Hermann Wagner

Bio: Hermann Wagner is an academic researcher from RWTH Aachen University. The author has contributed to research in topics: Interaural time difference & Sound localization. The author has an hindex of 41, co-authored 189 publications receiving 6733 citations. Previous affiliations of Hermann Wagner include California Institute of Technology & Queen's University.

Using Virtual Acoustic Space to Investigate Sound Localisation

Abstract: It is an important task for the future to further close the gap between basic and applied science, in other words to make our understanding of the basic principles of auditory processing available for applications in medicine or information technology. Current examples are hearing aids (Dietz et al., 2009) or sound-localising robots (Calmes et al., 2007). This effort will be helped by better quantitative data resulting from more and more sophisticated experimental approaches. Despite new methodologies and techniques, the complex human auditory system is only accessible in a restricted way to many experimental approaches. This gap is closed by animal model systems that allow a more focused analysis of single aspects of auditory processing than human studies. The most commonly used animals in auditory research are birds (barn owls, chicken) and mammals (monkeys, cats, bats, ferrets, guinea pigs, rats and gerbils). When these animals are tested with various auditory stimuli in behavioural experiments, the accuracy (distance of a measured value to the true value) and precision (repeatability of a given measured value) of the animal’s behavioural response allows to draw conclusions on the difficulty with which the animal can use the stimulus to locate sound sources. An example is the measurement of minimum audible angles (MAA) to reveal the resolution threshold of the auditory system for the horizontal displacement of a sound source (Bala et al., 2007). Similarly, one can exploit the head-turn amplitude of humans or animals in response to narrowband or broadband sounds as a measure for the relevance of specific frequency bands, as well as binaural and monaural cues or perception thresholds (e.g. May & Huang, 1995; Poganiatz et al., 2001; Populin, 2006). The barn owl (Tyto alba) is an auditory specialist, depending to a large extent on listening while localising potential prey. In the course of evolution, the barn owl has developed several morphological and neuronal adaptations, which may be regarded as more optimal solutions to problems than the structures and circuits found in generalists. The owl has a characteristic facial ruff, which amplifies sound and is directionally sensitive for frequencies above 4 kHz (Coles & Guppy, 1988). Additionally, the left and right ear openings and flaps are asymmetrically with the left ear lying slightly higher than the right one. This asymmetry creates a steep gradient of interaural level differences (ILDs) in the owl’s frontal field (Campenhausen & Wagner, 2006). These adaptations to sound localisation are one of the reasons why barn owl hearing was established as an important model system during the last decades.

Group report: The behavior of natural and artificial systems: Solutions to functional demands

Abstract: At the current state there is no unified view onto the functional demands and their solutions in natural and artificial systems. Artificial systems have well-defined inputs and their desired outputs are given in terms of system requirements that are defined by the users or designers of the systems. Natural systems, on the other hand, have evolved in order to survive in a complex environment. As we lack complete knowledge of the constraints given by the outside world, we cannot clearly de­ fine the actual optimization goal that implicitly un­ derlies the observed organism. However, some striking features in natural organisms seem to be powerful solutions to functional demands. Some of these solutions are by far not yet achieved in artificial systems. The most striking examples are the capabilities of the human brain to process nat­ ural languages and to build up concepts of the world. However, also small brains, even in insects, seem to incorporate powerful solutions to tasks that are not yet captured by computer systems, e.g., in object recognition and flight control. In the working group we discussed some areas where artificial and natural systems seem to have

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Spiking Neuron Models: Single Neurons, Populations, Plasticity

Abstract: Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.

Neuroscience 細胞死：最近の知見

Abstract: 中枢神経系疾患の治療は正常細胞（ニューロン）の機能維持を目的とするが，脳血管障害のように機能障害の原因が細胞の死滅に基づくことは多い．一方，脳腫瘍の治療においては薬物療法や放射線療法といった腫瘍細胞の死滅を目標とするものが大きな位置を占める．いずれの場合にも，細胞死の機序を理解することは各種病態や治療法の理解のうえで重要である．現在のところ最も研究の進んでいる細胞死の型はアポトーシスである．そのなかで重要な位置を占めるミトコンドリアにおける反応および抗アポトーシス因子について概要を紹介する．

Competitive Hebbian learning through spike-timing-dependent synaptic plasticity

Abstract: Hebbian models of development and learning require both activity-dependent synaptic plasticity and a mechanism that induces competition between different synapses. One form of experimentally observed long-term synaptic plasticity, which we call spike-timing-dependent plasticity (STDP), depends on the relative timing of pre- and postsynaptic action potentials. In modeling studies, we find that this form of synaptic modification can automatically balance synaptic strengths to make postsynaptic firing irregular but more sensitive to presynaptic spike timing. It has been argued that neurons in vivo operate in such a balanced regime. Synapses modifiable by STDP compete for control of the timing of postsynaptic action potentials. Inputs that fire the postsynaptic neuron with short latency or that act in correlated groups are able to compete most successfully and develop strong synapses, while synapses of longer-latency or less-effective inputs are weakened.