salient because they are less predictable.

We hypothesized greater activation in the mesolimbic reward system due to the infrequent (high salience) relative to frequent (low salience) stimuli and that the functional connectivity within the reward system would be modulated by saliency.

2. MATERIALS AND METHODS

2.1. Subjects

Twenty‐six right‐handed, healthy subjects (14 females), ages 20–35 years (mean: 25.27 years, SD: 4.21 years) were recruited from an academic environment. Subjects had normal or corrected‐to‐normal vision and no history of neurological or psychiatric disorders. Further exclusion criteria were lifetime diagnosis of substance dependence, substance abuse during the last month and cannabis abuse during the last two weeks. Ethical approval from local ethics committee and written informed consent were acquired before investigation. Subjects were paid for participation.

2.2. Experimental task

One day before the fMRI measurement, subjects underwent an operant conditioning task and a training session of the DRD paradigm. In the operant conditioning, nine differently colored squares were presented in a shuffled mode. Each trial consisted of two simultaneously presented colors. By free button choice, subjects were encouraged to explore which of these two presented colors were associated with an immediate reward to maximize their overall outcome by selecting one out of the two colors. Pressing button 1 meant that the left color was selected, whereas button 2 meant that the right color was selected. Two of the nine colors (red and green) always led to an immediate reward of 10 bonus points. Already in the operant conditioning task, red was presented six times less than the green squares. Decisions were immediately followed by a feedback indicating whether the decision for the left or right color led to an immediate reward or not. The overall goal of this procedure was to establish stimulus‐response‐reward contingencies, relevant for the next phase of the experiment.

On the second day, after successful conditioning and training session, subjects underwent fMRI while performing a modified version of the DRD paradigm (see also Diekhof and Gruber, 2010). Stimuli were the same as in the operant conditioning phase, but now subjects had to pursue a superordinate long‐term goal during task blocks of eight trials to acquire 50 points at the end of each block (see Figure 1). The superordinate task goal of an individual block was indicated by a cue showing the two target colors that had to be selected every time they occurred. When a target stimulus and a conditioned reward stimulus (CR) were presented simultaneously (dilemma situation), subjects always had to select the target stimulus. Otherwise they lost the 50 points and were only able to collect bonus points. In addition, subjects were allowed to select the CR for an immediate bonus, when it was presented together with a nontarget stimulus (desire situation). These bonus points were added to the 50 points at the end of each block, if the long‐term goal was successfully reached.

Figure 1.

Figure 1

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Experimental design of the “desire‐reason dilemma paradigm”. The superordinate task goal of each block was to collect all target stimuli and additionally collect all conditioned reward stimuli, when they were presented together with a nontarget in the desire situation. However, subjects were forced to reject these stimuli when they were presented together with a target stimulus in the dilemma situation, in order to reach the superordinate task goal of 50 points at the end of each block [Color figure can be viewed at http://wileyonlinelibrary.com]

Seven of the nine colored squares occurred with same frequency during the whole experiment. The remaining two colors (red and yellow) were presented infrequently. Red was previously conditioned as a reward, served as salient conditioned reward stimulus (sCR) and occurred six times less than the nonsalient conditioned reward stimulus (green; CR). Additionally, yellow served as salient control condition for the sCR and was presented six times less than the blue colored square, serving as control condition for the CR. Both yellow and blue were never presented as target stimuli, were never presented simultaneously with a sCR and CR, respectively and were always shown as nontarget. These stimuli were introduced to create an experimental baseline condition for the subsequent subtraction contrasts and to investigate brain responses to saliency per se without a reward association. Stimuli properties including location, exact timing as well as preceding and following trials were pseudorandomized and counterbalanced in each run so that the sole manipulation of salience resulted from relative frequency. For more information, see Supporting Information.

2.3. Behavioral data analysis

Behavioral data were analyzed using the software package SPSS (IBM SPSS statistics 24.0). A repeated‐measures ANOVA was performed with the three factors saliency (trials containing salient stimuli vs. nonsalient stimuli), reward (reward stimuli vs. nonreward stimuli), and context (desire vs. reason (trials containing target stimuli)). Error and omission trials were excluded. Normal distribution of performance and reaction time data was tested using the Kolmogorov‐Smirnov test. Differences between individual experimental conditions were subsequently assessed with a Bonferroni post hoc t‐test, correcting for multiple comparisons.

