How connectivity rules affect cortical behaviour

Analytical examination of eigenvalue spectra

24th April, 2015
An example eigenvalue spectrum for a sparse network.

How does the behaviour and stability of a neuronal network depend on the connectivity rules used to build it? A common approach is to build many stochastic instances of a network, tweak the parameters, simulate and analyse, and then try to derive an impression about stability. We instead used an analytical approach, to directly relate connectivity rules and parameters to bounds on stability.

Putting vision into context

And adding context to vision

21st December, 2015
This optical illusion shows how strongly the context of a visual scene influences what we see, and how that context can sometimes mislead us. The three people in the picture are exactly the same size. However, because our brain judges the size of an object based on its perceived distance, the person at the back seems to be further away and therefore appears larger.

Our brain does not faithfully interpret visual information, but instead uses a complex mixture of prior experience and context to shape our perception of the world. We described a pathway in the brain for this contextual information, from the mouse thalamus to visual cortex.

Pattern motion responses in mouse visual cortex

Model-based analysis of cortical responses

8th August, 2015

Example imaging region in mouse V1

Example imaging region in mouse V1

Green: OGB labelling of neurons. Red: Sulforhodamine labelling of astrocytes. Scale: 50um.

In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. In principle, the architecture of rodent cortex would enable local circuits to integrate sensory information — however, whether feature integration occurs in rodent primary sensory areas has not been examined directly. Our results show that a broad range of pattern integration already takes place at the level of V1.