There is accumulating evidence that the entorhinal-hippocampal network is important for temporal memory. However, relatively little is known about the precise neurobiological mechanisms underlying memory for time. In particular, whether the lateral entorhinal cortex (LEC) is involved in temporal processing remains an open question. During high-resolution functional magnetic resonance imaging (fMRI) scanning, participants watched a ~28-min episode of a television show. During the test, they viewed still-frames and indicated on a continuous timeline the precise time each still-frame was viewed during the study. This procedure allowed us to measure error in seconds for each trial. We analyzed fMRI data from retrieval and found that high temporal precision was associated with increased blood-oxygen-level-dependent fMRI activity in the anterolateral entorhinal (a homolog of the LEC in rodents) and perirhinal cortices, but not in the posteromedial entorhinal and parahippocampal cortices. This suggests a previously unknown role for the LEC in processing of high-precision, minute-scale temporal memories.
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We thank M. Tsai, J. Noche and A. Chun for assistance with data collection. We also thank C. Stark, N. Fortin and D. Huffman for helpful discussions. This work was supported by US NIH grants nos. P50AG05146, R01MH1023921 and R01AG053555 (PI: M.A.Y.), and Training Grant no. T32DC010775 (to M.E.M., PI: Metherate).
Integrated supplementary information
A one-way repeated-measures ANOVA was conducted to determine whether performance differed as a function of each trial’s distance from a segment boundary at encoding (n = 19 participants). A segment boundary is defined as the beginning or end of a video segment at encoding (the episode was split into three segments). We conducted a one-way repeated-measures ANOVA comparing trials that were of short (2–107 seconds), medium (108–186 seconds) and long (200–277 seconds) distances from a segment boundary, which was not statistically significant [F(2,18)= 3.29, p = 0.0506], indicating that error does not differ significantly based on a trial’s distance from a segment boundary.
After scanning, participants viewed the still-frames one more time and were asked to indicate how vividly they could recall the scene associated with each one on a 5 point scale (n = 12 participants). High, medium, and low vividness trials were entered into a GLM. Paired t-tests were conducted on high and low vividness beta coefficients, and no significant results were found after correcting for multiple comparisons using the Bonferroni-Holm method in the alEC [t = 0.4983, df = 11, two-tailed p = 0.6281], pmEC [t = 1.947, df = 11, p = 0.0774], angular gyrus [t = 3.06, df = 11, p = 0.0109], MPFC [t = 2.956, df = 11, two-tailed p = 0.0131; critical p is 0.0083], PRC [t = 0.4744, df = 11, two-tailed = 0.6445], PHC [t = 1.976, df = 11, two-tailed p = 0.0738; critical p is 0.01], ACC [t = 0.5422, df = 11, two-tailed p = 0.5985], PCC [t = 0.1654, df = 11, two-tailed p = 0.8716], DGCA3 [t = 0.7672, df = 11, two-tailed p = 0.4591], CA1 [t = 0.6167, df = 11, two-tailed p = 0.549], precuneus [t = 0.3441, df = 11, two-tailed p = 0.7373], RSC [t = 0.703, df = 11, two-tailed p = 0.4967]).
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Nature Neuroscience (2019)