The Free Energy Principle and Predictive Processing with Friederike Fabritius and Mark Solms
Manage episode 493020479 series 3635005
Can you train your brain to make better decisions?
Friederike Fabritius and professor Mark Solms, author of 'The Hidden Spring,' discuss two eye-opening concepts you may not have heard about: the free energy principle and predictive processing theory. Solms explains what free energy is as it relates to the brain and our “system” elaborates on the brain’s role as an efficient prediction machine. By reducing prediction errors, your brain can better meet your biological and emotional needs, which in turn ensures survival. Solms discusses the significance of updating our predictions based on past experiences, stating that memories are created in the past but they are for the future. If you want to understand why you make the decisions that you do, and why you might be stuck in patterns that don’t serve you, this is the episode you need to listen to.
01:13 Understanding the Free Energy Principle
02:13 Predictive Processing and Memory
06:31 Practical Applications of Predictive Processing
09:01 Prioritising Emotional Needs
17:10 Exploration vs. Exploitation
19:31 Conclusion and Final Thoughts
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Professor Mark Solms is Director of Neuropsychology at the Neuroscience Institute of the University of Cape Town. He is also Honorary Lecturer in Neurosurgery at the St Bartholomew’s & Royal London Hospital School of Medicine and an Honorary Fellow of the American College of Psychiatrists. He is a member of the British Psychoanalytical Society and the American and South African Psychoanalytic Associations. He has received numerous honours and awards, including the Sigourney Prize. He has published 350 scientific papers, and eight books, the latest being The Hidden Spring (Norton, 2021). He is the authorized editor and translator of the Revised Standard Edition of the Complete Psychological Works of Sigmund Freud (24 volumes) and the forthcoming Complete Neuroscientific Works of Sigmund Freud (4 volumes).
26 episodes