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Background: There is extensive evidence that explicit memory, which involves conscious recall of encoded information, can be modulated by emotions; emotions may influence encoding, consolidation or retrieval of information. However, less is known about the modulatory effects of emotions on procedural processes like motor memory, which do not depend upon conscious recall and are instead demonstrated through changes in behaviour. Experiment 1: The goal of the first experiment was to examine the influence of emotions on motor learning. Four groups of subjects completed a motor learning task performing brisk isometric abductions with their thumb. While performing the motor task, the subjects heard emotional sounds varying in arousal and valence: (1) valence negative / arousal low (V-/A-), (2) valence negative / arousal high (V-/A+), (3) valence positive / arousal low (V+/A-), and (4) valence positive / arousal high (V+/A+). Descriptive analysis of the complete data set showed best performances for motor learning in the V-/A- condition, but the differences between the conditions did not reach significance. Results suggest that the interaction between valence and arousal may modulate motor encoding processes. Since limitations of the study cannot be ruled out, future studies with different emotional stimuli have to test the assumption that exposure to low arousing negative stimuli during encoding has a facilitating effect on short term motor memory. Experiment 2: The purpose of the second experiment was to investigate the effects of emotional interference on consolidation of sequential learning. In different sessions, 6 groups of subjects were initially trained on a serial reaction time task (SRTT). To modulate consolidation of the newly learned skill, subjects were exposed, after the training, to 1 of 3 (positive, negative or neutral) different classes of emotional stimuli which consisted of a set of emotional pictures combined with congruent emotional musical pieces or neutral sound. Emotional intervention for each subject group was done in 2 different time intervals (either directly after the training session, or 6 h later). After a 72 h post-training interval, each group was retested on the SRTT. Re-test performance was evaluated in terms of response times and accuracy during performance of the target sequence. Emotional intervention did not influence either response times or accuracy of re-testing SRTT task performance. However, explicit awareness of sequence knowledge was enhanced by arousing negative stimuli applied at 0 h after training. These findings suggest that consolidation of explicit aspects of procedural learning may be more responsive toward emotional interference than are implicit aspects. Consolidation of different domains of skill acquisition may be governed by different mechanisms. Since skill performance did not correlate with explicit awareness we suggest that implicit and explicit modes of SRTT performance are not complementary. Experiment 3: The aim of the third experiment was to analyze if the left hemisphere preferentially controls flexion responses towards positive stimuli, while the right hemisphere is specialized towards extensor responses to negative pictures. To this end, right-handed subjects had to pull or push a joystick subsequent to seeing a positive or a negative stimulus in their left or right hemifield. Flexion responses were faster for positive stimuli, while negative stimuli were associated with faster extensions responses. Overall, performance was fastest when emotional stimuli were presented to the left visual hemifield. This right hemisphere superiority was especially clear for negative stimuli, while reaction times towards positive pictures showed no hemispheric difference. We did not find any interaction between hemifield and response type. Neither was there a triple interaction between valence, hemifield and response type. In our experimental context the interaction between valence and hemifield seems to be stronger than the interaction between valence and motor behaviour. From these results we suppose that under certain conditions a hierarchy scaling of the asymmetry patterns prevails, which might mask any other existing asymmetries.
Participants trained aiming movements of the right hand to several targets with a prism-like virtual displacement of the location of one of the targets, receiving either terminal or continuous visual feedback. After training, the same targets were to be reached with the untrained left hand under manipulated feedback conditions. The right hand movements continuously adapted to the unnoticed visual displacement, significantly less with continuous than with terminal feedback. Under terminal but not under continuous feedback the adaptation to the manipulated target generalized to targets in the same horizontal direction but not to targets in the opposite direction. Finally, the movements of the untrained left hand showed the same qualitative changes to the targets as the movements of the trained right hand. The data are in line with the notion that the adaptation of the right hand movements is mainly based on a re-interpretation of target locations on which movement control of both hands draws.
