We investigated the impact of reward motivation on the dynamics of mesolimbic and mesocortical dopaminergic regions in a network comprising VTA, NAcc and dlPFC. Importantly, our task structure permitted us to isolate neural activity concurrent with onset of information signaling potential reward and distinct from processing related to reward outcomes, allowing the observation of motivation preceding the execution of goal-directed behavior. Our results indicate that during a simple rewarded reaction time task, information about expected reward entered this network solely at the dlPFC. This reward information increased the dlPFC's modulation of the VTA and the NAcc, structures that are known to influence the physiology and plasticity of networks supporting motivated behavior, attention and memory throughout the brain. Together, these findings suggest that, in response to goal-relevant information, the PFC harnesses these modulatory pathways to generate physiological states that correspond to expectancy and motivation.
To characterize the network of brain regions involved in motivation, we used dynamic causal modeling (DCM). Importantly, DCM does not assume that temporal precedence is necessary for causality. Because the lag between neural activity and BOLD activation can theoretically vary across brain regions, due to vascular factors, DCM is particularly appropriate for detecting network interactions in BOLD data. In addition, DCM allows for inference about causal interactions between regions that depend on the experimental context. These inferences can be tested across a theoretically unlimited model-space, here allowing us to test amongst all possible driving input configurations.
Our DCM analysis of the VTA-NAcc-dlPFC network during reward motivation indicated that the driving input was exclusively to the dlPFC. This means that in this behavioral context and within the modeled network, information signaling potentially available reward entered the dopamine system at the dlPFC and not at the other regions in the model. Furthermore, driving input unique to the dlPFC appeared to be the feature of the models that was most important for determining model fit. Our findings demonstrate that reward cues directly increased dlPFC activation, and only influenced activation in the VTA or NAcc indirectly, via connections from the dlPFC.
Besides the regions modeled in our analysis, previous research has identified other candidate regions, such as the medial prefrontal cortex, orbitofrontal cortex, and habenula (Staudinger et al., 2009
; Bromberg-Martin et al., 2010
) that could plausibly initiate motivated behavior. The question of how these regions interact with this network, especially the dlPFC, is an important avenue of future research. However, it is important to note that if any of these regions were driving the modeled network via efferents to the VTA or NAcc, one would expect to see this influence expressed in our data as a driving input to the VTA or NAcc. Thus, our finding of a unique driving input to the dlPFC indicates that in this behavioral context, information signaling potential reward entered the modeled network neither via subcortical relays nor other prefrontal cortical inputs to the VTA, but rather via the dlPFC.
In addition to demonstrating PFC modulation of VTA in awake animals during motivated behavior, the current findings are, to our knowledge, the first demonstration of a prefrontal influence on the VTA in humans or other non-human primates. Bayesian Model Averaging revealed strong modulation of the VTA by the dlPFC specifically during reward motivation; this VTA-dlPFC pathway was not engaged intrinsically. Moreover, there was a nearly three-fold increase in connectivity strength from the dlPFC to the NAcc during reward motivation. Conversely, intrinsic VTA-NAcc connectivity was significant, but was not modulated by reward. This result could indicate that connectivity between the VTA and NAcc is always strong regardless of the level of motivation. However, based on prior research showing that reward information has an effect on VTA modulation of NAcc (Bakshi and Kelley, 1991
; Ikemoto and Panksepp, 1999
; Parkinson et al., 2002
), this interpretation is unlikely to be correct. More plausible is that changes in VTA-NAcc connectivity existed, but because their effect size was small relative to that of dlPFC connectivity, they did not contribute significantly to the model evidence, further suggesting that dlPFC modulation was highly influential for the function of this network.
The finding that there was no increase in the connection strength from the VTA to the dlPFC may seem to conflict with physiology literature demonstrating dopaminergic modulation over the PFC (Williams and Goldman-Rakic, 1995
; Durstewitz et al., 2000
; Gao and Goldman-Rakic, 2003
; Paspalas and Goldman-Rakic, 2004
; Seamans and Yang, 2004
; Wang et al., 2004
; Gao et al., 2007
). Although we found a modest intrinsic influence of the VTA on the PFC, this influence did not change with motivational state. However, we do not believe our findings to be contradictory to the above literature, as the modulatory influences may contribute to separate, but strongly interacting, behavioral processes. We believe the PFC's modulatory role over the VTA contributes to goal-directed, instrumental components of behavior, and the VTA's modulatory role over the PFC may be especially important to other behavioral processes, such as updating or task-switching, which were not manipulated in our paradigm. Thus, our findings, in the context of the previous literature, suggest that paradigms that evoked motivated executive behaviors would reveal bi-directional modulations between the VTA and dlPFC.
