skip to content

Adaptive Brain Lab



Following my Electrical and Computer Engineering degree, I joined the Adaptive Brain Lab in 2013 as a PhD student of Peterhouse college. In my PhD, I was part of the Marie Curie PRISM network and investigated structural and functional brain plasticity in statistical learning. I received my PhD in February 2018 and I am now a postdoctoral researcher in the lab. I investigate the brain dynamics involved in visual adaptation using state-of-the-art dynamic connectivity analysis during rest and task

Outside the lab I enjoy playing and watching football, as well as cycling around Cambridgeshire.


During my PhD, I studied the role of basal ganglia in the brain and more specifically the involvement of the corticostriatal loops in statistical learning. I employed diffusion tensor imaging to measure structural connectivity, resting-state fMRI to measure functional connectivity and behavioural modelling to describe individual differences in learning strategies. In addition, I employed graph theory analysis in conjunction with partial least squares regression to combine multimodal imaging data and predict individual differences in behaviour.

In my postdoctoral work, I investigate functional connectivity changes during sensory adaptation as a marker of short-term plasticity. In particular, I employ dynamic functional connectivity analysis in conjunction with temporal graphs to capture how information flows during adaptation from primary visual areas (V1) to the rest of the brain.

Read more about Decision strategies for statistical learning , Learning to predict and Brain networks and dynamics in visual adaptation


Key publications: 

Frangou P, Emir UE, Karlaftis VM, Nettekoven C, Hinson EL, Larcombe S, Bridge H, Stagg CJ, Kourtzi Z (2019) Learning to optimize perceptual decisions through suppressive interactions in the human brain, Nature Communications 10:474

Karlaftis VM, Giorgio J, Vértes PE, Wang R, Shen Y, Tino P,  Welchman AE, Kourtzi Z (2019). Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning, Nature Human Behaviour 

Karlaftis VM, Wang R, Shen Y, Tino P, Williams G, Welchman AE, Kourtzi Z (2018) White-matter pathways for statistical learning of temporal structures. eNeuro, 5(June), ENEURO.0382-17.2018. 

Giorgio J, Karlaftis VM, Wang R, Shen Y, Tino P, Welchman AE, Kourtzi Z (2017) Functional brain networks for learning predictive statistics. Cortex 2017 Aug 18. pii: S0010-9452(17)30271-X. doi: 10.1016/j.cortex.2017.08.014.

Bettinardi RG, Deco G, Karlaftis VM, Van Hartevelt, TJ, Fernandes HM, Kourtzi Z, Kringelbach ML, Zamora-Lopez G (2017) How structure sculpts function: Unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure. Chaos, 27: 047409

Not available for consultancy