Do you speak Brain? Master the neuroscience behind learning

Emotion as the pivotal motor of biological learning

In this lecture, we explore how emotion drives learning from a biological perspective. You'll discover why emotional engagement isn't just beneficial — it's essential to how organisms learn and adapt.

In this lecture, we take a broader view to explore learning as a flexible and comprehensive process. We discuss its relationship to reasoning, prediction, artificial intelligence, and resilience. Finally, we touch on innate and imprinted behaviors, laying the groundwork for the evolutionary perspective to come in Section 4.

Biological vs. artificial neurons

We begin with a first look at what neurons are and how they function, then contrast them with artificial neurons used in AI. It’s a playful but critical comparison to ground your understanding of real learning systems.

The synaptic dance
Now that you’ve met the neuron, we go deeper into its structure and the magic of the synapse. You’ll learn how the brain strengthens or eliminates connections — a process at the heart of all learning.

Why timing matters

This lecture introduces the principle of synchronization. You’ll see how coordinated activity between neurons helps form stronger, lasting connections — and what that means for the brain’s ability to learn.

From invertebrates to vertebrates

We begin with a provocative question: Does learning require a brain? You'll explore how simple organisms learn, how brains evolved in vertebrates, and what defines a central nervous system.

Folding to compact the neocortex

Why are some brains wrinkled? This lecture explores how folding enables the packing of more cortex into limited space, a clever evolutionary adaptation that supports complex behaviors.

The cons of big brains

Big brains aren’t always better. Here, we examine the costs and trade-offs associated with brain size, including energy demands, developmental time, and vulnerability.  All part of evolution’s balancing act.

Specialization vs. integration

Using the metaphor of a company, we examine how various brain systems collaborate to support learning. This lecture highlights the balance between specialized roles and flexible integration, clarifying outdated ideas such as phrenology.

What is cognition, really?

We define cognition and introduce the central departments of Brain Inc., with a focus on perception. Far from being a passive gateway, perception is shown as an active, complex process deeply tied to how we learn.

Top-down vs. bottom-up control

We dive into how information flows in the brain. You'll learn the difference between bottom-up (sensory-driven) and top-down (goal-driven) processing, and why their interaction shapes how we learn.

The triangle: perception, attention, and memory
Meet the core team behind learning. Using a progressive model, we begin with a triangle comprising perception, attention, and memory — each with distinct roles yet deeply interconnected.

The pentagon: language joins the team

We complete our model by adding language, transforming the square into a pentagon. This final structure gives us a dynamic view of how these systems interact to shape real-world learning.

What science can (and can’t) say

This lecture introduces scientific methodology and its limits. We explore why neuroscience alone can’t prescribe the “best” school or method — and how learning is shaped by multiple fields of research.

Mapping complexity

Using neuroimaging as a case study, we dive into how brain research works. You’ll learn how complex networks (not isolated “centers”) are key to understanding learning in real brains.

Plasticity, myths, and goodbyes

In our final lecture, we debunk seductive but misleading claims about brain performance. We explore what plasticity really means, its possibilities and limits, and I leave you with a warm farewell.