We previously pointed out (Ryan and Di Domenico, 2016) that the concept of intrinsically motivated exploration is consistent with the “affective neuroethological” perspective of Panksepp and colleagues (Panksepp, 1998; Ikemoto and Panksepp, 1999; Alcaro et al., 2007; Alcaro and Panksepp, 2011; Panksepp and Biven, 2012). These researchers have argued that mammals are hardwired with a general-purpose SEEKING system that energizes many types of foraging and exploratory activities. Although the SEEKING system does service homeostatic imbalances and is responsible for energizing learned appetitive behaviors, it continuously operates to keep animals in a state of exploratory engagement with their environments. That is, the SEEKING system is believed to function as an objectless appetitive system—a “goad without a goal”—until the exploratory disposition it produces leads to the discovery and learning of useful regularities.

It is worth pointing out that even within radical behaviorism this inherent activity of organisms could not be fully ignored, though it was marginalized by Skinner’s concept of “the operant”. Skinner acknowledged that organisms do “operate” on their environments, but regarded such exploratory activities as random behaviors that come under the control of external reinforcement.

The core structures that comprise the SEEKING system in the rat are the ventral tegmental area (VTA), the nucleus accumbens (NAcc), the ventromedial prefrontal cortex (VMPFC), and the dopaminergic projections originating from the VTA that innervate these areas (Panksepp, 1998; Panksepp and Biven, 2012). These regions are frequently called the “brain reward network” because, as Olds and Milner (1954) discovered, rats will learn to instrumentally obtain electrical stimulations in this area. However, the invigorated searching and sniffing following such electrical stimulations look like states of invigorated curious exploration rather than states of calm satiation (see White, 1959): “The most dramatic observation…is that animals getting this kind of brain stimulation frantically explore their environments, taking notice of all the new stimuli they encounter” (Panksepp and Biven, 2012, p.126). These basic SEEKING urges are elaborated into more complex forms of exploration in behaviorally and cognitively sophisticated animals: our dexterity affords the manipulation and exploration of complex objects and our cognitive faculties afford interest in ideas, abstract objects and possibilities that we can explore and manipulate with our minds. The SEEKING system is thus believed to energize “many mental complexities that humans experience as persistent feelings of interest, curiosity, sensation seeking and, in the presence of a sufficiently complex cortex, the search for higher meaning” (Panksepp, 1998, p.145).

The first experimental studies on intrinsic motivation were conducted on nonhuman animals (Harlow, 1950) and it is therefore fitting that the first insights on the neurobiology of intrinsic motivation have been derived in animal research. Although generalizations based on animal research must be made with caution, affective neuroscience suggests that human intrinsic motivation is an elaboration of ancient mammalian motivations for exploratory SEEKING. The affective neuroethological point of view from which this system is conceptualized dovetails the organismic perspective from which SDT developed (Ryan and Deci, 2017). It is remarkable and telling that independent lines of research stemming from such methodologically diverse traditions should converge on similar points of view.

Intrinsic motivation is a complex cognitive, affective, and behavioral phenomenon that is likely mediated by multiple neural structures and processes. For this reason, a useful point of entry for elucidating the neurobiology of intrinsic motivation is to consider the broad neurotransmitter systems that may underlie it.

Three lines of evidence suggest that dopamine is a key substrate of intrinsic motivation. First, as the review above suggests, intrinsic motivation in humans is an elaboration of the exploratory activities subserved by the mammalian SEEKING system, and dopamine is central to the neurochemistry of this system (Panksepp, 1998; Panksepp and Biven, 2012). Second, like intrinsic motivation, dopamine is associated with increased positive affect, cognitive flexibility, creativity (Ashby et al., 1999), behavioral persistence (Salamone and Correa, 2016), and exploration in the face of novelty (DeYoung, 2013). Importantly, the positively affective states associated with dopamine reflect energized appetitive “wanting” not consummatory “liking”, the hedonic effects of which are mediated by opioids (Berridge, 2007; Kringelbach and Berridge, 2016). Third, there is some evidence of a direct link between intrinsic motivation and dopamine. Using positron emission tomography, de Manzano et al. (2013) found that people who are disposed to experience intrinsically motivated flow states in their daily activities have greater dopamine D2-receptor availability in striatal regions, particularly the putamen. This finding suggests that people’s capacities for intrinsic motivation are associated with the number of targets within the striatum for dopamine to act upon. More recently, Gyurkovics et al. (2016) found that carriers of a genetic polymorphism that affects striatal D2-receptor availability were more prone to experience flow during study- and work-related activities. Altogether, it would thus seem reasonable to forward the initial working hypothesis that dopamine is a key substrate of intrinsic motivation.

