The researchers at UCLA Health have found a way that the brain creates memories while using less energy, even during sleep. This efficient memory process takes place in a crucial part of the brain for learning and memory, and where Alzheimer’s disease starts. The findings are published in the journal Nature Communications.This might sound familiar to you: You walk into the kitchen to grab something, but once you get there, you can’t remember what you needed. This is an example of your working memory failing. Working memory refers to the ability to hold onto information for a short period while you are doing other things. We rely on working memory constantly. People with Alzheimer’s and dementia often struggle with working memory, and it can also be seen in those with mild cognitive impairment (MCI). As a result, a lot of research has been done to understand how the complex networks of neurons in the brain create working memory.
During tasks that require working memory, the outer layer of the brain,The neocortex, also known as the neocortex, is responsible for sending sensory information to deeper parts of the brain, including the entorhinal cortex. The entorhinal cortex plays a crucial role in the formation of memories and its neurons exhibit a complex range of responses that have baffled scientists for a long time. This complexity was even recognized with the 2014 Nobel Prize in medicine, but the specific mechanisms behind it remain unknown. Notably, the entorhinal cortex is where Alzheimer’s disease typically starts to develop.
Understanding the intricate processes that occur in the cortico-entorhinal network, when the neocortex communicates with the entorhinal cortex, is therefore of great importance.The study’s corresponding author, Mayank Mehta, a neurophysicist and head of the W. M. Keck Center for Neurophysics and the Center for Physics of Life at UCLA, discussed how the research could lead to an early diagnosis of Alzheimer’s disease, related dementia, and mild cognitive impairment. To address this issue, Mehta and his colleagues came up with a unique approach: a “mathematical microscope.” In the field of physics, mathematical models have been employed by scientists like Kepler, Newton, and Einstein to uncover extraordinary phenomena that were previously unknown or unimagined, such as the inner workings of subatomic particles and the interior of a black hole.In the realm of brain sciences, computational models are utilized, but their predictions are not afforded the same level of gravitas as in physics. This discrepancy can be attributed to the fact that in the field of physics, the predictions stemming from mathematical theories are subject to quantitative testing, rather than purely qualitative evaluation.
Furthermore, the notion of subjecting mathematical theories to quantitatively precise experimental tests is widely perceived as implausible within the realm of biology, primarily due to the immensely intricate nature of the brain in comparison to the physical world. The mathematical theories in physics are often characterized by their simplicity, encompassing a minimal number of free parameters, which facilitates the conduction of precise experimental tests. Conversely, the brain comprises billions of neurons and trillions of connections, presenting a markedly more complex landscape.The researchers described the task as a mathematical puzzle and a very precise microscope. Dr. Krishna Choudhary, the lead author, explained their approach to addressing the challenge of creating a simple theory that can accurately explain memory dynamics in living organisms. They hypothesized that the interaction between the cortex and the entorhinal cortex, which is responsible for memory, occurs even when the subjects are sleeping or under anesthesia. The researchers also assumed that the dynamics of the entire cortex and the entorhinal cortex during sleep.Electrical activity in the brain can be controlled by only two neurons. This simplification reduces the complexity of interactions between billions of neurons to just the strength of input from the neocortex to the entorhinal cortex and the strength of recurrent connections within the entorhinal cortex. While this approach makes the problem easier to understand from a mathematical standpoint, it leads to the question of its accuracy.
“Without quantitative testing of our theory using data from live subjects, it’s just an interesting mathematical exercise, not a true understanding of how memories are formed,” Mehta explained.
To validate this theory, advanced experimental methods are needed.Experiments conducted by Dr. Thomas Hahn, who is now a professor at Basel University and a clinical psychologist, focused on the entorhinal cortex. According to Hahn, in order to test the theory effectively, they required experimental techniques that could not only accurately measure neural activity, but also determine the precise anatomical identity of the neuron. Dr. Sven Berberich, another coauthor, collaborated with Hahn to measure the membrane potential of identified neurons from the entorhinal cortex in vivo using the whole cell patch clamp technique. They then utilized anatomical techniques to identify the neurons.The researchers simultaneously measured the parietal cortex’s activity, which is a part of the neocortex that sends inputs to the entorhinal cortex. “A mathematical theory and sophisticated in vivo data are necessary and cool, but we had to tackle one more challenge — how does one map this simple theory onto complex neural data?” said Mehta. “This required a protracted period of development, to generate a ‘mathematical microscope’ that can directly reveal the inner workings of neurons as they make memory,” said Choudhary. “As far as we know, this has not been done before.” The authors observed that the process was similar to an ocean wave forming and then crashing.The neocortex signals fluctuate between on and off states while a person or animal sleeps, similar to a swimmer moving with the waves. The data and model both supported this observation. The model then uncovered a new memory state called spontaneous persistent inactivity, according to Mehta. It’s like the entorhinal cortex ignoring a wave and remembering that there was no wave recently.Ignore the current wave and choose not to respond at all. This is known as persistent inactivity,” Mehta explained. “On the other hand, persistent activity occurs when the cortical wave disappears but the entorhinal neurons remember that there was a wave very recently, and continue rolling forward.”
While previous theories of working memory had suggested the existence of persistent activity, the authors discovered that persistent inactivity, as predicted by the model, had never been observed before.
“The interesting thing about persistent inactivity is that it requires virtually no energy, unlike persistent activity, which requires a lot of energy,” Mehta explained.
According to the researcher, the combination of persistent activity and inactivity can significantly increase memory capacity while reducing metabolic energy cost.
Dr. Choudhary expressed skepticism, stating that they pushed their mathematical microscope beyond its normal operating conditions to test its accuracy. He was surprised to find that the microscope continued to work perfectly even in unconventional situations.
Mehta added that the mathematical microscope made multiple accurate predictions about various brain regions, demonstrating its near perfect performance.The unprecedented agreement between a mathematical theory and experiments is a major breakthrough in neuroscience. According to Mehta, the mathematical model that perfectly matches the experiments is like a new microscope, revealing things that were previously unseen. He emphasized that no existing microscope could have revealed the same information, regardless of how many neurons were imaged. Additionally, Mehta pointed out that metabolic deficiencies are a common characteristic of various memory disorders. His lab is currently building on this research to gain insight into the formation of complex working memory and to understand the malfunctions in the entorhinal cortex during Alzheimer’s disease., dementia and other memory disorders.