Encoding Redundancy for Task-dependent Optimal Control : A Neural Network Model of Human Reaching
(2008)
The human motor system is adaptive in two senses. It adapts to the properties of the body to enable effective control. It also adapts to different situational requirements and constraints. This thesis proposes a new neural network model of both kinds of adaptivity for the motor cortical control of human reaching movements, called SURE_REACH (sensorimotor unsupervised learning redundancy resolving control architecture). In this neural network approach, the kinematic and sensorimotor redundancy of a three-joint planar arm is encoded in task-independent internal models by an unsupervised learning scheme. Before a movement is executed, the neural networks prepare a movement plan from the task-independent internal models, which flexibly incorporates external, task-specific constraints. The movement plan is then implemented by proprioceptive or visual closed-loop control. This structure enables SURE_REACH to reach hand targets while incorporating task-specific contraints, for example adhering to kinematic constraints, anticipating the demands of subsequent movements, avoiding obstacles, or reducing the motion of impaired joints. Besides this functionality, the model accounts for temporal aspects of human reaching movements or for data from priming experiments. Additionally, the neural network structure reflects properties of motor cortical networks like interdependent population encoded body space representations, recurrent connectivity, or associative learning schemes. This thesis introduces and describes the new model, relates it to current computational models, evaluates its functionality, relates it to human behavior and neurophysiology, and finally discusses potential extensions as well as the validity of the model. In conclusion, the proposed model grounds highly flexible task-dependent behavior in a neural network framework and unsupervised sensorimotor learning.
Effects of dopamine on BDNF / TrkB mediated signaling and plasticity on cortico-striatal synapses
(2021)
Progressive loss of voluntary movement control is the central symptom of Parkinson's disease (PD). Even today, we are not yet able to cure PD. This is mainly due to a lack of understanding the mechanisms of movement control, network activity and plasticity in motor circuits, in particular between the cerebral cortex and the striatum. Brain-derived neurotrophic factor (BDNF) has emerged as one of the most important factors for the development and survival of neurons, as well as for synaptic plasticity. It is thus an important target for the development of new therapeutic strategies against neurodegenerative diseases. Together with its receptor, the Tropomyosin receptor kinase B (TrkB), it is critically involved in development and function of the striatum. Nevertheless, little is known about the localization of BDNF within presynaptic terminals in the striatum, as well as the types of neurons that produce BDNF in the cerebral cortex. Furthermore, the influence of midbrain derived dopamine on the control of BDNF / TrkB interaction in striatal medium spiny neurons (MSNs) remains elusive so far. Dopamine, however, appears to play an important role, as its absence leads to drastic changes in striatal synaptic plasticity. This suggests that dopamine could regulate synaptic activity in the striatum via modulation of BDNF / TrkB function. To answer these questions, we have developed a sensitive and reliable protocol for the immunohistochemical detection of endogenous BDNF. We find that the majority of striatal BDNF is provided by glutamatergic, cortex derived afferents and not dopaminergic inputs from the midbrain. In fact, we found BDNF in cell bodies of neurons in layers II-III and V of the primary and secondary motor cortex as well as layer V of the somatosensory cortex. These are the brain areas that send dense projections to the dorsolateral striatum for control of voluntary movement. Furthermore, we could show that these projection neurons significantly downregulate the expression of BDNF during the juvenile development of mice between 3 and 12 weeks.
In parallel, we found a modulatory effect of dopamine on the translocation of TrkB to the cell surface in postsynaptic striatal Medium Spiny Neurons (MSNs). In MSNs of the direct pathway (dMSNs), which express dopamine receptor 1 (DRD1), we observed the formation of TrkB aggregates in the 6-hydroxydopamine (6-OHDA) model of PD. This suggests that DRD1 activity controls TrkB surface expression in these neurons. In contrast, we found that DRD2 activation has opposite effects in MSNs of the indirect pathway (iMSNs). Activation of DRD2 promotes a rapid decrease in TrkB surface expression which was reversible and depended on cAMP. In parallel, stimulation of DRD2 led to induction of phospho-TrkB (pTrkB). This effect was significantly slower than the effect on TrkB surface expression and indicates that TrkB is transactivated by DRD2. Together, our data provide evidence that dopamine triggers dual modes of plasticity on striatal MSNs by acting on TrkB surface expression in DRD1 and DRD2 expressing MSNs. This surface expression of the receptor is crucial for the binding of BDNF, which is released from corticostriatal afferents. This leads to the induction of TrkB-mediated downstream signal transduction cascades and long-term potentiation (LTP). Therefore, the dopamine-mediated translocation of TrkB could be a mediator that modulates the balance between dopaminergic and glutamatergic signaling to allow synaptic plasticity in a spatiotemporal manner. This information and the fact that TrkB is segregated to persistent aggregates in PD could help to improve our understanding of voluntary movement control and to develop new therapeutic strategies beyond those focusing on dopaminergic supply.