Christoph D. Dahl

Associate Professor

Currently, there are projects available for MSc and PhD students. The projects are in the fields (3) to (5) as described below. Contact me if you are interested in any of the topics.


My research programmes focus on

(1) Computational ethology

Computational ethology is the interdisciplinary research domain that addresses the lack of instrumental methods in ethology by introducing tools originating in mathematics and computer sciences, in particular in artificial intelligence and machine learning. The defined goals of computational ethology are to (a) detect predefined behaviours in freely moving animals and (b) discover novel behavioural patterns and new behaviours (Wiltschko et al., 2015; Dahl, Wyss, Zuberbühler, & Bachmann, 2018).

CD Dahl, E Ferrando, K Zuberbühler – Animal cognition, 2020
CD Dahl, C Wyss, K Zuberbühler, I Bachmann – Animal cognition, 2018


(2) Higher-order cognition in small-brained animals

The goal in this research programme, is to (a) describe similarities (and dissimilarities) of small-brained animal sensory systems (Borst & Helmstaedter, 2015; Wilson, 2013), particularly in combination to higher-cognitive processes, to (b) understand the neuronal circuitries of internal representation and to (c) pursue these objectives in a virtual and actual environment; the latter providing free animal behaviour partly in interaction with conspecifics. The study of small-brained animal cognition and cognitive computation is in very early stages, however, providing a unique window into the function of neuronal mechanisms and circuitries underlying cognition due to a ”simpler” brain.

(3) Social interaction and group dynamics in zebrafish

A useful computationally and quantitative valid description of the behavioural dynamics in groups of zebra fish during learning tasks is essential for the subsequent establishment of a link between social behaviour and neural activations using modern neuroscience methods. This data-driven research approach for characterizing social interaction behaviour in groups of animals is only just beginning, but already led to very promising results. For instance, by tracking social interaction in groups of mice a new high-order structure was found [Shemesh et al., 2013]. In particular, it was found by tracking the exact movement trajectories of a group of mice in a semi-natural environment over a long time that the statistics of the spatial configuration of the mice over time could not explain by a model only relying on pairwise correlations. Instead higher order terms had to be taken into account to explain the data hinting at a more complicated social interaction structure as previously thought. The goal of this research is to establish a similar data-driven approach to characterize social interactions in zebrafish. Moreover, we are interested in the changes of the dynamics of the interaction structure and the characterization of the flow of knowledge (e.g. information about a reward source) from one individual to others while the group performs a social learning task.

(4) Human higher-level vision

Higher-level vision refers to the complex cognitive processes that occur after the initial stages of visual perception. Higher-level vision involves the interpretation, recognition, and understanding of visual information, allowing us to make sense of the world around us. One of the central topics in higher-level vision is how humans recognize and identify objects in their visual field. Psychophysical studies examine the processes involved in recognizing familiar objects, faces, and scenes. Face perception is a specialized area of higher-level vision. Out studies aim to understand how we recognize faces, detect facial expressions, and extract important social and emotional information from facial features. Research often involves experiments related to face identity, facial emotion recognition, and facial processing in various

CD Dahl, C Wallraven, HH Bülthoff, NK Logothetis – Current Biology, 2009

CD Dahl, NK Logothetis, HH Bülthoff, C Wallraven – Proceedings of the Royal Society B: Biological …, 2010

(5) Dog cognition 

Dog cognitive is a fascinating and evolving field that explores the mental and behavioural processes of dogs. Dogs have co-evolved with humans for about 15’000 years, a process that affected their brains and behaviour. We focus on the following aspects in canine cognition:

Social Cognition: Dogs derive from wolves and, hence, form strong bonds with each other. Dogs additionally form bonds with humans. Understanding how dogs perceive and interpret social signals from conspecifics and heterospecifics, such as body language and vocalizations, is a fundamental aspect of our research. 

Communication and Language: Exploring the extent to which dogs can understand and communicate with humans through gestures, vocal commands, and other forms of non-verbal and verbal communication. 

Inter-breed variability in cognition: Dogs vary in morphology, giving raise to assume that dogs are not comparable. Most modern attempts on dog research, therefore accounts for inter-breed variability. We here focus on olfactory capabilities of dogs that varies largely according to their skull shape (from brachycephalic to dolichocephalic) and, as a consequence, the size and shape of neural correlate responsible for olfaction. This research is at the interface of applied ethology, addressing welfare issues due to selective breeding practices.

E Ferrando, CD Dahl – Animal Cognition, 2022
CD Dahl, E Ferrando, K Zuberbühler – Animal cognition, 2020