Building on the wealth of previous research outlining the influence of midbrain dopamine on target regions, the current findings suggest a model in which the dlPFC integrates information about potential reward and implements goal-directed behavior by tuning mesolimbic dopamine projections. This interpretation is consonant with evidence from the rodent literature showing that the PFC is the only cortical region that projects to dopamine neurons in the VTA (Beckstead et al., 1979
; Sesack and Pickel, 1992
; Sesack and Carr, 2002
; Frankle et al., 2006
) The findings fill a critical gap in this literature: stimulation of the PFC has been shown to regulate the firing patterns of dopamine neurons in rodents (Gariano and Groves, 1988
; Svensson and Tung, 1989
; Gao et al., 2007
), and multi-site recordings demonstrate phase-coherence between the PFC and the VTA that mediates slow-oscillation burst firing (Gao et al., 2007
), but there has been no demonstration that these physiological relationships are driven by motivation and goal-directed behavior. Furthermore, the absence of an expanded frontal cortex in the rodent makes an appropriate rodent correlate of primate dlPFC unclear. Although there is evidence in primates for excitatory projections from the PFC to midbrain dopamine neurons (Williams and Goldman-Rakic, 1998
; Frankle et al., 2006
), the functional significance of these relatively sparse projections has been questioned. Our findings showing a physiological relationship between prefrontal cortex and VTA in humans thus fill a second critical gap in the extant literature on human (and non-human primate) motivation.
Within the PFC, dlPFC is well situated to orchestrate motivated behavior because of its role in planning and goal maintenance. Primate physiology studies have demonstrated that while both the orbitofrontal cortex and the dlPFC encode reward information, only dlPFC activity predicts which behaviors a monkey will execute (Wallis and Miller, 2003
). Further, the dlPFC maintains goal-relevant information during working memory (Levy and Goldman-Rakic, 2000
; Wager and Smith, 2003
; Owen et al., 2005
), updates this information as goals dynamically change during task switching (Dove et al., 2000
; Kimberg et al., 2000
; MacDonald et al., 2000
; Rushworth et al., 2002
; Crone et al., 2006
; Sakai, 2008
; Savine et al., 2010
), and arbitrates between conflicting goals during decision-making (MacDonald et al., 2000
; McClure et al., 2004
; Ridderinkhof et al., 2004
; Boettiger et al., 2007
; McClure et al., 2007
; Hare et al., 2009
). These previous findings suggest a role for the dlPFC in implementing behavioral goals, but they do not characterize the nature and direction of interactions between dlPFC and other regions supporting motivated behavior. Computational and neuroimaging work has posited a role for the dlPFC in modulating the striatum in the context of instructed reward-learning (Li et al., 2011
; Doll et al., 2009
). Our results corroborate these recent findings, and further implicate the DLPFC in initiating motivated behavior, via the novel demonstration of a directed influence on the VTA. Transcranial magnetic stimulation of the dlPFC changes the valuation of both cigarettes (Amiaz et al., 2009
) and food (Camus et al., 2009
), and also induces dopamine release in the striatum (Pogarell et al., 2006; Ko et al., 2008); however, these results do not reveal how dlPFC activation affects network activation or dynamics. The current findings directly demonstrate dlPFC influence over not only the NAcc but also the VTA during reward-motivated behavior, as postulated by prior work.
In summary, we found that motivation to obtain reward is instantiated by a transfer of information from the dlPFC to the NAcc and VTA; we saw no evidence of the reverse. These findings show that the dlPFC can orchestrate the dynamics of this neuromodulatory network in a contextually appropriate manner. Further, by suggesting an anatomical source for information about expected reward that activates dopaminergic regions, the findings also shed light on the fundamental question of how dopamine neurons define value. Finally, because of the widespread effects of VTA activation and resultant dopamine release, this interaction represents a candidate mechanism whereby dorsolateral prefrontal cortex modulates physiology and plasticity throughout the brain in order to support goal-directed behavior.