Evidence map›Paper›PMID 30131668›Full record

ArticleFrontiers in neuroscience2018

A Population-Based Model of the Temporal Memory in the Hippocampus.

Sorinel A Oprisan, Mona Buhusi, Catalin V Buhusi

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sorinel A OprisanDepartment of Physics and Astronomy, College of Charleston, Charleston, SC, United States.
Mona BuhusiInterdisciplinary Program in Neuroscience, Department of Psychology, Utah State University, Logan, UT, United States.
Catalin V BuhusiInterdisciplinary Program in Neuroscience, Department of Psychology, Utah State University, Logan, UT, United States.

Funding

South Carolina IDeA Networks of Biomedical Research (SC INBRE V)P20GM103499 · NIGMS · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI EDIE C GOLDSMITH · 2012 to 2026
$61.0M
Supplement for South Carolina BRIN - 1P20 RR16461P20RR016461 · NCRR · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · PI DOOLEY, R. LARRY · 2001 to 2011
$32.3M
REPRESENTATION OF TEMPORAL INFORMATIONR01MH073057 · NIMH · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BUHUSI, CATALIN V. · 2006 to 2009
$824k
INTERVAL TIMING IN MOUSE MODELS OF PARKINSONISMR15NS090283 · NINDS · UTAH STATE UNIVERSITY · PI BUHUSI, MONA · 2014 to 2014
$425k
NCRR NIH HHS P20 RR016461NIGMS NIH HHS P20 GM103499NIMH NIH HHS R01 MH073057NINDS NIH HHS R15 NS090283
6 · The paper itself

Abstract

Spatial and temporal dimensions are fundamental for orientation, adaptation, and survival of organisms. Hippocampus has been identified as the main neuroanatomical structure involved both in space and time perception and their internal representation. Dorsal hippocampus lesions showed a leftward shift (toward shorter durations) in peak-interval procedures, whereas ventral lesions shifted the peak time toward longer durations. We previously explained hippocampus lesion experimental findings by assuming a topological map model of the hippocampus with shorter durations memorized ventrally and longer durations more dorsal. Here we suggested a possible connection between the abstract topological maps model of the hippocampus that stored reinforcement times in a spatially ordered memory register and the "time cells" of the hippocampus. In this new model, the time cells provide a uniformly distributed time basis that covers the entire to-be-learned temporal duration. We hypothesized that the topological map of the hippocampus stores the weights that reflect the contribution of each time cell to the average temporal field that determines the behavioral response. The temporal distance between the to-be-learned criterion time and the time of the peak activity of each time cell provides the error signal that determines the corresponding weight correction. Long-term potentiation/depression could enhance/weaken the weights associated to the time cells that peak closer/farther to the criterion time. A coincidence detector mechanism, possibly under the control of the dopaminergic system, could be involved in our suggested error minimization and learning algorithm.

Indexed as

computer simulationshippocampusneural networksscale invariancetime cellstopological map

Identifiers

PMID30131668
PMCPMC6090536

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.