Category: Biology of Information
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Enriched Environment helps decision
Inter-Individual Differences in Cognitive Tasks: Focusing on the Shaping of Decision-Making Strategies is a recent publication about the Mouse Gambling Task. It revealed about 30% of healthy mice displaying risk-averse choices while about 20-25% of mice make risk-prone choices. These strategies are accompanied by different brain network mobilization and individual levels of regional -prefrontal and…
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Active Inference – The book
Available, – Open Access – free to download – great reading … Active Inference: The Free Energy Principle in Mind, Brain, and Behavior By Thomas Parr, Giovanni Pezzulo, Karl J. Friston The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding…
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Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds
This post is a pointer to a great article from Michael Levin, just published in Frontiers in Systems Neurosciences All known cognitive agents are collective intelligences, because we are all made of parts; biological agents in particular are not just structurally modular, but made of parts that are themselves agents in important ways. There is…
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French Horn taught me everything I needed to Know – Arthur Brooks
‘From Strength to Strength:’ Follow this link, fill out the CAPTCHA and … Arthur Brooks discusses his new book. He discusses about a nice set of ideas on building a happy and interesting life. His book, From Strength to Strength: Finding Success, Happiness, and Deep Purpose in the Second Half of Life is a practical…
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Machine Learning Article deserves to have the best ‘Plain Language Summary’
I share the opinion that “all plain language summaries should aspire to the glorious heights of this piece of literary art.”I also like the conclusion presented 🙂
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Why Can the Brain (And Not a Computer) Make Sense of the Liar Paradox?
Ordinary computing machines prohibit self-reference because it leads to logical inconsistencies and undecidability. In contrast, the human mind can understand self-referential statements without necessitating physically impossible brain states. Why can the brain make sense of self-reference? This paper addresses this question by defining the Strange Loop Model, which features causal feedback between two brain modules,…
