We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
Published online by Cambridge University Press: 05 June 2012
In this chapter, we show how to model complex dendritic and axonal morphology using the multi-compartmental approach. We discuss how to represent an axon or a dendrite as a number of compartments derived from the real neurite's morphology. We discuss issues with measurement errors in experimentally determined morphologies and how to deal with them. Under certain assumptions, complex morphologies can be simplified for efficient modelling. We then consider how to match compartmental model output to physiological recordings and determine model parameters. We discuss in detail the techniques required for determining passive parameters, such as membrane resistance and capacitance over a distributed morphology. The extra problems that arise when modelling active membrane are also considered. Parameter estimation procedures are introduced.
Modelling the spatially distributed neuron
The basis of modelling the electrical properties of a neuron is the RC electrical circuit representation of passive membrane, consisting of a capacitor, leak resistor and a leak battery (Figure 2.14). Active membrane channels may be added by, for example, following the Hodgkin–Huxley approach. Further frameworks for modelling the myriad of ion channels found in neuronal membrane are covered in Chapter 5. If we are interested in voltage changes in more than just an isolated patch of membrane, we must consider how voltage spreads along the membrane. This can be modelled with multiple connected RC circuits. This approach is used widely and often referred to as multi-compartmental modelling or, more simply, compartmental modelling.
To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Find out more about the Kindle Personal Document Service.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.
