Laminar-PL: Ultra-high field imaging of perceptual learning and human brain plasticity
The human brain has extraordinary capacity to adapt to changes in noisy and variable environments. Learning and experience have been shown to shape critical functions of the adult brain to support our interactions in complex and dynamic environments. Investigating the brain mechanisms that mediate perceptual learning – that is, our ability to improve our performance when making perceptual judgments due to training – is at the core of understanding plastic brain changes. Understanding this learning-dependent plasticity not only has potential practical implications for designing training programmes for lifelong learning, but may also aid remediation and recovery in brain dysfunction.
Type of action: MSCA-IF-EF-ST (Standard European Fellowships)
Grant Agreement: 840271
Beneficiary: The chancellor, masters and scholars of the University of Cambridge
Secondment: Brain Innovation BV
Supervisor: Prof. Zoe Kourtzi and Prof. Rainer Goebel
Fellow: Ke Jia
Marie Curie Fellow
Research Objectives
Objectives of the Ultra-high field imaging of perceptual learning and human brain plasticity (Laminar-PL) project have been to combine interdisciplinary methods to investigate the neural mechanisms that mediate perceptual learning.
- combine psychophysical experiments, machine learning and ultra-high field imaging to investigate the neural locus of learning-dependent brain plasticity after extensive training and test competing theories of learning (i.e., learning-dependent changes at early stages of information encoding vs. later stages of decision making).
- use cutting-edge computational neuroimaging methods to demonstrate the computational processes underlying perceptual learning (e.g., feedforward vs. recurrent vs. feedback).
- measure laminar connectivity across brain areas based on task-related measurements (i.e., how different brain areas work together) that supports behavioral improvement due to training.
- combine cutting-edge techniques and construct a working protocol for laminar imaging data analyses, which will provide valuable insights into the future development of software for MRI data analysis (e.g. BrainVoyager developed by Brain Innovation-secondment partner).
- foster the development of the individual researcher.
Publications
Jia K, Zamboni E, Rua C, Goncalves NR, Kemper V, Ng AKT, Rodgers C, Williams G, Goebel R & Kourtzi Z (2021). A protocol for ultra-high field laminar fMRI in the human brain. STAR Protocols, 2(2), 100415. https://doi.org/10.1016/j.xpro.2021.100415. PMID: 33851140 PMCID: PMC8039727. Click here for key results and figures.
Jia K, Zamboni E, Kemper V, Rua C, Reis Goncalves N, Ka Tsun Ng A, Rodgers CT, Williams G, Goebel R and Kourtzi Z (2020) Recurrent Processing Drives Perceptual Plasticity, Current Biology; 30, 4177-4187. DOI: 10.1016/j.cub.2020.08.016 PMID 32888488 PMCID: PMC7658806. Click here for key results and figure.
Zamboni E, Kemper VG, Goncalves NR, Jia K, Karlaftis VM, Bell SJ, Giorgio J, Rideaux R, Goebel R and Kourtzi Z (2020) Fine-scale computations for adaptive processing in the human brain, eLife 2020;9:e57637. DOI: 10.7554/eLife.57637 PMID: 33170124 PMCID: PMC7688307.