Ideomotor theory holds that motor plans producing action and the sensory effects of the actions are cognitively represented in a functionally similar way. The response-effect (R-E) association is considered bidirectional and automatic in nature. The current research project was designed to test the hypothesized bidirectional nature of R-E associations by determining if motor codes were activated following perception of an effect. The automaticity of motor code activation was investigated via TMS–induced motor evoked potentials (MEPs) following the presentation an after-effect. To this end, participants completed a training phase in which they learned a specific R-E association. During the testing phase, the effects were presented prior to the imperative and TMS stimuli. Behavioural results replicated previous research; participants preferred to execute the response associated with the presented effect. MEP data, however, did not support the initial hypothesis. These results are discussed with relation to ideomotor theory and experimental design.

Ideomotor theory holds that motor plans producing action and the sensory effects of the actions are cognitively represented in a functionally similar way. The response-effect (R-E) association is considered bidirectional and automatic in nature. The current research project was designed to test the hypothesized bidirectional nature of R-E associations by determining if motor codes were activated following perception of an effect. The automaticity of motor code activation was investigated via TMS–induced motor evoked potentials (MEPs) following the presentation an after-effect. To this end, participants completed a training phase in which they learned a specific R-E association. During the testing phase, the effects were presented prior to the imperative and TMS stimuli. Behavioural results replicated previous research; participants preferred to execute the response associated with the presented effect. MEP data, however, did not support the initial hypothesis. These results are discussed with relation to ideomotor theory and experimental design.

Imitation is a fundamental way of acquiring knowledge in human development. In their theory of goal-directed imitation (GOADI), Wohlschl&auml / ger et al. (2003) divide the representation of observed movements into hierarchically organized aspects the highest of which is usually the goal. In a face-to-face imitation task young children usually copy the (spatial) goal of the body movement in terms of perceptual mirror symmetry rather than match them conceptually onto their own body, as adults do. We refer to these imitation schemes as &ldquo / mirroring&rdquo / and &ldquo / matching&rdquo / respectively. In the present study, we investigate the effects of age and perspective of the child with respect to the experimenter (0&deg / , 90&deg / , 180&deg / ) in two imitation tasks, a hand-to-ear and a cup-grasping task. Moreover, we evaluate the developmental changes in the imitative behavior of children from a dynamical systems perspective. Children were supposed to imitate the movements of the experimenter. Tasks were conducted on 4.5- to 11-year-old Iranian pre-school and elementary school children (81 female, 84 male). Imitation scores for the spatial goal were analyzed in terms of mirroring or matching. Imitation schemes varied according to age and perspective in both tasks. Overall, older children&rsquo / s imitations of movements were more adult-like as established by an adult Iranian control group than those of the younger ones. They rather matched than mirrored observed movements. In the 180&deg / and 90&deg / conditions the mirroring scheme was predominant, but in 0&deg / matching was predominant. GOADI was confirmed / however it was qualified by the child&#039 / s perspective on the experimenter. Children&rsquo / s imitations showed a non-linear shift from perceptually-based mirroring to conceptually-based matching of observed movements onto their own body. This shift happens between 6 and 8-9 years of age. The amount of matching depends not only on age but also on control parameters such as spatial perspective, task demands, and exposure.

