scholarly journals Toward understanding structure and function of neural circuits in the visual system

2017 ◽  
Vol 149 (6) ◽  
pp. 274-280 ◽  
Author(s):  
Masanari Onda ◽  
Fumitaka Osakada
Keyword(s):  
Visual System ◽  
Neural Circuits ◽  
Structure And Function ◽  
And Function

scholarly journals Inter-species comparison of the orientation algorithm directing larval chemotaxis in the genus Drosophila

2021 ◽  
Author(s):  
Elie Fink ◽  
Matthieu Louis
Keyword(s):  
Neural Circuits ◽  
Rapid Evolution ◽  
Structure And Function ◽  
Olfactory Behavior ◽  
Species Comparison ◽  
Closely Related Species ◽  
Genetic Studies ◽  
Phenotypic Differences ◽  
Peripheral Olfactory System ◽  
And Function

Animals differ in their appearances and behaviors. While many genetic studies have addressed the origins of phenotypic differences between fly species, we are still lacking a quantitative assessment of the variability in the way different fly species behave. We tackled this question in one of the most robust behaviors displayed by Drosophila: chemotaxis. At the larval stage, Drosophila melanogaster navigate odor gradients by combining four sensorimotor routines in a multilayered algorithm: a modulation of the overall locomotor speed and turn rate; a bias in turning during down-gradient motion; a bias in turning toward the gradient; the local curl of trajectories toward the gradient ("weathervaning"). Using high-resolution tracking and behavioral quantification, we characterized the olfactory behavior of eight closely related species of the Drosophila group in response to 19 ecologically-relevant odors. Significant changes are observed in the receptive field of each species, which is consistent with the rapid evolution of the peripheral olfactory system. Our results reveal substantial inter-species variability in the algorithms directing larval chemotaxis. While the basic sensorimotor routines are shared, their parametric arrangements can vary dramatically across species. The present analysis sets the stage for deciphering the evolutionary relationships between the structure and function of neural circuits directing orientation behaviors in Drosophila.

scholarly journals Individual differences as a window into the structure and function of the visual system

2017 ◽  
Vol 141 ◽  
pp. 1-3 ◽  
Author(s):  
Jenny M. Bosten ◽  
John D. Mollon ◽  
David H. Peterzell ◽  
Michael A. Webster
Keyword(s):  
Individual Differences ◽  
Visual System ◽  
Structure And Function ◽  
And Function

scholarly journals Long Term Temporal Changes in Structure and Function of Rat Visual System After Blast Exposure

2018 ◽  
Vol 59 (1) ◽  
pp. 349 ◽  
Author(s):  
Daniel F. Shedd ◽  
Nikolaus A. Benko ◽  
Justin Jones ◽  
Brian E. Zaugg ◽  
Robert L. Peiffer ◽  
...  
Keyword(s):  
Visual System ◽  
Temporal Changes ◽  
Structure And Function ◽  
Blast Exposure ◽  
And Function

scholarly journals Learning the architectural features that predict functional similarity of neural networks

2020 ◽  
Author(s):  
Adam Haber ◽  
Elad Schneidman
Keyword(s):  
Neural Networks ◽  
Architectural Design ◽  
Neural Circuits ◽  
High Accuracy ◽  
Structure And Function ◽  
Functional Similarity ◽  
Architectural Features ◽  
Wide Range ◽  
And Function ◽  
Sparse Set

ABSTRACTThe mapping of the wiring diagrams of neural circuits promises to allow us to link structure and function of neural networks. Current approaches to analyzing connectomes rely mainly on graph-theoretical tools, but these may downplay the complex nonlinear dynamics of single neurons and networks, and the way networks respond to their inputs. Here, we measure the functional similarity of simulated networks of neurons, by quantifying the similitude of their spiking patterns in response to the same stimuli. We find that common graph theory metrics convey little information about the similarity of networks’ responses. Instead, we learn a functional metric between networks based on their synaptic differences, and show that it accurately predicts the similarity of novel networks, for a wide range of stimuli. We then show that a sparse set of architectural features - the sum of synaptic inputs that each neuron receives and the sum of each neuron’s synaptic outputs - predicts the functional similarity of networks of up to 100 cells, with high accuracy. We thus suggest new architectural design principles that shape the function of neural networks, which conform with experimental evidence of homeostatic mechanisms.

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