skip to primary navigationskip to content
 

New papers in eLife and Nature Communications reveal the role of GABAergic inhibition in visual perceptual learning

last modified Jan 08, 2019 02:18 PM
We are delighted to announce two new publications from our lab on the role of GABAergic inhibition in visual perceptual learning. We have used multi-modal human brain imaging (MR Spectroscopy, task fMRI, resting state fMRI) to investigate changes in the concentration of the neurotransmitter GABA during training across decision-making circuits.
Our new publication in eLife by Dr. Polytimi Frangou and Professor Zoe Kourtzi combines GABA with fMRI measurements in the human brain to uncover distinct suppression mechanisms that optimise perceptual decisions through learning and experience-dependent plasticity in the visual cortex. Read the article here: https://elifesciences.org/articles/35854
Further, work by Dr. Polytimi Frangou, Dr. Vasileios Karlaftis and Professor Zoe Kourtzi from our lab, in collaboration with Professor Charlotte Stagg (University of Oxford), Associate Professor Holly Bridge (University of Oxford) and Assistant Professor Uzay Emir (Purdue University) has just been accepted in Nature Communications. The paper combines ultra-high field MR Spectroscopy of GABA during training with resting state fMRI connectivity to uncover the role of GABAergic inhibition in decision-making circuits for optimising perceptual judgements through learning and experience.

 

 

RSS Feed Latest news

New paper in Nature Human Behaviour!

Jan 15, 2019

A new publication by Dr. Vasilis Karlaftis, Joseph Giorgio, Dr. Andrew Welchman and Professor Zoe Kourtzi combines behavioural modelling with functional and structural brain connectivity and shows that individuals learn the structure of variable environments by employing alternate decision strategies that engage distinct brain networks:

New paper in e-Neuro!

Jan 08, 2019

A new publication by Dr. Vasilis Karlaftis, Dr. Andrew Welchman and Professor Zoe Kourtzi answers how we extract meaningful structure and make predictions in novel environments.

View all news