2.4. FMRI data acquisition and analysis

The experiment was performed on a 3 Tesla MRI scanner (Magnetom TIM Trio; Siemens Healthcare, Erlangen, Germany). Thirty‐four axial slices parallel to the anterior‐posterior commissure were acquired in ascending acquisition order (slice thickness = 3 mm; gap 20%) using a T2*‐sensitive echo‐planar imaging (EPI) sequence (interscan interval 1,800 ms; echo time 30 ms; flip angle 70°; field‐of‐view 192 mm). A total of 1,527 image volumes were acquired over the course of three functional runs. In the scanner, subjects saw the stimuli through goggles (Resonance Technology, Nothridge, USA) and responded via button presses on a fiber optic computer response device (Current Designs, Philadelphia, USA). Generation of stimuli and triggering of visual stimulation was achieved using the Presentation® Software (Neurobehavioral Systems, Albany, USA). Functional images were preprocessed and analyzed with SPM 8 (Wellcome Trust Centre for Neuroimaging, University College London, London, UK). At single subject level, each experimental condition was convolved with the hemodynamic response function to form regressors for each individual trial type: trials where a nontarget was paired with a nontarget, nontarget paired with a target, CR paired with a nontarget and CR paired with a target, each both for the nonsalient trials and for the salient trials. The block cues indicating the target stimuli and the block feedback were also modeled as independent regressors, resulting in a total of 10 regressors. Linear t‐contrasts were defined for assessing the specific effects of each condition of interest. Single‐subject contrast images were taken to the second level to assess group effects with random‐effects analyses. Group effects were examined using a full factorial model with the factors saliency (salient trials versus nonsalient trials) and experimental trial type (trials combining nontarget plus nontarget stimulus; nontarget plus target; CR plus nontarget; CR plus target). For detailed information regarding calculated contrasts see Supporting Information.

Statistical effects were determined at a search criterion of p < .005, uncorrected, with a minimum cluster size of 10 voxels, if not otherwise indicated. Corrections for multiple comparisons were performed using family‐wise error (FWE) at p < .05. For brain regions with a priori hypotheses i.e., for the bilateral VTA and vStr (VTA: ±8 −16 −16; 8 mm sphere; vStr: ±12 12 −4; 6 mm sphere, coordinates taken from Diekhof & Gruber, 2010) we used small volume corrections (SVC). To illustrate the magnitude of change due to the influence of salience, means of parameter estimate values for the desire and reason contrast were plotted. For this purpose, the MarsBar software (Brett, Anton, Valabregue, & Poline, 2002) was used to extract each region of interests (ROIs) mean blood oxygenation level‐dependent (BOLD) beta value with a sphere of 6 mm around the reported peak levels for each participant (see Figure 4 and Supporting Information Figure S1).

2.5. Psychophysiological interaction analysis

We assessed the functional interaction between the VTA and vStr to reveal the impact of saliency processing on the reward system by performing psychophysiological interaction (PPI) analyses (Friston et al., 1997). As seed regions, individual BOLD signal time courses were extracted from first eigenvariate time series (VOI; sphere of 8mm) of the local activation maxima within the right VTA (MNI coordinates: 9 −16 −17) and left vStr (MNI coordinates: −9 5 −8), which were the second‐level local activation maxima in response to the salient nontarget stimuli in the saliency contrast (see Table 1: saliency contrast: salient nontarget vs. nontarget > nontarget vs. nontarget). As we found increased activations of the bilateral VTA and vStr in the desire saliency contrast (sDC) and reason saliency contrast (sRC), first, we conducted a PPI analysis where the psychological vector consisted of the comparison between the sDC with the DC and second, where the psychological vector consisted of the comparison between the sRC with the RC.

Table 1.

Saliency‐related brain activations in the saliency contrast (SC) without a reward association

Region MNI coordinates (t‐value)
Saliency contrast
L dorsal/ventral Striatum −9 5 −8 (2.31)+
R midbrain/VTA 9 −16 −17 (2.50)*
L OFC −54 29 −5 (1.74)+
L IFG/pars triangularis −54 29 1 (1.81)+
R BA 6/precentral gyrus 42 −4 31 (2.09)+
L BA 6/precentral gyrus −42 −7 31 (2.20)+
L fronto‐opercular cortex/anterior insular cortex −21 17 1 (2.08)+
R dorsal ACC 12 8 28 (2.52)+
L dorsal ACC −18 11 25 (1.85)+
L intraparietal cortex −21 −46 40 (2.11)+
L inferior parietal lobule −51 −25 40 (2.49)
R middle temporal gyrus 54 5 −20 (2.11)+
R extrastriate occipital cortex 24 −100 16 (2.84)
L extrastriate occipital cortex −15 −94 −8 (2.61)
L parahippocampal gyrus −21 −52 −8 (2.28)+
L putamen −24 5 −5 (2.13)+
L/R superior colliculus 0 −31 1 (2.22)+
R medial globus pallidus 18 −7 −8 (3.06)
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Abbreviations: ACC, anterior cingulate cortex, BA, brodmann area; L, left; n.s., not significant; OFC, orbitofrontal cortex; R, right. Activations are reported at p < .005, uncorrected, with a minimum cluster size of 10 voxels; + p < .05, uncorrected, with a minimum cluster size of 10 voxels; *p < .05 FWE‐corrected for small volume.

Furthermore, to examine functional interactions between further saliency‐processing brain regions, VOIs of the second‐level local activation maxima within the left OFC (MNI coordinates: −54 29 −5), left IFG (MNI coordinates: −54 29 1) and bilateral ACC (MNI coordinates: −18 11 25; 12 8 28) in response to the salient nontarget stimuli in the saliency contrast were extracted (see also Table 1). Based on these four seed regions, we also calculated two PPI analyses in the contrasts comparing the sDC with the DC and comparing the sRC with the RC. For more information, see Supporting Information.

3. RESULTS

3.1. Behavioral results

Mean percentages of correct responses and reaction times were compared across salient and nonsalient trials (see Table 2 for arithmetic mean ± SEM; see also Figure 2).