In the course of development organisms learn to associate their actions with the effects these actions have in the environment. Recent studies have shown that perceiving or anticipating action-effects automatically activates actions, which formerly have been experienced to cause these effects (Elsner & Hommel, 2001). Using subliminal priming paradigms and electrophysiological measures I investigated whether subliminally (i.e., not consciously perceivable) presented action-effects can automatically activate associated actions and if so, whether this response priming by action-effects can bias free-choice actions. Secondly I investigated whether action-effects with different emotional valences influence response selection differently. To address the first question three experiments were performed. Each experiment consisted of two experimental phases. The first phase, the acquisition-phase, was a learning phase were simple key-press actions were associated with simple visual stimuli (i.e., action-effects; diamond or square) that were contingent on the actions. Immediately after the acquisition-phase the test-phase followed, in which participants performed free-choice actions after the presentation of a Go-signal. In Experiments 2 and 3 a NoGo-signal indicating that responses had to be withheld could appear with the same likelihood as the Go-signal. Unknown to the participants, one of the former action-effects (diamond or square) was presented subliminally prior to each Go- and NoGo-signal to investigate the influence of unconscious action-effects on response selection. Taken together, the results of the test-phases provided strong evidence that even subliminally presented (i.e., unconscious) action-effects can automatically activate associated responses. The response priming by action-effects became evident in the lateralized readiness potential (LRP), an electrophysiological indicator of specific response activation processes. Under certain circumstanced this automatic response activation can bias free-choice actions although participants experienced the actions as freely chosen. In the test-phase of the first experiment more acquisition-phase-consistent than –inconsistent responses were chosen. If, for instance, a left key-press had been associated with a square during the acquisition-phase, the left key was chosen significantly more often after the subliminal presentation of a square in the test-phase. At least three factors seemed to influence which responses were chosen and executed: The strength of the priming effect, the complexity of the task (i.e., pure Go-blocks or intermixed Go/NoGo-blocks), and the elapsed time between the prime stimulus and the Go-signal. To address the second question simple key-press actions were linked to action-effects with different emotional valences (positive vs. negative pictures accompanied by high or low tones) during the acquisition-phase. In the subsequent test-phase, the effects-tones that had been associated with negative or positive pictures were presented and followed by a Go-signal, after which participants had to freely choose to press one of the two response keys. Results indicated that the anticipation of the emotional valence of an action-effect influenced free-choice action. Whereas the effect-tones induced a clear response bias (i.e., more acquisition-consistent than –inconsistent key-choices) if they had been associated with a positive emotional valence, this response bias was not reliable for action-effects associated with negative emotional features. In summary, the present results provide further proof for ideomotor theories of action control (James, 1890; Elsner & Hommel, 2001) which state that actions are automatically activated by anticipating their consequences.

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No. of bitstreams: 2 Dissertacao Lorena Dias Resende - 2013.pdf: 1401725 bytes, checksum: b4f101e9ff3343d1112e15b4cb3e94f5 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013-10-01 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / Introduction: Gait apraxia is characterized by a deficiency in the integration of the sensorial, motor and cerebellar functions necessary for gait. The patients with this compromise have difficulty initiating and there is a congelation of the gait, mainly when turning ove their own axle. It is frequently associated with an emotional instability, a urinary bladder dysfunction and behavioral abnormalities. It is generally observed in gait disturbances high level cortical functions, but its relationship to disease progression and cognitive function is unknown. Objectives: To evaluate the gait apraxia in patients with dementia, its prevalence and association with other types of apraxia as well as observing what phase of the disease in which it appears. Methods: Gait apraxia has been researched in a universe of patients with dementia consecutively assisted in the HC-UFG Neurodementia Ambulatory. The instruments used were the Mini-Mental State Examination and Clinical Dementia Rating Scale (CDR) to evaluate the cognitive functions, Pfeffer's Questionnaire for the functional evaluation of the activities of the daily life, the Scale of Berg's Functional Balance (BERG) and the Timed Up and Go Test (TUG) for the balance mensuration, besides the evaluation of the gait and the posture of the trunk (AWS). Results: A total of fifteen patients, a sample 160, with gait apraxia were included in the study and all had some other associated apraxia. The prevalence of patients with dementia and apraxia of gait was 9,37%. Regarding the CDR showed that 33,3% of patients were mild stage of the disease, 46,7% in the moderate and 20% in the severe. In Pfeffer Questionnaire patients had an average of 19,6±1,40. There balance and coordination deficit in all patients, since the scores of the tests BERG and TUG showed inferior results. On the scale of BERG total score obtained average 11,07±8,06 and varying between 2 and 24 points. The TUG test was performed above 20 seconds for all the patients. In AWS the average score was 14,0±6,88 ranging between 7 and 27 