Summary: Researchers have discovered that kid length during non-REM sleeping correlates with memory combination. When children agreement, the mind focuses on consolidating fresh reminiscences, when dilated, it processes older types.
This separation prevents” severe forgetting,” enabling the mind to effectively manage both new and existing information. These findings may help individuals develop better memory-enhancing strategies and inspire more effective artificial neural networks.
Important Information:
- Pupil Size and Memory: Contracted children coincide with fresh recollection consolidation, while enlarged pupils process older thoughts.
- Memory Separation: The head alternates between new and old information during non-REM sleeping to avoid intervention.
- Artificial Programs: Insight into remembrance running perhaps help improve performance in artificial neural networks.
Origin: Cornell University
The eye may be the windows to the heart, but the instructor is key to understanding how, and when, the head forms solid, long-lasting thoughts, Cornell researchers have found.
The scientists discovered that new thoughts are being replayed and consolidated when the kid is contracted during a subset of non-REM sleep by studying animals equipped with head sensors and little eye-tracking cameras. When the kid is dilated, the process repeats for older thoughts.
The body’s capacity to distinguish these two sleep stages from one another’s by separating them from one another’s prevents” fatal forgetting,” in which consolidation of one memory wipes out another.  ,
The results could improve human memory and enable computer professionals to improve the efficiency of artificial neural networks.
The review,  , published Jan. 1 in Nature, was led by , Azahara Oliva, associate professor in the Department of Neurobiology and Behavior, and , Antonio Fernandez-Ruiz, associate professor and Nancy and Peter Meinig Family Investigator in the Life Sciences, both in the College of Arts and Sciences.
Doctoral scholar Hongyu Chang and postdoctoral scholar Wenbo Tang were the writer’s co-lead artists.  ,
Although there is a strong connection between sleep and storage, the neural mechanisms that drive their interaction are still elusive. Generally speaking, research to understand how memory retention works in sleeping humans and molecular, mobile research in sleeping rodents are conducted in one of two ways.
Combining those two areas of study has proved challenging because the content are so diverse. Rodents have been thought to have a very simple, two-step sleep structure – rapid eye movement ( REM) sleep, when dreaming occurs, and non-REM slow-wave sleep.
However, people ‘ slow-wave sleeping is more difficult, with four rounds, the deepest of which is when scientists suspect the head trawls through and organizes its memories.
Through their joint , test, Oliva and Fernandez-Ruiz used their combined experience in animal habits, technology development and mathematical evaluation to see just what goes on in a sleeping mouse’s eye – and neurons.
A group of animals were taught a variety of jobs over the course of a fortnight, such as obtaining cookie rewards or liquid from a jungle. The animals were finally given small spy cams that hung in front of their eyes to record the instructor relationships and mind wires. When the mice slept, the electrodes recorded their neural activity and the cameras recorded the changes to their pupils as they learned a new task.
” Non-REM sleep is when the actual memory consolidation happens, and these moments are very, very short periods of time undetectable by humans, like 100 milliseconds”, Oliva said.
How do these screenings of memory that are very quick and brief throughout the night get distributed by the brain? And how does that separate the new knowledge that is entering so that it doesn’t conflict with the previous knowledge that we already possess in our minds?
The recordings revealed that the temporal structure of sleeping mice is more diverse and closely related to that of humans ‘ sleep stages than previously believed. The researchers were able to parse the processes by interfering with the mice’s sleep at various times and later evaluating how well they recalled the tasks they had learned.
The pupil of a mouse shrinks when it enters a subset of non-REM sleep, where the newly learned tasks, i .e., the new memories, are being reactivated and consolidated while previous knowledge is not. Conversely, older memories are replayed and integrated when the pupil is dilated.
” It’s like new learning, old knowledge, new learning, old knowledge, and that is fluctuating slowly throughout the sleep”, Oliva said. We propose that the brain has an intermediate time frame that distinguishes the new from the outdated knowledge.
According to Oliva, the noninvasive method of sleep pupil tracking opens up opportunities for human research, and it might be especially useful for those with memory problems brought on by mental health conditions.
The advantages even extend beyond humans to the realm of machine learning, which is incredibly cumbersome in comparison to the effectiveness of the brain.  ,
How the brain processes memory in large quantities of information with only a small number of neurons is not well understood.
How, in contrast to ChatGPT, which uses hundreds of thousands of times more energy than the brain, can it accomplish such a formidable feat of memory and cognitive skills with such limited resources? ” Fernandez-Ruiz said.
This method of dividing up two crucial memory functions over time is what underlies the vast potential of biological brains to have such incredible memory capacities with relatively few resources.
” This opens a new window to train artificial neural networks to be more effective, perhaps by being more similar to how actual brains function.”
Co-authors include Annabella Wulf ‘ 24, Thokozile Nyasulu ‘ 24 and Madison Wolf ‘ 25.
Funding: The research was supported by the National Institutes of Health, the Sloan Foundation, the Whitehall Foundation, the Klingenstein-Simons Fellowship Program, and the Klarman Fellowships Program.
About this information on sleep and memory research
Author: David Nutt
Source: Cornell University
Contact: David Nutt – Cornell University
Image: The image is credited to Neuroscience News
Original Research: Closed access.
Azahara Oliva and colleagues ‘ paper,” Memory replay is organized by the sleep microstructure..” Nature
Abstract
Memory replay is organized by the sleep microstructure.
As a first step in their consolidation, newly acquired memories are first reactivated in the hippocampus while they sleep.
This process coincides with the hippocampal reactivation of previous memories, which raises the issue of how to prevent interference between older and recent, initially labile, memory traces.
According to theoretical research, combining multiple memories at the same time as minimizing interference can be accomplished by randomly interleaving their reactivation.
Alternately, a temporal microstructure of sleep might encourage the reactivation of various memory types in particular substrates.
We developed a method to simultaneously record large hippocampal ensembles and monitor sleep dynamics through pupillometry in naturally sleeping mice in order to test these two hypotheses.
Oscillatory pupil fluctuations revealed a previously unexplored microstructure of non-REM sleep-associated memory processes.
We discovered that sharp-wave ripples during contracted pupil substates of non-REM sleep predominately influenced memory replay of recent events, while replay of previous events was more prevalent during dilated pupil substrates.
The recall of recent memories was impacted by selective closed-loop disruption of sharp-wave ripples during contracted pupil non-REM sleep, whereas the same manipulation during dilated pupil substates had no behavioural impact.
The contracted pupil substate was characterized by stronger extrinsic excitatory inputs, whereas dilated pupil substrates were more prominently reliant on local inhibition recruitment.
Thus, the microstructure of non-REM sleep organizes memory replay, with previous versus new memories being temporally segregated in different substates and supported by local and input-driven mechanisms, respectively.
Our findings support the existence of multiple distinct cognitive processes in the brain that can be used together without interruption to support continuous learning.