Table 2.

Percentages of correct responses and reaction times of 26 participants (mean ± SEM)

Nonsalience Salience
No reward nontarget vs. nontarget trials

99.9% ± 0.04%

749ms ± 26.3ms

99.8% ± 0.2%

763ms ± 28.8ms
nontarget vs. target trials

98.8% ± 0.2%

556ms ± 20.8ms

98.1% ± 0.5%

581ms ± 19.2ms
Reward CR vs. nontarget trials

93.7% ± 1.0%

849ms ± 27.3ms

91.2% ± 1.3%

858ms ± 27.4ms
CR vs. target trials

93.2% ± 0.9%

605ms ± 19.0ms

91.9% ± 1.3%

640ms ± 23.0ms
Overall

96.4% ± 0.5%

690ms ± 16.4ms

95.3% ± 0.6%

710ms ± 16.3ms
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Figure 2.

Figure 2

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Behavioral findings. (a) Mean percentage of correct performance rates in response to nonsalient trials and salient trials (mean ± SEM; *p < .01). (b) Correct reaction times in response to nonsalient trials and salient trials (mean ± SEM; **p < .001). Post hoc analyses revealed a significant increase in reaction times when subjects responded to the target stimuli presented together with a salient nontarget (*p < .01) and presented together with a salient conditioned reward (**p < .001) compared to the corresponding nonsalient trials. Nonsalient trials are represented by dark gray bars and salient trials are represented by light gray bars. For more details see Table 1

Analysis of performance data revealed significant main effects of salience (F (1,25)=9.486, p = .005), reward (F (1,25)=49.207, p < .0001) and an interaction effect of salience × reward (F (1,25)=6.934, p = .014). However, context did not exhibit a significant effect on correct responses (F (1,25)=2.315, p = .141). Bonferroni post hoc t‐tests revealed significantly higher performance rates for all nonsalient trials compared to salient trials (t (25)=3.080, p = .005) as well as for all trials without a CR compared to trials including CR (t (25)=7.016, p < .0001).

In addition, reaction time data showed main effects of salience (F (1,25)=30.602, p < .0001), reward (F (1,25)=72.799, p < .0001) and context (F(1,25)=213.099, p < .0001), as well as interaction effects of salience × context (F (1,25)=5.661, p = .025) and reward × context (F (1,25)=20.848, p < .0001), confirming the successful experimental implementation of saliency in this study. Post hoc t‐tests correcting for multiple comparisons uncovered a significant increase of reaction times when subjects responded to the target stimuli presented together with a salient nontarget (t (25)=3.836, p = .001) and presented together with a salient CR (t (25)=4.245, p < .0001) compared to the corresponding nonsalient trials (Figure 2). This may demonstrate enhanced working memory demands in recalling and comparing information regarding the target stimulus and the infrequently presented salient stimuli leading to a prolonged reaction compared to the frequently presented stimuli, replicating previous findings (Gruber et al., 2009, 2010).

3.2. FMRI results

In line with previous findings (Diekhof & Gruber, 2010), in the desire contrast reliable bottom‐up activation of the bilateral vStr and VTA (see Table 3, (1)) and of an extended bilateral fronto‐parietal network was found (Supporting Information Table S1). In addition, in the reason contrast simultaneous presentation of CR and target stimulus led to a significant down‐regulation of activation in the bilateral vStr and VTA (see Table 4 (4)).

Table 3.

Reward‐related brain activations in the desire contrast (DC), desire saliency contrast (sDC) and the comparison between them

MNI coordinates (t‐value)
Region Desire contrast Desire saliency contrast

Desire saliency contrast > Desire contrast

 Desire contrast > Desire saliency contrast
(1) (2) (3)
R dorsal/ventral Striatum 12 8 −2 (4.78)* 12 8 1 (4.73)** n.s. n.s.
L dorsal/ventral Striatum −15 8 −2 (4.16)* −12 8 −2 (3.69)* n.s. −6 5 −11 (2.21)+
R midbrain/VTA 9 −19 −20 (4.53)* 9 −19 −14 (2.81)* n.s. n.s.
L midbrain/VTA −6 −22 −17 (3.82)* −3 −22 −26 (2.65) n.s. n.s.
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Abbreviations: L, left; n.s., not significant; R, right. Activations are reported at p < .005, uncorrected; + p < .05, uncorrected, with a minimum cluster size of 10 voxels; *p < .05 FWE‐corrected for small volume; **p < .05, FWE‐corrected (whole brain).

Table 4.

Reward‐related brain activations in the reason contrast (RC), reason saliency contrast (sRC) and the comparison between them

MNI coordinates (t‐value)
Region Reason contrast Reason saliency contrast

Reason saliency contrast >

Reason contrast

 Reason contrast > Reason saliency contrast
(4) (5) (6)
R dorsal/ventral Striatum n.s n.s. n.s. n.s
L dorsal/ventral Striatum n.s. −12 5 1 (2.41)+ −12 5 1 (2.43)+ n.s.
R midbrain/VTA n.s. 12 −16 −14 (2.73)* 6 −19 −11 (2.05)+ n.s.
L midbrain/VTA n.s. −6 −16 −8 (2.18)+ −3 −19 −8 (1.73)+ n.s.
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Abbreviations: L, left; n.s., not significant; R, right. Activations are reported at + p < .05, uncorrected, with a minimum cluster size of 10 voxels; *p < .05 FWE‐corrected for small volume; **p < .05, FWE‐corrected (whole brain).

