A2
Neurocognitive processes supporting flexible voluntary action
Project Aims
Project A2 has been pursuing the agenda to better understand how adaptive behavior results from a well-balanced calibration of cognitive and neural processes promoting either ‘stability’ or ‘flexibility’ depending on circumstances. Stability, on the one hand, is tightly linked to the notion of routine or habitual behavior resulting from its repeated successful implementation in similar situations in the past. Flexibility, on the other hand, is linked to notions such as willfully adopting novel behaviors or orienting behavior towards future goals – in contrasts to routine behavior reflexively triggered by the immediate stimulus situation. In a first research strand, using a mix of behavioral and neuroimaging methods project A2 has utilized different experimental paradigms to better understand the neuro-cognitive mechanisms underlying behavioral flexibility as expressed in (i) goal-oriented (vs. reflexive stimulus-bound) action and (ii) willfully adopted novel behavior based on explicit instructions. A second research strand examined the neuro-cognitive mechanisms that determine the balance between flexibility and stability especially when habitual and goal-directed action tendencies are in conflict. Moreover, we examined how this balance is affected by modulatory factors such as acute psychosocial stress and how it is altered in different clinical syndromes, the latter relying on both internal and external cooperation.
Over the past two funding periods we could identify cortical and striatal brain regions and their integration into larger cortico-striatal network structures differentially linked to newly instructed behavior, goal-oriented action, and habit-related mechanisms, as well as the role (some of) these regions and networks play when habitual and goal-directed action tendencies are in conflict. Of particular importance for our future plans in funding phase 3 is that some of the striatal brain regions associated with the implementation of newly instructed behavior overlapped with striatal regions we found to be linked to goal-oriented action (anterior caudate) whereas others overlapped with striatal regions we found to be linked to reflexive habit-like behavior (putamen). These latter findings suggest that the implementation of newly instructed behavior exhibits features of both, goal-directed action as well as reflexively stimulus-triggered action. This is consistent with theoretical concepts from cognitive psychology which have proposed terms such as the ‘prepared reflex’ or ‘intention-based reflexivity’ to characterize the nature of instruction-based stimulus-response learning.
In funding period three, project A2 will directly follow-up on these earlier findings by adopting two approaches. First, we aim to explore more systematically how ‘intentionality’ and ‘reflexivity’ relate to the conditions under which novel behaviors are learned and how this impacts the balance between goal-directed and habitual action. To this end, we will directly compare instruction-based learning of novel behaviors (via direct instruction or via observation-based instruction) with the conventional route to habit formation involving experience-based reinforcement learning via trial-and-error. Moreover, we will examine how these different forms of learning affect the implementation of competing actions and how this depends on the amount of practice (initial few trials, hundreds of trials). Second, building on the body of correlational evidence accumulated in the previous funding phases, we will test the causal contributions of some of the identified cortical regions by means of transcranial magnetic stimulation (TMS) using both offline and online TMS protocols. Functional MRI following offline TMS will be used to examine differential functional network connectivity changes that were so prominent in our previous experiments. These results will be informative not only for the particular topic of this subproject but bears potential importance for understanding brain (re-) organization principles on a more general level.
Project Members
Principal Investigators
Prof. Dr. rer. nat. Hannes Ruge
Head of the research group Neuroimaging of Higher Cognitive Brain Function
Phone: +49 (0)351 463-33824
E-Mail:
Prof. Dr. rer. nat. Uta Wolfensteller
Head of the research group Neuroimaging of Higher Cognitive Brain Function
Phone: +49 (0)351 463-32582
E-Mail: uta.wolfensteller@.tu-dresden.de
Staff
M. Sc. Sofia Fregni
Doctoral researcher (Predoc)
Phone: +49 (0)351 463-42431
E-Mail:
M. Sc. Alexander Baumann Doctoral researcher (Predoc) Phone: +49 (0)351 463-37486 E-Mail:
Publications
Key Publications
Ruge, H., Schafer, T. A., Zwosta, K., Mohr, H., & Wolfensteller, U. (2019). Neural representation of newly instructed rule identities during early implementation trials. Elife, 8, e48293. doi:10.7554/eLife.48293
Zwosta, K., Ruge, H., Goschke, T., & Wolfensteller, U. (2018). Habit strength is predicted by activity dynamics in goal-directed brain systems during training. Neuroimage, 165, 125-137. doi:10.1016/j.neuroimage.2017.09.062
Mohr, H., Wolfensteller, U., Betzel, R. F., Misic, B., Sporns, O., Richiardi, J., & Ruge, H. (2016). Integration and segregation of large-scale brain networks during short-term task automatization. Nature Communications, 7, 13217. doi:10.1038/ncomms13217
Publications (all; by year)
Jargow, J., Wolfensteller, U., Pfeuffer, C. U., & Ruge, H. (2022). Instructing item-specific switch probability: Expectations modulate stimulus-action priming. Psychological Research.