Dopamine neurons originate in the midbrain and have two modes of activity, tonic and phasic (Grace, 1991). In the tonic mode, the neurons exhibit a steady baseline rate of firing in which dopamine is steadily released to target structures. This tonic activity promotes the normal functioning of relevant neural circuits (Schultz, 2007) and may reflect the general strength of animals’ exploratory SEEKING tendencies (Alcaro and Panksepp, 2011). In the phasic mode, dopamine neurons exhibit short bursts of activity or inactivity (above or below their baseline) in response to specific events, resulting in an increase or decrease of dopamine in target structures lasting several seconds. The phasic mode of dopamine transmission may “transiently activate SEEKING patterns in coincidence with specific cue- or context-dependent information, attributing to such information an incentive motivational, action-orienting effect” (Alcaro and Panksepp, 2011, p.1810). Of course, the tonic and phasic modes of dopamine transmission likely interact in complex ways to regulate intrinsic motivation. For example, Alcaro et al. (2007) advanced the hypothesis that moderately high levels of tonic dopamine optimize the SEEKING behavior promoted by phasic dopamine release: when tonic levels of dopamine are too low, phasic signals lack the efficacy to promote exploration; but when tonic levels are too high, phasic signals lose their informational value and exploratory behavior patterns are uncoupled from relevant contextual stimuli. Given the nascent state of the field, however, questions about how the tonic and phasic modes of dopamine release interact to influence intrinsic motivation remain outside the scope of the present effort. We instead focus on making the less specific case for a general relation between dopamine and intrinsic motivation.

Bromberg-Martin et al. (2010) recently proposed a model of dopaminergic function that is based on the recognition of two types of dopamine neurons that exhibit distinct types of phasic activity: value-coding neurons and salience-coding neurons. We review the properties of these neurons and their relevance to intrinsic motivation below.

Value-coding neurons are phasically excited by unexpected rewarding events and inhibited by unexpected aversive events; events that are wholly expected elicit little or no response. Value-coding dopamine neurons are found in the ventromedial substantia nigra pars compacta (SN) and throughout the VTA. From these midbrain regions, these neurons project axons that innervate the NAcc shell, the dorsal striatum (caudate and putamen), and the VMPFC, where they send signals about the availability of rewards, evaluation of outcomes, and learning. The phasic signals emitted by value-coding neurons are classically recognized as “reward-prediction errors” within neobehaviorist theories and are believed to be an important mechanism through which animals learn about external reinforcement contingencies (Schultz, 2007).

However, Tricomi and DePasque (2016) recently argued that, even in the absence of external rewards, this dopaminergic pathway registers the endogenous signals of positive and negative feedback that are elicited during the performance of many activities. The types of activities that people find intrinsically motivating provide just-manageable challenges, clear proximal goals, and immediate feedback (Nakamura and Csikszentmihalyi, 2014; Ryan and Deci, 2017). For example:

Another way of describing this optimally challenging nature of intrinsically motivated activities is to say that the positive and negative feedback that people receive during their performance of such activities is not entirely unexpected—a performative context that suggests phasic dopaminergic signaling. Following Tricomi and DePasque (2016), we therefore propose that a high rate of dopaminergic signaling within the value system is inherent to the performance of intrinsically motivating activities.

In addition to value-coding neurons, Bromberg-Martin et al. (2010) identified salience-coding neurons. These dopamine neurons are phasically excited by both unexpected rewarding and punishing events. These neurons are found in the dorsolateral SN and medial VTA, and project to the NAcc core, the dorsal striatum, and the dorsolateral PFC (DLPFC). The regions innervated by salience-coding neurons support the orienting of attention, cognitive processing, and the invigoration of actions. Dovetailing Loewenstein’s (1994) information-gap hypothesis of curiosity, DeYoung (2013) proposed that salience-related dopaminergic activity energizes exploration “in response to the incentive value of the possibility of gaining information—that is, it drives curiosity and the desire for information” (p.4). Curiosity and interest are of course long recognized components of intrinsic motivation. For example, the Intrinsic Motivation Inventory (Ryan et al., 1983), a self-report measure of intrinsic motivation for experimental settings that is used to predict free choice behavioral persistence, includes items such as “I found the task very interesting” and “I thought the task was very boring (reverse scored)”. These items describe the type of eager attentiveness and behavioral engagement that may be associated dopaminergic salience signaling. Thus, building on DeYoung (2013), we propose that the salience-coding system also subserves intrinsic motivation.

