Neurosalience #S6E7 with Marta Garrido - Predictive coding, MEG, and understanding psychosis

Neurosalience #S6E7 with Marta Garrido - Predictive coding, MEG, and understanding psychosis

“Predictive coding offers a powerful lens for understanding psychosis…”


Dr. Marta Garrido is a professor at the Melbourne School of Psychological Sciences, where she leads the Cognitive Neuroscience and Computational Psychiatry Laboratory and directs the Cognitive Neuroscience Hub. She is also a research program lead at the Graeme Clark Institute. With a background in engineering physics from the University of Lisbon and a PhD in neuroscience from University College London under the mentorship of Professor Karl Friston, Marta has become a leading figure in understanding how the brain processes predictions and surprise. Her research spans mismatch negativity, predictive coding theory, dynamic causal modeling, and the development of cutting-edge neuroimaging technologies, including Australia’s first optically pumped MEG system.


In this episode, Peter and Marta explore the elegant framework of predictive coding and its implications for understanding psychiatric conditions like psychosis. They discuss how the brain generates predictions about sensory input and how disruptions in these mechanisms may contribute to symptoms of mental illness. Marta shares her journey from engineering to neuroscience, her transformative PhD experience, and the challenges of building a new MEG system from the ground up. The conversation covers fascinating topics including mismatch negativity as a prediction error signal, subcortical shortcuts for processing threatening stimuli, the phenomenon of blindsight, and the critical importance of mentorship in academic careers. Marta also offers candid reflections on being a woman in neuroscience and her vision for the future of computational psychiatry.


We hope you enjoy this episode!


Chapters:

00:00 - Introduction to Dr. Marta Guerrero

04:46 - Journey from Engineering to Neuroscience

10:39 - Understanding Predictive Coding and Bayesian Inference

18:34 - Implications of Predictive Coding in Schizophrenia

27:08 - Advancements in Brain Imaging Techniques

36:31 - Exploring Blindsight and Subcortical Shortcuts

44:14 - Reverse Engineering the Brain: Challenges and Ambitions

51:23 - The Journey of Developing Optically Pumped Magnetometers

01:00:29 - Promoting Women in Neuroscience and Leadership Challenges


Works mentioned:

15:59 - Randeniya et al. (2018). Sensory prediction errors in the continuum of psychosis. https://doi.org/10.1016/j.schres.2017.04.019

18:36 - Goodwin et al. (2026). Predictive processing accounts of psychosis: Bottom-up or top-down disruptions. https://doi.org/10.1038/s44220-025-00558-5

26:02 - Larsen et al. (2019). 22q11.2 deletion syndrome: intact prediction but reduced adaptation. https://doi.org/10.1016/j.nicl.2019.101721

29:40 - Garvert et al. (2014). Subcortical amygdala pathways enable rapid face processing. https://doi.org/10.1016/j.neuroimage.2014.07.047

29:40 - McFadyen et al. (2017). A rapid subcortical amygdala route for faces. https://doi.org/10.1523/JNEUROSCI.3525-16.2017


Episode producers:

Karthik Sama, Xuqian Michelle Li

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