points. The correlation between AWS and scale BERG was significant (p=0,001). Apraxia dynamics (90,9%), ideatory (72,2%) and kinetic members (63,6%) were more frequent among patients. Forms of dementia who had gait apraxia were corticobasal degeneration (53,3%), frontotemporal dementia (13,3%), Alzheimer's disease (6,6%), dementia with chronic subdural hematoma (6,6%), normal pressure hydrocephalus (6,6%), dementia in Parkinson's disease (6,6%) and multiple system atrophy (6,6%). Conclusion: Gait apraxia is little prevalent in the universe of dementia and it is always associated with corticcortical dementia. Other forms of apraxia frequently follow gait apraxia. The corticobasal degeneration is the type of dementia most associated with the gait apraxia. / Introdução: Apraxia da marcha é caracterizada por deficiência na integração das funções sensoriais, motoras e cerebelares necessárias para a deambulação. Os pacientes com este comprometimento têm dificuldade em iniciar a marcha e há um congelamento desta, principalmente ao girar sobre o próprio eixo. É freqüentemente associada a uma instabilidade emocional, disfunção da bexiga e anormalidades comportamentais. É geralmente observada em distúrbios da marcha de alto nível das funções corticais, mas sua relação com aprogressão da doença e função cognitiva é desconhecida. Objetivos: Avaliar a apraxia da marcha em pacientes com demência, sua prevalência e associação com outras formas de apraxia, bem como observar em que fase da doença mais aparece. Métodos: Foi pesquisada a apraxia de marcha em um universo de pacientes com demência consecutivamente atendidos no ambulatório de neurodemência do HC-UFG, entre 2012 e 2013. Os instrumentos utilizados foram o Mini-Exame do Estado Mental e a Escala Clínica de Demência (CDR) para se avaliar o grau da demência, o questionário de Pfeffer para avaliação funcional das atividades instrumentais de vida diária, a Escala de Equilíbrio Funcional de Berg (BERG) e o Timed Up and Go Test (TUG) para a mensuração do equilíbrio; além da avaliação qualitativa da marcha e avaliação postural do tronco (AWS). Resultados: Um total de quinze pacientes, de uma amostra de 160, que apresentavam apraxia da marcha foi incluído no estudo e todos apresentaram alguma outra apraxia associada. A prevalência de pacientes com demência e apraxia da marcha foi de 9,37%. Em relação ao CDR observou-se que 33,3% dos pacientes estavam em estágio leve da doença, 46,7% no moderado e 20% no grave. No questionário de Pfeffer os pacientes obtiveram média de 19,6±1,40. Houve déficit de equilíbrio e coordenação em todos os pacientes, uma vez que a pontuação dos testes de BERG e TUG apresentaram resultados inferiores. Na escala de BERG a pontuação total obteve média de 11,07±8,06 e variação entre 2 e 24 pontos. O teste de TUG foi realizado com tempo acima de 20 segundos por todos os pacientes. Na AWS a média de pontuação foi de 14,00±6,88 variando entre 7 e 27 pontos. Houve correlação significativa entre AWS e a escala de BERG. A apraxia dinâmica (90,9%), ideatória (72,2%) e cinética de membros (63,6%) foram as mais frequentes entre os pacientes. As formas de demência que apresentaram apraxia da marcha foram: degeneração córtico-basal (53,3%), demência fronto-temporal (13,3%), doença de Alzheimer (6,6%), demência por hematoma sub-dural crônico (6,6%), hidrocefalia de pressão normal (6,6%), demência na doença de Parkinson (6,6%) e atrofia de múltiplos sistemas (6,6%). Conclusão: A apraxia de marcha é pouco prevalente no universo das demências e mostrou-se associada a demências córtico-subcorticais. Outras formas de apraxia frequentemente acompanham a apraxia de marcha. Degeneração córtico-basal é a forma de demência mais associada à apraxia de marcha.

Notre capacité à anticiper les événements futurs sur base de notre expérience nous permet d'interagir adéquatement avec notre environnement. Depuis presque deux siècles, cette observation a constitué une question centrale pour deux traditions de recherche différentes, à savoir la théorie idéomotrice de l'action et la théorie de l'apprentissage par renforcement. Alors que la première s'est concentrée sur les effets sensoriels associés avec une action donnée, la seconde tend à considérer que le comportement peut uniquement être influencé par les récompenses et punitions potentielles. Cette thèse de doctorat vise à lier ces deux approches, sur la base du modèle prédictif de la perception. À cette fin, nous avons conduit une série de six expériences explorant différents aspects de la relation entre les prédictions sensorielles et les prédictions de récompense au moyen de méthode de mesure comportementales, de techniques d'électroencéphalographie (EEG) et d'oculométrie. Nos résultats indiquent que (1) les contenus sensoriels et émotionnels appartenant à des stimuli complexes sont évalués ensembles, que (2) les différences inter-individuelles influencent la manière dont nous formons des prédictions et que (3) la mesure de la taille des pupilles est un outil prometteur pour l'étude des prédictions sensorielles. / Our ability to anticipate future events based on prior knowledge about our environment is shaping the way we engage with it. For almost two centuries, this observation has been a central topic for two different research traditions, namely the ideomotor theory and the reinforcement learning literature. Whereas the former focussed is inquiries on the sensory effects associated with a given action, the latter considered that behaviour was only influenced by potential rewards or punishments. This dissertation constitutes an attempt to bridge these two approaches, based on the predictive model theory. For this purpose, we conducted six experiments exploring various aspects of the relationship between reward and sensory prediction using classical behavioural and EEG methods, but also pupil size measurements. Our results suggest that (1) sensory and emotional features of complex stimuli are processed together, that (2) inter-individual differences influence prediction mechanisms and (3) pupil size measurement is a useful tool for sensory prediction.

