Here comes the flood: Functional memory insights

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  • Published: Jul 1, 2014
  • Author: David Bradley
  • Channels: MRI Spectroscopy
thumbnail image: Here comes the flood: Functional memory insights

Memorable familiarity

Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory

Many people are familiar with how a simple trigger, a scent, a familiar face, a colour, a piece of music, a photograph can bring back a "flood" of disparate memories all at once. There are mathematical theories called global similarity models that attempt to explain this phenomenon. Now, a functional magnetic resonance study (fMRI) on memory and categorization has put this mathematical model on a firm neurobiological footing for the first time.

The fMRI results show that the mathematics correctly explains processing in the medial temporal lobes, a region of the brain associated with long-term memory that is disrupted by memory disorders like Alzheimer’s disease.

Counterintuitive memory

Psychologist Tyler Davis of Texas Tech's Neuroimaging Institute is a specialist in neurobiological approaches to learning and memory, he and his colleagues are delving into global similarity models of memory. One might assume that when you see a familiar face or visit a favourite restaurant that only the most similar or recent memories are activated for comparison. Global similarity models, the feeling of familiarity for a particular stimulus suggests that we pull in a range of memories all at once.

"Since at least the 1980s, scientists researching memory have believed that when a person finds someone's face or a new experience familiar, that person is not simply retrieving a memory of only this previous experience, but memories of many other related and unrelated experiences as well," Davis explains. "Formal mathematical theories of memory called global similarity models suggest that when we judge familiarity, we match an experience, such as a face or a trip to a restaurant, to all of the memories that we have stored in our brains. Our recent work using fMRI suggests these models are correct."

A particular stimulus, the taste of peppered steak at that restaurant also activates memories not only of previous trips to the same eatery, but also recalls the décor, the experience of the same meal a different establishment or even at home and perhaps entirely tangential memories, all at once. "In terms of global similarity theories and our new findings, the important thing is when you are judging familiarity, your brain doesn't just retrieve the most relevant memories but many other memories as well," Davis adds. "This seems counterintuitive to how memory feels. We often feel like we are just retrieving that previous trip to that one particular restaurant when we are asked whether we'd been there before, but there is a lot of behavioural evidence that we activate many other memories as well when we judge familiarity."

This does not mean that every memory we have stored contributes to familiarity in the same way. The more closely related a previous memory is to the current experience, the more it will contribute to how we judge it as familiar or otherwise. In terms of the peppered steak example, Davis explains that previous trips to the restaurant are going to impact the familiarity more than dissimilar memories, such as the recent trip out of town. However, similarity from these other less-related experiences can have a measurable effect in judgements of familiarity.

Memory patterns

The focus of the current fMRI studies was on the activation patterns of the medial temporal lobes. "We found that peoples' memory for the items in our experiments was related to their activation patterns in the medial temporal lobes in a manner that was anticipated by mathematical global similarity models," Davis explains. "The more similar the activation pattern for an item was to all of the other activation patterns, the more strongly people remembered it. This is consistent with global similarity models, which suggest that the items that are most similar to all other items stored in memory will be most familiar."

The implications of this work are that there may be a neurobiological basis for the mathematical models of memory. As such, this, in turn, may have implications for understanding memory problems that occur in a diverse range of patients, whether those with severe head injury or Alzheimer's disease or other forms of dementia.

Davis told SpectroscopyNOW that, "Our overarching goal is to reveal the computational algorithm the human brain uses to create and retrieve memories. To do this, we need to continually build stronger bridges between mathematical theories of memory and neurobiological measurement and data analysis." He points out that one of the biggest obstacles in relating mathematical models of memory and categorization to the brain is that the features contained in memories in the mathematical models are often assumed to be known. In terms of activation patterns, there is likely to be a lot of different information - not just about the features of memories - that contribute to these neural similarity measures.

"The next big question that we are tackling is how to better measure the contents of neural activation patterns so that we have a better understanding of how the specific features of memories we have stored in the brain are influencing our memory judgements," he adds. "For example, do the activation patterns that we are measuring mainly contain information about the overlap in meaning between words that participants are viewing? Do they also contain information about how particular words were encountered in the same context (e.g., during the same scan)? To discover the specific algorithm the brain uses to create and retrieve memories, we will need answers to these questions and many more."

Davis' colleagues include Gui Xue of the National Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research at Beijing Normal University; Bradley Love of University College London; and Alison Preston and Russell Poldrack of The University of Texas at Austin.

Related Links

J Neurosci, 2014, 34(22): 7472-7484: "Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory"

Article by David Bradley

The views represented in this article are solely those of the author and do not necessarily represent those of John Wiley and Sons, Ltd.

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