Apart from the aforementioned studies by de Manzano et al. (2013) and Gyurkovics et al. (2016), empirical studies have not directly examined the link between dopamine and intrinsic motivation. However, if intrinsic motivation is associated with dopaminergic transmission, then intrinsically motivated activities should be associated with activation across core regions of the dopaminergic systems identified by Bromberg-Martin et al. (2010). In the paragraphs that follow, we focus on neuroimaging findings relating intrinsic motivation to activity within regions of the dopaminergic value system. Studies relating intrinsic motivation to activity within regions of the dopaminergic salience system are reviewed separately because such findings are also consistent with the complementary proposition that intrinsic motivation is associated with patterns of activity across specific large-scale neural networks.

Murayama et al. (2010) examined the neural correlates of the undermining effect using fMRI. University undergraduates were asked to play a game-like stopwatch task in which they were asked to press a button within 50 ms of the 5 s mark. In a series of pilot tests, the authors determined that students found this task challenging and interesting, and therefore suitable for examining intrinsic motivation. Like classic studies on the undermining effect (e.g., Deci, 1971), participants were divided in two groups: a reward group that received performance-contingent rewards for each successful trail and a control group that received no payments. During an initial scanning session, participants in both groups evidenced greater activity in the midbrain and caudate upon the receipt of success feedback relative to failure feedback. Subsequent to the experimental manipulation, and consistent with previous behavioral studies on the undermining effect, participants in the reward group were less likely to voluntarily engage with the task during a free-choice time period relative to those in the control group. Importantly, this behavioral undermining of intrinsic motivation was paralleled by reduced activity in the caudate and midbrain during a second scanning session when monetary rewards were no longer administered to the reward group. In contrast the unrewarded group maintained its previous levels of activation. This difference in activity between the control and experimental groups is consistent with the idea that the dopaminergic value system is responsive to cues that signal task-related progress during intrinsically motivated activities.

In a more recent fMRI study, Murayama et al. (2015) had participants perform an adapted version of the stopwatch task (Murayama et al., 2010) in two conditions: an autonomy condition in which they were free to choose the appearance of the stopwatch according to their preferences and a forced-choice condition in which they had to proceed with the stopwatch selected by the computer. Results indicated that activity within the VMPFC (bilateral gyrus rectus and medial orbitofrontal gyrus) was greater upon the receipt of success feedback than failure feedback. However, this effect was modulated by the type of the trial conditions. On the one hand, the VMPFC exhibited similarly high levels of activity across success and failure feedback after free-choice (autonomy) trials. On the other hand, this region exhibited marked reductions in activity after forced-choice trials. Importantly, this sustained activity within the VMPFC in response to failure feedback was associated with enhanced performance within the free-choice condition. Present evidence suggests that value coding dopamine neurons in the midbrain project to the VMPFC and that this structure is involved in learning from negative reward prediction errors and updating outcome expectations during learning (Bromberg-Martin et al., 2010). These results are thus consistent with the idea that intrinsic motivation, and the perceived autonomy that phenomenally supports it, is associated with activity within the dopaminergic value system.

Conceptually related to these fMRI studies is research examining intrinsic motivation using electroencephalography (EEG). Two specific EEG waveforms that have been associated with intrinsic motivation are the “error-related negativity” (ERN) and the “feedback-related negativity” (FRN). Both of these waveforms are negative-going deflections in EEG recordings that arise during speeded-response tasks. Whereas the ERN appears within 100 ms following the commission of errors, the FRN appears between 200 ms and 350 ms following the receipt of negative feedback. Holroyd and Coles (2002) proposed that both the ERN and FRN arise as a consequence of phasic reductions in midbrain dopaminergic signaling to ACC, the purported neural generator of these waveforms. These phasic reductions in dopamine transmission to the ACC, and the consequent ERN and FRN, are believed to constitute a learning signal that tunes the ACC to optimize behavioral performance, an account that parallels the reward-prediction signaling of value-coding dopamine neurons (Schultz, 2007; Bromberg-Martin et al., 2010).

