A01 A02 A03 A04 A05 A06 A07 A09 A10 A11 A12 A13 A14 A18 A19 A21 F01 F02 INF Ö

F01 – Fokusgruppe Lerndynamik

Sen Cheng, Onur Güntürkün, Metin Üngör

Die Trial-by-trial Dynamik der Verhaltensänderungen kann Aufschluss über die Mechanismen des Lernens geben. Nichtsdestotrotz wird Lernen zumeist dadurch quantifiziert, dass die Performanz in einem Block vor mit einem Block nach dem Lernen verglichen wird. Dadurch ist die Analyse blind gegenüber der Lerndynamik. Andere Studien ermitteln Lernkurven, indem sie über verschiedene Probanden mitteln. Falls sich aber das Lernen zwischen Individuen systematisch unterscheidet, kann die gemittelte Lernkurve irreführend sein. Als Service für die anderen Teilprojekte wird diese Fokusgruppe Unterstützung und Training in der Anwendung dynamischer Analysemethoden an diese exportieren. Darüber hinaus wird die Fokusgruppe auch Daten aus anderen Teilprojekten importieren, um ein eigenes wissenschaftliches Ziel zu verfolgen: den Vergleich der Lerndynamik zwischen unterschiedlichen Individuen, Lernphasen, experimentellen Paradigmen und Spezies.

Leitfragen des Projekts F01:

  • Unterscheidet sich die Lerndynamik zwischen verschiedenen Lernparadigmen oder Spezies grundlegend oder nur in deren Parametern?
  • Werden die Dynamiken des Extinktionslernens und der Akquisition durch verschiedene Mechanismen gesteuert?
  • Welche Faktoren, wie z.B. Hinweisreize und Kontextinformationen, führen zu Veränderungen bei der Betrachtung auf Ebene einzelner Durchgänge und darüber hinaus auf der Ebene einzelner Individuen?
  • Wie verhalten sich die Dynamiken von Verhaltensänderungen zu neuronaler Aktivität und psychophysiologischen Variablen?
Zurück zur Projektübersicht

Sen Cheng

Projektleiter A14, F01

Ruhr-Universität Bochum

Onur Güntürkün

Projektleiter A01, F01, Z, Ö

Ruhr-Universität Bochum

Metin Üngör

Projektleiter F01

Philipps-Universität Marburg

10 projektrelevante Publikationen

Batsikadze G*, Diekmann N*, Ernst TM, Klein M, Maderwald S, Deuschl C, Merz CJ, Cheng S, Quick HH, Timmann D (2022) The cerebellum contributes to context-effects during fear extinction learning: a 7T fMRI study. NeuroImage:119080. https://doi.org/10.1016/j.neuroimage.2022.119080 

Donoso JR, Packheiser J, Pusch R, Lederer Z, Walther T, Uengoer M, Lachnit H, Güntürkün O, Cheng S (2021) Emergence of complex dynamics of choice due to repeated exposures to extinction learning. Anim Cogn 24:1279–1297. https://doi.org/10.1007/s10071-021-01521-4 

Nio E, Pereira PP, Diekmann N, Petrenko M, Doubliez A, Ernst TM, Batsikadze G, Maderwald S, Deuschl C, Üngör M, Cheng S, Merz CJ, Quick HH, Timmann D (2025) Human cerebellum and ventral tegmental area interact during extinction of learned fear. eLife 14:RP105399. https://doi.org/10.7554/eLife.105399 

Packheiser J, Donoso JR, Cheng S, Güntürkün O, Pusch R (2021) Trial-by-trial dynamics of reward prediction error-associated signals during extinction learning and renewal. Prog Neurobiol 197:101901. https://doi.org/10.1016/j.pneurobio.2020.101901 