選擇性模仿是指嬰兒在不同情境中選擇性地模仿他人的行為，為當今發展心理學備受矚目的議題。在Gergely、Bekkering與Király（2002）著名的研究中，當實驗者的雙手自由放在桌上，示範以額頭碰盒子開燈，嬰兒偏好模仿此新奇動作；但當實驗者雙手緊抓毛毯示範相同的動作則未發現嬰兒有顯著的模仿偏好。有些研究者認嬰兒可以透過目的推理理解他人的意圖，並認為模仿是建立在對意圖的解讀之上；相反地，動作－效果整合理論則認為動作本身的執行困難度與動作－效果連結的穩定性才是影響嬰兒選擇性模仿的主因。 為了解決兩者長久以來對於嬰兒模仿的爭議，本研究修訂Gergely等人（2002）的光盒研究派典，將焦點放在過去一直未受到重視的因果效能概念，降低示範動作的因果效能，嬰兒在實驗過程中會發現示範動作不是每次都能成功讓光盒發亮，藉此釐清目的推理論與動作－效果整合理論對嬰兒選擇性模仿的解釋適當性。實驗1的結果重製了Gergely等人（2002）的實驗結果，實驗2A與實驗2B皆發現18個月大的嬰兒在因果效能較低的情境中很少會模仿示範動作，顯示嬰兒的模仿行為較符合動作－效果整合理論的觀點，主要是受到動作執行的困難度與動作－效果聯結的穩定性的影響。 / Selective imitation refers to a phenomenon which infants differentially imitate the demonstrated action in different contexts. Recently, it has also become a popular research topic in developmental psychology. Gergely, Bekkering and Király (2002) uncovered a classic example of selective imitation. They found that infants tend to imitate the action of touching a light box with their forehead when they saw a model perform the action with her hands placed on the table, but not when her hands were restricted by a blanket. Some researchers claim that infants can interpret others’ intention through teleological reasoning, and they consider infants’ imitation is based on decoding of intentionality. Conversely, ideomotor theory argues that imitation depends on difficulty of the action execution and the stability of link between action and its effect. To address the long-standing dispute with infants’ imitation, we revised the paradigm in Gergely et al. (2002) and focused on the concept of causal efficacy which had been long ignored in the past. Infant would find that the demonstrated action, sometimes won’t turn on the light during the experimentation. In experiment 1, we replicated the results obtained in Gergely et al. (2002). Experiment 2A and 2B both found that 18-month-old infants rarely imitated the demonstrated action when the causal efficacy was relatively low. These results are closer to the ideomotor approach viewpoint of imitation, and it reveals that infants’ imitation depends on difficulty of the action execution and the stability of link between action and effect.