In a sample of school children, Fisher et al. (2009) found that intrinsic academic motivation was associated with larger ERN amplitudes during a flanker task. In a study that paralleled the design of Murayama et al. (2010), Ma et al. (2014) found that participants who had received performance-contingent monetary rewards while performing a challenging activity evidenced reduced FRN amplitudes whereas those in a control group evidenced consistently pronounced FRNs. In another study, this time paralleling the design of Meng and Ma (2015) and Murayama et al. (2015) found that having the opportunity to exercise choice during the performance of an intrinsically motivating task was associated with larger FRN amplitudes. An important caveat to these studies is their small sample sizes (N = 17, 36 and 18, respectively), which raises uncertainty about reliability of their reported effects. To this point, Jin et al. (2015; N = 16) found lower FRN amplitudes when participants received negative feedback on a supposedly interesting task relative to a boring task. In light of these small sample sizes and diversity of findings, it is clear that more decisive larger-sample studies are required. Nevertheless, the available evidence from these EEG studies is generally consistent with the idea that intrinsic motivation is associated with dopaminergic signaling.

Other evidence of a link between intrinsic motivation and the dopaminergic system comes from studies examining the neural correlates of curiosity. Kang et al. (2009; Study 1) used fMRI to examine curiosity as it is framed by the information-gap theory of Loewenstein (1994). We previously pointed out that the information-gaps in people’s knowledge structures, and the ensuing feelings of curiosity that such gaps elicit, can be productively framed in terms of people’s orienting toward optimal challenges. Participants reflected upon a series of trivia questions (e.g., What instrument was invented to sound like a human singing?) and rated their curiosity for each one. During the presentation of the trivia questions, items that elicited greater curiosity were associated with activations in the left caudate and parahippocampal gyri (PHG). Furthermore, when trivia answers were revealed following incorrect responses, participants’ level of curiosity was associated with greater activity in the midbrain and left PHG. Although Bromberg-Martin et al. (2010) did not identify the PHG as a core component of the dopamine system, Kang et al. (2009) point out that this region is involved in successful memory encoding and its activity during states of curiosity is therefore consistent with the idea that intrinsic motivation is associated with enhanced learning.

A follow-up study by Gruber et al. (2014) more directly assessed the relation between curiosity and learning. This study used trivia questions similar to Kang et al. (2009) to examine if states of curiosity improved memory for task-relevant information and for information that was incidental to the main task. Incidental information consisted of face stimuli that were presented to participants when they anticipated trivia answers. During the presentation of trivia questions, curiosity was associated with activity in the left SN/VTA, bilateral NAcc, and bilateral dorsal striatum. Furthermore, replicating the behavioral results of Kang et al. (2009; Study 2), in both immediate and delayed memory tests, participants recalled more answers for high- relative to low-curiosity questions. Extending these previous behavioral findings, Gruber et al. (2014) also found enhanced recall of incidental face stimuli presented during high-curiosity questions. These memory effects were associated with greater activity in the SN/VTA and the hippocampus during the presentation of trivia questions and increased functional connectivity between these regions when participants anticipated answers to the trivia questions.

A complementary approach to theorizing about the neural systems that support intrinsic motivation is to map its phenomenology with the activity of large-scale neural networks (Ryan and Di Domenico, 2016). Research on structural and functional brain organization has revealed multiple large-scale brain networks that support various cognitive functions (Bressler and Menon, 2010). Among these is the so-called salience network, which is believed to support the detection of subjectively important events and the mobilization of attentional and working memory resources in the service of goal-directed behavior (Menon and Uddin, 2010; Menon, 2015). The salience network is anchored in the anterior insula (AI) and dorsal ACC and includes major subcortical nodes in the amygdala, NAcc, the SN, and VTA. These subcortical nodes are believed to send signals about the motivational significance of stimuli to the AI; the AI in turn is believed to integrate this information with incoming sensory inputs from both the external environment and the viscera for the bottom-up detection of contextually important events. Through its reciprocal connections with the dACC, a key structure for executive control, the AI is believed to selectively amplify neural signals of important events for the effective deployment of cognitive resources.

