Main Content

Ten selected Publications

• Torrents-Rodas, D., Koenig, S., Uengoer, M., Lachnit, H. (2023). 
  The effect of prediction error on overt attention and learning in humans. 
  Behavioural Processes 206, 1–10.  
  DOI: 10.1016/j.beproc.2023.104843
• Koenig, S., Koerfer, K., Lachnit, H., & Glombiewski, J. (2021).
  An attentional perspective on differential fear conditioning in chronic pain: The informational value of safety cues.
  Behaviour research and therapy 144, 103917, Pergamon, 2021/9/1.
  DOI: 10.1016/j.brat.2021.103917
  
  
• Torrents-Rodas, D., Koenig, S., Uengoer, M., Lachnit, H. (2021).
  A rise in prediction error increases attention to irrelevant cues.
  Biological Psychology, 159, 108007, Elsevier, 2021/‌2/‌1.
  DOI: 10.1016/j.biopsycho.2020.108007
  
  
• Thorwart, A. & Lachnit, H. (2020).
  Inhibited Elements Model – Implementation of an associative learning theory.
  Journal of Mathematical Psychology, 94, Article Number: 102310.
  DOI: 10.1016/j.jmp.2019.102310
  
  
• Koenig, S., Kadel, H., Uengoer, M., Schubö, A., & Lachnit, H. (2017).
  Reward draws the eye, uncertainty holds the eye: Associative learning modulates distracter interference in visual search.
  Front. Behav. Neurosci,
  DOI: 10.3389/fnbeh.2017.00128
  
  
• Koenig, S., Uengoer, M., & Lachnit, H. (2017).
  Pupil dilation indicates the coding of prediction error during associative learning.
  Psychophysiology, 00:000-000.
  DOI: 10.1111/psyp.13020
  
  
• Lachnit, H., Thorwart, A., Schultheis, H., König, S., Lotz, A., & Uengoer, M, (2013).
  Indicators of early and late processing reveal the importance of within-trial-time for theories of associative learning.
  PLoS ONE 8(6): e66291.
  DOI:10.1371/journal.pone.0066291
  
  
• Koenig, S. & Lachnit, H. (2011).
  Curved saccade trajectories reveal conflicting predictions in associative learning.
  Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 1164-1177.
  DOI: 10.1037/a0023718
  
  
• Melchers, K. G., Shanks, D. R., & Lachnit, H. (2008).
  Stimulus coding in human associative learning: Flexible representations of parts and wholes.
  Behavioural Processes, 77, 413-427.
  DOI: 10.1016/j.beproc.2007.09.013
  
  
• Deisig, M., Giurfa, M., Lachnit, H., & Sandoz, J.-C. (2006).
  Neural representation of olfactory mixtures in the honeybee antennal lobe.
  European Journal of Neuroscience, 24, 1161-1174.
  DOI: 10.1111/j.1460-9568.2006.04959.x