Evidence map›Paper›PMID 39071325›Full record

ArticlebioRxiv : the preprint server for biology2024

Persistent activity during working memory maintenance predicts long-term memory formation in the human hippocampus.

Jonathan Daume, Jan Kamiński, Yousef Salimpour, William S Anderson, Taufik A Valiante, Adam N Mamelak, Ueli Rutishauser

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jonathan DaumeDepartment of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA.ORCID 0000-0002-6516-7288
Jan KamińskiCenter of Excellence for Neural Plasticity and Brain Disorders: BRAINCITY, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.
Yousef SalimpourDepartment of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States.
William S AndersonDepartment of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States.
Taufik A ValianteKrembil Research Institute, Toronto Ontario, Canada.ORCID 0000-0002-3443-3790
Adam N MamelakDepartment of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA.
Ueli RutishauserDepartment of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, CA.ORCID 0000-0002-9207-7069

Funding

Neuronal mechanisms of human episodic memoryU01NS117839 · NINDS · CEDARS-SINAI MEDICAL CENTER · PI MAMELAK, ADAM NATHANIEL, RUTISHAUSER, UELI · 2020 to 2024
$7.8M
NINDS NIH HHS U01 NS117839
6 · The paper itself

Abstract

Working Memory (WM) and Long-Term Memory (LTM) are often viewed as separate cognitive systems. Little is known about how these systems interact when forming memories. We recorded single neurons in the human medial temporal lobe while patients maintained novel items in WM and a subsequent recognition memory test for the same items. In the hippocampus but not the amygdala, the level of WM content-selective persist activity during WM maintenance was predictive of whether the item was later recognized with high confidence or forgotten. In contrast, visually evoked activity in the same cells was not predictive of LTM formation. During LTM retrieval, memory-selective neurons responded more strongly to familiar stimuli for which persistent activity was high while they were maintained in WM. Our study suggests that hippocampal persistent activity of the same cell supports both WM maintenance and LTM encoding, thereby revealing a common single-neuron component of these two memory systems.

Identifiers

PMID39071325
PMCPMC11275810

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.