Little is presently known about the specific role of dopamine in the functioning of the salience network. However, AI does receive inputs from the amygdala, the likely source of the motivational salience signals sent to dopamine neurons in the midbrain, from the ventral striatum, which receives dopaminergic projections from the midbrain, and from the SN and the VTA, the midbrain regions from which dopamine neurons originate (Bromberg-Martin et al., 2010; Menon and Uddin, 2010; Menon, 2015). Additionally, the AI has reciprocal connections with the dACC, which likely receives direct input from both value- and salience-coding dopamine neurons (Bromberg-Martin et al., 2010). These connections imply that the AI may play a role in contextualizing the signals of motivational significance transmitted by both value- and salience-coding dopamine neurons. Most relevant in this regard is the suggestion that the AI functions as a dynamic hub for modulating the activity of two other large-scale brain networks (Menon and Uddin, 2010; Menon, 2015). The first, known as the default mode network, has major nodes in the MPFC and the posterior cingulate cortex (PCC). These regions show high levels of activity during passive resting states (Gusnard and Raichle, 2001), tasks involving internally-focused, self-referential cognition (Northoff et al., 2006), and mind-wandering (Mason et al., 2007). The second, known as the central executive network, includes the DLPFC and the posterior parietal cortex (PPC). The regions of this network, which are important substrates of working memory and executive functions, typically show elevated activity during cognitively demanding, externally-focused tasks. Importantly, activity across the default mode and central executive networks often fluctuates in an antagonistic manner, such that activity in one is often accompanied by suppressed activity in the other.

The antagonistic dynamic between the default mode and central executive networks, along with the role of the salience-mediating switching instigated by the AI, may inform three characteristics of intrinsic motivation. First, in its most experientially abundant state, intrinsic motivation entails cognitive absorption and non-self-conscious enjoyment of an activity (Csikszentmihalyi, 1990; Nakamura and Csikszentmihalyi, 2014). This phenomenology suggests diminished activity within regions of the default mode network, which are commonly activated during self-focused mental activity (e.g., self-reflection, rumination) and mind-wandering, and heightened activity within the central executive network, which is engaged during bouts of externally focused attention. Second, intrinsic motivation is reliably associated with enhanced performance, cognitive flexibility, and deeper conceptual learning (e.g., Grolnick and Ryan, 1987). This relation between intrinsic motivation and enhanced task performance is consistent with, and may be partly explained by, greater mobilization of the central executive network during intrinsically motivating tasks (Ryan and Di Domenico, 2016). Third, classic perspectives that describe autonomy or authenticity as a state of “organismic congruence” (e.g., Rogers, 1961) characterize it as an embodied cognitive process whereby sensory and visceral information is permitted to access and direct one’s attention, in a bottom-up manner, to events of subjective importance and meaning (also see Peterson, 1999). The salience network, and the AI most specifically, with its receipt of sensory and visceral input and its interoceptive functions (Craig, 2009; Menon and Uddin, 2010; Menon, 2015), would seem well-suited to support this aspect of autonomy, especially during intrinsic motivation when people orient themselves to stimuli that spontaneously grip their attention and interest.

Neuroimaging studies have reported patterns of neural activity consistent with the idea that intrinsic motivation recruits the salience and central executive networks, while suppressing the default mode network. In the aforementioned study by Murayama et al. (2010), the undermining of intrinsic motivation was associated with decreases in lateral PFC activity in response to task onset cues. The study by Murayama et al. (2015) found increased activity within the midbrain, ACC, and bilateral insula in response to free-choice (autonomy) cues relative to forced-choice cues at the onset of task trials. The curiosity studies by Kang et al. (2009) and Gruber et al. (2014) found greater activity within the lateral PFC during curiosity-inducing questions. More recently, Marsden et al. (2015) observed neural activations within several structures that comprise the SN. Specifically, their study found participants who spent more free-choice time solving remote-associate word problems (i.e., a behavioral marker of intrinsic motivation) showed greater activity in the ACC, amygdala, anterior and posterior insula, PHG, and caudate nucleus after trial onsets that immediately followed negative feedback for preceding trials. Jepma et al. (2012) examined the neural correlates of perceptual curiosity. Participants viewed blurry images of otherwise easily recognizable objects that induced feelings of curiosity, and were subsequently shown clear images of the objects to satisfy their curiosity. Results indicated that induction of curiosity was associated with significant activations within the AI and ACC, the core regions of the salience network, and significant deactivations within regions associated with the default mode network. Additionally, this study found that the resolution of perceptual curiosity was associated with activity within the left caudate, putamen, and NAcc, regions that comprise the core of the dopaminergic system.

