When did you last walk down memory lane? How memories are organized in time
By monitoring rats during an odor memory task, scientists are beginning to understand the mechanism that allows the brain to organize memories in time and subsequently inform decision making.
In a collaborative study, Norbert Fortin’s University of California, Irvine (UCI; CA, USA) team combined neurobiology with machine learning in the analysis of the neural patterns of rats performing a sequence memory task. The study elucidates how the hippocampus organizes memories into chronological sequence and how this informs subsequent decision making. By improving our understanding of how memories are encoded it lays the groundwork for understanding how memory failure may occur in Alzheimer’s disease or dementia.
The hippocampus is pivotal to the storing, temporal organization, and informing of our behavior from our memories. Whilst it is understood that the hippocampus is responsible, the question of how the hippocampus carries out these memory related mechanisms still remains.
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“Our brain keeps a pretty good record of when specific experiences or events occur. This ability helps us function in our daily life, but before this study, we didn’t have a clear idea of the neuronal mechanisms behind these processes,” described Fortin. “Where it connects with everybody is that this type of memory is strongly impaired in a variety of neurological disorders or simply with aging, so we really need to know how this brain function works.”
In Fortin’s study, rats were subjected to an odor memory task in which five distinct odors were presented to the rat in differing orders. The team used electrodes to analyze the neurons firing during the test as the rats attempted to memorize the correct sequence. The neural activity was measured at millisecond intervals during the task to visualize the dynamic changes as the brain processed the stimuli and encoded memories of the different odors.
Due to the large quantity of data generated, the team collaborated with Babak Shahbaba at UCI Donald Bren School of Information & Computer Sciences, using statistical machine learning analysis to process the results.
When neurons encode memories the signature pattern of spiking neural activity can be recorded. The unique neural patterns caused by processing information of each odor can then be used to determine which odor the rats are thinking about at each interval.
“We found that we could treat these neural patterns as images, and this unlocked our ability to apply deep machine learning methods,” Shahbaba explained. “We analyzed the data with a convolutional neural network, which is a methodology used frequently in image processing applications such as facial recognition.”
“We know what the signature for odor B looks like, just as we know the ones for A, C and D,” Fortin added. “Because of that, you can see when those signatures reappear at a different moment in time, such as when our subjects are anticipating something that has yet to happen. We’re seeing these signatures being quickly replayed as they’re thinking about the future.”
From their analysis, Fortin’s group determined that hippocampal neural patterns provide significant temporal coding within different stimuli sequences, allow for distinction of the different stimuli sequentially within events, and exhibit theta wave-associated reactivation of the chronological relationships between events. Collectively, these results strongly imply that the hippocampus is characterized by the encoding and preserving of memories, and the predicting of event sequences.
Fortin hopes to apply the techniques utilized in the study to investigate the function of different regions of the brain to uncover the big picture of the involved processes.
