Record extracellular spiking activity from a cockroach leg in response to different stimulus intensities
Physiology is the study of how cells, tissues, and organs function within larger systems and respond to external events. Neurophysiology is the study of how neurons function within the brain to process events in the environment and produce behaviors in response. Sensory events, neural activity, and behavior are all dynamic, and neurophysiologists need to be able to record those dynamics to study how they relate to each other. Fortunately, as neurons perform their function, they generate electrical signals that can be detected with sensitive instruments.
We will be using a classical method for detecting and recording neural activity that involves sensing and amplifying tiny electrical signals created by outside cells when they generate action potentials. You should all be familiar with how action potentials are generated, but for a refresher you can work through this series of videos from the Howard Hughes Medical Institute.
In this exercise, you will be making extracellular recordings from a cockroach leg, and learning how to measure the spikes caused by different stimuli. Once you can detect spikes, you are ready to record, quantify, and graphically present electrophysiology data. The method you will use to compare differences in spiking from different stimuli is called rate coding and it is one of the most reliable tools in neuroscience. Rate coding is simply measuring the number of spikes that occur during a set period of time. However, even though it is simple, rate coding can be used to answer complex questions about how neurons respond to stimuli.
The extracellular potentials generated by neural action potentials are very small (microvolts), and the currents they can induce in a recording electrode are also very small. We will use amplifiers from Backyard Brains to increase the power of the signals so that you can hear them and record them using a computer or smartphone.
Turn your SpikerBox on! If you hear a popcorn sound, congratulations, you have just heard your first neuron firing! If you are not sure whether you are listening to spikes or noise, lightly touch spines located on the tibia with a toothpick. If you don’t hear spikes in response to toothpick stimulations, try reinserting your electrodes, switching which one is in the coxa and femur. Once you are hearing spikes consistently, plug the cable back into the spikerbox. You should see spikes that look something like this:
Now you will do a controlled experiment to see how different strengths of stimulation affect the cockroach leg. You will use compressed air on your lab bench to stimulate the cockroach leg for this experiment, varying the distance from the preparation to control the stimulus intensity. Use the provided tape measures to find the correct distances.
In each trial, you will record 30 seconds of spontaneous activity (without blowing), then about 30-60 seconds of stimulus. Be sure to note the start and stop time of the stimulus relative to the start of the recording. Repeat each stimulus condition 4 times.
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Remove the electrode from the femur and move it to the tibia, as shown in the diagram.
Repeat the same series of measurements that you made in the femur and record them in a table like the one above.
The first step is to isolate your spikes. Begin with the file for your first 4 cm trial, then repeat the procedure for each of the other trials.
Open the file and zoom in to a representative region of your control period (with no stimulus). Continue to zoom in until you can see individual spikes. They may look something like this:
As in the example, not all your spikes may look the same. This happens for several reasons. One is that background noise produces random distortions in the spike shapes; another is that spikes are sometimes emitted as groups or bursts; and a third is that you are probably recording from more than one neuron at once, and there are differences in the shapes of the waveforms that the electrode picks up. In some experiments, people will take care to isolate a single neuron, or unit, but in many cases (including this one), the average activity from multiple neurons is enough.
Click the button at the top left that look like a flask. You will notice that this adds two controls to the right of the trace that can be dragged up and down. Adjust them so that the lower trace is above the background noise and the upper trace is above the peaks of the spikes. This configures an algorithm that will detect spikes in the recording. Save the detected spikes by clicking the disk icon. Click the flask again to go back to the recording. You should see marks above the trace that indicate where the spikes were detected. This is an example of a raster plot.
You now need to count the number of spikes that were evoked during the baseline and the stimulus period. Click and drag with the right mouse button to select around 10 s of baseline for analysis. The screen will show the duration of your analysis window, the number of spikes, and the RMS. Make a note of all three in the table below. Now select the interval when you presented a stimulus and note the same quantities. Repeat this analysis for all the recordings you made; note that you will be making two entries per trial, one for the baseline and one for the stimulus.
Create two graphs like the ones below by hand or using your spreadsheet program to show the average spike rate as a function of stimulus intensity in the two locations you recorded, indicating the standard errors of your averages with error bars. Think carefully about what will go on the x and y axes.
Try plotting RMS in the same way. Is RMS a good approximation of spike rate?
If time allows, discuss the following questions with your partner and/or neighboring groups:
Submit a document with your tables, graphs, and an answer to one of the discussion questions by the beginning of class next week. Make sure you save the recordings and analysis files you made! We will be using them next week.