Successful modulation of salience in the present experiment was ensured by implementing both infrequent CR and infrequent nontargets without a reward association. First, we wanted to examine the effect of infrequent and therewith salient nontargets on the mesolimbic reward system. Indeed, presentation of infrequently presented nontargets compared to the frequently presented nontargets elicited reliable activation of the left vStr, right VTA and further saliency‐processing brain regions including the left OFC, left IFG and bilateral ACC (Table 1 and Figure 3). These brain regions were activated due to saliency per se.

Figure 3.

Figure 3

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Saliency‐related brain activations in the saliency per se contrast. Top left Increased activation of the left vStr; Top right Increased activation of the left OFC and IFG/pars triangularis; Bottom left Increased activation of the left VTA; Bottom right Increased activation of the bilateral dorsal ACC in response to the infrequent neutral events. For display purposes activation was thresholded at p < .05, uncorrected. t‐values are indicated by color bars. Regions listed in Table 4 [Color figure can be viewed at http://wileyonlinelibrary.com]

Second, infrequent and therefore salient CR also elicited reward‐related activation in the bilateral vStr and VTA (Table 3; see also Supporting Information Figure S1), as well as in several fronto‐parietal brain regions in the desire saliency contrast (Supporting Information Table S2). Furthermore, in the reason saliency contrast we found reduced suppression of reward‐related activation in the left vStr and bilateral VTA (Table 4, (5)). Interestingly, comparison of the sRC and RC, when it was not allowed to choose the CR (salient or not), revealed an increased activation of the left vStr and bilateral VTA (Table 4, (6) left; Figure 4), indicating a boosting of activation in these brain regions due to the saliency of the CR.

Figure 4.

Figure 4

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Reward‐related brain activations in the comparison of the reason saliency contrast (sRC) vs. reason contrast (RC). (a) left Increased activation of the left vStr; right contrast estimates at the vStr (mean ± SEM; *p < .05). (b) left Increased activation of the bilateral VTA; right contrast estimates at the VTA (mean ± SEM; *p < .05). For display purposes activation was thresholded at p < .05, uncorrected. t‐values are indicated by color bars. Regions listed in Table 3. For more details see Supporting Information Table S2 [Color figure can be viewed at http://wileyonlinelibrary.com]

3.3. PPI results

To further examine the effects of the modulation of salience on cortico‐subcortical interactions, at first we explored the functional connectivity of the VTA and vStr in the desire saliency and reason saliency contrasts. We observed a significantly increased functional interaction between the right VTA and the right vStr in the sDC compared to the DC (seed: 9 −16 −17; Table 5 (A); see also Figure 5). In addition, we also detected an increased functional coupling between these regions when comparing the sRC with the RC (seed: 9 −16 −17; Table 5 (B); Figure 5), consistent with the boosting of activation in these brain regions (as shown in Table 4). This enhanced functional connectivity was also found between the left vStr and the right vStr as well as between the bilateral VTA in the sDC compared to the DC (seed: −9 5 −8; Table 5 (A)). Moreover, both VTA and vStr showed an increased functional coupling with the OFC and/or amygdala in the observed contrasts (see Table 5 (A) + (B) and Figure 6). In a second step, we explored the functional connectivity of further saliency‐processing brain regions including the OFC, IFG and ACC, which were additionally activated due to the salient nontarget stimuli in the saliency contrast. Once more, we found increased functional interactions between these seed regions and the VTA and/or vStr, in both the sDC > DC and sRC > RC contrasts (see Supporting Information Table S3), demonstrating the existence of multiple increased functional connections between cortical and subcortical brain regions when processing saliency.

Table 5.

Increased psychophysiological interactions of the right VTA and left vStr in the (A) desire saliency contrast compared to the desire contrast and (B) the reason saliency contrast compared to the reason contrast

MNI coordinates (t‐value)
Seed area R VTA (9 −16 −17) Seed area L vStr (‐9 5 −8)
Region

(A) sDC > DC

(B) sRC > RC

(A) sDC > DC

(B) sRC > RC
R dorsal/ventral Striatum 9 17 −8 (1.82)+ 9 26 −11 (2.45)+ 15 8 −8 (2.95)* n.s.
L dorsal/ventral Striatum n.s. n.s. n.s. n.s.
R midbrain/VTA n.s. 6 −10 −17 (2.20)+ 6 −10 −14 (2.66)+ n.s.
L midbrain/VTA n.s. −6 −10 −17 (1.86)+ −9 −19 −8 (1.83)+ n.s.
R OFC n.s. 39 53 −11 (2.24) 27 38 −8 (2.37)+ 51 32 −5 (2.07)+
L OFC n.s. −21 53 −5 (2.18)+ −21 38 −14 (2.32)+ −36 44 −5 (1.94)+
L amygdala n.s. n.s. −21 −4 −14 (3.30)* n.s.
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Abbreviations: L, left; n.s., not significant; OFC, orbitofrontal cortex; R, right. Activations are reported at p <.005, uncorrected; + p < .05, uncorrected; *p < .05, FWE‐corrected for small volume.

