Poster No:
845
Submission Type:
Abstract Submission
Authors:
Xuhao Shao1, Bi Zhu1
Institutions:
1Beijing Normal University, Beijing, China
First Author:
Xuhao Shao
Beijing Normal University
Beijing, China
Co-Author:
Bi Zhu
Beijing Normal University
Beijing, China
Introduction:
Previous studies have shown that inter-subject neural pattern similarity supports shared memories of movies across individuals (Chen et al., 2017; Lee et al., 2022). However, it was unclear whether eyewitnesses' shared neural representations of event details (e.g., where did the thief hide?). To investigate shared neural representations of event details by eyewitnesses, the present study used fMRI to obtain functional brain imaging data from individuals who witnessed the same event but with different details, as well as their subsequent free recall. We then compared the difference in shared neural signals between individuals who saw the same details versus those who saw different details.
Methods:
This study recruited 43 healthy college students (mean age: 22 years; 27 females and 16 males). Inside the fMRI scanner, subjects viewed 400 images of the 8 events. These images were design by the authors and have been reported in previous studies (Shao et al., 2023). Each event contained 12 critical images and 38 control images. Two versions of each critical image were presented counterbalanced across subjects. For example, in a critical image, about half of the subjects saw version a of the image showing the thief hiding behind a lamppost, while the other half saw version b of the image showing the thief hiding behind a tree. After a 10-minute break, subjects were given 3 minutes to recall of each of the 8 events by verbal report inside the fMRI scanner. To assess the recall of each of the 96 critical images, raters scored them based on whether they could accurately recall critical details (e.g., "the thief hid behind a lamppost"). With respect to the corresponding image, the "same version" inter-subject correlation indicates the similarity between subjects who saw an image with the same details, while the "different version" inter-subject correlation indicates the similarity between subjects who saw an image with different details. As a baseline, we also calculated their similarity in terms of non-corresponding images (i.e., the similarity between an image seen by one subject and the other 49 non-corresponding images in the same event seen by another subject). Item-specific similarity was indicated by a greater similarity of corresponding items compared to the average similarity of non-corresponding items in the same event. To compute shared neural representations of critical details at encoding, we computed item-specific neural pattern similarity between subjects who saw the same version and then compared it to subjects who saw different versions. To compute shared neural representations of critical details at recall, we analyzed the item-specific neural representations of critical details shared by subjects on critical images that were recalled.
Results:
At encoding, item-specific neural pattern similarity in visual cortex was greater between subjects who saw the same version than between subjects who saw different versions. At recall, item-specific neural pattern similarity in multiple brain regions (e.g., posterior medial cortex) existed not only between subjects who saw the same version, but also between subjects who saw different version. However, there was no difference in item-specific neural pattern similarity at recall between subjects who saw the same version and those who saw different versions.
Conclusions:
We found that neural representations of event details are shared between individuals during encoding but not during recall. At the time of eyewitness observation of an event, visual cortex may be involved in encoding details of the event, and its neural signals for event encoding are shared between individuals. At the time of recall, however, an individual's recollection of event details may be individualized. Future studies need to collect recall data over multiple time periods to examine the role of shared neural representations of event details as a predictor of long-term memory.
Learning and Memory:
Long-Term Memory (Episodic and Semantic) 1
Modeling and Analysis Methods:
Multivariate Approaches 2
Keywords:
FUNCTIONAL MRI
Learning
Memory
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Other
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Healthy subjects
Was this research conducted in the United States?
No
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Yes
Were any animal research approved by the relevant IACUC or other animal research panel?
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Not applicable
Please indicate which methods were used in your research:
Functional MRI
Behavior
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
AFNI
SPM
FSL
Free Surfer
Provide references using APA citation style.
Chen, J., Leong, Y. C., Honey, C. J., Yong, C. H., Norman, K. A., & Hasson, U. (2017). Shared memories reveal shared structure in neural activity across individuals. Nature Neuroscience, 20(1), 115–125.
Lee, H., & Chen, J. (2022). Predicting memory from the network structure of naturalistic events. Nature Communications, 13(1), 4235.
Shao, X., Li, A., Chen, C., Loftus, E. F., & Zhu, B. (2023). Cross-stage neural pattern similarity in the hippocampus predicts false memory derived from post-event inaccurate information. Nature Communications, 14(1), 2299.
No