Petrenko M, Coenen L, Doubliez A, Ernst TM, Nio E, Diekmann N, Uengoer M, Cheng S, Merz CJ, Timmann D, Batsikadze G (2025) Appetitive and aversive classical conditioning: Self-reports and physiological responses. Behav Brain Res 484:115509. https://doi.org/10.1016/j.bbr.2025.115509 

Pusch R, Packheiser J, Azizi AH, Sevincik CS, Rose J, Cheng S, Stüttgen MC, Güntürkün O (2023) Working memory performance is tied to stimulus complexity. Commun Biol 6:1–16. https://doi.org/10.1038/s42003-023-05486-7 

Rayan A*, Donoso JR*, Mendez-Couz M, Dolón L, Cheng S, Manahan-Vaughan D (2022) Learning shifts the preferred theta phase of gamma oscillations in CA1. Hippocampus 32:695–704.https://doi.org/10.1002/hipo.23460 

Sevincik CS, Packheiser J, Donoso JR, Cheng S, Rose J, Güntürkün O, Pusch R (2025) Divide and conquer: How avian „prefrontal“ and hippocampal neurons process extinction learning in complementary ways. bioRxiv 2025.03.21.644535. https://doi.org/10.1101/2025.03.21.644535 

Thieme A, Spisák Z, Zeidan P, Klein M, Nio E, Ernst TM, Diekmann N, Göricke S, Cheng S, Merz CJ, Yavari F, Nitsche MA, Batsikadze G, Timmann D (2025) Cerebellar transcranial alternating current stimulation in the theta band facilitates extinction of learned fear responses. bioRxiv:2025.01.13.632735. https://doi.org/10.1101/2025.01.13.632735 

Walther T, Diekmann N, Vijayabaskaran S, Donoso JR, Manahan-Vaughan D, Wiskott L, Cheng S (2021) Contextdependent extinction learning emerging from raw sensory inputs: a reinforcement learning approach. Sci Rep 11:2713. https://doi.org/10.1038/s41598-021-81157-z

New Year, New Me: The Facts

As the calendar turns to a new year, millions of people around the world commit to New Year’s resolutions, making promises to use the new year as a fresh beginning and an opportunity for transformation. In 2024, almost three-quarters of the British population set themselves New Year’s resolutions — that’s around 40 million people (or the entire population of Canada). This tradition was particularly strong among younger generations, with 96% of Generation Z (aged 18-27) planning resolutions, compared to just 35% of the Silent Generation (aged 79+).

Most common new years resolutions:

  1. Saving more money (52%)
  2. Eat healthier (50%)
  3. Exercise more (48%)
  4. Lose weight (37%)
  5. Spend more time with family/friends (35%)

How long do most resolutions normally last before being broken?

  • Data from America (2016) shows that 75% of individuals maintain their resolutions through the first week. 
  • 64% of individuals maintain their resolutions through the first month. 
  • 46% of individuals in America keep their resolutions past the 6-month mark.

What makes resolutions stick?

Oscarsson et al. (2020) conducted research into what makes New Year’s resolutions stick. Biggest success rates depended on how people phrased their goals. Participants who set approach-oriented goals (trying to move toward or maintain a desirable outcome or state) than those with avoidance-oriented goals (trying to move toward or maintain a desirable outcome or state) were significantly more successful (58.9% vs. 47.1%) at sticking to their goals.

The study also investigates the effects of outside support. These participants received monthly follow-ups and emails with information and exercises for coping with hurdles when striving toward personal goals, and were also encouraged to set goals using the SMART technique and to set interim goals. The group that received some support was exclusively and significantly more successful compared to the groups who received a lot of support or no support at all. 

Additionally, you might feel more successful if you set goals that are measurable in numbers. While success for a person striving to quit smoking or lose weight could easily be measured in the number of cigarettes smoked or body mass index, the success for a person striving to „take better care of themselves“ could be highly subjective and possibly impossible to measure.

So as we enter 2026, let’s remember to work with our brain’s natural learning system: Frame your goals positively, break them into manageable steps, and celebrate small wins along the way.