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Top: Simulink <t>(MATLAB)</t> implementation of the physiologically-inspired model in . The bar speed (90° s –1 ) is integrated over a quite narrow time window (~200 ms) and the integration starts with a spatial offset with respect to the visual midline (~11°). This means that T3 neurons might encode the bar speed and a downstream partner might integrate this information over a selective amount of time, encoding the bar position and triggering a saccade when the amount of calcium reaches a specific threshold. In this model, saccade amplitudes are considered a fixed parameter (30°) but in an alternative version they could be easily tuned to the bar speed. Bottom: simulation of the fly behavior (angular position) in a bar tracking task according to the control model.
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Top: Simulink <t>(MATLAB)</t> implementation of the physiologically-inspired model in . The bar speed (90° s –1 ) is integrated over a quite narrow time window (~200 ms) and the integration starts with a spatial offset with respect to the visual midline (~11°). This means that T3 neurons might encode the bar speed and a downstream partner might integrate this information over a selective amount of time, encoding the bar position and triggering a saccade when the amount of calcium reaches a specific threshold. In this model, saccade amplitudes are considered a fixed parameter (30°) but in an alternative version they could be easily tuned to the bar speed. Bottom: simulation of the fly behavior (angular position) in a bar tracking task according to the control model.
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Image Search Results


Top: Simulink (MATLAB) implementation of the physiologically-inspired model in . The bar speed (90° s –1 ) is integrated over a quite narrow time window (~200 ms) and the integration starts with a spatial offset with respect to the visual midline (~11°). This means that T3 neurons might encode the bar speed and a downstream partner might integrate this information over a selective amount of time, encoding the bar position and triggering a saccade when the amount of calcium reaches a specific threshold. In this model, saccade amplitudes are considered a fixed parameter (30°) but in an alternative version they could be easily tuned to the bar speed. Bottom: simulation of the fly behavior (angular position) in a bar tracking task according to the control model.

Journal: eLife

Article Title: Columnar neurons support saccadic bar tracking in Drosophila

doi: 10.7554/eLife.83656

Figure Lengend Snippet: Top: Simulink (MATLAB) implementation of the physiologically-inspired model in . The bar speed (90° s –1 ) is integrated over a quite narrow time window (~200 ms) and the integration starts with a spatial offset with respect to the visual midline (~11°). This means that T3 neurons might encode the bar speed and a downstream partner might integrate this information over a selective amount of time, encoding the bar position and triggering a saccade when the amount of calcium reaches a specific threshold. In this model, saccade amplitudes are considered a fixed parameter (30°) but in an alternative version they could be easily tuned to the bar speed. Bottom: simulation of the fly behavior (angular position) in a bar tracking task according to the control model.

Article Snippet: Both stimuli were generated, as mentioned above, using custom-written MATLAB code and randomly chosen during each trial among 96 different patterns.

Techniques: Control