Time cells in the human hippocampus and entorhinal cortex support episodic memory

Umbach, Gray; Kantak, Pranish A.; Jacobs, Joshua; Kahana, Michael J.; Pfeiffer, Brad E.; Sperling, Michael R.; Lega, Bradley

doi:10.1073/pnas.2013250117

Cited by 157 publications

(171 citation statements)

References 71 publications

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“…The observed temporal coding in the PM network parallels the firing of hippocampal neurons in rodents 47 and so-called “time cells” in humans 48 , 49 . These neurons show selective increases in firing at specific temporal positions, providing a basis for sequence learning and recall.…”

Section: Discussionmentioning

confidence: 57%

Distinct cortical systems reinstate the content and context of episodic memories

et al. 2021

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Episodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. Evidence from functional neuroimaging and invasive recordings in humans suggest that reinstatement organizes our memories by time or content, yet the neural systems involved in reinstating these unique types of information remain unclear. Here, combining computational modeling and intracranial recordings from 69 epilepsy patients, we show that two cortical systems uniquely reinstate the semantic content and temporal context of previously studied items during free recall. Examining either the posterior medial or anterior temporal networks, we find that forward encoding models trained on the brain’s response to the temporal and semantic attributes of items can predict the serial position and semantic category of unseen items. During memory recall, these models uniquely link reinstatement of temporal context and semantic content to these posterior and anterior networks, respectively. These findings demonstrate how specialized cortical systems enable the human brain to target specific memories.

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Section: Discussionmentioning

confidence: 57%

Distinct cortical systems reinstate the content and context of episodic memories

et al. 2021

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“…By emphasizing the importance of sensory content in time perception, our approach may provide a link between time perception and episodic memory that has been lost by content-free "clock" approaches. By providing a simple algorithm for how the stream of basic sensory processing is segmented into salient events, our approach may afford some insight into how low-level sensory information is transformed into the temporally sequenced form of memory associated with the activity of so-called "time cells" (44)(45)(46), linking the content of basic sensory processing with temporal properties of episodic memory within the powerful predictive coding approach (20,37,47).…”

Section: "Surprise" Time Perception and Episodic Memorymentioning

confidence: 99%

Trial-by-trial predictions of subjective time from human brain activity

Sherman

Fountas

Seth

et al. 2020

Preprint

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Author ContributionsWR conceived of the study. MTS and WR designed and pre-registered the experiments and analyses. MTS collected, analyzed, and constructed models of human behavioral and neuroimaging data. ZF constructed the artificial network model and analyzed the data. MTS and WR wrote the manuscript. AKS and ZF provided critical revisions on the manuscript. AbstractHuman experience of time exhibits systematic, context-dependent deviations from objective clock time. For example, time is experienced differently at work than on holiday. The cognitive and neural bases of how time perception interacts with the content of experience remain unclear, and leading explanations of human time perception are not equipped to explain this interaction. We propose an alternative account of human time perception, based on the dynamics of sensory processing. Our approach naturally links content of experience with time perception through a common foundation in basic sensory processing. We provide evidence for this proposal in model-based analyses of the dynamics of perceptual processing in an artificial neural network and in the activity of human sensory cortex. Healthy human participants watched naturalistic, silent videos and estimated their duration while fMRI was acquired. The same videos were used as stimuli for the artificial network.We constructed a computational model that predicted video durations from salient events in the activity of the artificial network, or in participants' visual cortex. The artificial network model reproduced human-like duration estimates, including biases in estimation depending on the content of a given video. Most importantly, the model based on human visual cortex activity reproduced trial-by-trial biases in our human participants' subjective reports, whereas control models trained on auditory or somatosensory activity did not. Together, our results reveal that human subjective time is based on information arising during the processing of our dynamic sensory environment, providing a computational basis for an end-to-end account of time perception. Significance StatementOur perception of time depends on the contents of experience, reflected in expressions such as "a watched pot never boils". Prevailing accounts of human time perception cannot provide good explanations for this. We tested a new explanation: time perception arises from the processing of our dynamic sensory environment. Supporting this theory, human participants' duration reports of silent videos correlated with estimates we reconstructed from activity in the visual cortex of their brain while they watched those videos. This was not a brain-wide phenomenon; reconstructions based on other brain regions did not correlate with subjective reports of duration. Our results validate our new theory, linking content of experience and perception of time through a common foundation in basic sensory processing.

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“…What is more interesting and still lacking, to our knowledge, is again a quantitative study of the degree of randomness of the recall process, in the context of remembering lists for example—a study made inherently difficult by the need to use novel items in a within subjects design. The same need effectively prevents the analysis of the recalled string at the single neuron level: even when recording the activity of neurons in awake patients, only generic forms of selectivity can be reliably studied, e.g., that expressed by putative “time” cells [ 47 ]. Interestingly such a study has been recently carried out in rats, pointing at the random walk character of the spatial trajectories they recall shortly after experiencing them [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

Latching dynamics as a basis for short-term recall

et al. 2021

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We discuss simple models for the transient storage in short-term memory of cortical patterns of activity, all based on the notion that their recall exploits the natural tendency of the cortex to hop from state to state—latching dynamics. We show that in one such model, and in simple spatial memory tasks we have given to human subjects, short-term memory can be limited to similar low capacity by interference effects, in tasks terminated by errors, and can exhibit similar sublinear scaling, when errors are overlooked. The same mechanism can drive serial recall if combined with weak order-encoding plasticity. Finally, even when storing randomly correlated patterns of activity the network demonstrates correlation-driven latching waves, which are reflected at the outer extremes of pattern space.

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Time cells in the human hippocampus and entorhinal cortex support episodic memory

Cited by 157 publications

References 71 publications

Distinct cortical systems reinstate the content and context of episodic memories

Distinct cortical systems reinstate the content and context of episodic memories

Trial-by-trial predictions of subjective time from human brain activity

Latching dynamics as a basis for short-term recall

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