Figure 5.

Figure 5

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Increased VTA‐vStr connectivity. Increased functional interaction between (a) right VTA and right vStr in the direct comparison of the (b) desire saliency contrast vs. desire contrast and (c) reason saliency contrast vs. reason contrast. For display purposes activation was thresholded at p < .05, uncorrected. t‐values are indicated by color bars. Regions listed in Table 5 [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 6.

Figure 6

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Increased functional connectivity within the mesolimbic reward system. Increased functional interaction between (a) left vStr and (b) the OFC as well as amygdala in the direct comparison of the desire saliency contrast vs. desire contrast and (c) the OFC in the reason saliency contrast vs. reason contrast. For display purposes activation was thresholded at p < .05, uncorrected. t‐values are indicated by color bars. Regions listed in Table 5 [Color figure can be viewed at http://wileyonlinelibrary.com]

4. DISCUSSION

In the present study, we investigated the impact of the modulation of salience on the functional activity and connectivity of the human mesolimbic reward system, focusing on the functional response of the VTA and vStr to infrequent events in a reward‐based decision making task.

An important new feature of the applied DRD paradigm is the introduced factor saliency as implemented by the manipulation of both rewarding and neutral stimuli through relative frequency. Infrequent stimuli with long intervals between consecutive events are unexpected and hence more salient. Behavioral results confirmed the successful experimental implementation of saliency in this study, as analyses of reaction time data revealed significant main effects of salience, reward and context. Reaction times for trials including target stimuli plus infrequent reward stimuli were significantly longer than for trials including target stimuli plus frequent reward stimuli. The same applies to presented trials encompassing target stimuli plus infrequent nontarget stimuli compared to trials with frequent nontarget stimuli. Infrequent stimuli independent of the reward association increased the reaction times to target stimuli, demonstrating the occurrence of contextual mismatch effects that may impose increased demands on cognitive control processes (Gruber et al., 2009). In line with this finding, it has been shown that unexpected auditory pitch deviants that were behaviorally irrelevant led to significant longer reaction times and higher error rates in an auditory target‐detection task (Sussman et al., 2003). Furthermore, previous studies reported prolonged reaction times for infrequent novels compared to frequently presented events (Kirino, Belger, Goldman‐Rakic, & McCarthy, 2000).

In line with these behavioral data, neuroimaging findings confirmed the successful experimental implementation of saliency by showing that infrequently presented neutral stimuli led to an increased activation of the VTA and vStr due to saliency per se. Additionally, these salient stimuli elicited reliable activation of the left OFC, left IFG and bilateral ACC (see Figure 3). Previous studies have used oddball paradigms to assess brain responses to infrequent salient stimuli without a reward association, by reporting on the one hand no striatal activity (Clark, Fannon, Lai, Benson, & Bauer, 2000; Kirino et al., 2000) and on the other hand VTA activity in response to infrequent behaviorally relevant deviants in a cued task‐switching paradigm (Gruber, Diekhof, Kirchenbauer, & Goschke, 2010). We could extend these findings by showing that the VTA as well as the vStr were significantly activated in response to these infrequent stimuli. Moreover, the results of the present study reveal that activity in the VTA and vStr increased in response to both frequent and infrequent rewarding stimuli, replicating previous findings (Diekhof & Gruber, 2010; Diekhof, Keil, et al., 2012; Diekhof, Nerenberg, et al., 2012).

There is growing consensus that the brain computes and compares value and saliency signals at the time of decision making (Rangel, Camerer, & Montague, 2008). Value signals provide a measure of the desirability of a stimulus, constituted by the associated amount of reward. Saliency signals, in turn, provide a measure of the importance of the stimulus, relating to motivational and attentional processes in the brain (Rangel et al., 2008).

On the biological level, there is evidence for independent dopaminergic processing pathways of reward and saliency leading to the assumption that midbrain dopamine neurons are not homogeneous (Matsumoto & Hikosaka, 2009; Matsumoto & Takada, 2013). It is hypothesized that on the one side, a proportion of neurons respond to rewarding and reward‐predicting stimuli, encoding the motivational value for positive outcomes, engendering value learning and seeking behavior (Berridge, 2012). Alternatively, other neuron populations in the midbrain encode a motivational salience signal by responding more generally to salient stimuli, triggering orienting and explorative behavior (Bromberg‐Martin, Matsumoto, & Hikosaka, 2010).

Comparison of infrequent reward trials and frequent reward trials did not show stronger mesolimbic activation in response to the salient features of the reward stimuli (see Supporting Information Figure S1). One previous study dissociated value and saliency signals at the time of choice and showed that the vStr was modulated by both value and salience (Litt, Plassmann, Shiv, & Rangel, 2011). Furthermore, it was found that the vStr also correlates with both saliency and valence during the anticipation of probabilistic rewards (Cooper & Knutson, 2008). However, the implementation of saliency between these studies and the present study varied widely. In the applied DRD paradigm, infrequent rewards combined both rewarding and salient attributes. It is reasonable that the underlying neural activities may interfere in our study and that a higher spatial resolution of fMRI is needed to disentangle the overlapping activities. In a follow‐up study, accelerated multiband echo‐planar imaging sequence with higher spatial resolution will be used to obtain functional data in order to identify potential subregions within the midbrain and striatum.

