Brain scans, like social distancing, are inherently very lonely.
Regardless of the equipment, brain scans often rely on a single person performing a single task, often completely still, outside of their normal environment. It’s powerful, that’s for sure. Brain mapping projects have not only uncovered hidden anatomical highways between regions of the brain, but also how they transiently organize into neural networks to support sensations, memories, thoughts, decisions, and life. .
Yet, as this year brutally pointed out, our brains do not work in isolation. Social distancing, isolation, and loneliness are hard to tolerate because our emotions, well-being, and high-level thought processes rely on other people. Even extreme introverts spend their lives forging and learning social connections. The electrical waves in our brain literally synchronize when we listen to a story or watch movies together. In a way, our brain is subconsciously adapted to those around us. In autism, depression, schizophrenia, and other neurological hiccups, these mechanisms break down.
It’s high time to map our social connectomes, says a new article in Neuron.
The last decade of neuroscience magic has primarily focused on mapping a single person’s connectome. Connectomes are often thought of as transient “cognitive maps” that underlie the way we think and act. Yet what is sorely lacking is the impact of others on our brains. With the rise of social robots like Pepper and our increasing interactions with self-driving cars, it’s even more essential to understand how our neurons engage in social interactions, whether with humans or machines.
“Our actions and decision-making in day-to-day life are heavily influenced by others,” but we know very little about how brains mate, said author Dr Antonia F. by C. Hamilton of University College London. The good news? A new ‘game-changing’ technique has the power to change that. In other words, if we are very careful about how to interpret what we find.
Collective brain maps
Discover hyperscanning, a marriage between neurotech, mental reading and serious mathematics.
For about two decades, a growing voice among neuroscientists has argued that we should be using non-invasive brain-reading technologies on multiple people simultaneously. Scientists can then observe their entire brain in action as volunteers collaborate or compete on a single task. Add in a deluge of complicated math, and then it’s possible to statistically see what’s going on in multiple brains while people hang around at the same time. This is conceptually similar to extending the connectome from a single person to a group brain map, albeit at a much lower resolution.
It is a technique with a slight whiff of voodoo. Humans are, after all, independent creatures and our interactions are rather unpredictable. But it has been a quiet success in tackling social neuroscience, like the way our neurons encode social commitments. In a landmark study, a team from Stanford used lasers to measure the brain activity of two people playing side-by-side in a collaborative game.
The Near-Infrared Spectroscopy (NIRS) scanner uses light to detect how oxygen in the blood changes in a given part of the brain. Because neurons consume oxygen when triggered with activity, oxygen levels in the blood provide a proxy for the amount of activity that occurs in any part of the brain. The beauty of NIRS is that the setup is much simpler than a traditional brain scanner: volunteers can literally wear all the scanning equipment like a swim cap and walk around, or talk and work with other people. It was a game-changer for the study of human social interaction, Hamilton said, because it shows that it is possible to scan the brains of multiple people at once.
The study found that people who successfully associate with a task tend to see the frontal part of their brain activity sing in harmony. Since then, several studies have observed the same consistency in our neurons when we connect with other people, for example during eye contact, conversations or collective decisions.
The problem, Hamilton says, is how much we should trust this brain scan data alone.
NIRS is a way to easily scan multiple brains. But there are other options: EEG (electroencephalography), which measures electrical activity of the brain through the scalp, or its sibling EMG, which does the same using magnets. These configurations, once limited to certain laboratories, have become increasingly sensitive and precise and are now entering the sphere of consumers. Add in hyper sci-fi setups with multiple sensors, and we seem to be at a crossroads in being able to “read the mind” of multiple brains at once, decoding how social interactions make our brains work, or not.
Not so fast, Hamilton said. Claiming that one person’s brain activity influences that of another sounds like “telepathy,” disconnected from how we understand the brain or even anything that is currently neurobiologically plausible, has it? she declared.
Yes, our brains sync when we watch a movie together. But all this reflects could be a “common cognitive processing” mechanism – basically, the basic operating system of the brain – that kicks in together and results in synchronized brains, rather than a brain-specific social mechanism. . in itself.
“To get past the hype, we may have to do bigger and better experiments and interpret them within a more solid theoretical framework,” she said.
One way to get clearer answers is to add other bodily inputs, such as what we see, feel, or feel. Think about your last interaction with a loved one, friend, or coworker – your body is responding, too. This type of “built-in mutual prediction” is essential, says Hamilton, so it is possible to collect complementary neural electrical data and heart rate or other biomarkers to analyze social interactions. For example, to gauge how well a group is working together, scientists can potentially measure a team’s brain and biomarker responses over a period of time, capture their neural activity and bodily responses, and use statistical analyzes and models to see how consistent their brain activity is.
“It will be possible to understand how the coordination of social brains is embodied in the interaction of social bodies,” Hamilton said.
Loyalty brain scanners?
Of course, this is all very preliminary. For now, hyperscanning algorithms in social neuroscience and social prediction are still in their infancy. We do not yet have a perfect mathematical model – or algorithm – that can appropriate the response from one person to another at the level of neurons or neural networks. To understand someone else, you need to both capture your own thoughts and assess the other person’s intention, whether you are cooking a meal together, playing a duet, or knowing when to take part in a. conversation in turn.
Neuroscientists are now working on a “mutual prediction theory” to map how our neurons can function to support these processes. The main idea is that everyone has two predictive powers: one that assesses and controls our own behaviors, and the other that predicts and maps the behavior of the people you interact with. At the back of the two are powerful biological software algorithms that can model both your behaviors and those of your interacting partner. The key is to decode these algorithms in the brain while it is engaged with another brain.
It might sound very vague, but this is the type of study that might provide more information on how much people are willing to sacrifice during a lockdown, or how we respond to people with different mask wear values. Using an algorithm called a General Linear Cross Model (xGLM), for example, scientists may be able to understand how people predict other people’s responses and how they in turn react.
Overall, argues Hamilton, any study of social interaction should include brain scans and how our bodies react. Hyperscanning is perhaps the sexiest kid in the social neuroscience block. But adding in the reactions of our body captures how we feel and react during social engagements, to hell with subconscious brain processes. The combination of the two leads us towards a powerful model of social interaction, allowing us to “transfer social neuroscience research to the real world”. How children react to virtual learning. How therapists lead patients to happier and more fulfilling lives. How isolated being alone feels like being crushed. How Zoom calls are changing the pace of a business team.
And if there has ever been a year to better understand what our brains get from face-to-face interactions, this is it.
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