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-===Research ​Projects=== +===Research=== 
-Research projects in our group focus on mammalian as well as insect ​systems. We investigate ​neural ​computation ​in the entorhinal cortexincluding biophysical single-cell ​properties ​that shape subthreshold resonance ​and membrane-potential oscillations ​as well as phase precession in grid cellsHow evolutionary constraints ​-- such as limited energetic resources, ​limited ​size, or variable temperatures -- affect ​the design ​of neural ​systems ​is explored ​in the auditory periphery ​of grasshoppers ​and cricketsCurrent ​projects ​cover: +Our passion is to uncover principles of neural computation across species and systems. ​More specifically,​ my lab’s research is driven by two major interests:  
-====== - subthreshold resonance,​====== + 
-====== - phase precession,​====== +(1) We are convinced that neurons are not just simple units whose function is to integrate inputs. Admittedly, the striking success of artificial ​neural ​networks ​in solving complex tasks is grounded on learning processes that adjust connectivity weights in networks of simplified neurons that sum inputs. Yet these approaches usually neglect that real neurons provide a tremendous computational repertoire of their own. The analogue, nonlinear computations performed by individual cells are highly efficient, in particular as they can be implemented at the compartmental (like the dendritic) and even the molecular level. Moreovercellular ​properties ​are readily adapted to different states via a diverse set of neuromodulators. To date, however, it is still unclear to which extent ​and how cell-based computations shape network function. **Our research, therefore, seeks to shed light on how cellular processes bear consequences for network behavior and contribute to neural computation.** 
-====== - auditory ​computation ​in the grasshopper,​====== + 
-====== - influence ​of ion channel cooperativity on neuronal dynamics,​====== +(2) No matter which brain region or part of the nervous system we investigate,​ to decipher neural computation investigations primarily focus on the specific system’s computational task. From an evolutionary ​as well as engineering perspective,​ however, investments to achieve a particular function are only well placed if the latter can be maintained stably, without being easily compromised by external or intrinsic influencesThis is why we consider it important to also study neural function under evolutionary constraints. These may include ​limited energetic resources, ​variable temperatures, ​size limitations, or a degree of flexibility that allows a system to switch between different modes. **Our goal is to understand whether and how evolutionary constraints have impacted ​the principles ​of neural ​design.** ​  
-====== - dendritic computation.======+ 
 +To address these topics, we employ computational and mathematical methods. Our approach ​is interdisciplinary and we actively seek to engage ​in collaborative projects with experimental groups: be it to put theoretical predictions to test or to be inspired by experimental observations that guide new modelling approaches. We thus exploit ​the “luxury ​of the theoretician” ​and apply the flexible modeling and data analysis methods to a wide range of species and systemsThe lab’s research work thus encompasses ​projects ​ranging from the auditory ​system ​in the locust to navigation in the mammalian hippocampal formation. The largest benefit ​of this wide scope is that it allows for an overarching view beyond a specific system that sharpens the eye in the search of generic principles that extend beyond a particular system.