Furthermore, the mesolimbic reward system showed significantly increased activation in response to the salient reward stimuli when presented together with target stimuli (sRC) as compared to the frequent and therefore less salient reward stimuli (RC), possibly indicating a boosting of activation in the vStr and VTA (see Figure 4). PPI analyses could confirm this assumption by revealing a significantly increased functional connectivity between the VTA and vStr in both the comparison of the desire saliency contrast with the desire contrast and the reason saliency contrast compared to the reason contrast (see Figure 5). A previous study has provided evidence for inhibitory influences of the anteroventral prefrontal cortex (avPFC) on the mesolimbic dopamine system during self‐controlled decisions (Diekhof & Gruber, 2010). However, the strong functional coupling between VTA and vStr may indicate that the saliency‐modulated dopamine input from the VTA to the vStr may be stronger compared to inhibitory influences of the avPFC and in turn, that the saliency signal in the VTA apparently was not suppressed by prefrontal regulatory mechanisms (Bromberg‐Martin et al., 2010; Macpherson, Morita, & Hikida, 2014), leading to the boosting of activation in situations where top‐down control was needed. In addition to that, the VTA and vStr showed an increased functional coupling with the OFC and the amygdala (see Figure 6). Moreover, we could show multiple increased functional interactions between the OFC, IFG, ACC and subcortical brain regions. As part of the reward circuit, the OFC has been shown to play a central role in processing of incentive and motivational value in animals (Schultz et al., 2000; Sesack & Grace, 2010), in detecting motivationally significant events outside the current focus of attention, and the OFC has been further shown to exhibit an increased functional interaction with the VTA when processing salient events in humans (Diekhof, Falkai, & Gruber, 2009). It was previously hypothesized that dopamine may not signal the motivational significance of stimuli itself but may rather regulate orbitofrontal and amygdalar glutamatergic inputs to striatal regions, which is necessary for adaptive decision making (Horvitz, 2000). Animal studies provided evidence that stimulation of the vStr influenced OFC activity and possibly connectivity (Ewing & Grace, 2013) and, in turn lesions in OFC led to changes in striatal dopamine levels (Clarke et al., 2014), demonstrating the necessity of the interaction between OFC and mesolimbic structures in guiding adaptive behavior. In addition, the dorsal ACC together with the insula constitute the salience network, which is mainly involved in sensory perception and the coordination of behavioral responses (Lamichhane, Adhikari, & Dhamala, 2016). Furthermore, the ACC has also commonly been observed in oddball processing and target detection (Brázdil et al., 2005; Downar, Crawley, Mikulis, & Davis, 2001) as well as in reversal learning studies (Kringelbach & Rolls, 2003). Likewise, activations of the IFG have been found to be evoked by both response conflicts and by contextual mismatches (Gruber et al., 2009) as well as in response inhibition and instrumental learning in go/no‐go tasks (Guitart‐Masip et al., 2012). Overall, this study provided clear evidence for the importance of increased functional interactions between cortical saliency‐processing brain regions and mesolimbic structures of the reward system in adaptive decision making.

In conclusion, these findings contribute to the growing understanding of how brain mechanisms may process and integrate the influence of salient and rewarding information on decision making. We could show that coding of infrequent and therefore salient events led to a significant boosting of activation in the VTA and vStr. Specifically, we further revealed significantly increased functional coupling between these key regions of the reward system that may underlie the boosting of activation. Moreover, our findings highlight the existence of multiple increased functional interactions between brain regions within and beyond the mesolimbic reward system underlying adaptive processing of salient events and successful behavioral decision making.

CONFLICT OF INTEREST

Oliver Gruber was honorary speaker for the following companies: Astra Zeneca, Brystol Myers Squibb, Janssen Cilag, Lilly, Servier, and Otsuka. He has been invited to scientific congresses by Astra Zeneca, Janssen Cilag and Pfizer and has received a research grant from Servier. The present work is unrelated to these grants and relationships. No other disclosures were reported.

Supporting information

Additional Supporting Information may be found online in the supporting information tab for this article.

Supporting Information

Click here for additional data file. (61.2KB, docx)

ACKNOWLEDGMENTS

We would like to thank Ilona Pfahlert and Britta Perl as well as the staff of the unit “MR‐Research in Neurology and Psychiatry” at the University Medical Center Göttingen (Germany) for help with data acquisition.

This work was partially funded by a Deutsche Forschungsgemeinschaft (DFG) grant to Oliver Gruber (GR1950/8‐1).

Richter A, Gruber O. Influence of ventral tegmental area input on cortico‐subcortical networks underlying action control and decision making. Hum Brain Mapp. 2018;39:1004–1014. 10.1002/hbm.23899

Funding information This work was partially funded by a Deutsche Forschungsgemeinschaft (DFG) grant to Oliver Gruber (GR1950/8‐1).

