Our brains change as we learn, according to researchers

Kevin Dural

Learning can result in the increase of how much information our brains can hold, researchers have found.

Researchers at UT-Austin, the Salk Institute for Biological Studies and the University of Otago in New Zealand discovered that the capacity of a synapse, the junctions between brain cells, expand in response to learning.

“Our most recent finding found that the range of a synapse is not fixed,” said Kristen Harris, a UT neuroscience professor. “On the other hand, if you buy a flash drive, the factory determined how much info you could store; it’s at a fixed level. Our brains are not like that.”

The team applied theoretical computational modeling and information theory, the study of how information is stored, to assess how much information can be contained within synapses. According to Harris, while some synapses experience quite a large expansion, others actually get smaller. The team simply expected synapses to grow larger due to learning; instead, the investigation revealed that balance remains as the capacity of some synapses shrink to allow for the expansion of others.

“These are all within the same region,” Harris said. “Interestingly, learning affects different regions of the brain differently.”

Harris said that not all parts of the brain have the same capacity, largely following differences in function. She highlighted the significance of the relationship between structure and function and said that the findings are consistent with ideas behind information theory, the universe and computers.

The function of a synapse can be excitatory or inhibitory, according to Harris. Represented in binary form, every “bit” can be represented as 0 or 1.

“You can have a whole bunch of zeros and ones to define what your computer can do,” she said. “The brain, even just in its content of synaptic size, behaves in a similar way.”

Instead of 0 or 1, the number of distinct states that each synapse can maintain jumps from two to 26 different states.

“This (represents) an explosion in computation,” Harris said. “Now, we have a huge amount of information that can be stored in the structure. The state of each molecule adds another whole level of complexity.”

Harris said that the team faced some challenges in the investigative process, such as difficulties in obtaining consistent data.

“At all stages, it takes years to collect and analyze data,” she said. “Years of effort in the beginning of the experiment included simply collecting the images.”

Harris added that the findings may prove to be significant in the subfields of memory and learning within the field of neuroscience.

“The conclusions from this paper give us a logical framework to assess how structure changes in response to learning and memory,” she said. “As well, this paper provides new insights into how new experiences can be stored in the brain while maintaining overall stability.”

Harris said she enjoys her research because there is a surprise every day.

“It’s really exciting to work out the pieces of the puzzle that is the brain,” she said. “It’s full of surprises; it’s never boring.”