A set of studies (Lee et al., 2012; Lee and Reeve, 2013) examined the neural correlates of intrinsic motivation by comparing patterns of neural activity when undergraduate students imagined themselves performing intrinsically motivating activities (e.g., “writing an enjoyable article”) and extrinsically motivating activities (e.g., “writing an extra-credit article”). Most prominently, these studies found preferential activity within insular regions when participants imagined the enactment of intrinsically motivating activities. Building on this initial work, Lee (2016) more recently described the results of an fMRI study that examined functional connectivity between striatal regions and the AI when participants attempted trivia questions and anagrams. Results indicated that when participants worked on intrinsically motivating problems (curiosity inducing-questions and competence-enabling anagrams) they evidenced greater activity and functional connectivity between these regions.

Klasen et al. (2012) examined the neural correlates of flow using fMRI recordings obtained during free play of a video game. The authors developed an objective coding system for examining different components of the flow experience based on player-generated video game contents. Consistent with the idea that intrinsic motivation is associated with dopaminergic signaling, optimal challenge was associated greater activity within the caudate, putamen, and NAcc. Consistent with the idea that intrinsic motivation is associated with suppressed activity in default mode regions, concentrated focus and goal clarity were associated with reduced activity within the orbitofrontal cortex and ACC. Additionally, task-related failure was associated with increased activity within the cuneus, a structure included within the default mode network.

In another fMRI study, Ulrich et al. (2014) examined the neural correlates of flow by asking participants to work on mental arithmetic task and comparing experimentally challenging levels with boredom and overload conditions. Results indicated that flow states were associated with increased activity in the left putamen and left IFG, again implicating core regions of both the dopaminergic system and the central executive network. Results also indicated that flow was associated with deactivations within the MPFC, suggesting suppressed default mode network activity. In another study, Yoshida et al. (2014) used functional near-infrared spectroscopy (fNIRS) to examine the time course of neural activations within the prefrontal cortex during states of flow and boredom when participants played Tetris^®. Again, consistent with the idea that intrinsically motivated states recruit central executive regions, results indicated increasing bilateral activity within lateral PFC regions during flow. However, a subsequent fNIRS study by Harmat et al. (2015) that compared prefrontal activity across easy, optimally challenging, and difficult levels of Tetris did not any differences. Despite these mixed findings, the results of existing studies altogether suggest that future research would benefit by explicitly testing the proposition that intrinsic motivation is associated with patterns of activity across the salience, central executive, and default mode networks.

SDT uses intrinsic motivation as a broad term for diversity of activities that are inherently rewarding and growth promoting (Ryan and Deci, 2017). This is a large class of behaviors, minimally including curious exploration and mastery tendencies, on the one hand, and social play, on the other (Ryan and Di Domenico, 2016). To date, human neuroscience studies have focused on intrinsic motivation associated with curious exploration and mastery, rather than social play, and we accordingly based our review on this subset of intrinsically motivated behaviors. Yet, comparative affective neuroscience suggests that exploration and social play have both distinct and overlapping neurobiological and phenomenological underpinnings, the former being subserved by the SEEKING system and the latter by the PLAY system (Panksepp, 1998; Panksepp and Biven, 2012). The subcortical PLAY system governs the rough-and-tumble (R&T) interactions of mammals, energizing them to develop and refine their physical, emotional, and social competencies in a safe context (Panksepp, 1998; Pellis and Pellis, 2007; Trezza et al., 2010; Panksepp and Biven, 2012). In early mammalian development, R&T play constitutes a type of embodied social cognition that provides a basis for cooperation and the adaptive self-regulation of aggression (Peterson and Flanders, 2005). Humans are of course also capable of more sophisticated forms of play beyond R&T such as common playground games, sports play and friendly humor, but such human play may be nonetheless organized around basic PLAY motivations (Panksepp, 1998; Panksepp and Biven, 2012).

