Solved by a verified expert:Series of short response questions pertaining to visual fields.Question #1: Explain in your own words why these simple cells give larger responses when the bars are parallel to the axis of elongation than when they are perpendicular to them.Question #2: Explain in your own words why the receptive fields of LGN cells are not selective for the orientation of a stimulus.Question #3: Diagram a possible circuit where inputs from the LGN can be summed together to yield a cortical receptive field with elongated receptive fields.Question #4: Do you feel it is easier or more difficult to map the receptive field when the cell has a spontaneous rate higher than zero? What did you notice was different? Explain your answer in your own words.Question #5: Explain in your own words why the spatial frequency tuning curve assumes an inverted ‘U’ shape. In other words, why is it that the responses are low at both low and high spatial frequencies, and why is there is an intermediate spatial frequency that is optimal? Make and save a copy of your spatial tuning curve with a caption as part of your answer.Go back to the receptive_field window. In the ‘Spatial Frequency’ field on the left side of the window type the optimal spatial frequency of your cell. In this example only, the optimal spatial frequency is about 2.5. Your optimal spatial frequency may differ.Question #6: Run a simulation with the parameters set at the cell’s optimal orientation and optimal spatial frequency. Listen to the temporal pattern of the spikes. Explain in your own words why the cell fires in little ‘bursts’ with pauses in between.Question #7: Which curve is better tuned, the curve measured at a lower threshold or the curve measured at a higher threshold? That is, which curve shows a response for a smaller range of orientations? How can the different thresholds have such an effect on the orientation tuning curve? Explain your answers in your own words.Question #8: If the null hypothesis is that the surround has no influence on the perception of the central patch, what would be the expected shape of the graph?Question #9: Does the data conform to the null hypothesis? If not, how does it depart from the expected result of the null hypothesis? What does the departure mean in terms of how the orientations interact? Present your individual data and the group data, both with appropriate captions, as part of your answer.Question #10: Given that there is this known sensorimotor delay, if we now pull all the orientations from the data file that have a ‘1’ next to them (the orientations present when a key press occurs), what would be their expected distribution and why?Question #11: What do you think may happen if we now do the same analysis for orientations that preceded the key press? What would you expect if the probability of hitting a key was proportional to the firing rate of a cell tuned to vertical? We can do analysis and find out what the data say by looking at the orientations that immediately preceded the key press (that means a time lag of 1 presentation frame) or even higher delays (time lags of 2, 3, 4 and so on). Present your individual data and the group data, both with appropriate captions, when these analyses were made. [Note: You can present your individual data as several panels within one figure. Similarly, the group data can be presented as a single figure with many panels.] What was your individual reaction time to process and respond to the vertical grating? Use your data to justify your answer. How did your reaction time compare to the group overall? Explain.Question #12: Is there a time lag for which the distribution of orientations show some interesting structure? If so, what does it mean? Describe the shape of the curve that you see and what it means in terms of how orientations are interacting with each other. How can you use these data to estimate the “reaction time” — defined as the average time it takes for a subject to press a key after they observe the vertical stimulus?Question #13: Can you think of a simple modification to the model in Figure 46 that may explain both the tilt effect and the orientation dynamics data? Please clearly present such a modification to this model and explain how it accounts for both the tilt effect and the orientation dynamics. [Hint: It has to do with changing the shape of the tuning curves.]Question #14: (Part A) Draw a schematic of a neural circuit that could explain the phenomena of both the simultaneous tilt effect and the orientation dynamics, and give a thorough explanation of how it accounts for the phenomena. (Part B) Devise an experiment that would test the validity of your model.
Expert answer:VISUAL NEURAL SIMULATOR bio 14 questions answer
by | Sep 2, 2021 | Uncategorized
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