This thesis tested a principle according to which implicit motives influence implicit instrumental conditioning processes. Analyzing results from four studies I investigated possible scaling effects of implicit motives, motivational dispositions working outside of conscious awareness that select, energize and orient behavior, on implicit instrumental conditioning processes in a sequence learning paradigm. I focused on the power motive (n Power), the capacity to experience having impact on others as satisfying. Given a high motive level, an affect-amplifying function inherent to implicit motives imbues motive-relevant positive incentives with an even stronger positive affective quality and motive-relevant disincentives with an even stronger negative quality. This should facilitate instrumental conditioning if such incentives or disincentives are used as reward or punishment stimuli. My indicator of conditioning effects was implicit learning in a sequence learning task similar to the Serial Response Task, the Differential Implicit Learning Task (DILT). It was combined with performance-contingent reinforcement according to an accuracy criterion, the number of errors made when executing the sequences or sequence elements. Implicit learning was assessed as accuracy on fixed, repeating, learnable sequences versus accuracy on random sequences (negative transfer effect). Accuracy was chosen as dependent variable, because the basal ganglia, which play a role both in n Power-dependent reinforcement phenomena and in learning spatial stimulus-sequences, influence learning particularly via error signals. Also, the basal ganglia have been linked to social intuition. Based on theories linking implicit learning and social intuition and on Motivational Field Theory (MFT) which includes the incentive value of different facial expressions of emotion (FEEs) for different implicit motives and thus builds on motives affect-amplifying effect, n Power-relevant FEEs were used as reinforcers for performance-contingent feedback on the DILT. Dominant FEEs as reinforcers, like joy or anger, as n Power disincentives should deteriorate implicit learning performance compared to neutral FEEs, while submissive displays (surprise) as n Power incentives should improve it. Based on previous studies, my analyses besides n Power included activity inhibition (AI; assessed by counting the word “not” in the Picture Story Exercise, PSE, the projective standard measurement method for implicit motives) and gender match (match between perceiver gender and sender gender of the persons on the FEE-pictures). Exploratively, I also investigated possible effects of the affiliation motive (n Affiliation), the capacity to experience harmonious relationships with other people as satisfying. In Study 1, I compared the implicit learning accuracy potential of four DILT-versions of differing sequence length (eight vs. 12 trials) and distractor usage (no vs. one distractor in addition to the target stimulus), each featuring one blue and one yellow sequence and three interspersed negative transfer effect assessments. Overall implicit learning in terms of accuracy and speed was stable for my DILT-modifications. Sequence length per se did not influence implicit learning gains. Explicit learning assessed in three different awareness tests did not systematically influence main results for accuracy. Overall, keeping the 12-trial-sequence-DILT without distractors seemed advisable, because on a descriptive level error scores were highest there and accuracy gains were higher on no-distractor DILTs. Study 2 and 3 featured the first designs ever to combine performance-contingent reinforcement with implicit learning in a 12-element-DILT and implicit motives as assessed with the PSE. Accuracy gain differences between two sequences with different reinforcement contingencies were used as indicators of instrumental conditioning effects. To maximize the differential implicit learning gains, reward-FEEs on a blue sequence were the punisher-FEEs on a yellow sequence and vice versa. Deriving reinforcers from MFT to engage motives in instrumental conditioning, FEE-classes used as reward or punishment stimuli were a neutral and a dominance-relevant (joy in Study 2; anger in Study 3) FEE, respectively. A general motive-dependent scaling effect for n Power or the inhibited power motive (IPM), a combination of high n Power with high AI, was not obtained, respectively. However, in the context of joy-FEEs, IPM had a positive influence on differential learning gains for males in Study 2, and for male FEE-gender in the context of anger faces in Study 3, with the latter result being not robust. While there were no instrumental conditioning effects without considering motives, Gender x FEE-gender effects emerged, with for example opposite-sex anger being more detrimental to implicit learning than same-sex anger in Study 3. For n Affiliation, the only notable finding was a gender-match effect for low-affiliation individuals indicating a more negative influence of opposite- versus same-sex anger in Study 3. Overall, implicit learning in both studies was robust. Alternative explanations in terms of explicit learning were unlikely, as it did not systematically influence my main results. Study 4 combined insights from Study 1´s implicit learning optimization with massed trial-wise reinforcement, two test-blocks and reinforcer-FEEs pre-tested for senders implicit motive levels into a paradigm aiming at maximizing the probability for detecting motives` possible instrumental conditioning effects. Again comparing two sequences, MFT´s full dominance spectrum was used, contrasting surprise and anger, respectively, as reward or punishment. Additionally, I assessed liking for reinforcers with explicit questions on FEEs before and after the DILT. A direct, block-dependent n Power effect on differential accuracy gains (surprise versus anger) was obtained, which was negative at T1 and positive at T2, and a direct positive IPM effect. An additional Sender gender x n Power x AI interaction yielded stronger results for female faces, not for male faces like in Study 3. No instrumental conditioning effects regardless of motives and no general gender match effect were obtained. For n Affiliation, again an interaction with gender match like in Study 3 emerged, supplemented by block, with higher relative learning gains for same- versus opposite-sex faces at T1 in the context of a low n Affiliation. Explicit liking for the reinforcers used did not correlate with motives and did not systematically influence my results. Again results could draw on implicit learning and were not systematically moderated by explicit learning. From the four sub-studies, I derived the following conclusions: First, implicit motives replicably influence instrumental conditioning processes. For the first time, actually performance-contingent feedback was used. However, the direct effect of n Power was only observed in a block-dependent way in Study 4 and most likely the n Power x AI interaction, particularly IPM, is of special importance. Such an interaction was present in all three motive-relevant sub-studies, even if it was dependent on male gender or male sender gender in Study 2 and 3, respectively. This supports results indicating that IPM individuals exert their desire for impact in a more sophisticated way and react more socially adaptive to FEEs. Second, gender match plays a role in instrumental conditioning processes with FEEs, perhaps due to differential interactional goals in opposite- vs. same-sex encounters. Yet there were no replicable interactions of gender match with n Power or the n Power x AI interaction. Third, AI has to be considered in paradigms including n Power and FEEs, because the most consistent pattern of results across sub-studies with clearer results for IPM was only detected through inclusion of AI. Fourth, the DILT can be modified on a general level for usage with personality tests and for motive-specific use and afterwards produces clearer results. Contributions of this thesis are, among others, comparing different DILT-versions, adding trial-wise reinforcement, or usage of FEEs with known motive levels. Fifth, results were actually due to implicit instrumental conditioning, because they were systematically moderated by explicit learning just as little as they were by explicit evaluation of the reinforcers. Moreover, in line with previous research, results showed that accuracy is influenced by n Power in the presence of matching incentives. In closing, I interpret my results based on the notion that implicit motives, via their affect-amplifying function for motive-relevant stimuli or events, contribute to competency development, with an integrated learning experience promoting behavioral competency which in turn promotes future reinforcement-attaining behavior which enhances the learning experience in a virtuous circle. The striatum-mediated instrumental reinforcement of motor behavior in the basal ganglia is one of the pathways through which motives contribute to this learning experience. My results underscore the adaptive value of this learning experience particularly regarding social intuition. Taken together, the supposed principle was supported with slight limitations: implicit motives influence instrumental conditioning processes, but, at least for n Power, other factors have to be simultaneously considered, particularly AI.