We might therefore regard play as intrinsically motivated socialization (Ryan and Di Domenico, 2016), an expression of people’s complementary tendencies toward autonomy and sociality in development (Ryan, 1995; Ryan et al., 1997). Indeed, research in SDT suggests that in addition to competence and autonomy, people have a basic psychological need for relatedness, the sense of feeling meaningfully connected with others (Ryan and Deci, 2017). Whereas strong associations between exploratory intrinsic motivations and satisfactions of competence and autonomy have been clearly demonstrated, relatedness is usually seen to play a more distal role in the expression of these intrinsic motivations. Specifically, relatedness satisfactions provide people (especially children) with a sense of safety, a secure base from which their exploratory tendencies can be more robustly expressed (Ryan and Deci, 2017). Recognition of social PLAY signifies the centrality of the need for relatedness in some intrinsically motivated activities.

Interest in the overlaps and contrasts between intrinsically motivated exploration and play is thus an important agenda for future studies and both are relevant to intrinsic motivation as it is studied within SDT (Ryan and Di Domenico, 2016). Behavioral models of human intrinsic motivation have generally conflated exploration and play because these activities share common features such as an internal perceived locus of causality and perceived competence or mastery. Indeed, functional distinctions between intrinsically motivated exploration and object or manipulative play are subtle and suggest that, for many activities recognized as “playful”, the conflation is appropriate and productive. For example, Wilson (2000) suggested that “In passing from exploration to play, the animal or child changes its emphasis from ‘What does this object do?’ to ‘What can I do with this object?”’ (p.165). In fact, intrinsically motivated object play, manipulative play, and solitary gaming likely arise from the activity of the SEEKING system (Panksepp, 1998; Panksepp and Biven, 2012). Clearly, more empirical work is needed to differentiate these types of intrinsic motivation in humans.

Our principal intent in this review article, is to stimulate increasing integration between social behavioral research on intrinsic motivation and the neuroscience of motivation. We see many new and promising pathways opening up. At the same time, methodological issues persist that warrant serious considerations. We list but a few of these.

First, intrinsic motivation and the associated undermining effect of rewards on these behaviors pertain only to tasks that are interesting and enjoyable in the first place. Thus, researchers should pilot test target activities to ensure that the activities are suitable for examining the undermining effect. This is especially important in neuroscience, where contemporary methods such as fMRI often involve procedures that limit how interesting experimental tasks can be. Researchers should also use multi-method assessments of intrinsic motivation to validate their measures and to ensure that the correct behavioral phenomena are being tapped. For example, in an attempted (and failed) replication and extension of Murayama et al.’s (2010) fMRI study on the undermining effect, Albrecht et al.’s (2014) utilized a picture-discrimination task for which participants may not have been intrinsically motivated in the first place (pilot testing was not reported) and for which free-choice behavior was not examined as a dependent variable. In the absence of these important design characteristics, it is difficult to draw decisive conclusions from their experiment. Incidentally, we note that Albrecht et al.’s (2014) study did show that competence feedback increased participants’ self-reported fun and that it was also associated with increased activations within the midbrain, striatum, and lateral PFC, findings that are consistent with the idea that competence is associated with dopamine-related activity.

Second, replicability is a central concern, as it is throughout the social and personality neurosciences (Allen and DeYoung, 2016). Most studies to date have been small-sample investigations, and larger samples are needed if we are to derive foundational conclusions. A priori hypotheses concerning regions of interest will also add confidence to the interpretation of findings. Toward that end, the present review ought to provide future studies with a useful reference for making clear predictions about the neural basis of intrinsic motivation.

Intrinsic motivation is a topic of interest within both basic behavioral science and applied translational studies and interventions (Ryan and Deci, 2000, 2017). Yet important to the progress of empirical research on intrinsic motivation is integrating what is known from phenomenological and behavioral studies with neuroscience studies. As we suggested at the outset, neuroscience holds potential for testing existing models of the situational and social determinants of intrinsic motivation as well as for providing greater resolution on the affective and cognitive processes that underpin such activities. Movement toward consilience is a central concern to SDT and our hope is that the current synthesis provides some broad stoke encouragement for that agenda.