Literature DB >> 31470252

Constraining computational models using electron microscopy wiring diagrams.

Ashok Litwin-Kumar1, Srinivas C Turaga2.   

Abstract

Numerous efforts to generate "connectomes," or synaptic wiring diagrams, of large neural circuits or entire nervous systems are currently underway. These efforts promise an abundance of data to guide theoretical models of neural computation and test their predictions. However, there is not yet a standard set of tools for incorporating the connectivity constraints that these datasets provide into the models typically studied in theoretical neuroscience. This article surveys recent approaches to building models with constrained wiring diagrams and the insights they have provided. It also describes challenges and the need for new techniques to scale these approaches to ever more complex datasets.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2019        PMID: 31470252     DOI: 10.1016/j.conb.2019.07.007

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  9 in total

1.  Connectomic features underlying diverse synaptic connection strengths and subcellular computation.

Authors:  Tony X Liu; Pasha A Davoudian; Kristyn M Lizbinski; James M Jeanne
Journal:  Curr Biol       Date:  2021-12-15       Impact factor: 10.834

2.  Structured sampling of olfactory input by the fly mushroom body.

Authors:  Zhihao Zheng; Feng Li; Corey Fisher; Iqbal J Ali; Nadiya Sharifi; Steven Calle-Schuler; Joseph Hsu; Najla Masoodpanah; Lucia Kmecova; Tom Kazimiers; Eric Perlman; Matthew Nichols; Peter H Li; Viren Jain; Davi D Bock
Journal:  Curr Biol       Date:  2022-07-06       Impact factor: 10.900

3.  Training Spiking Neural Networks in the Strong Coupling Regime.

Authors:  Christopher M Kim; Carson C Chow
Journal:  Neural Comput       Date:  2021-04-13       Impact factor: 3.278

4.  A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection.

Authors:  Brad K Hulse; Hannah Haberkern; Romain Franconville; Daniel Turner-Evans; Shin-Ya Takemura; Tanya Wolff; Marcella Noorman; Marisa Dreher; Chuntao Dan; Ruchi Parekh; Ann M Hermundstad; Gerald M Rubin; Vivek Jayaraman
Journal:  Elife       Date:  2021-10-26       Impact factor: 8.713

Review 5.  Theoretical principles for illuminating sensorimotor processing with brain-wide neuronal recordings.

Authors:  Tirthabir Biswas; William E Bishop; James E Fitzgerald
Journal:  Curr Opin Neurobiol       Date:  2020-11-25       Impact factor: 6.627

6.  In Silico: Where Next?

Authors:  Adrienne L Fairhall
Journal:  eNeuro       Date:  2021-04-30

7.  Synaptic counts approximate synaptic contact area in Drosophila.

Authors:  Christopher L Barnes; Daniel Bonnéry; Albert Cardona
Journal:  PLoS One       Date:  2022-04-04       Impact factor: 3.240

8.  Reinforcement Learning for Central Pattern Generation in Dynamical Recurrent Neural Networks.

Authors:  Jason A Yoder; Cooper B Anderson; Cehong Wang; Eduardo J Izquierdo
Journal:  Front Comput Neurosci       Date:  2022-04-08       Impact factor: 3.387

9.  Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior.

Authors:  Takuya Ito; Guangyu Robert Yang; Patryk Laurent; Douglas H Schultz; Michael W Cole
Journal:  Nat Commun       Date:  2022-02-03       Impact factor: 17.694

  9 in total

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