Reverse engineering the brain

The human brain is thought to be a predictive, efficient, and adaptive machine. The goal of this research program is to understand how the brain’s circuitry implements the mechanisms which enable us to perceive the world through our senses, learn, and make inferences and decisions. Along with our work on typical cognition in healthy human individuals, our mission is to reverse engineer the brain to understand what goes awry in neurological and psychiatric conditions. To pursue this endeavour we use a combination of computational modelling, machine learning and brain imaging techniques.


  • Brain Signal analysis
  • Neuro and computational modelling
  • Brain image processing and statistical analysis
  • Diffusion-weighted MRI techniques
  • Functional brain imaging (fMRI)
  • Brain connectivity approaches
  • Bayesian inference
  • Machine Learning


  • 128-channel Electroencephalography (EEG) system
  • 64-channel EEG (x4) systems
  • Transcranial Magnetic Simulation (TMS)
  • Optically Pumped Magnetoencephalography (OP-MEG prototype)


Our research provides novel fundamental knowledge about the brain circuitries underpinning perception and cognition in typical individuals and in those with conditions such as schizophrenia, autism, addiction, and anxiety.

Program Leader

Associate Professor Marta Garrido