The Neural Basis of Cognitive Control and Flexibility
How prefrontal gating, geometric rule encoding, and metabolic cost shape flexible thought
Emergence in Neural Systems: When Wholes Exceed Their Parts
How collective neural dynamics produce properties no single neuron could predict—and what this means for mind.
Reservoir Computing: How Neural Networks Exploit Chaos for Computation
Random neural wiring isn't a flaw—it may be the brain's most powerful computational strategy
Neural Codes: How Information Format Constrains Computation
Why the format neurons use to represent information determines what computations the brain can easily perform
How Prediction Errors Drive Learning and Perception
The brain learns not from what happens, but from what surprises it—prediction errors are the universal currency of neural computation.
Why Cortical Hierarchies Process Information Bidirectionally
How the brain's backward connections implement prediction, attention, and iterative inference in cortical computation
Neural Codes for Space, Time, and Number
How the brain solves the problem of representing quantity across fundamentally different experiential domains
The Modularity Debate: How Specialized Is Neural Computation?
The brain is neither purely modular nor distributed—specialized computations emerge through flexible, reconfigurable network coalitions.
How Brains Implement Analogical Reasoning
The computational architecture enabling your brain to recognize that atoms resemble solar systems and arguments resemble wars
The Hard Problem: Why Explaining Consciousness Requires New Science
Neural mechanisms explain function, but why does any function feel like something? Science may need expansion, not just extension.
How the Brain Solves the Credit Assignment Problem
How does the brain know which synapses to modify when rewards arrive long after actions unfold?
Bayesian Brain: How Neural Circuits Might Implement Probabilistic Inference
How might neurons represent uncertainty, approximate Bayes' theorem, and combine prior expectations with sensory evidence?
How Attractor Dynamics Create Stable Thoughts in Unstable Networks
Why stable thoughts emerge from unreliable neurons through the mathematics of dynamical landscapes
Sparse Coding: Why Your Brain Activates So Few Neurons at Once
Understanding why neural silence speaks volumes about optimal brain computation.
Criticality in Neural Networks: Why Brains Operate at the Edge of Chaos
How your brain self-organizes to a narrow computational sweet spot where information processing, sensitivity, and flexibility are simultaneously maximized.
The Free Energy Principle: A Mathematical Theory of Everything Neural
Karl Friston's variational framework proposes that minimizing one mathematical quantity explains perception, action, and perhaps existence itself.
What Predictive Processing Reveals About the Nature of Perception
Your brain does not passively receive reality—it actively generates predictions that perception merely corrects, revealing mind as fundamentally generative.
Neural Oscillations: Why Brain Rhythms Are Computational Primitives
Discover how rhythmic brain activity solves fundamental computational problems through precise temporal coordination across multiple frequencies.
Integrated Information Theory: Measuring Consciousness Mathematically
A mathematical framework that quantifies consciousness as irreducible integrated information, generating testable predictions about which physical systems can and cannot experience.
Why Neural Noise Isn't Random: The Computational Role of Variability
Your brain's apparent randomness enables computational capabilities that perfectly reliable neural circuits could never achieve.
The Binding Problem: How Your Brain Creates Unified Experience from Distributed Processing
Discover how three competing theories attempt to explain your brain's most remarkable feat—weaving fragmented neural processing into seamless conscious experience.