First Neuropharmacological Contribution

Congratulations to Ali and Mariann for the first neuropharmacological contribution from our laboratory with the article A computational psychiatry approach identifies how alpha-2A noradrenergic agonist Guanfacine affects feature-based reinforcement learning in the macaque . This study first surveys all 14 different tasks that have ever been used with Guanfacine in nonhuman primate studies and than shows in a single case study how rigorous computational reinforcement learning modelling extends existing knowledge by informing about the fundamental learning mechanisms that this drug affects during complex reversal learning. This article is particular important as it paves the way for a more formal computational approach to understand the neural effects of systemically acting psychoactive drugs like Guanfacine (which is uses in Attention Deficit Hyperactivity Disorder, mild cognitive impairment, and more). Congrats Ali and Mariann and all co-authors that made this study possible!

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Theta and Beta Frequency

Theta and beta frequency range coherence between anterior cingulate cortex and frontal eye field indexes the successful preparation for anti-saccades and maintenance of working memory content – with larger ACC to FEF direction of granger causal information flow! These important findings is now published in Nature Communications by Sahand Babapoor-Farrokhran and Stefan Everling with contributions […]

Fronto-Striatal Circuits Optimize Feature-based Attention and Learning

Our new publication (Oemisch et al. (2018) Feature Specific Prediction Errors and Surprise across Macaque Fronto-Striatal Circuits during Attention and Learning) provides the first 4-brain-area survey of how prediction error information in the anterior cingulate – ventral striatum and lateral prefrontal – caudate fronto-striatal loops relate to feature-based attention and learning. We found prediction errors […]

3 minute Thesis Competition

Congratulations to Ben to win the York University 3 minute thesis competition in presenting his MSc graduation work ! Here is the University’s press release about the 2016 YorkU 3MT Winner ! Good luck from the laboratory when moving to the provincial level competition (still with only 3 minutes…for the whole thesis).