Introduction

Dr. rer. nat. Dennis Eckmeier

I am a neuroscientist, working with Megan Carey at the Champalimaud Foundation in Lisbon, Portugal. This page is to represent myself and my interests as a scientist. Please feel free to also follow me on Twitter (@DennisEckmeier) or read my blog.

neuroethology

By training I am a neuroethologist. I study a specific, naturally occurring behavior of an animal and the neuronal mechanisms that control this behavior. For example, as a doctoral student at Bielefeld University with Dr. Hans-Joachim Bischof (professor emeritus) and in collaboration with Drs. Egelhaaf and Kern,  I studied how animals with only limited stereovision are able to successfully maneuver clustered environments during fast locomotion. Birds, especially small and fast flying birds, must be able to use other visual cues when flying around, for instance, within the crown of a tree. It was already known that insects use image motion cues (optic flow) to estimate distance without relying on stereovision. Based on this knowledge we designed a behavioral study on zebra finches. The results indicated that zebra finches control their gaze in a way that would facilitate the extraction of depth cues from image motion (Eckmeier et al., 2008). We followed up on this result by studying a brain area that might perform the necessary computations to turn motion information into a three dimensional perception (Eckmeier et al., 2013).

As a postdoc I first worked with Dr. Stephen Shea at CSHL in the USA on olfactory learning, and brain state modulation during social interaction. Social animals need to interpret complex and subtle social cues in order to appropriately modulate their own behavior. Noradrenaline – which plays a role in the control of general brain state – is necessary to form a memory for another individual. In mice, the physiological and behavioral changes associated with learning the specific smell of another mouse could be artificially induced by electrically inducing noradrenaline release in the brain. Using this technique, I studied how an extended period of noradrenaline release changes response properties of neurons in the main olfactory bulb (Eckmeier & Shea, 2014). A second project aimed at the natural activation of the noradrenergic system in socially behaving mice.

I continue studying freely behaving animals and ‘naturally computing brains’ in the laboratory of Megan Carey, at the Champalimaud Neuroscience Programme in Portugal, which I joined very recently. Here, I will study the control of movements by the cerebellum.

It has become a fundamental understanding that neuronal processing is constantly modulated in the naturally behaving animal. Brains therefore function very differently in a freely behaving animal than in an anaesthetized one. What really happens in the brain while the animal is behaving naturally is almost completely unknown. This means that the many studies on anaesthetized animals or brain sections – although often very informative – usually lack a ‘reality check’ in the freely behaving animal.

The challenge of experiments on freely behaving animals lies in the many degrees of freedom the animal is given. In comparison with other behavioral studies in neuroscience, the animal is not restricted to a simple task that is repeated stereotypically and there is no defined stimulus it responds to. Every instance of the occurring behavior is unique. In order to understand what drives the animal at any given time, large amounts of detailed data on the animal’s behavior, physiology and environment must be collected and analyzed.

So far, my methodological experience covers different types of electrophysiology and wide-field imaging and the analysis of acquired data. I also have experience with the design, conduction and analysis of behavioral experiments. I conducted behavioral and physiological experiments on audiovocal behavior, visual behavior and olfactory behavior in frogs, songbirds and rodents, respectively. I wish to expand my knowledge towards computational and statistical methods to increase my understanding of computational modeling and to develop methods for the analysis of complex multi-modal data to correlate physiological events with behavioral and sensory events.