Evidence map›Paper›PMID 32278058›Full record

ReviewNeuroscience2021

The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation.

Michael E Hasselmo, Andrew S Alexander, Alec Hoyland, Jennifer C Robinson, Marianne J Bezaire, G William Chapman, Ausra Saudargiene, Lucas C Carstensen, Holger Dannenberg

Abstract readReview
In one paragraph

Review in Neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. 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

9 authors at 1 institution in 1 country.

Michael E HasselmoCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States. Electronic address: hasselmo@bu.edu.
Andrew S AlexanderCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
Alec HoylandCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
Jennifer C RobinsonCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
Marianne J BezaireCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
G William ChapmanCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
Ausra SaudargieneCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
Lucas C CarstensenCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
Holger DannenbergCenter for Systems Neuroscience, Department of Psychological and Brain Sciences, Boston University, 610 Commonwealth Ave., Boston, MA 02215, United States.
Boston University · US

Funding

NEUROMODULATION AND CORTICAL MEMORY FUNCTIONR01MH060013 · NIMH · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI HASSELMO, MICHAEL E · 2000 to 2019
$6.8M
COMPARATIVE COGNITION AND HIPPOCAMPAL FUNCTIONR01MH052090 · NIMH · STATE UNIVERSITY NEW YORK STONY BROOK · PI HASSELMO, MICHAEL E · 1994 to 2020
$6.4M
Mechanisms of Entorhinal Cortex FunctionR01MH061492 · NIMH · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI HASSELMO, MICHAEL E · 2000 to 2017
$5.0M
Egocentric and Allocentric Spatial Coding in CortexR01MH120073 · NIMH · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI HASSELMO, MICHAEL E · 2019 to 2023
$2.5M
NIMH NIH HHS R01 MH052090NIMH NIH HHS R01 MH060013NIMH NIH HHS R01 MH061492NIMH NIH HHS R01 MH120073
6 · The paper itself

Abstract

The space of possible neural models is enormous and under-explored. Single cell computational neuroscience models account for a range of dynamical properties of membrane potential, but typically do not address network function. In contrast, most models focused on network function address the dimensions of excitatory weight matrices and firing thresholds without addressing the complexities of metabotropic receptor effects on intrinsic properties. There are many under-explored dimensions of neural parameter space, and the field needs a framework for representing what has been explored and what has not. Possible frameworks include maps of parameter spaces, or efforts to categorize the fundamental elements and molecules of neural circuit function. Here we review dimensions that are under-explored in network models that include the metabotropic modulation of synaptic plasticity and presynaptic inhibition, spike frequency adaptation due to calcium-dependent potassium currents, and afterdepolarization due to calcium-sensitive non-specific cation currents and hyperpolarization activated cation currents. Neuroscience research should more effectively explore possible functional models incorporating under-explored dimensions of neural function.

Indexed as

Models, NeurologicalNeuronal PlasticityAction PotentialsMembrane Potentialsacetylcholinebiophysical simulationscomputational neurosciencedopamineneuromodulationpresynaptic inhibition

Identifiers

PMID32278058
PMCPMC7541517
OpenAlexW3015677622

What OpenQuestion holds

Textmetadata
LicenceTDM
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.