Computational model of a somatosensory cortical column

We continually change the way we perceive the world by actively changing the position and physical properties of our sensory organs, for instance by moving and focussing our eyes to pursue a moving object, yet we perceive objects in the world as stable entities. How the brain processes this changing sensory information, what computations it performs to create unvarying percepts and how the interaction between perception and active control of our sensory organs (sensorimotor integration) arises, is still largely unknown. I research these computations: How do neurons extract information about the world and represent it? How does the information sensory neurons extract influence active control over our sensory organs and vice versa?

Perception and sensorimotor integration are often studied in the rodent whisker system, for several reasons. Firstly, rodents use active sensorimotor integration to solve real-world problems like navigation, object localization and texture discrimination. Secondly, whisker motion can easily be tracked in millisecond resolution and manipulated experimentally, giving direct access to the sensory information that animals collect and to the motor plan they generate during touch sensing. Finally, the availability of molecular tools in the mouse makes it a good candidate to address neural circuit mechanisms. Even though the rodent whisker system has been experimentally well studied and lends itself to a mechanistic explanation of neural computation, there are not many computational models of it. Moreover, the models that have been proposed only describe certain modules in the whisker system, such as biomechanical whisker models, mechanoreceptor models, cortical models or behavioural models.

In this project, Chao Huang and me are developing an end-to-end model to allow the integration of and cross-validation between structural and functional aspects of sensory phenomena. We keep on updating the model with the latest insights. The model is based on anatomical reconstructions and includes known electrophysiological cell properties. The connectivity is probabilistic, so every time the model is run, a new realisation of the connectivity is established. The newest version can be found in the GitHub link below.

Currently, Prescilla Uijtewaal is investigating how the connectivity structure of the barrel cortex influences its information processing. Lino Vliex is extending the model to a functioning model of perception, in order to investigate whisker-related information processing. 


link to code:   GitHub