Thursday, 13 October, 2022
A microscopy image of neural cells where fluorescent markers show different types of cells. Green marks neurons and axons, purple marks neurons, red marks dendrites and blue marks all cells. Where multiple markers are present, colours are merged and typically appear as yellow or pink depending on the proportion of markers.
Image credit: Cortical Labs.
A Melbourne-led team has for the first time shown that 800,000 brain cells living in a dish can perform goal-directed tasks — in this case, the simple tennis-like computer game ‘Pong’. Published in the journal Neuron, the team’s so-called ‘DishBrain’ system is evidence that even brain cells in a dish can exhibit inherent intelligence, modifying their behaviour over time.
Serving as lead author on the study was Dr Brett Kagan, Chief Scientific Officer of biotech startup Cortical Labs, which is dedicated to building a new generation of biological computer chips. He worked with collaborators from 10 other institutions on the project, including Monash University, RMIT University, University College London (UCL) and the Canadian Institute for Advanced Research.
“In the past, models of the brain have been developed according to how computer scientists think the brain might work,” Kagan said. “That is usually based on our current understanding of information technology, such as silicon computing.
“But in truth, we don’t really understand how the brain works.
“From worms to flies to humans, neurons are the starting block for generalised intelligence. So, the question was, can we interact with neurons in a way to harness that inherent intelligence?”
To perform their experiment, the research team took mouse cells from embryonic brains as well as some human brain cells derived from stem cells and grew them on top of microelectrode arrays that could both stimulate them and read their activity. While scientists have for some time been able to mount neurons on multi-electrode arrays and read their activity, this is the first time that cells have been stimulated in a structured and meaningful way.
Electrodes on the left or right of one array were fired to tell DishBrain which side the Pong ball was on, while distance from the paddle was indicated by the frequency of signals. Feedback from the electrodes taught DishBrain how to return the ball, by making the cells act as if they themselves were the paddle.
“We’ve never before been able to see how the cells act in a virtual environment,” Kagan said. “We managed to build a closed-loop environment that can read what’s happening in the cells, stimulate them with meaningful information and then change the cells in an interactive way so they can actually alter each other.”
The researchers monitored the neurons’ activity and responses to this feedback using electric probes that recorded ‘spikes’ on a grid. The spikes got stronger the more a neuron moved its paddle and hit the ball. When neurons missed, their play style was critiqued by a software program created by Cortical Labs. This demonstrated that the neurons could adapt activity to a changing environment, in a goal-oriented way, in real time.
“The beautiful and pioneering aspect of this work rests on equipping the neurons with sensations — the feedback — and crucially the ability to act on their world,” said co-author Professor Karl Friston, a theoretical neuroscientist at UCL.
“Remarkably, the cultures learned how to make their world more predictable by acting upon it. This is remarkable because you cannot teach this kind of self-organisation, simply because — unlike a pet — these mini brains have no sense of reward and punishment.”
“An unpredictable stimulus was applied to the cells, and the system as a whole would reorganise its activity to better play the game and to minimise having a random response,” Kagan added. “You can also think that just playing the game, hitting the ball and getting predictable stimulation, is inherently creating more predictable environments.”
The theory behind this learning is rooted in the free energy principle, developed by Friston, which states that the brain adapts to its environment by changing either its world view or its actions to better fit the world around it.
“We faced a challenge when we were working out how to instruct the cells to go down a certain path,” Kagan said. “We don’t have direct access to dopamine systems or anything else we could use to provide specific real-time incentives, so we had to go a level deeper to what Professor Friston works with: information entropy — a fundamental level of information about how the system might self-organise to interact with its environment at the physical level.
“The free energy principle proposes that cells at this level try to minimise the unpredictability in their environment.”
Kagan said one exciting finding was that DishBrain did not behave like silicon-based systems. “When we presented structured information to disembodied neurons, we saw they changed their activity in a way that is very consistent with them actually behaving as a dynamic system,” he said.
“For example, the neurons’ ability to change and adapt their activity as a result of experience increases over time, consistent with what we see with the cells’ learning rate.”
By building a living model brain from basic structures in this way, scientists will be able to experiment using real brain function rather than flawed analogous models like a computer. Kagan and his team, for example, will next experiment to see what effect alcohol has when introduced to DishBrain.
“We’re trying to create a dose response curve with ethanol — basically get them ‘drunk’ and see if they play the game more poorly, just as when people drink,” Kagan said. This would potentially open the door for completely new ways of understanding what is happening with the brain, and could even be used to gain insights into debilitating conditions such as epilepsy and dementia.
“This new capacity to teach cell cultures to perform a task in which they exhibit sentience — by controlling the paddle to return the ball via sensing — opens up new discovery possibilities which will have far-reaching consequences for technology, health and society,” said Dr Adeel Razi, Director of Monash University’s Computational & Systems Neuroscience Laboratory.
“We know our brains have the evolutionary advantage of being tuned over hundreds of millions of years for survival. Now, it seems we have in our grasp where we can harness this incredibly powerful and cheap biological intelligence.”
The findings also raise the possibility of creating an alternative to animal testing when investigating how new drugs or gene therapies respond in these dynamic environments. According to Friston, “The translational potential of this work is truly exciting: it means we don’t have to worry about creating ‘digital twins’ to test therapeutic interventions. We now have, in principle, the ultimate biomimetic ‘sandbox’ in which to test the effects of drugs and genetic variants — a sandbox constituted by exactly the same computing (neuronal) elements found in your brain and mine.”
