‘Mathematical microscope’ reveals a new, energy-efficient mechanism of working memory that works even during sleep

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Researchers at UCLA Health have discovered a mechanism that creates memories while lowering metabolic costs, even during sleep. This efficient memory takes place in a part of the brain that is crucial for learning and memory, and where Alzheimer’s disease begins.

The discovery is published in the journal Nature communication.

Does this sound familiar? You go to the kitchen to get something, but when you get there, you forget what you wanted. This is your working memory failing. Working memory is defined as remembering certain information for a short period of time while doing other things. We use working memory almost all the time.

Alzheimer’s and dementia patients have deficits in working memory, and this is also manifested in mild cognitive impairment (MCI). Therefore, significant efforts have been made to understand the mechanisms by which the vast networks of neurons in the brain create working memory.

During working memory tasks, the outer layer of the brain known as the neocortex sends sensory information to deeper parts of the brain, including a central area called the entorhinal cortex, which is crucial for forming memories. Neurons in the entorhinal cortex exhibit a complex range of responses, which have long puzzled scientists and resulted in the 2014 Nobel Prize in Medicine, but the mechanisms that control this complexity are unknown. The entorhinal cortex is where Alzheimer’s disease begins to form.

“It is therefore crucial to understand what kind of magic happens in the cortico-entorhinal network, when the neocortex speaks to the entorhinal cortex, turning it into working memory. It could provide early diagnosis of Alzheimer’s disease and related dementia, and mild cognitive impairment. ” says corresponding author Mayank Mehta, a neurophysicist and head of the WM Keck Center for Neurophysics and the Center for Physics of Life at UCLA.

To solve this problem, Mehta and his co-authors came up with a new approach: a “mathematical microscope.”

In the world of physics, mathematical models are often used, from Kepler to Newton and Einstein, to reveal amazing things we’ve never seen or even imagined, such as the inner workings of subatomic particles and the inside of a black hole . Mathematical models are also used in brain sciences, but their predictions are not taken as seriously as in physics. The reason is that in physics, predictions of mathematical theories are tested quantitatively, not just qualitatively.

It is generally believed that such quantitatively accurate experimental tests of mathematical theories are infeasible in biology, because the brain is much more complex than the physical world. Mathematical theories in physics are very simple and involve very few free parameters and therefore precise experimental tests. In contrast, the brain has billions of neurons and trillions of connections, a mathematical nightmare, let alone a highly accurate microscope.

“To tackle this seemingly impossible challenge of coming up with a simple theory that can still explain the experimental of memory dynamics data in vivo data with high precision, we hypothesized that cortico-entorhinal dialogue and memory magic will occur even if the subjects to sleep. or sedated,” said Dr. Krishna Choudhary, the lead author of the study. “Just like a car behaves like a car when idling or going 70 miles per hour.”

The researchers then made another major assumption: the dynamics of the entire cortex and the entorhinal cortex during sleep or anesthesia can be recorded by just two neurons. These assumptions reduced the problem of interactions between billions of neurons to just two free variables: the strength of input from the neocortex to the entorhinal cortex and the strength of recurrent connections within the entorhinal cortex. While this makes the problem mathematically tractable, it begs the obvious question: is it true?

“If we test our theory quantitatively on in vivo data, these are just interesting mathematical games, and not a true understanding of the magic of memory making,” says Mehta.

The crucial experimental tests of this theory required advanced experiments by Dr. Thomas Hahn, a co-author who is now a professor at the University of Basel and a clinical psychologist.

“The entorhinal cortex is a complex circuit. To really test the theory, we needed experimental techniques that can not only measure neural activity with high precision, but also determine the precise anatomical identity of the neuron,” Hahn said.

Hahn and Dr. Sven Berberich, also co-author, measured the membrane potential of identified neurons from the entorhinal cortex in vivo, using the whole cell patch-clamp technique and then anatomical techniques to identify the neuron. At the same time, they measured the activity of the parietal cortex, a part of the neocortex that sends input to the entorhinal cortex.

“A mathematical theory and advanced in vivo data are necessary and cool, but we had to tackle another challenge: how do you map this simple theory to complex neural data?” Mehta said.

“This required a lengthy period of development to generate a ‘mathematical microscope’ that can directly reveal the inner workings of neurons as they make memory,” Choudhary said. “To our knowledge, this has not been done before.”

The authors noted that, similar to an ocean wave that forms and then crashes onto a coastline, signals from the neocortex intermittently oscillate between on and off states while a person or animal sleeps. Meanwhile, the entorhinal cortex acted like a swimmer in the water that can move up as the wave forms and then move down as it recedes. The data showed this and the model captured this too. But using this simple match, the model took on a life of its own and discovered a new kind of memory state known as spontaneous persistent inactivity, Mehta said.

“It’s like a wave comes in and the entorhinal cortex says, ‘There’s no wave. I’m going to remember that there wasn’t a wave recently, so I’m going to ignore this current wave and not respond at all.’ This is persistent inactivity,” said Mehta. “Alternatively, persistent activity occurs when the cortical wave disappears, but the entorhinal neurons remember that there was a wave very recently and continue to roll forward.”

Although many theories of working memory had shown the presence of persistent activity, which the authors found, the persistent inactivity was something that the model predicted and had never seen before.

“The nice thing about sustained inactivity is that it takes virtually no energy, unlike sustained activity, which takes a lot of energy,” says Mehta. “Even better, the combination of sustained activity and inactivity more than doubles memory capacity while cutting metabolic energy costs by half.”

“This all sounded too good to be true, so we really pushed our mathematical microscope to its limits, in a regime where it wasn’t designed to work,” said Dr. Choudhary. “If the microscope was right, it would continue to work perfectly even in unusual situations.”

“The mathematical microscope made a dozen predictions, not only about entorhinal but also about many other brain areas. To our great surprise, the mathematical microscope worked every time,” Mehta continued. ‘Such a near-perfect match between the predictions of a mathematical theory and experiments is unprecedented in neuroscience.

“This mathematical model that fits perfectly with experiments is a new microscope,” Mehta added. “It reveals something that without a microscope, no existing microscope could see. No matter how many neurons you imaged, it wouldn’t have revealed any of this. In fact, metabolic deficits are a common feature of many memory disorders.”

Mehta’s lab is now following up on this work to understand how complex working memory is formed and what goes wrong in the entorhinal cortex during Alzheimer’s disease, dementia and other memory disorders.

More information:
Spontaneous sustained activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity, Nature communication (2024). DOI: 10.1038/s41467-024-47617-6

Presented by the University of California, Los Angeles


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