Although we’ve reduced the response of our neuron down to a train of 1s and 0s, we have the information we need to analyze what caused the original neuron to fire. This means that when neurons communicate with each other, the peak voltage never changes - all the information must be conveyed in the rate or timing of the action potentials. This time-dependent sequence of 1s and 0s is referred to as a spike train, depicted in graph Figure 6.3b.Īnother characteristic of action potentials is that they are stereotyped: they are consistent with each other in voltage. With this in mind, a voltage response curve can be reduced to time-bins that either contain a spike (represented in a binary fashion by a 1) or do not (represented by a 0). This small increment of time is called a time bin. The length of time over which the neuron is recorded is called the integration window: we will first break up this window into lengths of time small enough that they can only contain one spike. When the voltage surpasses the threshold, a spike occurs. To do this, we need to remember that the axes of both graph A and B represent voltage over time. This characteristic allows us to represent spikes in a binary fashion. How should we analyze the information encoded in these action potentials?Īs we’ve previously discussed, action potentials are an all-or-none event. Graph A shows the recorded stimulus and graph B shows the recorded actions potentials during the stimulus.Īssume that we measured a neuron firing in response to a random sensory stimulus (shown in Figure 6.3a), and we recorded its voltage changes and displayed the signal in an oscilloscope. 12.6 Chapter 6: Reverse Correlation and Receptive Field Mappingįigure 6.3: Example of a spike train.12.3 Chapter 3: Passive Membrane Models.12.2 Chapter 2: Introduction to Computational Neuroscience.11.7 Chapter 7: Reverse Correlation and Receptive Field Mapping.11.4 Chapter 4: Passive Membrane Models.11.3 Chapter 3: What is Computational Neuroscience?.7 Reverse Correlation and Receptive Field Mapping.4.7.4 The flow of ions and equilibrium potentials.4.7.3 Main features of an action potential:.4.7.2 An action potential has six phases:.4.4.2 Negative feedback and repolarization.4.4.1 Positive feedback and depolarization.4.3 Membrane potentials and electrochemical gradients.3.6 The future of computational neuroscience.3.5 Applications of computational neuroscience.3.3.1 Can we make models that understand?. 3.3 What is computational neuroscience?.2.13 Coding Exercises for Learning Python.2.12 Conceptual Exercises for Learning Python.1.4 This book creates a public record of learning that exists after the semester ends.1.3 This book can be revised and disseminated more rapidly than traditional textbooks.All of the rare long collars and wrists, all of the rare short collars and wrists, purple diamond spiked collar, purple diamond spiked wrist, rare purple and white headdress, rare purple party hat, rare purple fox hat, rare black fox hat, purple Arctic hood, purple top hat, founders hat, beta tiara, pearly tiara, purple elf helmet, purple sunglasses, purple holiday scarf, black holiday scarf, rare purple worn, black worn, rare purple bow and arrows, rare black bow and arrows, purple pirate sword, black pirate sword, purple holiday bow, rare purple glove, rare black glove, gold ring, 2 silver rings, 2 glitched rings, beta purple elf tail, silver and gold elf tail, purple bone tail, phantom tail armor, purple Royal tiara, purple designer skirt, rare tutu, purple tutu, 7 purple tuxedos, 7 black tuxedos, purple sparkly bow, purple sparkly shoes, 2 candy cane crowns underwater, purple tutu underwater, ice cream cake freezer, ice cream cone display, diamond phantom, purple plaid couch, black plaid couch, beta computer, beta tv, beta fountain, blue vines floor, and pink forest walls.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |