Evidence map›Paper›PMID 24376415›Full record

ArticleFrontiers in computational neuroscience2013

Does the entorhinal cortex use the Fourier transform?

Jeff Orchard, Hao Yang, Xiang Ji

Open access · goldAbstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

8 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. A computational model for grid maps in neural populations.Journal of computational neuroscience · 2020
    Article
  3. Article
  4. Article
  5. Review
  6. Controlling phase noise in oscillatory interference models of grid cell firing.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2014
    Article
  7. A hybrid oscillatory interference/continuous attractor network model of grid cell firing.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2014
    Article
  8. Entrainment is sparse.Frontiers in human neuroscience · 2014
    Article
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 at 1 institution in 1 country.

Jeff OrchardCentre for Theoretical Neuroscience, University of Waterloo Waterloo, ON, Canada ; David R. Cheriton School of Computer Science, University of Waterloo Waterloo, ON, Canada.
Hao YangDavid R. Cheriton School of Computer Science, University of Waterloo Waterloo, ON, Canada.
Xiang JiCentre for Theoretical Neuroscience, University of Waterloo Waterloo, ON, Canada ; David R. Cheriton School of Computer Science, University of Waterloo Waterloo, ON, Canada.
University of Waterloo · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Some neurons in the entorhinal cortex (EC) fire bursts when the animal occupies locations organized in a hexagonal grid pattern in their spatial environment. Place cells have also been observed, firing bursts only when the animal occupies a particular region of the environment. Both of these types of cells exhibit theta-cycle modulation, firing bursts in the 4-12 Hz range. Grid cells fire bursts of action potentials that precess with respect to the theta cycle, a phenomenon dubbed "theta precession." Various models have been proposed to explain these phenomena, and how they relate to navigation. Among the most promising are the oscillator interference models. The bank-of-oscillators model proposed by Welday et al. (2011) exhibits all these features. However, their simulations are based on theoretical oscillators, and not implemented entirely with spiking neurons. We extend their work in a number of ways. First, we place the oscillators in a frequency domain and reformulate the model in terms of Fourier theory. Second, this perspective suggests a division of labor for implementing spatial maps: position vs. map layout. The animal's position is encoded in the phases of the oscillators, while the spatial map shape is encoded implicitly in the weights of the connections between the oscillators and the read-out nodes. Third, it reveals that the oscillator phases all need to conform to a linear relationship across the frequency domain. Fourth, we implement a partial model of the EC using spiking leaky integrate-and-fire (LIF) neurons. Fifth, we devise new coupling mechanisms, enlightened by the global phase constraint, and show they are capable of keeping spiking neural oscillators in consistent formation. Our model demonstrates place cells, grid cells, and phase precession. The Fourier model also gives direction for future investigations, such as integrating sensory feedback to combat drift, or explaining why grid cells exist at all.

Indexed as

entorhinal cortexfourier transformgrid cellsneural engineering frameworkoscillatorspath integrationphase precessionplace cells

Identifiers

PMID24376415
PMCPMC3858727
OpenAlexW2013702864

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.