“This is the start of a new frontier in understanding intelligence,” Kagan said. “It touches on the fundamental aspects of not only what it means to be human but what it means to be alive and intelligent at all, to process information and be sentient in an ever-changing, dynamic world.”
Serving as lead author on the study was Dr Brett Kagan, Chief Scientific Officer of biotech startup Cortical Labs, which is dedicated to building a new generation of biological computer chips. He worked with collaborators from 10 other institutions on the project, including Monash University, RMIT University, University College London (UCL) and the Canadian Institute for Advanced Research.
“In the past, models of the brain have been developed according to how computer scientists think the brain might work,” Kagan said. “That is usually based on our current understanding of information technology, such as silicon computing.
“But in truth, we don’t really understand how the brain works.
“From worms to flies to humans, neurons are the starting block for generalised intelligence. So, the question was, can we interact with neurons in a way to harness that inherent intelligence?”
To perform their experiment, the research team took mouse cells from embryonic brains as well as some human brain cells derived from stem cells and grew them on top of microelectrode arrays that could both stimulate them and read their activity. While scientists have for some time been able to mount neurons on multi-electrode arrays and read their activity, this is the first time that cells have been stimulated in a structured and meaningful way.
Electrodes on the left or right of one array were fired to tell DishBrain which side the Pong ball was on, while distance from the paddle was indicated by the frequency of signals. Feedback from the electrodes taught DishBrain how to return the ball, by making the cells act as if they themselves were the paddle.
“We’ve never before been able to see how the cells act in a virtual environment,” Kagan said. “We managed to build a closed-loop environment that can read what’s happening in the cells, stimulate them with meaningful information and then change the cells in an interactive way so they can actually alter each other.”
The researchers monitored the neurons’ activity and responses to this feedback using electric probes that recorded ‘spikes’ on a grid. The spikes got stronger the more a neuron moved its paddle and hit the ball. When neurons missed, their play style was critiqued by a software program created by Cortical Labs. This demonstrated that the neurons could adapt activity to a changing environment, in a goal-oriented way, in real time.
“The beautiful and pioneering aspect of this work rests on equipping the neurons with sensations — the feedback — and crucially the ability to act on their world,” said co-author Professor Karl Friston, a theoretical neuroscientist at UCL.
“Remarkably, the cultures learned how to make their world more predictable by acting upon it. This is remarkable because you cannot teach this kind of self-organisation, simply because — unlike a pet — these mini brains have no sense of reward and punishment.”
“An unpredictable stimulus was applied to the cells, and the system as a whole would reorganise its activity to better play the game and to minimise having a random response,” Kagan added. “You can also think that just playing the game, hitting the ball and getting predictable stimulation, is inherently creating more predictable environments.”
The theory behind this learning is rooted in the free energy principle, developed by Friston, which states that the brain adapts to its environment by changing either its world view or its actions to better fit the world around it.
“We faced a challenge when we were working out how to instruct the cells to go down a certain path,” Kagan said. “We don’t have direct access to dopamine systems or anything else we could use to provide specific real-time incentives, so we had to go a level deeper to what Professor Friston works with: information entropy — a fundamental level of information about how the system might self-organise to interact with its environment at the physical level.
“The free energy principle proposes that cells at this level try to minimise the unpredictability in their environment.”
Kagan said one exciting finding was that DishBrain did not behave like silicon-based systems. “When we presented structured information to disembodied neurons, we saw they changed their activity in a way that is very consistent with them actually behaving as a dynamic system,” he said.
“For example, the neurons’ ability to change and adapt their activity as a result of experience increases over time, consistent with what we see with the cells’ learning rate.”
By building a living model brain from basic structures in this way, scientists will be able to experiment using real brain function rather than flawed analogous models like a computer. Kagan and his team, for example, will next experiment to see what effect alcohol has when introduced to DishBrain.
“We’re trying to create a dose response curve with ethanol — basically get them ‘drunk’ and see if they play the game more poorly, just as when people drink,” Kagan said. This would potentially open the door for completely new ways of understanding what is happening with the brain, and could even be used to gain insights into debilitating conditions such as epilepsy and dementia.
“This new capacity to teach cell cultures to perform a task in which they exhibit sentience — by controlling the paddle to return the ball via sensing — opens up new discovery possibilities which will have far-reaching consequences for technology, health and society,” said Dr Adeel Razi, Director of Monash University’s Computational & Systems Neuroscience Laboratory.
“We know our brains have the evolutionary advantage of being tuned over hundreds of millions of years for survival. Now, it seems we have in our grasp where we can harness this incredibly powerful and cheap biological intelligence.”
The findings also raise the possibility of creating an alternative to animal testing when investigating how new drugs or gene therapies respond in these dynamic environments. According to Friston, “The translational potential of this work is truly exciting: it means we don’t have to worry about creating ‘digital twins’ to test therapeutic interventions. We now have, in principle, the ultimate biomimetic ‘sandbox’ in which to test the effects of drugs and genetic variants — a sandbox constituted by exactly the same computing (neuronal) elements found in your brain and mine.”
“This is the start of a new frontier in understanding intelligence,” Kagan said. “It touches on the fundamental aspects of not only what it means to be human but what it means to be alive and intelligent at all, to process information and be sentient in an ever-changing, dynamic world.”
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