Jargow, J., Zwosta, K., Korb, F. M., Ruge, H., & Wolfensteller, U. (2021). Low-Frequency TMS Results in Condition-Related Dynamic Activation Changes of Stimulated and Contralateral Inferior Parietal Lobule. Front Hum Neurosci, 15, 684367. doi:10.3389/fnhum.2021.684367
Muller, E. J., Munn, B., Mohr, H., Ruge, H., & Shine, J. M. (2021). Brain state kinematics and the trajectory of task performance improvement. Neuroimage, 243, 118510. doi:10.1016/j.neuroimage.2021.118510
Gluck, V. M., Zwosta, K., Wolfensteller, U., Ruge, H., & Pittig, A. (2021). Costly habitual avoidance is reduced by concurrent goal-directed approach in a modified devaluation paradigm. Behaviour Research and Therapy, 146, 103964. doi:10.1016/j.brat.2021.103964
Sheffield, J. M., Mohr, H., Ruge, H., & Barch, D. M. (2021). Disrupted Salience and Cingulo-Opercular Network Connectivity During Impaired Rapid Instructed Task Learning in Schizophrenia. Clinical Psychological Science, 9(2), 210-221. doi:Artn 2167702620959341
Ruge, H., Schafer, T. A., Zwosta, K., Mohr, H., & Wolfensteller, U. (2019). Neural representation of newly instructed rule identities during early implementation trials. Elife, 8, e48293. doi:10.7554/eLife.48293
Fechtelpeter, J., Ruge, H., & Mohr, H. (2019). The cingulo-opercular network controls stimulus- response transformations with increasing efficiency over the course of learning. 2019 Conference on Cognitive Computational Neuroscience. doi:10.32470/CCN.2019.1060-0
Ruge, H., Karcz, T., Mark, T., Martin, V., Zwosta, K., & Wolfensteller, U. (2018). On the efficiency of instruction-based rule encoding. Acta Psychologica, 184, 4-19. doi:10.1016/j.actpsy.2017.04.005
Shi, Y., Wolfensteller, U., Schubert, T., & Ruge, H. (2018). When global rule reversal meets local task switching: The neural mechanisms of coordinated behavioral adaptation to instructed multi-level demand changes. Human Brain Mapping, 39(2), 735-746. doi:10.1002/hbm.23878
Mohr, H., Wolfensteller, U., & Ruge, H. (2018). Large-scale coupling dynamics of instructed reversal learning. Neuroimage, 167, 237-246. doi:10.1016/j.neuroimage.2017.11.049
Mohr, H., Zwosta, K., Markovic, D., Bitzer, S., Wolfensteller, U., & Ruge, H. (2018). Deterministic response strategies in a trial-and-error learning task. PLoS Computational Biology, 14(11), e1006621. doi:10.1371/journal.pcbi.1006621
Ruge, H., Legler, E., Schäfer, T. A. J., Zwosta, K., Wolfensteller, U., & Mohr, H. (2018). Unbiased Analysis of Item-Specific Multi-Voxel Activation Patterns Across Learning. Frontiers in Neuroscience, 12, 723. doi:10.3389/fnins.2018.00723
Sheffield, J. M., Ruge, H., Kandala, S., & Barch, D. M. (2018). Rapid instruction-based task learning (RITL) in schizophrenia. Journal of Abnormal Psychology, 127(5), 513-528. doi:10.1037/abn0000354
Zwosta, K., Ruge, H., Goschke, T., & Wolfensteller, U. (2018). Habit strength is predicted by activity dynamics in goal-directed brain systems during training. Neuroimage, 165, 125-137. doi:10.1016/j.neuroimage.2017.09.062
Baum, F., Wolfensteller, U., & Ruge, H. (2017). Learning-Related Brain-Electrical Activity Dynamics Associated with the Subsequent Impact of Learnt Action-Outcome Associations. Front Hum Neurosci, 11(252), 252. doi:10.3389/fnhum.2017.00252
Mohr, H., Wolfensteller, U., Betzel, R. F., Misic, B., Sporns, O., Richiardi, J., & Ruge, H. (2016). Integration and segregation of large-scale brain networks during short-term task automatization. Nature Communications, 7, 13217. doi:10.1038/ncomms13217
Ruge, H., & Wolfensteller, U. (2016). Distinct contributions of lateral orbito-frontal cortex, striatum, and fronto-parietal network regions for rule encoding and control of memory-based implementation during instructed reversal learning. Neuroimage, 125, 1-12. doi:10.1016/j.neuroimage.2015.10.005
Ruge, H., & Wolfensteller, U. (2016). Towards an understanding of the neural dynamics of intentional learning: Considering the timescale. Neuroimage, 142, 668-673. doi:10.1016/j.neuroimage.2016.06.006
Zwosta, K., Ruge, H., & Wolfensteller, U. (2015). Neural mechanisms of goal-directed behavior: outcome-based response selection is associated with increased functional coupling of the angular gyrus. Front Hum Neurosci, 9, 180. doi:10.3389/fnhum.2015.00180
Mohr, H., Wolfensteller, U., Frimmel, S., & Ruge, H. (2015). Sparse regularization techniques provide novel insights into outcome integration processes. Neuroimage, 104(0), 163-176. doi:10.1016/j.neuroimage.2014.10.025
Ruge, H., & Wolfensteller, U. (2015). Distinct fronto-striatal couplings reveal the double-faced nature of response-outcome relations in instruction-based learning. Cognitive, Affective and Behavioral Neuroscience, 15(2), 349-364. doi:10.3758/s13415-014-0325-4
Wolfensteller, U., & Ruge, H. (2014). Response selection difficulty modulates the behavioral impact of rapidly learnt action effects. Front Psychol, 5, 1382. doi:10.3389/fpsyg.2014.01382
Zwosta, K., Ruge, H., & Wolfensteller, U. (2013). No anticipation without intention: response-effect compatibility in effect-based and stimulus-based actions. Acta Psychologica, 144(3), 628-634. doi:10.1016/j.actpsy.2013.09.014
Ruge, H., & Wolfensteller, U. (2013). Functional integration processes underlying the instruction-based learning of novel goal-directed behaviors. Neuroimage, 68(0), 162-172. doi:10.1016/j.neuroimage.2012.12.003
Wolfensteller, U., & Ruge, H. (2012). Frontostriatal mechanisms in instruction-based learning as a hallmark of flexible goal-directed behavior. Frontiers in Psychology, 3:192. doi:10.3389/fpsyg.2012.00192