REFERENCES

  1. Becerra, L. , Breiter, H. C. , Wise, R. , Gonzalez, R. G. , & Borsook, D. (2001). Reward circuitry activation by noxious thermal stimuli. Neuron, 32, 927–946. [DOI] [PubMed] [Google Scholar]
  2. Berridge, K. C. , & Robinson, T. E. (1998). What is the role of dopamine in reward: Hedonic impact, reward learning, or incentive salience? Brain Research Reviews, 28(3), 309–369. [DOI] [PubMed] [Google Scholar]
  3. Berridge, K. C. (2007). The debate over dopamine's role in reward: The case for incentive salience. Psychopharmacology, 191(3), 391–431. [DOI] [PubMed] [Google Scholar]
  4. Berridge, K. C. (2012). From prediction error to incentive salience: Mesolimbic computation of reward motivation. The European Journal of Neuroscience, 35(7), 1124–1143. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Brázdil, M. , Dobsík, M. , Mikl, M. , Hlustík, P. , Daniel, P. , Pazourková, M. , … Rektor, I. (2005). Combined event‐related fMRI and intracerebral ERP study of an auditory oddball task. Neuroimage, 26(1), 285–293. [DOI] [PubMed] [Google Scholar]
  6. Brett, M. , Anton, J. , Valabregue, R. , & Poline, J. B. (2002). Region of interest analysis using an SPM toolbox. Neuroimage, 16(Suppl 1), 1141. [Google Scholar]
  7. Bromberg‐Martin, E. S. , Matsumoto, M. , & Hikosaka, O. (2010). Dopamine in motivational control: Rewarding, aversive, and alerting. Neuron, 68(5), 815–834. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Clark, V. P. , Fannon, S. , Lai, S. , Benson, R. , & Bauer, L. (2000). Responses to rare visual target and distractor stimuli using event‐related fMRI. Journal of Neurophysiology, 83, 3133–3139. [DOI] [PubMed] [Google Scholar]
  9. Clarke, H. F. , Cardinal, R. N. , Rygula, R. , Hong, Y. T. , Fryer, T. D. , Sawiak, S. J. , … Roberts, A. C. (2014). Orbitofrontal dopamine depletion upregulates caudate dopamine and alters behavior via changes in reinforcement sensitivity. The Journal of Neuroscience, 34(22), 7663–7766. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Cooper, J. C. , & Knutson, B. (2008). Valence and salience contribute to nucleus accumbens activation. Neuroimage, 39, 538–547. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Corbetta, M. , & Shulman, G. L. (2002). Control of goal‐directed and stimulus‐driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201–215. [DOI] [PubMed] [Google Scholar]
  12. Diekhof, E. K. , Falkai, P. , & Gruber, O. (2009). Functional interactions guiding adaptive processing of behavioral significance. Human Brain Mapping, 30(10), 3325–3331. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Diekhof, E. K. , & Gruber, O. (2010). When desire collides with reason: Functional interactions between anteroventral prefrontal cortex and nucleus accumbens underlie the human ability to resist impulsive desires. The Journal of Neuroscience, 30(4), 1488–1493. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Diekhof, E. K. , Keil, M. , Obst, K. U. , Henseler, I. , Dechent, P. , Falkai, P. , & Gruber, O. (2012). A functional neuroimaging study assessing gender differences in the neural mechanisms underlying the ability to resist impulsive desires. Brain Research, 1473, 63–77. [DOI] [PubMed] [Google Scholar]
  15. Diekhof, E. K. , Nerenberg, L. , Falkai, P. , Dechent, P. , Baudewig, J. , & Gruber, O. (2012). Impulsive personality and the ability to resist immediate reward: An fRMI study examining interindividual differences in the neural mechanisms underlying self‐control. Human Brain Mapping, 33(12), 2768–2784. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Downar, J. , Crawley, A. P. , Mikulis, D. J. , & Davis, K. D. (2001). The effect of task relevance on the cortical response to changes in visual and auditory stimuli: An event‐related fMRI study. Neuroimage, 14(6), 1256–1267. [DOI] [PubMed] [Google Scholar]
  17. Downar, J. , Crawley, A. P. , Mikulis, D. J. , & Davis, K. D. (2002). A cortical network sensitive to stimulus salience in a neutral behavioral context across multiple sensory modalities. Journal of Neurophysiology, 87(1), 615–620. [DOI] [PubMed] [Google Scholar]
  18. Ewing, S. G. , & Grace, A. A. (2013). Long‐term high frequency deep brain stimulation of the nucleus accumbens drives time‐dependent changes in functional connectivity in the rodent limbic system. Brain Stimulation, 6(3), 274–285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Friston, K. J. , Buechel, C. , Fink, G. R. , Morris, J. , Rolls, E. , & Dolan, R. J. (1997). Psychophysiological and modulatory interactions in neuroimaging. Neuroimage, 6, 218–229. [DOI] [PubMed] [Google Scholar]
  20. Gruber, O. , Melcher, T. , Diekhof, E. K. , Karch, S. , Falkai, P. , & Goschke, T. (2009). Brain mechanisms associated with background monitoring of the environment for potentially significant sensory events. Brain and Cognition, 69(3), 559–564. [DOI] [PubMed] [Google Scholar]