In the course of development organisms learn to associate their actions with the effects these actions have in the environment. Recent studies have shown that perceiving or anticipating action-effects automatically activates actions, which formerly have been experienced to cause these effects (Elsner & Hommel, 2001). Using subliminal priming paradigms and electrophysiological measures I investigated whether subliminally (i.e., not consciously perceivable) presented action-effects can automatically activate associated actions and if so, whether this response priming by action-effects can bias free-choice actions. Secondly I investigated whether action-effects with different emotional valences influence response selection differently. To address the first question three experiments were performed. Each experiment consisted of two experimental phases. The first phase, the acquisition-phase, was a learning phase were simple key-press actions were associated with simple visual stimuli (i.e., action-effects; diamond or square) that were contingent on the actions. Immediately after the acquisition-phase the test-phase followed, in which participants performed free-choice actions after the presentation of a Go-signal. In Experiments 2 and 3 a NoGo-signal indicating that responses had to be withheld could appear with the same likelihood as the Go-signal. Unknown to the participants, one of the former action-effects (diamond or square) was presented subliminally prior to each Go- and NoGo-signal to investigate the influence of unconscious action-effects on response selection. Taken together, the results of the test-phases provided strong evidence that even subliminally presented (i.e., unconscious) action-effects can automatically activate associated responses. The response priming by action-effects became evident in the lateralized readiness potential (LRP), an electrophysiological indicator of specific response activation processes. Under certain circumstanced this automatic response activation can bias free-choice actions although participants experienced the actions as freely chosen. In the test-phase of the first experiment more acquisition-phase-consistent than –inconsistent responses were chosen. If, for instance, a left key-press had been associated with a square during the acquisition-phase, the left key was chosen significantly more often after the subliminal presentation of a square in the test-phase. At least three factors seemed to influence which responses were chosen and executed: The strength of the priming effect, the complexity of the task (i.e., pure Go-blocks or intermixed Go/NoGo-blocks), and the elapsed time between the prime stimulus and the Go-signal. To address the second question simple key-press actions were linked to action-effects with different emotional valences (positive vs. negative pictures accompanied by high or low tones) during the acquisition-phase. In the subsequent test-phase, the effects-tones that had been associated with negative or positive pictures were presented and followed by a Go-signal, after which participants had to freely choose to press one of the two response keys. Results indicated that the anticipation of the emotional valence of an action-effect influenced free-choice action. Whereas the effect-tones induced a clear response bias (i.e., more acquisition-consistent than –inconsistent key-choices) if they had been associated with a positive emotional valence, this response bias was not reliable for action-effects associated with negative emotional features. In summary, the present results provide further proof for ideomotor theories of action control (James, 1890; Elsner & Hommel, 2001) which state that actions are automatically activated by anticipating their consequences.

Behavior is considered goal-directed when the actor integrates information about the subsequent outcome of an action (Balleine & O'Doherty, 2010; Dickinson & Balleine, 1994; Kiesel & Koch, 2012), potentially enabling the anticipation of consequences of an action. Thus, it requires prior acquisition of knowledge about the current contingencies between behavioral responses and their outcomes under certain stimulus conditions (J. Hoffmann & Engelkamp, 2013). This association chain enables events lying in the future to be mentally represented and assessed in terms of value and achievability. However, while neural correlates of instructed goal-directed action integration processes have already been examined in a functional magnetic resonance imaging (fMRI) study using this paradigm (Ruge & Wolfensteller, 2015), there has been no information if those processes are also reflected in Electroencephalography (EEG) and if so which specific EEG parameters are modulated by them. This dissertation set out to investigate neurocognitive mechanisms of instructed outcome response learning utilizing two different imaging methods, namely EEG and fMRI. Study 1 was an exploratory study to answer the question what kinds of learning-related EEG correlates were to expect. The O-R outcome integration specific EEG correlates identified in Study 1 served as regressors in a unified general linear model (EEG-informed fMRI analysis) in the co-registered EEG-fMRI study (Study 2). One of the key questions in this study was if the EEG signal could help to differentiate between BOLD pre-response activation associated with processes related to response preparation or initiation and activation associated with post-response outcome integration processes. The foundation to both