The small red dots are the obstructive nerve cells inside the hippocampus of the brain. The pathogenetic tool, shown in green, allows researchers to measure the strength of messages to other nerve cells, using the light of light. Credit: Matt Udakis
In the years to come, personal memories of COVID-19 Unlike other memories of 2020, the epidemic is likely to spread in our brains with precision and clarity. What makes this process possible has kept scientists away for decades, but through research University of Bristol Have made progress in understanding how memories can be so different and lasting longer without messing up memories.
Study published in Nature Communications, Describes a newly discovered method of learning in the brain shown to stabilize memories and reduce interference between them. Its findings provide a new insight into how humans form expectations and accurately predict what may happen in the future.
Memories are formed when the connections between nerve cells become stronger when the brain sends and receives signals. This process has long been associated with changes in connections that stimulate neighboring nerve cells in the hippocampus, in this area of the brain crucial for memory formation.
These stimulatory connections must be balanced with inhibitory connections for healthy brain function, which crowd the nerve cell activity. The role of mutations in the power of inhibitory attachments has not been considered before, and researchers have found that inhibitory attachments between neurons, known as neurons, can be strengthened in the same way.
Working with computational neuroscientists at Imperial College London, The researchers showed how this allows memory representations to be stabilized.
Their findings reveal for the first time how two different types of inhibitory connections (from neurons featuring paravalbumin and somatostatin) can also increase their potency as stimulatory connections. Moreover, computational modeling demonstrated that this inhibitory learning enables hippocampus to stabilize changes in the power of stimulatory attachment, which prevents information from interfering with memory.
School Phys Physiology, Research Associate of Pharmacology and Neuroscience, first author Dr. Matt. Matt Udakis said: “We were all really excited when we discovered that all of these types of inhibitory neurons could change their connections and participate in learning.
“It provides an explanation for what we all know to be true; That memories do not disappear when we experience a new experience. These new findings will help us understand why.
“Computer modeling gives us an important new insight into how obstructive study memory does not become stable and susceptible to interference over time. This is really important because previously it was not clear how different memories can be accurate and strong. “
The research was funded by the UKRI’s Biotechnology and Biological Science Research Council, which has further funded teams to develop this research and tested their predictions from these findings measuring the stability of memory representations.
“Memories form the basis of our expectations about future events and enable us to make more accurate predictions,” said Jack Mellor, a senior author and professor of neuroscience at the Center for Synthetic Plastics. What the brain constantly does is match our expectations to reality, find out where the mismatch is found, and use this information to determine what we need to learn.
“We believe that what we have discovered plays a crucial role in predicting how accurate our predictions are and so important new information is. In the current environment, our ability to manage our expectations and make accurate predictions has never been more important.
“This is an excellent example of how research on the interface of two different disciplines delivers exciting science with new insights. Memory researchers at Bristol Neuroscience are one of the largest communities of memory-focused research in the UK, with a wide range of skills and approaches. It was a great opportunity to work together and start answering these big questions, which neuroscientists have been grappling with for decades and have far-reaching implications. ”
References: Matt Udakis, Victor Pedrosa, Sophie EL Chamberlain, Claudia Clopeth and Jack R. September 2, 2020 by Mellor, “CA1 Pyramidal Neurons Shapes Interneuron-Specific Plasticity in Paravalbumin and Somatostatin Inhibitory Synapses at Hippocampal Outputs” Nature Communications.
DOI: 10.1038 / s41467-020-18074-8
