Scientists Discover Brain Network That Distinguishes Novelty From Familiarity

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Each morning, on your daily stroll to work, you migrate along the same streets, pass the same shops, smell the same aromas seeping out of the same cafes, and even habitually step on the same drain covers. But one day, you notice a new street sign, or perhaps a different gâteau amongst the usual delectable spread in a patisserie window. You’re immediately aware of its unfamiliarity, but how does your brain so readily distinguish between novel and known things? A newly discovered brain network may hold some answers.

Named the parietal memory network (PMN), this learning and memory system processes data differently depending on whether it’s novel or something we have experienced before. This helps us quickly distinguish between new and “old” items in our environment, such as faces or objects. The findings could have important implications for research into neurodegenerative diseases like Alzheimer’s, in which the ability of individuals to identify friends, family and even themselves can deteriorate.

As described in Trends in Cognitive Sciences, the newly identified network came to light after researchers from Washington University in St. Louis pooled and compared data from numerous brain-imaging studies, a statistical technique known as a meta-analysis. They were looking for brain areas that commonly lit up, indicating activity, during memory processing, but more specifically regions that seemed to be associated with successful memory retrieval.

This led to the discovery of a network of three distinct regions located within the parietal cortex of the left hemisphere. These areas – the prenucleus, the mid-cingulate cortex and the dorsal angular gyrus – all displayed consistent patterns of activity and quiescence during memory processing, spanning both the initial encoding of information and later retrieval.

Interestingly, the researchers discovered that during data processing, the PMN’s activity could be used to predict how the information is stored and thus its availability for subsequent retrieval. They found that when incoming information was familiar, the neurons within the network fired up, but when the stimulus was novel, activity dampened. So with increasing familiarity, there was a concomitant rise in activity.

But perhaps unexpectedly, the patterns of activity seemed to remain consistent, in spite of the task being performed. This meant that rather than becoming wildly excited during one particular type of task, but less so during another, the activity displayed actually reflected how its novelty or familiarity grasped our attention.

Alongside probing how the PMN’s behavior changed while a variety of different cognitive tasks were undertaken by participants, the scientists were also able to observe how the three different regions interacted with one another during rest periods, when no tests were being performed. This led the researchers to another interesting observation, which involved another system called the default mode network. Rather than displaying activity during particular tasks, the default mode network is most active while a person is at rest, like when we daydream.

While the regions of these two networks were found to be in close proximity to one another, and both displayed similar patterns of activity during rest, the observations so far seem to suggest that they are indeed distinct networks.

“A really cool feature of the PMN is that it seems to show its response patterns regardless of what you’re doing,” first author Adrian Gilmore said in a statement. “The PMN doesn’t seem to care what it is that you’re trying to do. It deactivates when we encounter something new, and activates when we encounter something that we’ve seen before. This makes it a really promising target for future research in areas such as education or Alzheimer’s research, where we want to foster or improve memory performance broadly, rather than focusing on specific tasks.” 

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