Functional Role of Feedback in Sensory Representation

A key feature of the mammalian neocortex is its ability to associate aspects of perceived experience with internal representations of the world to make predictions about the outcomes. This project is a collaborative research effort between experimentalists and theoreticians trying to understand the abstract principle that guide our brains to make correct prediction about the future.

To perform such as detailed investigation, scientists has developed a virtual reality for mice in which they performed decision that reflect their prediction about the work. In this context, mice were trained to play a game to collect reward of sweet condensed milk. In this task, mice have to guess the timing when sweet milk is delivered or to try again. This is very similar to us, humans, when betting money based on our choices.

With the advent of state-of-the-art behavioural and neuroimaging methods, scientists managed to record detailed activities of thousands of single neurons during mice betting for sweet milk. As the brain is formulated of excitatory and inhibitory neurons, scientists isolated and identified the contribution of different neurons during prediction.

Using different mathematical models to build relationships between excitatory and inhibitory neurons, scientists managed to identify potential mathematical principles that our brain may use to filter sensory information and combine it with previous knowledge.


Funding period: 05/2017 - 04/2020

Prof. Dr. Matthew Larkum
Humboldt-Universität zu Berlin
Neurocure Cluster of Excellence
Charitéplatz 1
10117 Berlin
Phone: 030 / 450539117

Prof. Dr. Henning Sprekeler
Technische Universität Berlin
Modellierung Kognitiver Prozesse
Marchstrasse 23
10587 Berlin
Phone: 030 / 31424390

Applicants: Humboldt-Universität zu Berlin, Technische Universität Berlin