(how to get to us)

The BCCN-group on Computational Neuroscience is mainly interested in understanding neuronal systems embedded in their environment.

Over decades neurons and brains have mainly been investigated as stimulus-response systems, where the output of the system does not affect its own inputs. Animals (and humans), however, operate differently in quite a fundamental way: Whatever action we perform, it will almost always immediately affect our sensory inputs. In writing these lines I see my fingers moving over the keyboard, feel their touch, hear the clicking of the keys, notice letters appezring bksp bksp bksp bksp bksp appearing, where every typo (feedback error-signal) will enact a correction closing the perception-action loop.

Hence, such perception-action loops are the normal mode of operation of all animals. Within such a loop some signals that come back to the animal’s sensors are of direct relevance (like the seeing of a typo in writing), while others do not immediately drive the loop (like the clicking of the keys).

Fundamentally, it is only the animal/human/agent who can decide which of the arriving sensor signals are relevant for the momentarily existing task and which are not. The behaviour of any creature is therefore controlled by measuring its own inputs (input-control) and normally not by reinforcement from an external observer¹. Improved fitness will arise if an animal can do this in a predictive way, hence if it can use predictive mechanisms to anticipate the outcome of its own actions and, to some degree, also the “behaviour of the world”.

Our research agenda: The goal of our studies is to understand how autonomous behaviour arises in animals and agents through the development of complex perception-action loops and the learning of adaptive, anticipatory behaviour through input-control with minimal external interference.

To this end we investigate (using neuro-physiological data as well as robots):

Input: Information processing in the visual system and its use in machine vision.

Adaptation: The biophysics of synaptic plasticity and correlation based learning mechanisms in animals and robots.

Reasoning: Decision making, planning and the discovery of the structure of the agent’s environment.

Output: The sequencing of actions towards goal-directed behaviour.