  21. Gruber, O. , Diekhof, E. K. , Kirchenbauer, L. , & Goschke, T. (2010). A neural system for evaluating the behavioral relevance of salient events outside the current focus of attention. Brain Research, 1351, 212–221. [DOI] [PubMed] [Google Scholar]
  22. Guitart‐Masip, M. , Huys, Q. J. , Fuentemilla, L. , Davan, P. , Duzel, E. , & Dolan, R. J. (2012). Go and no‐go learning in reward and punishment: Interactions between affect and effect. Neuroimage, 62(1), 154–166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Haber, S. N. , & Knutson, B. (2010). The reward circuit: Linking primate anatomy and human imaging. Neuropsychopharmacology, 35(1), 4–26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Horvitz, J. C. (2000). Mesolimbocortical and nigrostriatal dopamine responses to salient non‐reward events. Neuroscience, 96(4), 651–656. [DOI] [PubMed] [Google Scholar]
  25. Kirino, E. , Belger, A. , Goldman‐Rakic, P. , & McCarthy, G. (2000). Prefrontal activation evoked by infrequent target and novel stimuli in a visual target detection task: An event‐related functional magnetic resonance imaging study. Journal of Neuroscience, 20, 6612–6618. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Knutson, B. , Westdorp, A. , Kaiser, E. , & Hommer, D. (2000). FMRI visualization of brain activity during a monetary incentive delay task. Neuroimage, 12(1), 20–27. [DOI] [PubMed] [Google Scholar]
  27. Knutson, B. , Fong, G. W. , Bennett, S. M. , Adams, C. M. , & Hommer, D. (2003). A region of mesial prefrontal cortex tracks monetarily rewarding outcomes: Characterization with rapid event‐related fMRI. Neuroimage, 18(2), 263–272. [DOI] [PubMed] [Google Scholar]
  28. Kringelbach, M. L. , & Rolls, E. T. (2003). Neural correlates of rapid reversal learning in a simple model of human social interaction. Neuroimage, 20(2), 1371–1383. [DOI] [PubMed] [Google Scholar]
  29. Lamichhane, B. , Adhikari, B. M. , & Dhamala, M. (2016). Salience network activity in perceptual decisions. Brain Connectivity, 6(7), 558–571. [DOI] [PubMed] [Google Scholar]
  30. Litt, A. , Plassmann, H. , Shiv, B. , & Rangel, A. (2011). Dissociating valuation and saliency signals during decision‐making. Cerebral Cortex (New York, N.Y.: 1991), 21(1), 95–102. [DOI] [PubMed] [Google Scholar]
  31. Macpherson, T. , Morita, M. , & Hikida, T. (2014). Striatal direct and indirect pathways control decision‐making behavior. Frontiers in Psychology, 5(1301), 1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Matsumoto, M. , & Hikosaka, O. (2009). Two types of dopamine neuron distinctly convey positive and negative motivational signals. Nature, 459(7248), 837–841. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Matsumoto, M. , & Takada, M. (2013). Distinct representations of cognitive and motivational signals in midbrain dopamine neurons. Neuron, 79(5), 1011–1024. [DOI] [PubMed] [Google Scholar]
  34. Rangel, A. , Camerer, C. , & Montague, P. R. (2008). A framework for studying the neurobiology of value‐based decision making. Nature Reviews Neuroscience, 9(7), 545–556. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Redgrave, P. , Prescott, T. J. , & Gurney, K. (1999). Is the short‐latency dopamine response too short to signal reward error? Trends in Neurosciences, 22(4), 146–151. [DOI] [PubMed] [Google Scholar]
  36. Schultz, W. , Tremblay, L. , & Hollerman, J. R. (1998). Reward prediction in primate basal ganglia and frontal cortex. Neuropharmacology, 37(4–5), 421–429. [DOI] [PubMed] [Google Scholar]
  37. Schultz, W. , Tremblay, L. , & Hollerman, J. R. (2000). Reward processing in primate orbitofrontal cortex and basal ganglia. Cerebral Cortex (New York, N.Y.: 1991), 10(3), 272–284. [DOI] [PubMed] [Google Scholar]
  38. Sesack, S. R. , & Grace, A. A. (2010). Cortico‐Basal Ganglia reward network: Microcircuitry. Neuropsychopharmacology, 35(1), 27–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Sussman, E. , Sheridan, K. , Kreuzer, J. , & Winkler, I. (2003). Representation of the standard: stimulus context effects on the process generating the mismatch negativity component of event‐related brain potentials. Psychophysiology, 40(3), 465–471. [DOI] [PubMed] [Google Scholar]
  40. Zink, C. F. , Pagnoni, G. , Martin, M. E. , Dhamala, M. , & Berns, G. S. (2003). Human striatal response to salient nonrewarding stimuli. The Journal of Neuroscience, 23(22), 8092–8097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Zink, C. F. , Pagnoni, G. , Martin‐Skurski, M. E. , Chappelow, J. C. , & Berns, G. S. (2004). Human striatal responses to monetary reward depend on saliency. Neuron, 42(3), 509–517. [DOI] [PubMed] [Google Scholar]

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