An Unexpected Beginning
There's something poetic about studying the brain - this complex organ that generates our thoughts, emotions, and the very curiosity that drives us to understand it. My journey with this paper began not in a lab, but on a clear evening walk along Toronto's waterfront, where the stars above and city lights below created a cosmic tapestry reflected in Lake Ontario's gentle waves.
While watching how ripples spread across Lake Ontario from passing boats, I had a thought: perhaps the brain's response to stimulation follows its natural organizational hierarchy - from simple sensory processing to complex cognitive functions.
I was already working with a dataset shared by researchers at the Claudio Munari Epilepsy Surgery Center in Milan – a rare treasure in neuroscience: simultaneous recordings of high-density EEG and direct intracerebral electrical stimulation in epilepsy patients. What made this dataset extraordinary wasn't just the data itself, but the meticulous work done by the Milan team led by Andrea Pigorini. His pioneering efforts to collect and openly share these recordings represented years of careful clinical work with epilepsy patients. This data sharing embodied the best of scientific collaboration – making rare, valuable recordings available to the broader scientific community to accelerate discovery.
The Question That Wouldn't Let Go
The human brain has a fascinating architecture – from primary sensory areas that process basic information like vision and touch, to higher-order networks that integrate information and support complex cognition. This hierarchy had been mapped using techniques like fMRI, but no one had systematically investigated whether brain stimulation responses might follow this same organizational principle.
A Tale of Two Networks
While analyzing this data, we discovered something fascinating about how different parts of the brain respond to electrical stimulation. Imagine the brain as a city with different neighborhoods - some are bustling downtown districts handling complex activities, while others are specialized industrial areas focused on specific tasks.
What we found was that the "downtown districts" of the brain - networks responsible for complex thinking, self-reflection, and planning (like the Default Mode Network and Frontoparietal Network) - showed much stronger responses when stimulated than the "industrial zones" - networks that handle basic sensory information like vision and touch (Visual and Somatomotor Networks).
This wasn't just a small difference. We observed a clear pattern - a gradient of responsiveness that perfectly matched the brain's known hierarchical organization. The higher a network sits in the brain's processing hierarchy, the more dramatically it responds to stimulation.
Beyond Description: Seeking Mechanisms
Finding this pattern was exciting, but understanding why it exists was the real challenge. This is where computational modeling entered our story.
Imagine trying to understand why some neighborhoods in a city are buzzing hubs of activity while others operate at a more measured pace. You'd need a map of the city's transportation system, knowledge of how people move around, and a way to test what happens if certain roads are closed.
This is exactly what we did with the brain. Our computational models were like detailed city simulations that incorporated not just the physical layout of streets (anatomical connections), but also the traffic patterns (neural activity) flowing through them.
Think of our "virtual dissections" as temporarily closing certain highways in this simulated city to see how traffic patterns change. When we blocked connections coming into high-order networks from the rest of the brain, their activity dramatically decreased – like bustling downtown areas becoming ghost towns when all highways leading to them are closed. In contrast, when we did the same to sensory networks, they continued functioning relatively normally – like self-contained suburbs that can operate even when disconnected from the larger metropolitan area.
It's a bit like the difference between a global company that depends on international supply chains versus a local farm-to-table restaurant. Disrupt global shipping, and the multinational corporation struggles to function; the local restaurant, sourcing everything nearby, continues with minimal disruption.
These experiments revealed something fundamental: the responsiveness of high-order brain networks doesn't just come from their internal properties, but from their position in the brain's interconnected web. They are "global" by nature – their very identity and function emerging from constant dialogue with distant regions.
A Journey's End and Beginning
Our paper represents years of collaborative work spanning continents, but in many ways, it's just the beginning. We've identified a fundamental principle of brain organization -- that excitability and recurrence follow hierarchical gradients across cortical networks -- but many questions remain about how these principles relate to cognition, development, and disease.
As I reflect on this journey, I'm grateful for the open science practices that made it possible, for the patients who contributed to the research, and for the collaborative spirit of researchers across institutions and countries who came together to unravel one small piece of the brain's magnificent complexity.
The beauty of science is that each answer reveals new questions. Our discovery of excitability gradients in the brain is not an endpoint but a doorway to deeper understanding of how the brain's architecture shapes its function -- and perhaps, eventually, to better treatments for those suffering from brain disorders.