studies of this work was an experimental paradigm of instructed S-R-O learning, which included a learning and a test phase. Stimuli were four abstract visual patterns that differed in each block. Each visual stimulus required a distinct manual response and was predictably followed by a distinct auditory outcome. Instructions were delivered via a “guided implementation” procedure in which the instruction was embedded within the first three successful behavioral implementation trials. In these first three trials, the visual stimulus was followed by an imperative stimulus highlighting the correct response. The guided implementation phase was followed by an unguided implementation phase where the correct response now had to be retrieved from memory. Behaviorally, the strength of acquired O-R associations can be analyzed via O-R compatibility effects measured in a subsequent outcome-priming test phase (Greenwald, 1970). In this test phase a previously learned outcome becomes an imperative stimulus that requires either the response, which produced that outcome in the preceding learning phase (O-R compatible), or a response, which produced a different outcome (O-R incompatible). The experimental design was embedded into an EEG recording setup in study 1 while study 2 comprised a simultaneous EEG-fMRI recording setup in which EEG scalp potentials were continuously recorded during the experimental session inside the MR scanner bore. Study 1 revealed various ERP markers correlated with outcome response learning. An ERP post-response anterior negativity following auditory outcomes was increasingly attenuated as a function of the acquired association strength. This suggests that previously reported action-induced sensory attenuation effects under extensively trained free choice conditions can be established within few repetitions of specific R-O pairings under forced choice conditions. Furthermore, an even more rapid development of a post-response but pre-outcome fronto-central positivity, which was reduced for high R-O learners, might indicate the rapid deployment of preparatory attention towards predictable outcomes. Finally, the study identified a learning-related stimulus-locked activity modulation within the visual P1-N1 latency range, which was thought to reflect the multi-sensory integration of the perceived antecedent visual stimulus with the anticipated auditory outcome. In general, study 2 was only partially able to replicate the EEG activity dynamics related to the formation of bidirectional R-O associations that were observed in study 1. Primarily, it was able to confirm the modulation in EEG negativity in the visual P1-N1 latency range over the learning course. The EEG-informed analysis revealed that learning-related modulations of the P1-N1 complex are functionally coupled to activation in the orbitofrontal cortex (OFC). More specifically, growing attenuation of the EEG negativity increase from early to late SRO repetition levels in high R-O learners was associated with an increase in activation in the OFC. An additional exploratory EEG analysis identified a recurring post outcome effect at central electrode sites expressed in a stronger negativity in late compared to early learning stages. This effect was present in both studies and showed no correlation with any of the behavioral markers of learning. The EEG-informed fMRI analysis resulted in a pattern of distinct functional couplings of this parameter with different brain regions, each correlated with different behavioral markers of S-R-O learning. First of all, increased coupling between the late EEG negativity and activation in the supplementary motor area (SMA) was positively correlated with the O-R compatibility effect. Thus, high R-O learners exhibited a stronger coupling than low R-O learners. Secondly, increased couplings between the late EEG negativity and activation in the somatosensory cortex as well as the dorsal caudate, on the other hand, were positively correlated with individual reaction time differences between early and late stages of learning. Regarding activation patterns prior to the behavioral response the results indicate that the OFC could serve as a (multimodal) hub for integrating stimulus information and information about its associated outcome in an early pre-stage of action selection and initiation. Learnt S-O contingencies would facilitate initiating the motor program of the action of choice. Hence, the earlier an outcome is anticipated (based on stimulus outcome associations), the better it will be associated with its response, eventually leading to stronger O-R compatibility effects later on. Thus, one could speculate that increased activation in response to S-R-O mappings possibly embodies a marker for the ongoing transition from mere stimulus-based behavior to a goal-directed behavior throughout the learning course. Post-response brain activation revealed a seemingly two-fold feedback integration stream of O-R contingencies. On one hand the SMA seems to be engaged in bidirectional encoding processes of O-R associations. The results promote the general idea that the SMA is involved in the acquisition of goal-directed behavior (Elsner et al., 2002; Melcher, Weidema, Eenshuistra, Hommel, & Gruber, 2008; Melcher et al., 2013). Together with prior research (Frimmel, Wolfensteller, Mohr, & Ruge, 2016) this notion can be generalized not only to extensive learning phases but also to learning tasks in which goal-directed behavior is acquired in only few practice trials. However, there