Dr. María Herrojo Ruiz


Goldsmiths University of London
Department of Psychology



Current academic positions

Reader in Psychology at Goldsmiths University of London (UK).

Co-Director of the MSc in Computational cognitive Neuroscience at Goldsmiths (UK).

Leading Research Fellow at the Institute of Cognitive Neuroscience of the Higher School of Economics, Moscow (Russia).

Research interests

My research focuses on methodological and computational approaches to study central questions regarding the neural bases of sensorimotor learning and motor control in healthy and clinical populations.

Some of our recent work focuses on understanding the role of neuronal oscillations in the modulation of reward-based motor learning and decision making.

Another line of research investigates the effect of anxiety on these processes. With the support of the British Academy, Leverhulme trust, and Economic and Social Research Council (ESRC), we are using neuroscientific methods and computational modelling to investigate the effect of anxiety on motor variability to assess motor skill learning. Using a similar approach, we are investigating the impact of everyday experiences such as anxiety, motivation, and prior expectations upon learning and decision making.

In a third line of research, we are examining the contribution of interoceptive processes to motor skill learning and skilled performance. We are studying the role of  implicit cardiovascular interoceptive information in piano performance. In addition, we’re working on applying predictive coding models of interoception to the area of motor control.




In our research, we use electroencephalography, magnetoencephalography, intracraneal recordings, deep brain stimulation and non-invasive stimulation in combination with computational modelling and machine learning methods.

General research interests:

  • Sensorimotor learning and motor control
  • Music cognition and performance
  • Computational Modelling
  • Expectation and prediction
  • Anxiety and cognitive biases
  • Bayesian inference
  • Statistics
  • Neurological disorders
  • Deep brain stimulation
  • Dynamical systems
  • Stochastic processes