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Research Interests

The Leibold laboratory works on three major topics combining theory, computational modeling, and data analysis.


Temporal processing in the auditory system

When perceiving a sound, the pressure wave at the ear drum is translated to a volley of electrical activity in the auditory nerve. Neither the pressure wave nor the neural activity conveys explicit information about the content of the sound or the position of the sound. All information is hidden in their temporal structure. Understanding the mechanisms underlying the temporal dynamics in the auditory pathway is thus essential to study auditory information processing. In our lab we particularly focus on the low-frequency binaural system which encodes the position of a sound source by means of interaural time differences. We study the underlying binaural coincidence detection using computational models of single neurons and apply coding theory to the neuronal population responses.


Theory and Modelling of the hippocampal formation

One of an animal's first and most fundamental tasks is to know about its location in space. The hippocampal formation is one of the brain areas assumed to be involved in spatial navigation since many cells exhibit space-selective firing rates (place fields and grid fields) and space related temporal firing patterns (theta phase precession; reply, preplay). However, we still lack a satisfactory understanding of how hippocampal subregions integrate sensory input and external cues. Our goal is to develop mathematical theories of neural network interactions, to offer insights on how the hippocampus and related brain areas such as the entorhinal and medial prefrontal cortices wire up to perform the computations necessary for representing, memorizing and planning trajectories in space.

Subproject: Cellular biophysics of Sequence replay

Simultaneous recordings of many place cells reveal sequential activity patterns, which repeat during periods of immobility. In local field potential recordings, these repetitions are accompanied by so called sharp-wave ripples (SWRs). The function of these sequences is assumed to be related to memory consolidation and path planning. To study the function of cellular biophysical properties, we develop a multi-compartmental model of a CA1 pyramidal neuron receiving postsynaptic currents recorded from pyramidal cells in CA1 slices during spontaneous occurring SWRs.

Subproject: Interaction of Brain Areas

Neuronal space representations are not only found in the hippocampus and medial entorhinal cortex. All related brain areas are encoding space either directly via there firing rate or in the firing phase with respect to the theta oscillation (or both). It is unclear why space is so ubiquitously represented and particularly how the different space representations talk to each other. We are working several models addressing the interaction of different brain areas to explain different functions and phenomenons like pattern separation, path planning, phase precession and gridfield formation.


Data Analysis of Temporal Hippocampal Activity Patterns

In addition to place-selective firing rates, hippocampal neurons convey spatial information also via their precise spike timing in two ways. First, during theta oscillations the phase of the spikes is decreases in each cycle thereby providing a temporal code of space on a single neuron level and a population code of spatial topology on a population level. Second, during sharp waves, replay and preplay in the place cell population expresses sequences of activity resembling the topology of space. How both phenomena are modulated by behavioral and environmental manipulations and how different brain areas contribute to the temporal ordering in the hippocampus is largely unresolved. We analyse data from several in-vivo experiments to address these questions.