is an ongoing debate on whether SMA activation can be clearly linked to sub-processes prior or subsequent to an agent’s action (Nachev, Kennard, & Husain, 2008). The results of this work provide additional evidence favoring an involvement of the SMA only following a performed action in response to an imperative stimulus and even more, subsequent to the perception of its ensuing effect. This may give rise to the interpretation that the SMA is associated with linking the motor program of the performed action to the sensory program of the perceived effect, hence establishing and strengthening O-R contingencies. Furthermore, the analysis identified an increased coupling of a late negativity in the EEG signal and activation in the dorsal parts of the caudate as well as the somatosensory cortex. The dorsal caudate has not particularly been brought into connection with O-R learning so far. I speculate that the coupling effect in this part of the caudate reflects an ongoing process of an early automatization of the acquired behavior. It has already be shown in a similar paradigm that behavior can be automatized within only few repetitions of novel instructed S-R mappings (Mohr et al., 2016).:Table of contents Table of contents II List of Figures IV List of Tables VI List of Abbreviations VII 1 Summary 1 1.1 Introduction 1 1.2 Study Objectives 2 1.3 Methods 3 1.4 Results 4 1.5 Discussion 4 2 Theoretical Background 7 2.1 Introduction 7 2.2 Theories of acquiring goal-directed behavior 9 2.2.1 Instrumental learning 9 2.2.1.1 Behavioral aspects 9 2.2.1.2 Neurophysiological correlates 14 2.2.2 Acquisition of goal-directed behavior according to ideomotor theory 16 2.2.2.1 Behavioral aspects 16 2.2.2.2 Neurophysiological correlates 22 2.3 Summary 25 2.4 Methodological background 26 2.4.1 Electroencephalography (EEG) 26 2.4.2 Functional magnetic resonance imaging (fMRI) 28 2.4.3 Co-registered EEG-fMRI 29 3 General objectives and research questions 34 4 Study 1 – Learning-related brain-electrical activity dynamics associated with the subsequent impact of learnt action-outcome associations 36 4.1 Introduction 36 4.2 Methods 39 4.3 Results 47 4.4 Discussion 60 5 Study 2 - Within trial distinction of O-R learning-related BOLD activity with the means of co-registered EEG information 64 5.1 Introduction 64 5.2 Methods 66 5.3 Results 86 5.4 Discussion 101 6 Concluding general discussion 109 6.1 Brief assessment of study objectives 109 6.2 Novel insights into rapid instruction based S-R-O learning? 109 6.2.1 Early stimulus outcome information retrieval indicates the transition from stimulus based behavior to goal-directed action 110 6.2.2 Post-response encoding and consolidation of O-R contingencies enables goal-directedness of behavior 112 6.3 Critical reflection of the methodology and outlook 116 6.3.1 Strengths and limitations of this work 116 6.3.2 Data quality assessment 117 6.3.3 A common neural foundation for EEG and fMRI? 119 6.3.4 How can co-registered EEG-fMRI contribute to a better understanding of the human brain? 121 6.4 General Conclusion 123 7 References 124 Danksagung Erklärung

Le but de ce travail de thèse était de contribuer à une meilleure compréhension des mécanismes par lesquels nous nous représentons nos propres actions et celles d'autrui. En nous situant notamment dans la perspective de la théorie idéomotrice, nous avons examiné ces questions tout d'abord dans le cadre de l'imitation. Nos résultats indiquent un effet de l'apprentissage idéomoteur sur l'imitation intentionnelle (Etude 1), confirmant la flexibilité des liens perception-action, et démontrant le rôle des associations réponse-effet dans l'imitation. Toutefois, les performances à une tâche d'imitation automatique n'étaient pas influencées par un tel type d'apprentissage (Etude 2), possiblement en raison de processus différents n'ayant pas la même sensibilité à l'apprentissage idéomoteur. Nous avons ensuite étendu nos recherches au cadre des tâches conjointes (Etude 3). Nous montrons qu'une expérience idéomotrice corrélant l'exécution d'une action avec celle d'un agent non-humain conduit à la co-représentation de l'action de cet agent (présence d'un effet Simon social). Ainsi, l'expérience idéomotrice pourrait également permettre de modifier la co-représentation de l'action d'autrui en situation de tâche partagée. Ce travail confirme donc l'approche idéomotrice de la perception et de la représentation des actions d'autrui. / The aim of present work was to better understand the mechanisms by which we represent our own actions and those of others. Within the frame of the ideomotor theory, we first examined these questions in relation to imitation. Our results indicated an effect of ideomotor learning on intentional imitation (Study 1), confirming the flexibility of perception-action links, and demonstrating the role of action-effect associations in imitation. However, automatic imitation was not influenced by this type of learning (Study 2), which may suggest different processes with less sensitivity to learning ideomotor learning. We then extended our research to joint-action tasks (Study 3). We showed that an ideomotor experience, where action execution triggered actions of a non-human agent, induced a subsequent co-representation of this agent's actions (as indexed by social Simon effect). Ideomotor experience therefore seems to influence also the way we represent the actions of others in task-sharing. This work confirms the ideomotor approach to perception and representation of others' actions.