The current article provides the insight on format of working memory and how our memories are stored in brain. Here the ability of storing the information for a period of time is termed as “working memory”. In fact, working memory is a building block for our cognitive processes, and any dysfunction in working memory is at heart of neurologic and psychiatric symptoms such as schizophrenia.
A team of scientists discovered the formatting of working memory, as this finding will enhance the understandings on storage of visual memories. Clayton Curtis, a professor of psychology at New York University explained that

“Researchers have wondered the nature of neural representation that support our working memory”.

Scientists have used both analytical and experimental techniques to represent the working memory format in brain. Despite the importance of working memory, very little is known about how brain stores working memory representation. Curtis stated that

“We can predict the working memory content from brain activity patterns, what these patterns are coding for is impenetrable”.

Curtis and Yuna Kwak (a doctoral student at New York University) hypothesized that our brain not only discard the irrelevant features, but also re-code the task relevant features into working memory format that are distinct and efficient from the perceptual inputs. It’s been known since decades that human beings re-code the visual information about numbers and letters into sound based or phonological codes that are used for verbal working memory. For example, when we see phone number digits, we do not store the information in our mind until we finish dialing the complete number, or we store the sounds of number. This only show that we re-code the information, but it does not show how the brain format a working memory which was the focus of Neuron study.

Scientists measured the brain activity with magnetic resonance imaging to explore the brain formatting a working memory. A trial was performed on visual working memory related tasks. In each trial, a visual stimulus was presented to the participants for few seconds and participant had to remember it, and make a memory based judgement. There were two kinds of visual stimulus, one was tilted grating and the other was cloud of moving dots. The participant had to indicate the exact angle of dot clouds or exact angle of grating tilts after the memory delay.

It was observed that, despite the two different kinds of visual stimulation (dot motion and grating), the neural activity pattern in parietal and visual cortex (parts of brain used in memory storage and processing) were interchangeable during memory. Interestingly, the pattern trained to predict the grating orientation may also predict the motion direction, and vice versa to it. But these findings further prompted the question that, why those memory representations were interchangeable?

Curtis explained to this question that “only task relevant features of stimulus were extracted and re-coded into shared memory format and might take the line like shape to match whether the direction of dot motion or grating orientation”. This hypothesis led the scientists of New York University to turned into a novel approach of visualizing the brain activity pattern. The researchers projected the memory pattern onto a 2-D representation of visual space. This activity allowed the researchers to see in screen pattern of subjects, revealing a line like presentation of both grating and motion stimuli. Curtis further added that “we see the activity lines across topographic maps at angles corresponding to grating and motion direction”. Thus, the novel visualization approach offered opportunity to see how the working memory representation encoded in neural population. On the base of novel visualization approach, it was concluded that

“Visual memory of human being is flexible and it can be thought of what we see and drive by the behaviors”.

Reference: “Unveiling the abstract format of mnemonic representations” by Yuna Kwak and Clayton E. Curtis, 7 July 2022, Neuron.
DOI: 10.1016/j.neuron.2022.03.016