Evidence map›Paper›PMID 1504242›Full record

ArticleBiophysical journal1992

Significance of glomerular compartmentalization for olfactory coding.

D Schild, H Riedel

Abstract read
In one paragraph

Article in Biophysical journal, 1992. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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

2 authors.

D SchildPhysiologisches Institut, Universität Göttingen, Germany.
H Riedel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper deals with the dendritic signal processing by mitral cells in the olfactory bulb and its meaning for olfactory coding. The output signals of olfactory receptor neurones are sent to the olfactory bulb where they converge onto the secondary neurones, the mitral cells. On a short time scale, the connectivity between receptor and mitral cells can be assumed to be constant, whereas on a longer time scale, when considering the ongoing de- and regeneration, it is necessary to model the synaptical weights between receptor and mitral cells as variables. In a first approach we used Hebb's rule to this end and presumed that a mitral cell can be represented by one compartment only. In this case, and with a sequence of realistically modeled receptor activity signals, the synaptical weights of all mitral cells converged to the same point though every mitral cell had initial weights different from those of any other mitral cell. This means that a mitral cell, when modeled as one compartment, does not become sensitive to any particular odor quality. A similar lack of quality tuning turned out to occur when one-compartment mitral cells were connected among each other by laterally inhibiting interneurones. We therefore took into account the glomerular fine structure of mitral cell dendrites, assuming electrotonically decoupled dendritic subbranches. This feature together with local inhibitory circuitry at the subbranches led to a fundamentally different type of synaptical convergence pattern. In this case, mitral cells developed differential sensitivities for different odors. Mitral cells have thus to be regarded as multicompartment cells, and local, non-Hebbian learning rules for their afferent synapses are necessary to achieve a reasonable map of odors upon mitral cell activities.

Indexed as

Models, NeurologicalAnimalsDendritesMathematicsNeuronsOlfactory BulbSensory Receptor CellsSignal TransductionSmellSynapses

Identifiers

PMID1504242
PMCPMC1260288

What OpenQuestion holds

Textmetadata
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.